Next Article in Journal
Tissue IL-6/LIF/LIFR and CXCL9 Expression Correlates with High-Risk NBI Patterns and Squamous Cell Carcinoma in Vocal Fold Lesions
Previous Article in Journal
When Estrogen Signaling Refuses to Die: Receptor Rewiring, Compartmentalization, and Endocrine Plasticity in Gynecological Cancers
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Reexamining Fat: Exploring Diversity, Plasticity, Development, Functional Implication, and Therapeutic Options

by
Presley D. Dowker-Key
1,
Praveen Kumar Jadi
1,
Rawon Alfatlawi
2,
Richard J. Giannone
3 and
Ahmed Bettaieb
1,4,5,*
1
Department of Nutrition, University of Tennessee, Knoxville, TN 37996-0840, USA
2
Department of Biomedical Engineering, University of Tennessee, Knoxville, TN 37996-0840, USA
3
Oak Ridge National Laboratory, Oak Ridge, TN 37831-6191, USA
4
Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN 37996-0840, USA
5
Department of Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996-0840, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2026, 27(4), 1925; https://doi.org/10.3390/ijms27041925
Submission received: 22 December 2025 / Revised: 30 January 2026 / Accepted: 6 February 2026 / Published: 17 February 2026

Abstract

Obesity has become so prevalent in many developed countries that it is increasingly perceived as a new norm, despite decades of interventions and drug development. Although research continues to explore novel strategies, no single approach to date has demonstrated sustained success in reducing its population-level dominance. This underscores the need to better evaluate and integrate the growing body of knowledge surrounding obesity’s multifaceted nature. Stamped under one ‘fat’ name, adipose tissue varies by color, location, morphology, composition, and function. This variability suggests a level of complexity that demands deeper investigation. Although the relevance and roles of different adipose types have been extensively discussed throughout the literature, their interdependence, synergy, and collective impact on the body remain to be fully expounded. This review aims to further consolidate and elucidate the available information on the different adipose tissue types and their association with obesity and metabolic health. We also discuss existing and emerging therapeutic strategies, highlighting their respective strengths and limitations.

1. Introduction

Obesity is an increasing health concern that was formally recognized by the World Health Organization as a global epidemic in the late 90s [1]. Among developed countries, the United States is projected to have one of the highest obesity rates by 2030, affecting one in two American adults [2]. Obesity’s detriment is largely attributed to various complex comorbidities that accompany it’s more modest definition—excess fat accumulation that poses a threat to human health [3]. While many associated comorbidities directly affect physical health [4], obesity has also been reported to inflict economic, social, and psychological burden [5,6]. In fact, aside from direct medical costs, other aspects of livelihood, such as work productivity, transportation, and overall human capital, are severely impacted by this disease [7]. Therefore, metabolic dysfunction is just the tip of the iceberg.
Traditional approaches to determining obesity have relied heavily on body mass index (BMI) to estimate excess adiposity and related health risk. Contemporary frameworks instead support a more refined classification that distinguishes between preclinical and clinical obesity, with preclinical obesity describing excess adiposity in the setting of preserved organ and tissue function but elevated risk for future metabolic disease, and clinical obesity marked by clear organ dysfunction or functional limitations attributable to excess fat [8]. In this newer model, BMI is used primarily as a population-level surrogate rather than an individual diagnostic tool, and clinical assessment of obesity emphasizes confirmation of excess fat through direct body composition measures or validated anthropometric indices such as waist circumference and waist-to-hip ratio [8]. According to this strategy, individuals identified with preclinical obesity are directed toward structured counseling and preventive monitoring, whereas those with clinical obesity are offered evidence-based interventions aimed at improving or reversing obesity-related health impairment; this approach is consistent with the widely accepted definition of obesity as a complex, multifactorial chronic disease.
Despite this more recent consensus, BMI is still commonly used in clinical practice to determine a patient’s weight category. BMI classifications range from <18.5 kg/m2 (underweight) to 40 kg/m2 (class III obese), with the lowest mortality rate correlated with a BMI of 20.0–24.9 kg/m2 [9]. Although BMI is a cost-effective, straightforward measurement, it faces several limitations when used as a tool to indicate whole body adiposity and obesity. For instance, inherent bounds such as differences among race and ethnicity have been shown to influence BMI classification [10]. Moreover, the limitations associated with the full reliance on BMI to directly distinguish the body’s composition greatly reduces its ingenuity to infer fat mass or denote health status [11,12]. Therefore, other calculated measurements including waist-to-stature ratio, waist circumference, and waist-to-hip ratio have been suggested to assess body fat to account for BMI’s imprecision [8].
More advanced anthropometric tools, such as dual-energy X-ray absorptiometry, have significantly improved the accuracy of evaluating body fat; however, these measures still lack the competence to justify the core cause of obesity [13,14,15,16]. Furthermore, there are many factors that can influence an individual’s predisposition to obesity [17], although often placed at fault is a ‘simple’ energy imbalance that caters to a positive intake and negative output. The commonly referenced Western diet is notorious for being energy dense, having high sugar content, and serving sizable portions. The high caloric index of Western foods has been shown to negatively influence gut microbiome and energy metabolism and, in turn, promote obesity [18]. However, diet is considered a modifiable factor of obesity; thus, actions can be taken to alter outcomes [19]. Additionally, levels of physical activity, stress, and sleeping patterns have also been reported as modifiable factors that either promote or discourage weight gain and obesity, depending on an individual’s routine habits [20,21,22].
While the previously mentioned factors are amendable, others such as age, sex, race/ethnicity, and genetic makeup are considered non-modifiable [23]. For instance, the first identified and, still to-date, most renowned gene locus correlated with increased body weight and obesity risk is the fat mass obesity-associated gene [24]. Moreover, it has been demonstrated that ~17% of the phenotypic variance in BMI can be linked to common single-nucleotide polymorphisms [25]. In fact, a genome-wide association study suggested common variances may even account for more than 20% of BMI differences [26]. While genetics plays a recognized role, it does not fully explain the differences in BMI among individuals. Consequently, there is a growing interest in understanding the role of epigenetics and its relationship to obesity development. Epigenome-wide association studies have reported gene–environment interactions that underly the risk of obesity and metabolic diseases [27]. Moreover, a subset of endocrine disrupting chemicals, referred to as ‘obesogens’, have also been suggested to alter obesity risk [28]. The identification of these risk factors has not only extended our understanding of how obesity may be initiated or nurtured but also has unveiled several approaches that may aid in its prevention. However, a large portion of the target population is beyond the benefits of receiving preventative care, and retrospective actions are required. Therefore, characterizing pathophysiological outcomes and clinical manifestations of obesity will be critical for developing effective treatments that provide sustained benefits.
It is well-known that obesity contributes to metabolic and organ dysfunction [29]. Under normal physiological conditions, fat is traditionally stored in the form of triacylglycerol (TAG), which protects the body against damage that can be caused by oxidative stress due, in part, to excessive release and circulation of free fatty acids (FFAs) [30]. Furthermore, since obesity supports an excess accumulation of fat, lipids infiltrate and settle in less suitable tissues, leading to lipotoxicity and a variety of clinical consequences such as insulin resistance and type 2 diabetes (T2DM). In fact, the repeatedly demonstrated association between obesity and diabetes granted the now widely recognized, portmanteau “diabesity” [30,31]. Moreover, obesity increases cardiovascular disease risk factors [32] while also facilitating an inflammatory state that largely affects adipose tissue homeostasis and function [33]. For instance, obesity may disrupt immune homeostasis by elevating pro-inflammatory cytokines while suppressing anti-inflammatory mediators, driven by a pronounced shift in adipose tissue macrophage (ATM) polarization from predominantly anti-inflammatory M2-like to pro-inflammatory M1-like states [32,34,35]. In addition, pulmonary disorders and hepatic and renal diseases, as well as neurological disturbances, have been noted in many cases [36,37]. Despite the many decades of obesity research that have resulted in an extensive catalog of therapies, the ongoing search for a more effective and long-lasting option(s) highlights their struggle to efficiently mitigate the problem. Therefore, the following section will examine current obesity therapies and their limitations, aiming to provide a comprehensive overview of the current state of treatment options.

2. Current Obesity Therapies and Their Limitations

The heterogeneity of obesity—its varying causes, complications, and clinical presentation—presents a significant challenge for treatment [38]. Current therapeutic approaches include non-pharmacological interventions (lifestyle modifications), pharmacological options (anti-obesity drugs and gene therapy), and surgical interventions (bariatric surgery) [39] (Figure 1).
Lifestyle modifications with low-calorie diets, high levels of physical activity, and behavioral interventions have shown beneficial effects on weight loss and glycemic control in patients with obesity with T2DM [56,57,58]. However, most patients experience weight regain without continuous work. Additionally, adherence can be extremely difficult; therefore, many patients may seek a more permanent and effortless solution [59,60]. Bariatric surgery is an intervention used to treat patients with a BMI ≥ 40 kg/m2 (severe obesity) or BMI ≥ 35 kg/m2 (moderate obesity) and with at least one obesity-associated disorder [61,62,63]. Bariatric approaches are divided into malabsorptive (proximal jejunum was bypassed to the distal ileum), restricted (reduces the size of the stomach), and combination operations [60,61]. Worldwide, the most frequently used bariatric procedures are Roux-en-Y gastric bypass, (the upper part of the stomach is divided into small proximal), sleeve gastrectomy (the stomach is excised leaving a narrow medial aspect), biliopancreatic diversion with duodenal switch (sleeve gastrectomy-like gastrectomy is performed forming tubular pouch and small intestine cut in two places), and adjustable gastric banding procedures [64,65,66]. Bariatric surgeries promote weight loss and potentially improve metabolic profile in patients with obesity; however, they are associated with several complications, including infection of the gastric band, sepsis, anastomotic leaks, iron deficiency, and venous thromboembolism [61,67]. Therefore, due to high costs, specified eligibility, and accessory complications related to surgery, non-surgical interventions combined with anti-obesity drugs (AODs) may be more suitable for the common majority.
AODs initiate weight loss by reducing food intake and enhancing satiety by acting on the central nervous system, mainly on the arcuate nucleus of the hypothalamus [68]. Studies have shown that usage of AODs along with lifestyle modifications enhanced achievable weight loss [69,70]. Throughout the history of AODs, numerous drug molecules were introduced into the market for treating obesity; however, most of them were withdrawn from the market due to their adverse side effects. For example, dinitrophenol was used to treat patients with obesity in the 1930s, but it was withdrawn due to its irreversible side effects, such as rashes, cataracts, and even death due to hyperthermia [71]. Amphetamine and amphetamine-related compounds were approved in the 1940s and 1950s, yet their use became limited due to the struggle to define the efficacy and safety of these drugs and their addictions [72]. Trends of discontinuing drugs from clinical use continued until drugs like fenfluramine plus phentermine (fen-phen) and dexfenfluramine were approved in the mid-1990s, which gave rise to long-term use to treat obesity. However, adverse effects linked with fen-phen, including valvular abnormalities [73] and dexfenfluramine-induced pulmonary hypertension and neurotoxicity in preclinical models [72] caused a withdrawal from the market. FDA-approved drugs for treating obesity, their mode of action, and their side effects are described in Table 1. From the various studies that have explored new AODs, the drugs that are in clinical trials are outlined in Table 2. In addition to the chemically synthetic compounds, molecules derived from natural products such as polyphenols, flavonoids, alkaloids, etc., have been shown to have anti-obesity activity (e.g., promoting the browning of white adipose tissue (WAT)) [74]; however, their clinical relevance are limited due to their poor solubility, stability, and bioavailability [75,76]. To address these concerns, within the past decade, researchers have been focusing on developing drug delivery systems (DDSs) to enhance their bioavailability, specificity, and efficacy. To achieve more efficient (or better outcomes) DDSs, biocompatible polymers (natural and synthetic polymers) have been used in designing different formats like liposomes, and nano- and microcarrier systems to deliver drugs to target sites in a sustained-release manner and enhance their efficacy [77]. Comparatively, microneedles [78] and hydrogels [79] are typically used as carriers. Various nanocarrier systems are being utilized now to deliver AODs to target specific fat depots. Some examples include targeting WAT vasculature to stimulate angiogenesis, promoting the browning of WAT [80], and targeted disruption of adipose vasculature to reduce body weight in diet-induced obesity (DIO) mice [81]. Additionally, other systems have been used to enhance the internalization and bioavailability of drugs to promote brown-specific gene expression and reduce subcutaneous adipose tissue expansion [82,83]. DDSs designed for the delivery of AODs to treat obesity in vivo models are described in Table 3.
Because the development of obesity is multifactorial, the interplay between genetic, epigenetic, and environmental factors [84], as well as modulations in the functions of genes regulating appetite and body weight are a key focus of obesity research. Therefore, gene therapy may be another viable approach to treat obesity via delivering therapeutic genes into appropriate cells, restoring their function, and maintaining energy homeostasis [85]. For example, leptin-deficient mice treated with recombinant adenovirus expressing the mouse leptin cDNA resulted in a dramatic reduction in food intake and body weight [86]. In another study, a recombinant adeno-associated virus (rAAV) vector encoding leptin triggered enhanced non-shivering thermogenic (NST) energy expenditure in brown adipose tissue (BAT) [87]. Similarly, gene editing using clustered regularly interspaced short palindromic repeats (CRISPR) systems, transcription activator-like effectors, and zinc finger nucleases [77] have resulted in reductions in inflammation, body weight, and restored hepatic steatosis in obese mice [88]. Additionally, CRISPR-mediated gene activation (CRISPRa) of Sim1 and Mc4r in haploinsufficient heterozygous mouse models reversed their obesity phenotype [89]. Although viral vector-associated delivery systems have demonstrated successful targeted delivery, they might be associated with immune response and broad viral tropism [90]. Therefore, novel approaches that will be as efficient yet mitigate undesirable side effects are highly warranted.
Given that adipose tissue in excess is the principal driver of obesity, a more comprehensive understanding of adipose tissue biology is essential to elucidate the development of innovative therapeutic strategies. In this review, we synthesize current knowledge on the heterogeneity of adipose tissue, outlining the defining characteristics and functions of each depot in both physiological and pathological contexts. Through this synthesis, we aim to integrate emerging evidence into a cohesive framework that not only deepens our understanding of adipose biology but also guides future development of targeted strategies to prevent and treat obesity.
Table 1. FDA-approved anti-obesity drugs used to treat obesity and their mode of action.
Table 1. FDA-approved anti-obesity drugs used to treat obesity and their mode of action.
Name of the DrugMode of ActionAdverse Side Effects
Phentermine HClReduces appetite and enhances metabolic rate [91].Dry mouth, insomnia, dizziness, palpitations, flushing, fatigue, and constipation [92].
OrlistatInhibits pancreatic and gastrointestinal lipases, which block the hydrolysis of triglycerides and minimize fatty acid absorption by intestinal endothelium [93].Various gastrointestinal side effects, along with oily stools, oily spotting, fecal urgency, fecal incontinence, hyper-defecation, and flatus with discharge [51,94].
LorcaserinA selective agonist of the 5-HT2C receptor, located in the central nervous system, that reduces caloric intake without affecting energy expenditure [95].Headache, nausea, and dizziness [96].
Long-term usage increases the potential signal of increased cancers and cancer-related mortality [97].
Liraglutide [An analog of glucagon-like peptide-1 (GLP-1)]Promotes weight loss by modulating appetite and enhancing satiety sensations [98].Hypoglycemia, headache, nausea, fatigue, dizziness, diarrhea, vomiting, constipation, decreased appetite, dyspepsia, abdominal pain, and increased lipase [99].
Semaglutide (An analog of GLP-1)Regulates appetite and caloric intake by targeting key neural circuits within the brain [100,101,102].Nausea, vomiting, diarrhea, abdominal pain, abdominal distension, constipation, dyspepsia, headache, fatigue, dizziness, eructation, hypoglycemia in patients with type II diabetes, flatulence, gastroenteritis, and gastroesophageal reflux disease [100,101,102].
Phentermine/TopiramatePhentermine is an appetite suppressant [99], whereas topiramate could minimize fat deposition either by stimulating energy expenditure or reducing food intake [103]. Dry mouth, insomnia, dizziness, paresthesia, constipation, and dysgeusia [99].
Naltrexone/BupropionReduction in food craving [99,104].Dry mouth, headache, nausea, dizziness, vomiting, and constipation [105].
SetmelanotideActs as an MC4R agonist [106].Injection site reactions, skin hyperpigmentation, headache, and gastrointestinal side effects [106].
Footnotes and abbreviations: 5-hydroxytryptamine 2C (5-HT2C); Hydrochloride (HCl); Glucagon-like peptide-1 (GLP-1); Melanocortin-4 receptor (MC4R).
Table 2. Anti-obesity drugs in clinical investigation.
Table 2. Anti-obesity drugs in clinical investigation.
Name of the DrugMode of ActionAdverse Side EffectsClinical Phase Completed
Tesomet (Tesofensine plus metoprolol)Induce weight loss by reducing food intake [107].Sleep disturbances, dry mouth, and headache [107].Phase 2 trial has been completed (NCT03845075) [107].
Cotadutide/MEDI0382 (dual GLP-1/glucagon receptor (GCGR) agonist)Induce weight loss by reducing food intake and increasing energy expenditure [108].Gastrointestinal adverse events, including nausea and vomiting [108].Clinical phase 2b study (NCT03235050) [109].
SAR425899 (dual GLP-1/GCGR agonist)Induces weight loss by reducing food intake and increasing satiety and energy expenditure [110].Gastrointestinal adverse events [110].Multiple-ascending-dose trials (NCT02411825).
Tirzepatide (formerly LY3298176) (Glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 receptor agonist)Promotes weight loss through a dose-dependent reduction in food intake, accompanied by measurable decreases in hunger and fullness ratings as assessed by a visual analog scale [111,112,113]Nausea, diarrhea, and vomiting [114]Phase 3 trial (NCT04660643).
Cagrilintide (amylin analog) Reduces weight by controlling appetite [115].Gastrointestinal adverse events (nausea, constipation, and diarrhea) and administration-site reactions [116].Phase 2 trial (NCT03856047).
Cagrilintide/SemaglutidePromote weight loss through multiple mechanisms that regulate energy balance, including reduced energy intake, delayed gastric emptying, and central appetite suppression [112].Gastrointestinal adverse events [117]Phase 1b trial (NCT03600480).
Arthrospira maxima intake with physical exercisePromote weight loss through several mechanisms, including inhibition of preadipocyte differentiation, reduction in de novo lipogenesis and triglyceride assembly, stimulation of lipolysis and fatty acid oxidation, and increased energy expenditure via thermogenic activation of BAT [118].No adverse effects related to were observed during the study [119].Double-blind, randomized, crossover trial (NCT02837666).
Velneperit (S-2367; type 5 neuropeptide Y receptor antagonist)It suppressed food intake [120].Nasopharyngitis, upper-respiratory infections, sinusitis, and headache [121].Phase 2 trial (NCT01126970).
Footnotes and abbreviations: Brown adipose tissue (BAT); Glp-1/glucagon receptor (GCGR); Glucose-dependent insulinotropic polypeptide (GIP); Glucagon-like peptide-1 (GLP-1).
Table 3. Drug delivery systems used to deliver AODs for treating obesity in preclinical models.
Table 3. Drug delivery systems used to deliver AODs for treating obesity in preclinical models.
Type of DDSMethods of Preparation, Conjugates, and Biocompatible
Polymers
DrugIn Vivo ModelsAdvantagesDrawbacks
Nanoparticles (NPs)PLGADibenzazepine
(a γ-secretase inhibitor)
DIO mice [83].Biocompatible and biodegradable [122].
The physicochemical properties of the NPs are easily tunable during the process of synthesis, which helps optimize drug loading and release.
The surface chemistry of the NPs can be tuned to enable targeted drug delivery while minimizing dosage requirements and associated side effects.
Enhanced drug delivery efficacy [39]
NP scale-up is difficult [39].
NPs’ size influences their biodistribution [123]
Aggregation of NPs [122].
Chitosan α-lipoic acid (ALA) and caffeineDIO Rats [124]
NPs were fabricated using soy PC, Kolliphor® HS15, αTA, and N-(methylpolyoxyethylene oxycarbonyl)-1,2-distearoyl-sn-glycero-3-phosphoethanolami -ne (DSPE-PEG5000)-maleimide. Ligand was conjugated to DSPE-PEG5000 using maleimide conjugation.Trans-resveratrolDIO mice [125]
Prohibitin-targeting peptides were conjugated DSPE-PEG5kDa using maleimide conjugation.
NPs were synthesized using egg yolk PC, cholesterol, stearyl-octa arginine, and DSPE-PEG5kDa-Peptide.
RosiglitazoneDIO mice [126]
Nanospheres were fabricated using PLGA and PVA DIO LDLR−/− mice [127]
NPs were synthesized using PLGA-b-PEG and PLGA-b-PEG-conjugated with targeted peptides (i.e., iRGD (CRGDK/RGPD/EC) or P3 (CKGGRAKDC)).DIO mice [80]
Nanocarriers were fabricated using Tween 20, PC, poloxamer Synperonic PE/F68, Glycerol monostearate and cetyl palmitate, linseed oil Oleoylethanolamide and Phenyl alaninol oleamide-PAO CapsaicinDIO Albino Swiss mice [128]
LiposomesPS and PC.IL-10DIO mice [129]Improved biocompatibility and biodegradability
Low toxicity and antigenicity.
Ability to deliver both polar and non-polar therapeutic molecules [39,122].
Reduced stability and increased drug leakage during storage
Liposomes were synthesized using PC, cholesterol, and 1,2-distearoyl-sn-glycerol-3-phosphoethanolamine-N-[poly(ethylene glycol)-2000-maleimide (DSPE-PEG2000-MAL). Liposomes were conjugated with glucagon for targeted delivery.T3Lepob mice [130]Increased risk of aggregation.
Allergic reactions.
Increased risk of phospholipid oxidation and hydrolysis [39,122].
Liposomes were synthesized using DSPC (phosphocholine), cholesterol, and PEG-2000 DSPE.Tesaglitazar (PPARα/γ dual agonists)Lepob and DIO mice [131]
Microneedle (MN) patches Methacrylated hyaluronic acid was used as a base material for microneedle patches, whereas NPs loaded in the MN patches were synthesized using dextran.Rosiglitazone DIO mice [78] Effective method for transdermal drug delivery.
Prevents gastrointestinal degradation of drugs.
Microneedle patches enable minimally invasive, patient-administered drug delivery [132].
Microneedle coatings support only minimal drug payloads.
Fragmented microneedles retained in the skin represent a potential biohazard [132].
PLGA/PLA CL316243 (β3 adrenergic receptor agonist)NIH mice [133]
HACaffeineC57BL/6J mice [134]
Capsaicin-loaded α-lactalbumin nano micelles were delivered to the adipose tissue using HA MN patches.CapsaicinDIO mice [135]
HydrogelsPLGAEpigallocatechin gallateDIO mice [136]Polymers facilitate controlled, sustained drug release through their inherent biocompatibility and biodegradability.
Injectable hydrogels provide minimally invasive administration [137,138,139].
Low mechanical strength results in uncontrolled, rapid drug release.
The hydrophilic properties restrict hydrophobic drug encapsulation and delivery.
Lack of polymer and drug interactions [140,141].
Footnotes and abbreviations: α-lipoic acid (ALA); Diet-induced obesity (DIO); Interleukin (IL); Low-density lipoprotein receptor (LDLR); Nanoparticles (NPs); Phenylalaninol oleamide (PAO); Phosphatidylcholine (PC); poly(lactide-co-glycolide) (PLGA); Peroxisome proliferator-activated receptor gamma (PPARγ); Phosphatidylserine (PS); polyvinyl alcohol (PVA); alpha-tocopherol acetate (αTA).

3. Adipose Tissue: Distribution and Types

Adipose tissue is a specialized organ found in all mammals, as well as some non-mammalian species [142,143]. In mammals, adipose tissue congregates into well-defined regions referred to as fat depots and is dispersed across and within various parts of the body. Adipose is generally categorized into two major depots based on their anatomical location: subcutaneous (surface, underneath the skin) and visceral (deeper, surrounding or within the main body cavities) [144]. In small mammals like rodents, a commonly used preclinical model of obesity research [145], anterior subcutaneous fat includes the inter-/subscapular, superficial cervical, and axillo-thoracic regions, while posterior subcutaneous fat is localized in the inguinal, gluteal, and dorso-lumbar areas. Meanwhile, visceral adipose is found within the abdominal cavities and thorax of these mammals [143]. Conversely, BAT in rodents includes the cervical, perirenal, supraclavicular, paravertebral, axillary, and inter/intrascapular depots [145,146]. In comparison, WAT distribution in humans also spans across the body and includes the two major depots previously discussed: subcutaneous (intra-muscular, abdominal, gluteoformal) and visceral (mesenteric, gonadal, pericardial, retroperitoneal, and omental) [147]. However, BAT tends to be less static in humans. During infancy, BAT resides in the intrascapular (main depot), cervical, and perirenal regions, then later regresses and forms in the cervical, supraclavlicar, axillary, and along the spinal column [146]. Over the course of early development, BAT is regarded highly for its crucial role in core-body temperature maintenance. However, beyond infancy, it was long thought that BAT offered little to no significance in adulthood. This assumption has since been reconsidered over the last two decades as several studies have identified the presence of active BAT in adults [148,149,150]. Adult BAT is allocated both viscerally and subcutaneously. Visceral brown fat is periviscus, perivascular, or found surrounding solid organs, while subcutaneous brown fat is positioned beneath the clavicles, within the axilla and anterior abdominal wall, and between the supraclavicular fossa and anterior cervical muscles [151]. Each depot’s phenotype is primarily reflected by the ratio of white to brown adipocytes; however, a unique phenomenon known as “browning,” or “beigeing,” the conversion of white adipocytes to brown-like adipocytes (also referred to as beige, brite, or taupe), underscores the organ’s morphological plasticity and potential to alter its native function [152,153].
White adipocytes are distinguished by their voluminous unilocular lipid droplet and compressed nucleus with low mitochondrial content. On the other hand, brown adipocytes maintain smaller, multilocular lipids with substantially larger mitochondria that are abundant and equipped with the brown hallmark protein, uncoupling protein 1 (UCP1). UCP1 permits the uncoupling of oxidative phosphorylation, thus allowing for heat dissipation and characterization of BAT’s thermogenic capacity [152,153]. Conversely, WAT does not maintain the same thermogenic integrity and instead serves as a major site for energy storage [153]. Importantly, the emergence of brown-like adipocytes, often referred to as beige/brite, basally resemble and reside within WAT, yet respond to external stimuli that promote the induction of classical thermogenic gene markers [154]. This observed phenomenon, combined with its known associated metabolic benefits, has continued the renewed interest in BAT and of browning as a therapeutic approach for obesity and its associated metabolic disorders. Furthermore, two additional types have been acknowledged in the literature, although far less characterized, pink and yellow. Briefly, pink adipocytes, which arise by the transformation process of “pinking,” convert white adipocytes in the mammary glands into milk-producing/secreting epithelial cells during pregnancy and lactation [155]. Yellow adipose tissue (YAT) has been described as a fat pad that resides within the bone marrow, a depot that has both WAT and BAT characteristics, and, further, is speculated to play a role in systemic energy metabolism [156,157]. A precise characterization of the various adipose tissue types—both independently and in terms of their potential interdependence—will undoubtedly transform our understanding of the adipose organ as a whole. Accordingly, the following sections of this review will examine each adipose tissue type and its contribution to metabolic homeostasis in both health and disease.

4. White Adipose Tissue (WAT)

4.1. Energy Metabolism

The reputation of white adipose tissue has widely varied, spanning from an early write-off as an inert storage vessel to its more iniquitous interpretation as the central driver behind the obesity epidemic. However, through decades of research, WAT is now acknowledged as an essential metabolic headquarters that integrates a variety of physiological processes to support whole-body homeostasis. Therefore, in order to avoid historical faux pas, in this section, we will attempt to cover all key attributes of WAT, beginning with its earliest recognition—as an energy reservoir.
A remarkable feature of adipose tissue in general is its ability to expand. White adipocytes, in particular, are proficient, yet variable expansion artists as their diameters have been recorded from low 20 µm to upper 100 µm. This fluctuation has been associated with BMI, energy balance, depot/location and may be affected by certain metabolic diseases such as obesity and diabetes [158,159,160]. Notably, adipose tissue normally expands by either hyperplasia, hypertrophy, or both, and although each is a distinct mechanism, both processes remodel white adipocytes’ major organelle, the lipid droplet [161]. While lipid droplets vary in size across cell types, they share a common architecture: a heterogeneous interior of neutral lipids encased by a phospholipid monolayer that is associated with various proteins [162].
In white adipocytes, lipid content primarily resides as molecules of TAG, which are assembled in the last steps of de novo lipogenesis (DNL) and involve the activities of four acyltransferases to esterify free fatty acids to a glycerol backbone [163,164]. Modulation of these adipose acyltransferases has been shown to impact adipocyte development, WAT’s ability to store lipid, and overall energy metabolism [165,166]. For instance, mice deficient of glycerol-3-phosphate acyltransferase (GPAT) 3, the first enzyme of DNL, exhibited increased energy expenditure, lower body adiposity, and resistance to diet-induced weight gain [167]. However, these outcomes were expected, as previous in vitro work had shown that GPAT3 helps facilitate adipocyte differentiation and GPAT3 knockdown hinders the expression of genes related to fuel uptake and lipogenesis [168]. In line with these findings, Sim and colleagues demonstrated that GPAT3 moderately promotes 3T3-L1 adipocyte differentiation through its co-interactions with the subsequent 1-acylglycerol-3-phosphate-O-acyltransferase (AGPAT) 2 and its scaffolding protein, seipin [169].Thus, disturbances in this signaling pathway could impair normal adipocyte differentiation, leading to pathological conditions such as lipodystrophy.
Notably, mutations of either are notoriously linked to congenital generalized lipodystrophy, an autosomal recessive disorder characterized by the extreme lack of body fat and manifestation of metabolic disturbances [170]. In patients with lipodystrophy, lipids are redirected to other organs, including the liver and skeletal muscle, provoking the development of clinical abnormalities, such as non-alcoholic fatty liver disease, steatohepatitis, and insulin resistance [171,172,173]. Congenital generalized lipodystrophy emphasizes the importance of WAT lipid storage to whole-body homeostasis. Without an energy safe zone, nomadic lipids will be forcibly redirected to organs that are less equipped to handle their accumulation. Phosphatidic acid, the yield of AGPAT, is dephosphorylated by the magnesium-dependent phosphatidate phosphatase lipin 1 to form the last intermediate before TAG formation [174]. Notably, regulating the expression of lipin-1 can adopt either extreme of adiposity (obesity or lipodystrophy) [175]. For instance, while lipin-1-deficient mice fail to appropriately store TAG in adipose depots and are resistant to diet-induced obesity [176,177],, transgenic mice overexpressing lipin-1 exhibit accelerated weight gain and increased fat mass compared to wild-type mice fed the same high-fat diet [175]. In another transgenic model, adipose-specific overexpression of lipin-1 protected mice from hepatic injury induced by alcohol consumption [178]. Plausibly, overexpression of lipin-1 restored DNL and inhibited alcohol-induced lipolysis in WAT [178]. However, it was recently proposed that changes in lipin-1 expression may be less influential in humans. For instance, patients with significantly less lipin-1 exhibit less PAP activity; however, WAT development and lipid storage composition were normal [179]. Unexpectedly, others have reported that human adipose lipin-1 expression does correlate with metabolic parameters such as insulin sensitivity and BMI status [177,180,181]. Altogether, these findings suggest that additional factors may influence the discrepancies observed between rodent and human data with respect to the role of lipin-1 in energy metabolism.
DNL concludes with the activity of acyl-coenzyme A: diacylglycerol transferase (DGAT) and the formation of a TAG molecule [182]. Mammals possess two isoforms of DGAT: DGAT1 and DGAT2. Harris et al. demonstrated that adipocytes with a single deletion of either isoform were still able to sufficiently synthesize TAG and form lipid droplets, yet with a double knockout (KO) approach, synthesis activity was significantly reduced, and cells were severely devoid of lipid content [183]. Intriguingly, double KO macrophages were able to still form sterol ester-containing lipid droplets in the presence of cholesterol-rich lipoproteins, indicating that other mammalian cells may not be as heavily reliant on DGAT for lipid storage as adipocytes [183]. Although some studies concur that DGAT1 and 2 may compensate for one another upon each other’s absence, distinctive roles independent of lipid storage have also been reported [183,184,185]. For example, DGAT1 was demonstrated to play a protective role in averting adipocyte ER stress and lipotoxicity in response to high-fat feeding or stimulated lipolysis [185,186]. DGAT2 was shown to profoundly affect basal triglyceride metabolism, energy and cutaneous homeostasis, and postnatal survival [184]. On the other hand, whole-body Dgat1 knockout mice are viable, maintain triglyceride biosynthesis, show increased energy expenditure, and exhibit enhanced insulin and leptin sensitivity [187,188,189]. Hence, DGAT1 and 2 might exhibit compensatory behavior occasionally but are by no means completely monotonous. In light of the studies above of the dynamic nature of WAT, lipid storage stands out as a vital gatekeeper of physiological homeostasis, challenging its historical reputation for being inert.
By nature, achieving any type of “balance” involves a counter; therefore, lipid storage is only half the narrative. WAT lipolysis involves the functioning of the key enzymes hormone-sensitive lipase (HSL) and adipose triglyceride lipase (ATGL), as they account for more than 95% of TG hydrolase activity in WAT [190]. It is well established that nutritional status, neuroendocrine inputs, and transcriptional regulators can influence the activities of HSL and ATGL largely by governing their intracellular localization and protein–protein interactions [191,192,193]. Briefly, canonical lipolysis begins with ATGL hydrolyzing TAG to yield an FFA and diacylglycerol (DAG). HSL then cleaves DAG to produce monoacylglycerol and another FFA. Subsequently, monoacylglycerol lipase breaks the remaining ester bond to release the last FFA from the glycerol backbone. FFAs then circulate around the body and are delivered to tissues for energy utilization. Importantly, intermediates of this process—DAG, monoacylglycerols, and FFAs—are also used as signaling messengers in various metabolic processes [194].
However, like lipogenesis, the regulation of HSL or ATGL expression impacts the efficiency of this counterbalance to maintain energy metabolism. Atgl whole-body-knockout mice exhibit significantly reduced lipolytic activity, mild hypertrophic obesity, and increased TG deposition in the heart, leading to cardiac dysfunction [195]. Consistently, primary triglyceride deposit cardiomyovasculopathy is characterized by mutations in the ATGL-encoding gene, PNPLA2, where ATGL deficiency fosters energy dysregulation and lipotoxicity of the myocardium and vasculature, consequently leading to heart failure in humans [196,197]. In an adipose-specific Atgl-KO model, basal lipolysis was significantly reduced, and when stimulated with a 48 h fast, mice became lethargic and hypothermic. These manifestations were arguably due to the lack of available substrate for energy production [198]. Likewise, HSL-deficient mice exhibit defective lipolytic activity and excess DAG accumulation yet seem to be resistant to genetic or diet-induced obesity [199,200,201]. But how can the consequences of one’s deficiency yield nearly opposite results to the other’s, when both enzymes appear to converge on the same pathway?
Whereas ATGL deficiency blocks the initial step of TAG hydrolysis, leading to fat entrapment, energy shortage, and lipid accumulation that promotes adipose expansion, HSL deficiency triggers a distinct compensatory response. Although HSL loss hinders lipolytic activity, it also alters the expression of genes governing adipogenic (e.g., peroxisome proliferator-activated receptor gamma (Pparg)) and lipogenic metabolism (e.g., Gpat3, Dgat1, Dgat2) in WAT [200,201], partly through the loss of intrinsic ligands required for PPARγ activation [202]. Consequently, HSL ablation not only disrupts lipid mobilization but also impairs adipocyte storage and hyperplasia—processes that can drive WAT expansion and obesity. However, as previously mentioned, when WAT fails to safely store lipid, excess FFAs are diverted to peripheral tissues, promoting ectopic fat accumulation and metabolic stress. Proper regulation of lipogenic and lipolytic enzymes is therefore essential not only for maintaining energy homeostasis but also for preserving WAT’s systemic influence, such as through its endocrine function.

4.2. Endocrine Function

4.2.1. Leptin

It has been thirty years since the identification of the secretory factor, leptin [203]. Leptin’s mid-90s debut primed WAT’s now-accepted role as an active endocrine organ, broadening its functional repertoire. However, studies 40 years prior to the leptin era helped pave the way for its present-day recognition [204,205]. Since leptin’s discovery, decades of research have brought to light its involvement in a wide span of physiological processes, including, but not limited to, appetite control, energy metabolism, growth and development, immune support, inflammation, and bone health [206,207]. For instance, case–control studies have shown that serum leptin levels are significantly elevated in patients with rheumatoid arthritis, an inflammatory autoimmune disease moderately associated with obesity [208,209]. Leptin promotes the secretion of pro-inflammatory cytokines, which in turn enhance leptin release from the adipose tissue, establishing a positive, yet unfortunate, feedback loop [210]. However, beyond its usual roles, some evidence suggests leptin may even be able to predict the future… well, sort of. Some studies suggest that leptin is critically involved during postnatal development and that ensuring this hormone’s sufficiency can predispose individuals to a healthy phenotype. This discrete susceptibility to a ‘healthier, happier’ adulthood is a concept being referred to, more specifically in this setting, as nutritional or metabolic programming [211,212]. Early-life nutrition experts have suggested that breastfed infants are at a lower risk to develop childhood obesity in comparison to non-breastfed babies [213,214]. Human breast milk is known to contain a variety of essential nutrients, among them the neurotrophic leptin [215]. However, this curated confidence that ‘breast is best’ is frequently challenged, given the inherent complexity of infant/child development and maternal variability [211]. Preclinical trials remain just as perplexed due to their own varied results. Some rodent studies have indicated that the majority of neonate leptin is exogenously and maternally acquired [216] and oral administration of leptin exhibits both short-term and long-term benefits in regard to a balanced caloric intake and adult bodyweight [217,218]. In fact, murine neonates supplemented with leptin during the lactation period were shown to be protected from diet-induced adult obesity and fat accumulation [218]. Alternatively, in a recent report, the attenuation of leptin improved adult metabolism of overnourished neonate mice [219]. Notably, in cases of obesity or diabetes, it is well-established that levels of adipokines (e.g., leptin, resistin, visfatin) are elevated, which can set the stage for leptin resistance [220]. It has been further observed that leptin antagonism enhanced hypothalamic leptin sensitivity [220], implying that metabolic programming is just as reliant on proper signaling and reception as substrate availability. Therefore, breast milk’s role as nature’s cure to obesity remains to be determined. Although leptin research is emphasized, white adipose tissue is known to supply the body with an abundance of other adipose-derived hormones, consequently termed ‘adipokines’ that regulate various aspects of normal physiology.

4.2.2. Adiponectin

The discovery of adiponectin closely followed that of leptin [221]. The main physiological function of this adipokine involves its relationship with glucose metabolism and insulin sensitivity [222]. These associations were first highlighted by research conducted in the early 2000s, when Berg et al. found that injecting mice with adiponectin was able to lower blood glucose in wild-type and diabetic mouse models independent of insulin [223]. Similarly, physiological doses of adiponectin, in combination with leptin, fully reversed insulin resistance in lipodystrophic mice while independent dosing of each adipokine was only partially successful [224]. These preliminary discoveries not only sparked a new era of enthusiasm in diabetic research but also propelled the exploration of adiponectin’s potential in other areas of homeostasis. Right on track and three decades later, adiponectin has been investigated in regard to both pro- and anti-inflammatory processes [225], metabolic reprogramming in cancer [226], lipid metabolism, and considered as a prospective therapeutic target for cardiovascular health [227,228].
Because adiponectin levels fluctuate with metabolic state, including obesity, it is often used as a biomarker of metabolic dysfunction [229]. Accordingly, adiponectin is notably reduced in individuals with T2DM [230] and cardiometabolic disorders [231]. Furthermore, therapies used to treat obesity-related diseases, including those mentioned above, have targeted adiponectin regulation and/or signaling mechanisms [232]. However, higher concentrations do not necessarily translate to better outcomes. The adiponectin paradox describes cases, particularly in cardiovascular disease, where elevated circulating levels of both adiponectin and leptin correlate with adverse outcomes rather than the anticipated protective effects. Impaired hepatic or renal clearance and diminished adipose tissue quality may contribute to these elevated levels without the expected metabolic benefits [233]. Therefore, attributing fixed outcomes to specific adipokines is overly simplistic, as even those traditionally viewed as beneficial, such as adiponectin, should be interpreted within their physiological context and on a case-by-case basis.

4.2.3. Resistin

Resistin, the adipokine with the largest contrast to adiponectin’s metabolic effects, is a polypeptide hormone secreted from visceral obese adipose tissue [234]. In rodent models, resistin levels are inversely correlated with tissue insulin sensitivity and overall metabolic function [235,236]. Experimentally induced hyper-resistinemia causes hepatic insulin resistance and dysregulated glucose production [236,237], while transgenic overexpression impairs glucose metabolism in skeletal muscle [238]. However, as with all great scientific breakthroughs, the key consideration is clinical translatability. Therefore, when translating these findings to humans, resistin is interestingly produced by macrophages within adipose tissue rather than the adipocytes themselves [239,240]. Human resistin is strongly influenced by inflammatory stimuli, which elevate resistin and upregulate pro-inflammatory cytokines, positioning it as an active modulator of inflammation [241,242,243]. Despite this difference in cellular origin, macrophages are intrinsic components of adipose tissue as a whole [244], and resistin levels remain correlated with obesity in both humans and rodents [245] supporting its potential as a target for therapeutic or preventative strategies against metabolic disease.

4.2.4. Omentin-1

Omentin, an adipokine named for its central adipose depot specificity [246], contrasts with resistin by exerting anti-inflammatory effects [247]. Circulating omentin levels are reduced in obesity and diabetes [248,249], and low omentin-1 has been identified as a potential predictor of gestational diabetes and T2DM [250]. The COVID-19 pandemic has highlighted the relevance of anti-inflammatory adipokines in disease outcomes. As such, patients with SARS-CoV-2 infection exhibit reduced serum omentin and chemerin levels, likely reflecting the heightened inflammatory state and the loss of their protective functions [251]. Independent of infection, omentin supports cardiovascular health through the promotion of vasodilation, endothelial protection, and anti-atherogenic effects [252]; a critical consideration given COVID-19’s association with long-term cardiovascular risk [253]. Therefore, omentin may be critical to both the onset and progression of obesity-related complications, including the heightened vulnerability to diseases such as COVID-19.

4.2.5. The Adipose Secretome Beyond Adipokines

Adipokines have been widely studied in both health and disease, as evidenced by decades of comprehensive reviews [254,255,256]. In fact, according to Kirichenko et al., over 600 adipokines have been identified as of 2022, which has given the field invaluable insight into their roles within and outside of the adipose organ as well as whole-body metabolism [257]. However, it is well-known that WAT’s secretome extends beyond peptide-based hormones [258]. For example, lipokines are bioactive molecules secreted by the adipose tissue and act as signaling messengers across the body. Cao et al. demonstrated that C16:1n7-palmitoleate regulates systemic glucose metabolism by acting on the muscle as an insulin-sensitizing hormone [259]. More recently, a longitudinal analysis also determined that plasma palmitoleate plays a beneficial role in glucose homeostasis and insulin sensitivity in humans by cross-communicating with liver and pancreatic β-cells [260]. Other lipokines, such as palmitic acid hydroxy stearic acids (PAHSAs), particularly 5-PAHSA and 9-PAHSA, possess anti-inflammatory and anti-diabetic effects due to their ability to regulate insulin action and glucose transport [261,262]. It has been theorized that these endogenous lipids may serve as a new avenue to treat various metabolic and immune disorders, although some reports suggest otherwise [263].
Moreover, investigating the mechanisms of biomolecule transport may be just as important as studying their roles in health and disease. For example, adipose-derived extracellular vesicles (AD-EVs) have become clinically relevant due to several of their innate properties, such as low immunogenicity and biocompatibility. As such, these exosomes have been leveraged in translational medicine applications, including skin grafting, wound healing, and drug delivery [264,265]. In addition, AD-EVs have also been implicated as biomarkers for several metabolic disorders, including obesity, T2DM, cardiometabolic disease, insulin resistance, and various cancers [266]. Studies elucidating the potential role of AD-EVs in cancer progression have noted a dual function that is dependent on the cargo they deliver. For instance, while some miRNAs packaged inside may promote tumor progression and malignancy, others have been shown to have protective anti-tumor effects [267]. Furthermore, owing to the intrinsic role of EVs in intercellular communication, cancer outcomes, such as cancer cachexia, have been shown to be influenced by crosstalk mediated by extracellular vesicles exchanged between adipose and tumor tissues [268]. Clearly, WAT exhibits a highly dynamic endocrine function, and advancing therapeutic strategies for metabolic disease will require understanding not only the various biomolecules it secretes but also how they are packaged, trafficked, and received by target tissues.

4.3. Additional WAT Functions

In addition to energy metabolism and endocrine function, WAT has been demonstrated to serve several non-metabolic roles. For instance, dermal white adipose tissue (dWAT), a distinct category of the subcutaneous white adipose [269,270,271] found in mice and humans, provides mechanical support/cushioning, insulation, and immunity. The crude assumption that dWAT is closely related to cutaneous function and homeostasis is not necessarily overreaching. As such, dermal adipose has been shown to be involved in thermoregulation in a variety of ways. Mice with a genetic depletion of syndecan-1, a heparan sulfate proteoglycan important during tissue regeneration, were shown to exhibit an abnormal phenotype that lacked intradermal fat. Subsequently, these mutant mice were chronically cold-stressed and had increased expression of BAT markers (UCP1 and p38-α) even at thermoneutrality [272,273]. Additionally, dWAT of mice subjected to an environmental challenge or genetic manipulation was shown to thicken in order to preserve heat and maintain body temperature [274]. Interestingly, a rapid expansion of the dermal fat layer was also observed in response to a microbial infection by Staphylococcus aureus, thus indicating a plausible role for dWAT in immune response [275].
Skin is largely known to provide a protective interface that defends vital internal tissues and organs from the external environment. However, upon injury, the integumentary system is also responsible for conducting a proper immune response that supports wound healing and repair [276,277]. Dermal adipocytes have been demonstrated to contribute to wound healing of the skin by activating essential inflammatory responses such as macrophage recruitment during the early phases of repair. Moreover, the lipolytic activity of dermal adipocytes was found to influence macrophage abundance and infiltration efficiency at the site of injury [278]. This is further supported by evidence exhibited by AZIP mutant mice. Besides the classical metabolic impairment presented by AZIP mutants, Schmidt and Horsley reported that these mice, which are deficient in mature white adipocytes, including in dWAT, exhibited defective wound healing and dermal remodeling processes through altered recruitment of fibroblasts to the wound bed [279]. Therefore, dWAT is a distinct subset of white adipocytes that highlights WAT’s role in providing mechanical support and immune health, complementing its more commonly recognized functions in metabolism and hormonal secretion.
Overall, WAT is not inherently harmful to the body. In fact, WAT accounts for roughly one-fourth of a healthy individual’s total body weight and is clearly necessary for normal physiological function. However, it is also undeniable that WAT in excess, such as what is seen in overnutrition like obesity, can lead to metabolic stress and dysfunction. Even individuals with excess adiposity in the ‘right places,’ conventionally referenced as metabolically healthy obesity, and who may be of normal weight, have been shown to have a higher cardiometabolic risk [280]. Therefore, strategies to eliminate excess WAT are warranted, with the field exploring WAT’s intrinsic plasticity as a means to reverse excess WAT accumulation.

5. Brown Adipose Tissue (BAT)

5.1. Thermoregulation

Although the renewed interest in BAT has largely stemmed from global concerns over obesity and its recognized therapeutic potential, this focus often overshadows some of BAT’s more fundamental value. Historically, brown adipose tissue was first described in the mid-16th century by Conrad Gessner, who termed it the glandula hibernica (“hibernating gland”) based on its anatomical localization in the interscapular region of hibernating marmots (Marmota marmota). Subsequently, this fat depot has been referred to by several other names, including the oil gland, the organ of hibernation, and, notably, brown-colored fat because of its characteristic pigmentation [281,282,283]. In a sense, hibernation is nature responding to ‘fight,’ versus ‘flight’ (e.g., migration), under severe thermal challenges, and centuries following Gessner’s interpretations, BAT was recognized as a thermogenic organ that aids in many inherent processes such as the hibernator’s torpor–arousal cycles [282,283]. Although hibernation is not pertinent to humans, the core principle remains—that being thermoregulation, or simply put, maintaining core-body temperature. The human body is programmed to be maintained at ~37 °C, give or take 0.5 degrees. Thermoreceptors across the body will communicate with the hypothalamus in order to integrate information and elicit an appropriate response [284]. Upon cold challenge, adult humans primarily rely on rapid, involuntary contractions of the skeletal muscle (shivering thermogenesis) to produce heat and reestablish temperature homeostasis, a luxury that newborns cannot yet rely on [285]. Instead, neonates are dependent on the non-shivering thermogenic capacity of BAT to adapt to the extrauterine environment [286]. BAT NST occurs by a neurophysiological mechanism that begins with the recognition of a stimulus. After birth, without corrective measures, newborns are at risk of hypothermia due to evaporative heat loss through their skin [287,288,289]. This immediate and continued loss of heat over the course of the infant’s first weeks of life initiates physiological responses mediated by hypothalamic neural signaling, which prompts sympathetic activity in BAT [290,291]. BAT receives information and direction from the output of sympathetic fibers, such as norepinephrine. From a more ‘topical’ perspective, one of BAT’s primary characteristics is its extensive innervation and vascularity. This high innervation functions as a critical component of the NST regime, which is evident based on BAT denervation studies that report that unilateral denervation greatly diminishes or completely blocks typical cold-induced effects [292]. Norepinephrine binding to β3-adrenergic receptors causes intracellular biochemical pathways such as protein kinase A- cyclic adenosine monophosphate (PKA-cAMP) to become activated and increase lipolysis for substrate availability [293]. Additionally, elevation of cAMP induces other signaling cascades such as the p38 MAPK pathway, which phosphorylates nuclear factor family members, namely peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) and activating transcription factor 2, to transactivate the Ucp1 promoter [294]. Ultimately, these effects are funneled down to a single organelle: the mitochondria. BAT is known to be enriched with mitochondria that are equipped with UCP1, which will recycle protons back into the matrix to generate heat at the expense of the energy equivalent, adenosine triphosphate [295,296]. Over the years, four proposed models have attempted to explain how UCP1 facilitates proton leakage: (1) H+ channel, (2) OH- channel, (3) H+ buffering model, and (4) fatty acid-cycling model. Unfortunately, due to the lack of a direct method to study UCP1 function, the exact mechanism remained elusive [297]. However, a research group from the University of California, San Francisco, utilized a patch-clamp method to directly measure proton currents across the inner mitochondrial membrane of BAT mitochondria. Their patch-clamp analysis suggested that UCP1 acts as a long-chain fatty acid (LCFA)–/H+ symporter that simultaneously transports LCFA anions and H+ across the inner membrane. LCFA anions were determined as the principal substrates of UCP1, while H+ are dependent on LCFA anions, and their pKa, to be shuttled from one side to the next [298]. This proposed shuttling mechanism offers a convincing model for how UCP1 transforms the proton motive force into heat and, moreover, how newborns defend their body temperature postpartum [299]. Of note, additional NST mechanisms that are UCP1-independent have been summarized elsewhere [300,301]; although, briefly, the notion of UCP1’s dispensability in adipose was highlighted by the peculiar findings of the Kozak group, who demonstrated that Ucp1 KO mice on a hybrid background were able to tolerate cold exposure with gradual acclimation [302]. While many studies have corroborated the previous findings, others have gone on to identify Ca2+-cycling and creatine substrate-cycling pathways as thermogenic UCP1-independent mechanisms [285,300,303]. In fact, some studies have suggested that sarcolipin-based thermogenesis in the skeletal muscle may be able to compensate for the loss and/or impairment of BAT function [304,305].

5.2. Secretion

While WAT has been established as a major secreting organ of the body, it is becoming more apparent that BAT may also possess a secretome that can influence (i) itself (autocrine), (ii) local/surrounding (paracrine) tissues, and/or (iii) more distant (endocrine) target sites [306,307]. The community often has a candid sense of humor when it comes to nomenclature, and the naming of BAT-derived factors was no exception. Therefore, molecules secreted from brown fat that regulate metabolism are commonly referred to as ‘batokines’ [307]. Despite this standard definition, there is ongoing debate about the exact criteria for a molecule to qualify as a true batokine. This dispute has been more thoroughly addressed elsewhere [306]. However, briefly, several discussions regarding this topic have included [i] the type of biomolecule (e.g., peptide v. non-peptide); [ii] brown fat exclusivity; [iii] preferential secretion (e.g., in comparison to specifically WAT); and [iv] explicit activated/stimulated release [306,308]. Due to this discordance, all relevant studies in this section will have some mention of their overall experimental design. Moreover, in recent decades, the field has rapidly identified numerous batokine candidates, with extensive coverage provided in other reviews [307,308,309]. While batokines are peripheral to our main focus, they are redefining the landscape of brown adipose tissue biology, revealing an unexpected control over its development, activity, and thermogenic capacity.

5.2.1. FGF21

Of BAT’s numerous secretory regulators, fibroblast growth factor 21 (FGF21) was one of the first to be recognized within this context. Although FGF21 is predominantly secreted by the liver [310], some studies have shown that cold exposure or adrenergic stimuli can induce the expression of FGF21 in other tissues, including adipose tissue [311]. For instance, around the time of BAT’s functional (re)discovery [148,149,312], Chartoumpekis et al. found that short-term cold exposure and/or adrenergic stimulation increases the expression of FGF21 in BAT but not in the liver. Additionally, it was noted that plasma levels of FGF21 remained unaltered in response to short-term (4 h) exposure, and it was speculated that cold-induced BAT FGF21 may benefit itself in an autocrine manner [313]. This assumption was not too speculative, as Hondares et al. had previously demonstrated that injecting fasting newborn mice with FGF21 activated BAT thermogenesis and raised body temperature. This was evidenced by the upregulation of several key thermogenic and oxidative BAT markers like UCP1, PGC-1α, and cytochrome c following injection [314]. On the other hand, Hondares and colleagues later found that rodents enduring longer periods of cold exposure exhibited increased plasma levels of FGF21, leading the authors to consider BAT as a major source of systemic FGF21 upon thermogenic activation [315]. However, some studies have contested the notion that stimulated BAT significantly contributes to the systemic pool of FGF21. Instead, using tissue-specific FGF21 KO models, Ameka et al. and Abu-Odeh et al. found that levels of circulating FGF21 during sympathetic stimulation are primarily determined by the liver’s production despite an observed increase in expression in adipose tissues [316,317]. Regardless, FGF21 is a notable hormonal regulator that has been associated with several metabolic processes, such as lipid metabolism, glucose handling, WAT browning, and, in particular, BAT activity in both mice and humans [318,319,320]. In a randomized controlled trial, Lee and colleagues successfully translated some of the previously mentioned preclinical findings [313,315] into a human context. These authors found that in healthy adults, plasma FGF21 follows a diurnal rhythm and mild-cold exposure augments its circulation levels, which affected the predicted degree of cold-induced thermogenesis (CIT) and lipolysis [321]. In following studies, two independent groups exploring the direct relationship between human BAT activity and circulating plasma levels of FGF21 demonstrated that levels were indeed correlated with BAT activity during cold exposure [322,323]. However, it was more recently observed that cold-induced levels of FGF21 were robustly associated with BAT volume but not necessarily with its thermogenic activity [324]. These observations may be partially explained by Moure et al.’s findings that the thermogenic response of adipose tissue depends on β-klotho levels, a required co-receptor of FGF21 actions. Suppression of β-klotho was shown to alter BAT’s response to chronic cold exposure, lowering normally surged protein levels of UCP1, despite increases in hepatic FGF21 circulation [325]. Conversely, adipose-specific overexpression of β-klotho was shown to increase endogenous FGF21 sensitivity as well as protect mice from DIO. The attenuation of DIO-related metabolic dysfunction was correlated with the induction of several thermogenic genes, namely Pgc1a, type II iodothyronine deiodinase (Dio2), Solute carrier family 2, facilitated glucose transporter member 4 (Slc2a4), and Ucp1 [326].

5.2.2. BMP(s)

Several members of the transforming growth factor β (TGF-β) superfamily, including bone morphogenetic proteins (BMPs), have been implicated across various stages of adipose tissue development. For instance, BMP 2 and 4 are recognized for their role in mesenchymal stem cell commitment towards the adipogenic lineage [327,328]. Notably, other BMPs have been further reported to influence phenotypic fate. As such, BMP 7 is shown to promote preadipocyte commitment towards the brown fat lineage [329]. Uniquely, in comparison to other BMPs, BMP 7 markedly induced the brown hallmark marker, UCP1, as well as other brown fat-specific genes [329]. Although more controversial, some studies have suggested BMP 4 imparts similar effects. For example, Xue et al. pretreated pluripotent C3H10T1/2 cells with BMP 4 or 7 and found that both activated a full brown-adipogenic program, inducing or upregulating gene expressions related to early brown-fat development, thermogenesis, and mitochondrial biogenesis [330]. Elsen and colleagues similarly demonstrated that the independent exposure of primary human adipose stem cells to either BMP leads to the induction of Ucp1 expression and reduction in the white-specific marker, transcription factor 21 (TCF21) in primary human adipose stem cells (hASCs) from subcutaneous adipose tissue [331]. Moreover, it was also demonstrated that BMP 4, but not BMP 7, is secreted from fully differentiated human adipose stem cells [331]. Accordingly, it had been previously suggested that secreted BMP 4 from mature adipose may act in a paracrine manner to promote the adipogenic commitment of precursor cells [332]. A possible explanation for the lack of BMP 7 secretion observed in the previous study could be the requirement of a specific stimulus. Boon and colleagues proposed that positive effects associated with BMP 7, such as BAT activation or recruitment, may be contingent upon sympathetic activation. These authors found that mice treated with BMP 7 and housed at 21 °C exhibited an increased total energy expenditure, BAT-specific gene profile, and BAT mass. However, these effects were blunted in treated mice kept at thermoneutrality, 28 °C [333]. BMP8B, a BMP predominantly expressed in BAT [334], was also found to be responsive to thermogenic stimuli and to directly regulate thermogenesis by sensitizing BAT’s peripheral response to adrenergic input [335]. Pellegrinelli et al. corroborated previous observations by demonstrating BMP8B’s involvement in adrenergic-induced neurovascular network remodeling [336]. Before interest in BAT’s potential for combating obesity and its related disorders emerged, it is important to recall that one of BAT’s more fundamental roles was understood to be thermoregulation, specifically in newborns (discussed in the following sections). Therefore, unsurprisingly, in a recent study examining the functional link between human newborn temperature regulation and BAT thermogenesis, it was determined that BMP8B may be involved in neonatal brown-fat adaptation to cold exposure and their overall thermoregulation [337].

5.2.3. Negative Regulators

While most batokines are associated with promoting BAT development or activity, others have been demonstrated to have opposing effects. For instance, the cleaved, secreted form of the LDL receptor relative, LR11, was shown to inhibit thermogenic pathways by disrupting BMP/suppressor of mothers against decapentaplegic homolog (SMAD) signaling. It was suggested that this mechanism is purposeful for preventing excessive energy expenditure during increased thermogenic activity [338]. Endocannabinoids, endogenous lipid-based neurotransmitters [339], have been found to act as autocrine factors that negatively regulate β3-adrenoceptor (β3-AR) -induced BAT activation by suppressing required levels of cAMP [340]. Conversely, Boon et al. demonstrated that blocking the cannabinoid 1 receptor, endocannabinoids’ main receptor that is highly expressed in BAT, induces brown-fat activation, potentially by enhancing cAMP/PKA signaling [341]. Similarly, obstructing the activin receptor IIB, a known integrator of myostatin and other TGFβ-related ligand signaling, was also shown to activate brown adipocyte differentiation and thermogenesis through the inhibition of Smad3 signaling [342]. Notably, myostatin potently downregulates the expression of several of brown adipocyte-related genes, such as PR domain containing 16 (Prdm16), Ucp1, and Pgc1a. These effects were due to myostatin’s ability to induce Smad3 phosphorylation and further the stabilization of β-catenin, a known inhibitor of adipogenesis [343]. Of note, the activity of β-catenin is initially mediated by secreted glycoproteins, collectively referred to as Wnts. Wnt ligands bind to Frizzled receptors, leading to the stabilization and release of β-catenin from the destruction complex. This release allows β-catenin to further modulate adipogenic gene expression [344]. For example, Wnt10b was shown to inhibit brown-fat development by suppressing the induction of the two master adipogenic regulators, PPARγ and CCAAT/enhancer-binding protein (C/EBP) α. However, in the same study, while forced expression of PPARγ and C/EBPα rescued adipogenesis, it failed to restore the cells’ thermogenic capacity (e.g., UCP1 expression). Instead, it was determined that Wnt10b mediates its inhibitory effects on UCP1 expression by suppressing PGC-1α. Therefore, co-expression of PGC-1α and PPARγ was required to negate the inhibitory effects of Wnt10b on both brown adipogenesis and thermogenesis [345]. Despite the fact that our understanding of BAT’s secretome is still evolving, there has been undeniable progress over the last few decades. Given BAT’s crucial role in energy expenditure and metabolic regulation, the bioactive molecules it secretes could be pivotal for obesity intervention, as they have been demonstrated to influence BAT development and thermogenic maintenance. Consequently, batokines stand out as a compelling target for further investigation.

5.3. Energy Metabolism

5.3.1. Cold-Induced Thermogenesis

It is widely acknowledged that brown adipose tissue differs from its white counterpart both morphologically and metabolically. As a result, BAT and WAT are known to distinctly contribute to whole-body energy homeostasis. Similar to thermoregulation, maintaining energy homeostasis within a narrow range is crucial as energy imbalances can lead to metabolic disturbances, such as obesity in overnutrition or, conversely, lipodystrophy in undernutrition. As discussed earlier, BAT is a thermogenic tissue that executes its functioning by means of uncoupling oxidative phosphorylation to produce heat and burn energy [298]. This characterized function, in combination with brown fat’s (re)discovery in adults, renewed interest in BAT as a regulator of general energy metabolism and potential therapeutic target for the global epidemic [346]. Over the decades, research has primarily used two methods to stimulate BAT activity: CIT and diet-induced thermogenesis (DIT) [347]. Although rodent models, such as mice and rats, have been the cornerstone of CIT mechanistic studies [348,349,350], human CIT has been proposed to function in a similar manner. This is a reasonable assumption as the framework of CIT encompasses three major factors: (1) response to sympathetic nerve activity, (2) oxidative metabolism, and (3) thermogenic functioning, all of which have been demonstrated in humans [351]. For instance, a strong positive correlation was observed between norepinephrine plasma concentrations and energy expenditure in response to mild-cold exposure or overfeeding in young healthy adults [352]. Fluorodeoxyglucose–positron emission tomography/X-ray computed tomography (FDG-PET/CT) analyses have traditionally served as the method of choice when studying BAT activation due to its non-invasive nature and quantitative reflection of a tissue’s metabolic behavior. Studies using FDG-PET/CT have consistently demonstrated that human BAT is activated in response to cold stimuli [353,354]. As such, van Marken Lichtenbelt et al. observed that 23 of the 24 cold-induced participants in their study exhibited a definite, yet variable, 18F-FDG uptake response in areas where brown adipocytes were confirmed to reside, in particular, the supraclavicular region [355]. A separate study corroborated the previous findings but also identified that FDG uptake in these areas was inversely related to BMI and visceral adiposity [355,356]. Similarly, 4(R,S)-18F-fluoro-6-thia-heptadecanoic acid (18F-FTHA) combined with PET/CT was used to evaluate FA uptake, another vital fuel source of BAT metabolism. It was found that cold stress upregulated both BAT FAU and blood perfusion in lean individuals in a non-shivering manner; however, these effects were diminished in individuals with obesity [357]. Although these studies demonstrated that human BAT responds to cold by increasing its fuel consumption, direct measures of oxidative metabolism were not always included. Therefore, studies have adjusted aspects of their methodologies, particularly in the selection of radiotracers, to more directly address this concern. For example, in addition to using 18FDG and 18F-FTHA, Ouellet et al. opted for 11C-acetate to assess the oxidative capacity of their participants’ BAT. During acute cold exposure, the clearance of 11C-acetate in activated BAT, but not other tissues, was significantly increased, indicating enhanced oxidative metabolism [358]. Similar findings have shown that short-term cold acclimation enhances BAT’s oxidative capacity sufficiently to influence the contribution of non-shivering thermogenesis in skeletal muscle [359,360]. Though oxidative activity provides invaluable insight into overall BAT metabolism, further validation of BAT’s thermogenic activity remains pertinent. Therefore, UCP1 expression, the key thermogenic marker, is commonly used to identify functional BAT in humans [312,361]. Again, using FDG-PET/CT as a ‘map,’ tissue biopsies were collected from areas where cold-exposed patients exhibited high glucose consumption and then were further evaluated for classical BAT thermogenic indicators. Indeed, Virtanen et al. found that higher mRNA expressions of the crucial thermogenic marker and several other BAT-specific signatures in BAT biopsies compared to their adjacent WAT equivalents [149]. Moreover, morphological data helped confirm the biochemical findings. While UCP1 expression is a valid marker of thermogenic potential, it does not guarantee its functional activity [362], nor metabolic improvement [363]. Therefore, mitochondrial bioenergetics profiling has been suggested as a more accurate assessment of UCP1-dependent thermogenesis [364]. Porter et al. used high-resolution respirometry on freshly permeabilized brown and white adipose samples from human biopsies to determine mitochondrial respiratory rates [365]. Their results showed that brown adipose has a 50-fold greater respiratory capacity than white adipose, and human supraclavicular BAT responds to guanosine diphosphate similarly to mouse inguinal BAT, suggesting a comparable UCP1 function between human and mice [365]. In a more recent study, cold-stimulated human BAT activation was associated with changes in serum metabolites involved in nicotinamide adenine dinucleotide (NAD)+ metabolism. Of these alterations, the authors reported that cold-induced activation of BAT increased tissue conversion of tryptophan to nicotinamide, a precursor of the NAD+ salvage pathway and indicator of proper mitochondrial functioning. Notably, tryptophan levels are inversely related to UCP1 expression, thus indicating its cold-activated utilization [366].

5.3.2. Diet-Induced Thermogenesis

Despite the fact that the cold is a potent and reliable stimulus for brown-fat activation, its impracticality limits its benefits for humans. Consequently, research has been investigating the thermogenic potential of DIT, given its contribution to daily energy expenditure [367,368]. Furthermore, it has been observed that increases in BAT oxygen consumption in humans following a carbohydrate-rich meal are comparable to those observed during CIT [369]. DIT refers to the body’s physiological response to caloric intake by which energy expenditure exceeds basal metabolic rate during food processing [368]. The energetic response of DIT can be further subdivided into its obligatory and facultative components, with the latter emphasizing BAT’s assumed contribution to energy metabolism [370]. Indeed, rodent models have demonstrated that calorie intake activates BAT, increasing thermogenic parameters, such as respiration rate, glucose utilization, fatty acid synthesis, and mitochondrial guanosine diphosphate binding [371,372,373]. In addition, rodent studies have identified UCP1 as an essential component in the mediation of diet-induced thermogenesis [374]. For example, Feldmann and colleagues demonstrated that UCP1 ablation not only induces obesity but also abolishes DIT in mice living at thermoneutrality [375]. Another study has corroborated these findings, reporting both the occurrence of obesity and a lack of evidence for DIT in UCP1-deficient mice, despite these mice originating from an obesity-resistant strain [376]. Unfortunately, human evidence regarding BAT DIT is less convincing due to the (1) inconsistencies found in the available, yet (2) limited data. Using whole-room indirect calorimetry, DIT and substrate utilization were measured in participants with and without 18F-FDG-PET/CT-detected BAT activity. The study found that BAT-positive participants had a higher energy expenditure and relative DIT (%), along with a lower respiratory quotient after meals, suggesting that DIT may contribute to energy metabolism in healthy subjects with metabolically detected BAT [377]. However, in a similar study, Loeliger et al. did not find an association between glucose-stimulated BAT and DIT and concluded that DIT is likely not an imperative function of human BAT [378]. Furthermore, a recent meta-analysis determined that diet and nutrition do not significantly affect human BAT activity [379]. Although human studies commonly use indirect calorimetry methods to support theories regarding BAT DIT, the inability of this approach to properly differentiate between various energy types presents a significant drawback, as it tends to overestimate the contribution of heat energy dissipation during the postprandial state. This issue was thoughtfully addressed in the review article “Diet-Induced Thermogenesis: Fake Friend or Foe?” by Ken K. Y. Ho, where Ho advises of the need to complement indirect calorimetry with other methods, such as direct calorimetry or infrared thermography, to improve the accuracy of evidence in future research [380]. Moreover, even at the preclinical level, the late L. P. Kozak had voiced early skepticism regarding the contribution of BAT DIT to energy homeostasis [381]. The widely accepted underlying premise of BAT DIT, like CIT, revolves around the functioning of UCP1. However, works from his lab challenged the legitimacy of this view, revealing intriguing evidence of resistance to hyperphagia and diet-induced obesity in their Ucp1 knockout mice [382,383,384,385]. To-date, findings from DIT studies are still fairly inconsistent, and these discrepancies have been attributed to various factors, such as small sample size or methodology [386]. However, NST mechanisms, both UCP1-dependent and independent, outside the scope of BAT exist and are being considered as an option to counter obesity. One of these approaches is the metabolic remodeling of the ‘culprit’ itself, WAT [387,388,389].

6. Browning of WAT

6.1. Stimuli

Before the phenomena of “browning” became widely acknowledged, Young et al. reported the peculiar detection of brown adipose within a fat pad commonly known to be exclusively white. In addition, they also noted that the density of this brown tissue increased when mice were exposed to cold temperatures [390]. Unknowingly, Young and colleagues had just helped lay the groundwork for the modern concept of browning, where intrinsic white adipocytes respond to stimuli and transform into an intermediate adipose type that exhibits characteristics of both white and brown types. Nearly five decades later, researchers are still investigating the molecular and functional dynamics of WAT browning, with many supporting its potential to combat obesity and related comorbidities [391].

6.1.1. Cold and Pharmacological Agonist

Cold exposure is frequently used in BAT research to promote its thermogenic function and is also a potent inducer of WAT browning [392]. This activation relies on sympathetic nervous system signaling for both BAT activation and WAT browning [393,394]. For example, in adult Sv129 female mice, cold acclimation increases noradrenergic branching and the number of Ucp1-positive adipocytes within white-fat depots [395]. Additionally, β3-adrenergic receptor activation, a primary receptor mediating the cold-induced effects in BAT, is essential for the transdifferentiation of white adipocytes into brown-like cells [396]. Supporting this, systemic treatment with a selective β3-AR agonist increases UCP1 expression and promotes BAT-like characteristics in inguinal WAT [397]. Radiotracer experiments further show that β3-AR agonists can enhance the metabolic activity of both interscapular BAT and inguinal WAT [398,399]. However, in cold-exposed mice lacking β3-AR signaling, the transdifferentiation of white to brown adipocytes is significantly diminished [400]. The most clinically relevant β3-AR agonist being used to elucidate the potential of sympathetic nervous system (SNS)-mediated WAT browning is the FDA-approved drug mirabegron. While initially developed for treating overactive bladders [401], clinical trials have demonstrated that mirabegron also exerts several metabolic effects, such as improving glucose tolerance and insulin sensitivity. Notably, these effects are associated with subcutaneous WAT browning (a.k.a. “beigeing”) [402,403,404]. More recent preclinical work has suggested that the browning of adipose tissue induced by mirabegron may be linked to the drug’s anticancer activity. It was proposed that mirabegron-induced tumor suppression is instigated by a UCP1-facilitated shift in glucose metabolism [405]. Remarkably, a post-authorization safety study observing over 5000 cancer incident reports found no association between mirabegron use and overall cancer risk [406]. However, in a subgroup analysis, it was determined that higher cumulative doses of mirabegron significantly increased kidney cancer incidence in comparison to lower doses. In addition to perinephric fat browning, the authors also reported that β3-AR agonists modulate tumor immune tolerance, which promotes cancer initiation and progression [407]. Other researchers caution that mirabegron-induced browning of WAT and/or activation of BAT may also elevate cardiovascular and cerebrovascular risks by exacerbating atherosclerotic plaque development [408]. However, opposite data obtained by Ying and colleagues determined that mirabegron not only induces WAT browning and stimulates BAT activity but also improves lipoprotein profiles that are associated with reduced atherosclerotic lesion size. The authors suggest that the discrepancies found between studies may be due to the specific characteristics of [408] selected model, which lacks hepatic TRL remnant clearance—an aspect not representative of the general human population [409]. Despite the conflicting results, clinical evidence suggests that a 100 mg dose of mirabegron can promote beneficial metabolic effects, such as increased energy expenditure, without elevating cardiovascular risks [410]. Supporting this, another group of investigators found that mirabegron’s effects are comparable to cold exposure, as both increased lipid oxidation, FFAs, and skin temperature while decreasing the brown-fat fraction [411]. A recent meta-analysis corroborated previous findings by concluding that mirabegron increases various parameters, including BAT activity, body temperature, resting energy expenditure, and non-esterified fatty acids. However, it was shown that mirabegron also modulates heart rate, blood pressure, and blood insulin levels, suggesting it may be a viable option for managing obesity-related comorbidities, such as cardiovascular disease and diabetes [412]. Despite the overall clinical potential of mirabegron and the reliability of cold exposure to promote the browning of white fat and/or modulate BAT activity, both mechanisms have limitations, such as off-target effects [413] or impracticality, respectively. This highlights the importance of more sustainable lifestyle approaches, like diet and exercise, in promoting adipose tissue browning and improving metabolic health.

6.1.2. Exercise

Exercise is known to benefit human health in many ways, some of which include improved sleep and cognitive function, mood stabilization, immune support, and prevention of certain diseases [414]. In addition, exercise has also been demonstrated as a browning agent that integrates factors from various organ systems to promote its effects. For instance, exercise training has been shown to induce the production and release of several exerkines from various tissues that ultimately converge to regulate UCP1 expression in WAT [415]. Among these are the PGC-1α-regulated expression of fibronectin type III domain-containing protein 5 (FNDC5). During exercise, PGC-1α stimulates FNDC5 expression in skeletal muscle, which is subsequently cleaved and then secreted in the form of irisin. Circulating irisin can then act on WAT to upregulate a brown-fat-like program [416]. This muscle–adipose crosstalk is further supported by Xiong et al.’s loss-of-function study that demonstrated that exercise-induced browning of WAT is diminished in their Fndc5 mutant mice [417]. It has also been suggested that TGF-β/SMAD signaling may play a role in WAT browning by suppressing the expression of FNDC5 and PGC-1α in skeletal muscle, thus reducing the production and/or secretion of irisin [418]. Further downstream of irisin’s initial cascade, CD81, a brown-fat-like progenitor surface protein, was shown to mediate integrin-focal adhesion kinase signaling in order to regulate the proliferation and biogenesis of brown-like progenitor cells [419]. While preclinical trials of irisin support its potential to promote browning and benefit metabolism, human studies are less consistent. In 2012, Boström et al. reported a significant increase in FNDC5 mRNA from muscle biopsies, with circulating irisin levels doubling in subjects after a controlled endurance training period. The authors suggest that irisin may play a role in mediating the metabolic benefits of exercise, potentially protecting against several human metabolic disorders [416]. Conversely, a study conducted one year later by Pekkala et al. reported opposite findings. They found no significant changes in either FNDC5 or serum irisin levels after exercise, regardless of training type—whether aerobic, endurance, or a combination of endurance and resistance. The authors suggest that other factors may regulate FNDC5 expression and irisin release, as their data showed an inconsistent correlation between PGC-1A mRNA expression and changes in FNDC5. Additionally, they further noted that neither FNDC5 nor irisin was associated with metabolic parameters, such as glucose tolerance, insulin sensitivity, and/or obesity status [420]. Others have corroborated these findings, with some studies reporting that the expression of FNDC5 or its product irisin does not even correlate with UCP1 mRNA in WAT [421,422,423]. These translational discrepancies urge researchers to invest time and resources elsewhere by either exploring the browning potential of other exerkines, such as FGF21 [424,425], interleukin 6 [426,427], growth differentiation factor 15 [428,429] and/or alternative approaches, including dietary components.

6.1.3. Nutraceuticals

Research suggests that certain natural compounds from various food sources may promote the conversion of WAT to a more thermogenically active and brown-like state, a process linked to increased energy expenditure and potential anti-obesity benefits.
Resveratrol—a polyphenol naturally found in the skins of berries and grapes—has been shown to encourage WAT browning [430] by modulating the activity of sirtuin (SIRT) 1, a deacetylase enzyme. Studies indicate that both resveratrol and resveratrol-like compounds regulate SIRT1 activity [431,432], leading to the deacetylation of PPARγ at specific lysine residues: Lys268 and Lys293. This deacetylation facilitates the recruitment of the thermogenic coactivator PRDM16 to PPARγ. As a result, brown-fat-specific genes, such as Ucp1 and Dio2, were shown to be upregulated while white-associated genes were repressed [433,434]. In addition, others have suggested that resveratrol may also induce brown-like adipocyte formation and enhance thermogenic function by activating the cellular energy sensor AMP-activated protein kinase (AMPK) α1 [435,436]. Interestingly, resveratrol has also been associated with regulating several of the aforementioned exerkines, including both FNDC5/irisin [437] and FGF21 [438].
Capsaicin—a compound extracted from chili peppers—is another dietary component investigated for its potential to induce WAT browning and promote anti-obesity effects [439]. Research by Baskaran and colleagues demonstrated that capsaicin promotes the expression of brown-fat-specific genes, including Ucp1 and Bmp8, in WAT. Capsaicin has also been shown to increase SIRT1 expression and activity, enhancing the interaction between PPARγ and PRDM16 similarly to resveratrol. This capsaicin-induced SIRT1 activation is mediated through a TRPV1 channel-dependent influx of intracellular calcium and the phosphorylation of AMPK and Ca2+/calmodulin-activated protein kinase [440]. In addition to capsaicin, other TRPV1-activating compounds have been found to promote WAT browning. Zhang et al. reported that hydroxy-α-sanshool, an active amide from the fruits of Zanthoxylum bungeanum Maxim, can activate the TRPV1/AMPK pathway, leading to PPARγ deacetylation and WAT browning [441]. Hydroxy-α-sanshool may serve as an alternative for individuals sensitive to the spiciness of capsaicin, as it provides a similar thermogenic effect without the same level of pungency. This should be considered, as some research suggests capsaicin, unlike its non-pungent analogs, is necessary for maximal TRPV1 activation and thermogenic response in WAT [442].
Another dietary component shown to induce WAT browning is fish oil [443]. For example, Kim and colleagues conducted a study demonstrating that mice fed fish oil (FO) began to exhibit a gene expression profile in their inguinal WAT that closely resembled that of BAT. This included key BAT-specific and thermogenic markers, such as UCP1 at the protein and gene levels, and Pgc1a, Prdm16, carnitine palmitoyltransferase 1b (Cpt1b), and cell death-inducing DFFA-like effector a (Cidea) at the gene level. In addition, the authors noted that both oxygen consumption and body rectal temperature were increased in response to FO feeding. These effects were concomitant with the upregulation of Ucp1 and the β3-adrenergic receptor (β3AR) gene (Adrb3), implying that fish oil may mediate its thermogenic effects via SNS activation [444]. Other researchers have noted similar effects of fish oil, highlighting that mice on a high-fat diet supplemented with fish oil exhibit an increased expression of genes associated with mitochondrial biogenesis and β-oxidation in both epididymal and subcutaneous fat pads [445]. Furthermore, Yamazaki et al. proposed that fish oil could be a beneficial dietary fat associated with DIT. Mice given FO exhibited a significant increase in several BAT/thermogenic markers, such as Ucp1 and Cidea, as well as other genes involved in β-oxidation, within their subWAT. Notably, the expression of Adrb3 was also found to be higher in mice fed FO compared to the control-fed group. This led to the speculation that FO might induce a thermogenic gene profile in subWAT via SNS [446]. In short, there are many ways to “brown” WAT, some more well-established than others, and the novelty of each browning agent has been discussed extensively in their own niche reviews [447,448]. However, the outcome of browning, regardless of what agent was used, is always the same: an intermediary adipocyte that resides in white fat but can function similarly to brown fat. Therefore, if the end goal is the same, then why does the literature entertain a catalog of synonyms when referring to the same adipocyte type?

6.2. Brown-like Adipose

The fundamental framework of WAT browning is solid. Converting excess white adipose tissue, as seen in obesity, into a type that might eventually resolve itself is a promising approach. However, the field seems to lack agreement on how to term these brown-like adipocytes, with some referring to them as ‘beige’ and others as ‘brite’. Moreover, just to add to this perplexity, the literature further accommodates a range of acronyms (‘BeAT’) [449,450], adjectives (‘inducible,’/‘recruitable,’/‘convertible’) [152,153,451,452,453], and novel pseudonyms (‘taupe’) [454]. Conventionally, many authors attempt to resolve this conundrum by lumping terms together when discussing their results [152,455]. However, returning to the start of this Section 6.1 may prompt a reconsideration of this grouping method. Young et al.’s report highlights several key findings: (1) the detection of brown “areas” within an otherwise known white-fat pad at a standard mouse housing temperature (~23 °C) and (2) the intensification and propagation of these brown areas upon cold exposure [390]. Therefore, Young et al.’s study was not only pioneering in documenting the browning phenomenon, but their results also suggest the presence of distinct cell populations that contribute to this process.

6.2.1. Markers of Identification

In order to fully elucidate the potential of beige adipocytes and their contribution to human health and obesity, it is first necessary to properly identify this subcategory of cells. Although this objective is rather challenging, as these adipocytes are known to be the intermediate of both WAT and BAT, several research groups have proposed a variety of enriched transcripts that may be unique to this population [450,456]. For instance, Wu et al. identified a pool of progenitors from the SVF of the inguinal depot that were reminiscent of, but not absolutely identical to, classical brown adipocytes. After differentiation, these inguinal-derived cells expressed basally low levels of several brown-fat genes, including Ucp1, cytochrome c oxidase subunit 7 isoform A1 (Cox7a1) and Cidea. Importantly, basal levels of these genes from this pool were comparable to the unstimulated levels in the subset determined as white. However, upon cAMP stimulation, this pool of adipocytes, but not the white subset, exhibited a large induction of Ucp1 and uncoupled respiration that either mirrored or outperformed brown adipocytes’ response, respectively. Transplantation experiments confirmed these cells’ ability to respond to SNS input and that the enhanced UCP1 gene expression observed was reproducible in an in vivo setting [457]. Differential gene analysis revealed several unique signatures of these responsive, inguinal-derived cells, such as transmembrane protein 26 (Tmem26), cluster of differentiation (CD) 137 (Cd137), and T-box 1 (Tbx1). Furthermore, fluorescence-activated cell sorting of primary inguinal SVF residents expressing either Cd137 or Tmem26 corresponded with groups of cells that exhibited basally elevated Ucp1 expression [457]. Additionally, recognized beige-selective markers, such as Cbp/p300-interacting trans-activator with Glu/Asp-rich carboxy-terminal domain 1 (CITED1) and SHOX homeobox 2 (SHOX2), have been detected in human BAT [458,459]. Beige-selected adipocytes using the above criteria were found to be UCP1 (+) and correlated with the brown-fat-selective gene PRDM16 [458,459,460]. It has been proposed that PPAR agonists, such as rosiglitazone, can function synergically with PRDM16 to confer the brown fat gene program in subcutaneous WAT [461]. However, other lines of evidence have suggested that the brown-fat-selective marker does not maintain a role in regulating the beige-induced phenotype in white depots and, instead, is only prioritized in the muscle relating to brown-fat fate [460,462]. In 2015, several of the proposed beige-selective markers, such as Cd137, epithelial stromal interaction 1 (Epsti1), Tbx1, Tmem26, carbonic anhydrase 4 (Ca4), Cited1, Fgf21, and homeobox C9 (Hoxc9), underwent an assessment where their validity as beige-fat markers was critically revisited. De Jong et al. concluded that, among the growing number of proposed beige markers, Cd137—and to an even lesser extent, Tbx1 and Tmem26—show the most potential as reliable marker genes at the tissue level. However, none of these markers were exclusively expressed in primary inguinal WAT cultures, highlighting the need for deeper assessment of the currently proposed markers and the potential identification of novel ones [463]. Accordingly, single-cell RNA sequencing recently enabled the identification of an adipose stem cell subpopulation within the inguinal WAT depot that exhibits the propensity for a beige phenotype in response to cold stimuli. Nahmgoong et al. characterized this subpopulation by the cell surface marker bone marrow stromal antigen 2high and, upon differentiation, found that these inguinal-derived adipose stem cells begin to highly express thermogenic markers, including Ucp1 and Dio2. In addition, it was noted that these cells were derived from a cluster also associated with beige expressions, including Tmem26 and IL33. Moreover, cold exposure was shown to increase the proportion of these bone marrow stromal antigen 2high ASCs, whereas high-fat feeding was shown to downregulate them and, correspondingly, Ucp1 expression [464]. Without a doubt, more sophisticated methods, such as single-cell RNA sequencing and large-scale bulk analyses, have significantly advanced our understanding and precision in distinguishing beige/brite adipocytes from classical WAT and BAT. However, the pesky challenge of pinpointing how these cells emerge still baffles researchers today—is it by de novo beige adipogenesis? WAT to brown-like transdifferentiation? or both?

6.2.2. Origins

It is widely accepted that these cells are indeed their own entity, not too brown and not too white, but just ‘brite.’ Evidence collected throughout the history of browning research has led studies to support each theory. While some investigators are convinced this subset of adipocytes arises from a distinct precursor, others contemplate the possibility of mature transdifferentiation. For example, after rats were treated with the β3AR agonist, CL-316243, ~17% of their retroperitoneal WAT adipocytes exhibited a multilocular appearance, compared to only about 0.3% from the control group. Furthermore, treated cells were almost completely negative for BrdU, suggesting that the accumulation of multilocular cells was not due to mitotic proliferation of precursors but instead the conversion of pre-existing unilocular cells [453]. Nearly a decade later, Barbatelli et al. supported the previous findings by demonstrating the occurrence of WAT-derived adipocytes that were UCP1-immunoreactive and exhibited a mixed morphology (paucilocular) following cold exposure. Importantly, quantitative electron microscopy determined these cold-induced paucilocular cells were not due to an induction of cell proliferation but again, by transdifferentiation [396]. Conversely, other reports from the same era, such as the study by Petrovic and colleagues, challenge this view and argue that the UCP1-induced adipocytes within the ‘purest’ WAT depots are in fact a molecularly distinct subcellular population. The authors conducted co-culture experiments to eliminate the possibility that a few preexisting brown preadipocytes might have simply overgrown and outcompeted white adipocytes during stimulation. Despite PPARγ activation causing a subset of epididymal-derived preadipocytes to acquire thermogenic capacity, rosiglitazone-treated cultures lacked many origin-specific myogenic and brown fat markers. Additionally, they seemed to exhibit markers of white fat origins, such as homeobox C9, distinguishing them from both classical brown and white adipocytes [462]. Vegiopoulos et al. demonstrated that cyclooxygenase 2—prostaglandin signaling lies downstream of the canonical β-adrenergic pathway and may play a role in shifting the differentiation of WAT mesenchymal progenitors towards a brown-fat phenotype. Importantly, and consistent with Petrovic et al.’s findings, classic brown-fat transcripts, including Myf5 and LIM/homeobox protein Lhx8 (Lhx8) genes, were not found to be enriched in either the CL-316243-induced or cyclooxygenase 2-overexpressing brown-like adipocytes, indicating their idiosyncratic origin [465]. Human studies have also indicated a separately defined and inducible subpopulation of adipocytes that reside within either known classical brown (cervical and supraclavicular) or white (periadrenal) depots [452,466,467,468]. Taken together, emerging evidence supports both perspectives, but future research must address key considerations to optimize the clinical translation of adipose browning. Critical questions include defining the precise molecular signatures of distinct cell populations and identifying targetable genes to control their differentiation fate. Does stimulus type matter (e.g., cold exposure versus dietary versus pharmacological interventions), and if so, what thresholds are required for functional thermogenesis that is clinically meaningful? Can the chosen pharmacological agents achieve physiologically relevant doses in humans, or are the stimuli even feasible? Beyond these hurdles, what are the turnover rates, sustainability, and long-term clinical implications of browning once stimuli are withdrawn? Would it prove more effective to expand novel progenitor cells ex vivo or reprogram mature white adipocytes in situ? Finally, do transdifferentiated cells revert to a functional white adipocyte state, or do they undergo stable epigenetic reprogramming that alters their response to future stimuli? Resolving these issues will be essential before positioning adipose browning as a viable anti-obesity therapeutic strategy.

7. Yellow Adipose Tissue (YAT)

While most preclinical research has traditionally focused on modulating white and brown adipogenesis, yellow adipose tissue, a fat depot localized within the bone marrow, has received little attention despite a growing body of evidence implicating it in human health and disease. Notably, YAT [a.k.a. bone marrow adipose tissue (BMAT) or marrow adipose tissue (MAT)] depots have been observed within the medullary canal of long bones (tibia, femur, and humerus), ribs, vertebrae, and sternum [469] and make up 10–15% of total adipose mass [470,471] (Figure 2).
Although still controversial, YAT has been initially proposed to originate from various MYF5-negative progenitor stem cells under the control of pRb [487,488,489]. However, recent studies argued that yellow adipocytes originate mostly from skeletal lineages [471,490,491]. A recent study by Ambrosi and colleagues delineated the molecular identity of the bone-resident yellow adipocytes and determined that only progenitor cells that are negative for both hematopoietic Cd45 and endothelial Cd31 markers but positive for mesenchymal Sca1 marker give rise to bona fide mature adipocytes within the bone marrow [481]. Furthermore, Scheller and colleagues identified two functionally different marrow adipose tissues: proximal ‘regulated’ MAT (rMAT) and distal ‘constitutive’ MAT (cMAT), fats with distinct roles in hematopoiesis. rMAT appears in the form of scattered single adipocytes with active hematopoiesis, whereas distal cMAT contains larger adipocytes and displays low hematopoiesis [469]. Taken together, these studies point to a unique type of fat with potentially critical functions in health and disease.
Functional YAT depots exhibit several unique features; however, under certain conditions, characteristics that resemble either BAT or WAT may emerge. For instance, despite their histological resemblance to white adipocytes with unilocular lipid droplets, marrow adipocytes express several markers of beige and brown adipocytes, including Tbx1, Dio2, Ucp1, Prdm16, Pgc1a [492]. As such, YAT depots have been shown to not only regulate hematopoiesis and bone remodeling, but they also play a critical role in energy balance and systemic metabolic homeostasis through both endocrine and paracrine functions [471]. Cawthorn and colleagues found that caloric restriction increases bone marrow adipose tissue mass concomitant with an elevation in the levels of circulating adiponectin [493]. Interestingly, the levels of secreted adiponectin were higher in MAT compared to WAT and were also increased in patients receiving cancer therapy [493] and mice treated with rosiglitazone [494]. Given the role of adiponectin in several biological and physiological processes in addition to metabolic homeostasis, such as neurogenesis, cardiovascular function, the immune system, and a plethora of other systems [493], it is reasonably arguable to assume that alterations to YAT development and function may contribute to the pathogenesis of several metabolic and non-metabolic diseases. As such, a deep understanding of the biology of this tissue may yield novel insights into its role in health and disease. This is also supported by the fact that YAT may exhibit changes to its metabolic activity in response to various physiological, environmental, and pharmacological stimuli, including aging [481,495,496], cold exposure [497,498], and treatment with Metformin, PPAR agonists, and several other drugs [499,500,501,502].
While early studies have established a strong association between obesity and bone marrow adipose tissue mass and inflammation [503,504], this association appears to be modulated by several factors. For instance, adipose tissue occupies the majority of long-bone marrow cavities and represents only 40% of iliac crest marrow, with the remaining 60% being hematopoietic cells [505]. Additionally, the distribution of bone marrow adipose tissue is also affected by other factors, such as ethnicity and health status, and can also be site- and species-specific, as bone marrow mass and location are different in human versus experimental models of human obesity [157,506]. These differences possibly suggest that the mechanisms of bone marrow adipogenic differentiation may also be affected by these factors and warrant further investigations [506]. In healthy premenopausal women, a positive correlation between bone marrow fat mass and visceral adiposity, independent of bone mineral density, was observed [503]. In line with these observations, exercise-induced body weight loss in mice was associated with a decrease in bone marrow fat mass and improved bone health [507]. Of note, increased bone marrow fat mass has been associated with several detrimental metabolic alterations. For example, Ermetici et al. demonstrated a negative correlation between bone marrow fat mass and insulin sensitivity in obese and non-obese premenopausal women [508], possibly caused by alterations to adiponectin and leptin levels and the subsequent effects on insulin sensitivity and glucose homeostasis [508,509]. According to this study, the increase in bone marrow fat mass could be attributed to a compensatory effect caused by changes to the levels of C/EBPα/δ and PPARγ2, all of which are key players in adipogenesis.
In support of its contribution to metabolic homeostasis, recent attention identified a potential relationship between bone marrow fat mass and diabetes, both type 1 and type 2, and the related skeletal fragility. However, while human studies have yet to provide robust evidence of such an association [510,511,512], experimental rodent models of type 1 diabetes (T1DM) often exhibit higher bone marrow fat mass compared to healthy animals, concomitant with lower bone mass [513,514,515]. Notably, Martin and McCabe demonstrated that bone marrow adiposity in diabetic mice could be location-dependent, as it is higher in the femurs and calvaria area but not in the vertebrae area [515]. In support of this observation, despite their lower peripheral adiposity and lean mass, diabetic C/EBPβ deficient mice displayed a five-fold increase in bone marrow adiposity compared with controls. These effects were concomitant with alterations to bone health as judged by the reduced bone stiffness and enhanced bone resorption in diabetic mice [516]. The increase in bone marrow fat mass was also evident in the streptozotocin-induced T1DM experimental model, where treatment with streptozotocin increased the differentiation of mesenchymal stem cells toward an adipocyte lineage [517]. However, despite the positive association between T1DM and bone adiposity, there is insufficient data to support a causal relationship. While treatment of T1DM with insulin ameliorated bone health, it failed to prevent adipocyte differentiation within the bone marrow, suggesting that other factors in addition to bone marrow fat cells contribute to bone loss in T1DM and require further investigation. On the other hand, treatment of insulin-deficient diabetic BALB/c with bisphenol-A-diglycidyl ether, a PPARγ agonist, blocked bone adiposity but failed to prevent diabetes-induced bone loss [518]. Taken together, these findings, while they establish an interplay between T1DM and bone fat mass, also advocate for a complex relationship that requires further examination.
The reciprocal relationship between bone marrow adiposity and glucose homeostasis has also been observed in T2DM, both in humans and rodent models. HbA1c levels were positively associated with higher marrow adiposity in adult men with morbid obesity [519]. Similarly, significant positive correlations were observed between vertebral bone marrow fat and T2DM in elderly men [520]. Conversely, treatment of healthy postmenopausal women with the antidiabetic drug rosiglitazone reduced bone marrow adiposity [521]. However, while the association between T2DM and bone marrow fat mass in humans has been challenged by other studies [522,523], experimental models of T2DM consistently demonstrated increased bone marrow fat mass in T2DM animals. Early onset of T2DM correlated with up to 50-fold-higher bone marrow adiposity in Tallyho mice [524]. Likewise, an increase in bone marrow fat mass was observed in high-fat-feeding-induced obesity and T2DM [525]. Although no effects on peripheral adiposity were observed upon treatment with metformin, a first-line treatment of T2DM, both bone marrow fat mass and T2DM were reversed [525]. These studies provide evidence for the role of bone marrow fat in the regulation of systemic energy metabolism and glucose homeostasis, a hypothesis that is further corroborated by studies demonstrating the ability of bone marrow fat to respond to insulin-sensitizing agents [499,500,525,526].
In addition to its role in metabolic regulation, several early and recent studies have identified bone marrow fat as a negative regulator of hematopoiesis [485,527,528,529]. Although the exact molecular mechanisms are yet to be determined, Harada and colleagues demonstrated that plasminogen activator inhibitor type-1 (PAI-1) is responsible for the detrimental effects of bone marrow fat on hematopoietic regeneration [528]. PAI-1 is produced by several tissues, including fat, and functions as a serine protease inhibitor. It has also been linked to the pathogenesis of several acute and chronic pathophysiological processes, including cardiovascular disease, tissue fibrosis, cancer, and age-related diseases [530]. PAI-1 not only affects the movement and retention of hematopoietic stem and progenitor cells within the bone marrow [531] but also plays a role in regulating insulin signaling in peripheral tissues, contributing to insulin resistance and metabolic dysfunction [532].
Given its role in systemic inflammation and obesity, it is not surprising that bone marrow fat mass is also associated with bone and metabolism [533]. Indeed, higher bone marrow fat mass has been linked to decreased bone mineral density and increased fracture risk [534,535,536]. Additionally, the lipid composition of bone marrow fat and the relative amounts of saturated versus unsaturated fat were demonstrated to have an impact on skeletal health, bone density, and fracture risks [537,538]. As demonstrated by Yeung and colleagues [539] and further confirmed by Li et al. [540], the fat unsaturation index was significantly lower in osteoporotic and osteopenic postmenopausal women compared to controls. Further research is needed to fully understand the molecular mechanisms mediating the association between bone density and bone marrow fat mass and composition. However, a study by Fazeli and colleagues investigating the relationship between several adipokines, fat mass, and bone mineral density in women with anorexia nervosa found an inverse association between bone mineral density of both the anteroposterior spine and lateral spine and the expression of several adipokines [541]. This includes preadipocyte factor-1, insulin-like growth factor (IGF)-I, IGF-binding protein 2 and leptin; all of which are well-established modulators of adipocyte and osteoblast differentiation, but also bone growth and density. For instance, IGF-I was demonstrated to directly regulate bone growth and density [542]. Likewise, an increase in the levels of IGF-II/IGF binding protein-2 complex stimulates bone formation and prevents loss of bone mineral density in a rat model of disuse osteoporosis [543]. Similarly, systemic administration of leptin in animals and humans was often associated with positive outcomes on bone health [544]. The role of preadipocyte factor-1 in bone health, on the other hand, is controversial and warrants additional investigation [545,546,547,548]. Together, while research highlights adipokines as crucial for bone health, the specific role of bone marrow fat in circulating these adipokines is still unclear. However, the observed link between bone density and bone marrow fat mass/composition suggests involvement of multiple mechanisms, with adipokines being a strong possibility.

8. Pink Adipose Tissue (PAT)

Recent advances in the field, led by Saverio Cinti from the University of Ancona, Italy, led to the identification and characterization of a novel type of lipid-rich parenchymal cell within the mouse mammary glands called “pink adipocytes.” These cells develop and are maintained during the maternal stages of pregnancy and lactation; however, they transdifferentiate into white and brown adipocytes upon the post-lactation period [155,549,550]. Pregnancy provokes white, brown, and brown-like adipocytes within the anterior and posterior subcutaneous depots to enter the “mammary gland cycle” to form lobuloalveolar structures (alveoli; alveologenesis) that support a milk-producing/secreting organ. This transdifferentiation occurs in two phases; first, alveoli develop as a result of possibly increased stem cell proliferation during the early stages of pregnancy. Then, intracellular lipid droplets emerge inside these cells during the second stage of pregnancy, leading to the formation of pink adipocytes, which occurs concomitantly with the shrinkage of subcutaneous fat [551] as the mammary ducts substitute most of the subcutaneous adipose tissue [552,553,554,555]. The post-lactation phase ultimately replaces the newly constructed alveoli with adipocytes, thus restoring it back to the original form: a subcutaneous depot infiltrated by branched epithelial ducts [155,551]. Ductal stem cell recruitment, transformation, and subsequent apoptosis form the fundamental essence of the leading hypothesis attempting to explain the adipocyte/epithelial transdifferentiation [549,556,557,558]. Although its clinical relevance is yet to be determined, the transdifferentiation of pink adipocytes into brown or brown-like adipocytes post-lactation [155,559]. insinuates their potential role in the metabolic homeostasis and remodeling of the surrounding microenvironment and warrants additional investigation.

9. Conclusions and Future Directions

It is clear that obesity research has come a long way since its declaration as a global health crisis. Importantly, we exist in an era where healthcare is adopting a more interdisciplinary approach that considers multiple expertise in order to provide the most efficient patient care [560]. It is reasonable to speculate that benchtop research may greatly benefit from this model as well. Therefore, in this review, we have explored the intricacies of the body’s different adipose tissues, examining each type’s unique and functional contributions to human health. Identifying areas of overlap and divergence among the various adipose tissues will allow for a honed, yet more comprehensive, perspective when addressing the rising epidemic. However, despite the field’s major advances on the topic, we are continuously seeing novel, and sometimes even revisited, avenues within adipose/obesity research. For instance, in more recent years, glucagon-like-peptide-1 (GLP-1) receptor agonists (RA), such as Liraglutide and Semaglutide, have been in high demand, particularly on account of their FDA approval and success for weight management in both diabetic and non-diabetic patients [561,562]. Various metabolic attributes, besides just weight loss and glycemic control, have been associated with the prescription of these drugs, including improved dyslipidemia, reduced blood pressure, anti-inflammatory, slowed gastric emptying/motility, appetite control, etc. [563,564,565]. Some preclinical studies have indicated that GLP-1RAs may be involved in BAT activation and thermogenesis as well as WAT browning, although firm clinical evidence remains limited [566,567,568,569,570]. A prevailing concern is that adults, especially those with obesity, tend to have significantly reduced amounts of BAT [571]. This has led to skepticism about the feasibility of targeting one of the body’s relatively minor tissue masses to address the broader, systemic challenge of obesity. While WAT browning has undoubtedly expanded the therapeutic landscape by enhancing the body’s thermogenic capacity and activity, the phenomenon of adipose tissue ‘whitening’—the conversion or reversion of BAT and beige adipose tissue to white adipose characteristics—may hamper some of its potential value [572]. In addition, several dose-dependent gastrointestinal adverse events—particularly nausea, vomiting, constipation, and/or diarrhea—have been reported with GLP-1RA use. Thus, these side effects may interfere with necessary dose escalation or even lead to patient discontinuation, thereby limiting GLP-1RA’s overall efficacy [573,574]. With these caveats in mind, some research teams have shifted their attention towards combination drug therapies that can complement the GLP-1RA mechanism while also subsiding some adverse effects [575,576,577]. One promising companion that has been evaluated is the glucose-dependent insulinotropic polypeptide (GIP) [578]. In phase 2 clinical trials, the dual-action agonist LY3298176 was demonstrated to significantly reduce fasting serum glucose and body weight in diabetic subjects [114,579]. Importantly, researchers reported that LY3298176 stayed within an acceptable range for safety and tolerability [114]. Phase 3 clinical trials have supported previous findings, confirming that the GLP-1/GIP dual-receptor agonist not only delivers on its promise but can also outperform some of its single-action competitors [114]. It has been speculated that, aside from its insulinotropic effects, GIP receptor agonist-based therapy may also target WAT health and expansion [580]. This interplay between GIP’s peripheral effects and the already anorexigenic and insulinotropic GLP-1 is becoming widely decreed as the future of drug development for T2DM and other obesity-related disorders [575]. Nonetheless, various loose ends remain. For instance, as previously noted, GLP-1 RAs have been linked to WAT browning, which could potentially conflict with GIP’s role in promoting WAT expansion. Within this context, it is reasonable to question how a dual agonist infringing on the metabolism and function of the same tissue will be able manage two seemingly opposing mechanisms. Another consideration is whether GIP-induced WAT maintenance, even in the context of “healthy” WAT expansion, could begin to paradoxically negate the dual agonist’s initial weight loss effects. Importantly, even patients with metabolically healthy obesity, classified as obesity that lacks overt metabolic symptoms, face many non-metabolic and psychosocial obstacles that are associated with excess WAT preservation [581,582]. Alternatively, it is also possible that GIP effects could be offset by the browning properties of GLP-1, as it has been demonstrated that GIP receptor expression is primarily localized in the tissue’s supporting cells and not directly in the adipocytes [582]. Therefore, careful elucidation of their exact molecular underpinnings, both individually and collectively, is highly warranted. Another emerging area of interest is addressing the sexual dimorphism observed in BAT activation and WAT browning studies. Notably, females appear more susceptible to WAT browning than males [583,584]. Therefore, future drug developments should consider these sex-specific differences to ensure the utmost efficacy and safety for both male and female clients. Taken together, given the multifaceted nature of obesity’s origins, our solutions should be equally as complex, which could involve targeting the activities of multiple adipose tissues and/or pathways to achieve a more comprehensive and effective obesity treatment.

Author Contributions

Conceptualization, All Authors; methodology, All Authors; software, P.D.D.-K. and P.K.J.; validation, All Authors; formal analysis, Not Applicable; investigation, Not Applicable; resources, Not Applicable; data curation, Not Applicable; writing—original draft preparation, All Authors; writing—review and editing, All Authors; visualization, P.D.D.-K. and P.K.J.; supervision, R.J.G. and A.B.; project administration, A.B.; funding acquisition, P.D.D.-K. and A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the American Heart Association, Award Number 26POST1563678 to P.D.D.-K. and The National Institute of Food and Agriculture—NIFA-AFRI-2021-007052 to A.B.

Institutional Review Board Statement

Not Applicable.

Informed Consent Statement

Not Applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
18F-FTHA18F-fluoro-6-thia-heptadecanoic acid
AD-EvsAdipose-derived extracellular vesicles
AGPAT21-acylglycerol-3-phosphate-O-acyltransferase 2
AMPKAMP-activated protein kinase
AODAnti-obesity drug
BATBrown adipose tissue
BMATBone marrow adipose tissue
BMIBody mass index
BMPBone morphogenetic proteins
C/EBPCCAAT/enhancer-binding protein
cAMPCyclic adenosine monophosphate
CDCluster of differentiation
CIDEACell death inducing DFFA like effector a
CITCold-induced thermogenesis
Cbp/p300-interacting trans-activator with Glu/Asp-rich carboxy-terminal
Cited 1domain 1
cMATconstitutive marrow adipose tissue
CRISPRClustered regularly interspaced short palindromic repeats
CTComputed tomography
DAGDiacylglycerol
DDSDrug delivery systems
DGATDiacylglycerol Acyltransferase
DIODiet-induced obesity
Dio2Type II iodothyronine deiodinase
DITDiet-induced thermogenesis
DNLDe novo lipogenesis
dWATDermal white adipose tissue
FDGFluorodeoxyglucose
FFAFree fatty acid
FGF21Fibroblast growth factor 21
FNDC5Fibronectin type III domain-containing protein 5
FOFish oil
GIPGlucose-dependent insulinotropic polypeptide
GLP-1Glucagon-like peptide-1
GPAT3Glycerol-3-phosphate acyltransferase 3
HSLHormone-sensitive lipase
IGFInsulin-like growth factor
KOKnockout
LCFALong chain fatty acid
MATMarrow adipose tissue
NADNicotinamide adenine dinucleotide
NSTNon-shivering thermogenesis
PAHSAPalmitic acid hydroxy stearic acids
PAPPA phosphohydrolase
PETPositron emission tomography
Pgc1αPeroxisome proliferator-activated receptor-gamma coactivator 1-alpha
PKAProtein kinase A
PRDM16PR Domain Containing 16
RAReceptor Agonist
rAAVRecombinant adeno-associated virus
rMATregulated marrow adipose tissue
SIRTSirtuin
SMADSuppressor of mothers against decapentaplegic homolog
SNSSympathetic nervous system
T1DMType 1 diabetes mellitus
T2DMType 2 diabetes mellitus
TAGTriacylglyerol
TBX1T-box 1
TGF-βTransforming growth factor-β
TMEM26Transmembrane protein 26
UCP1Uncoupling protein 1
WATWhite adipose tissue
YATYellow adipose tissue
β3-ARβ3-adrenoceptor

References

  1. James, W.P. WHO recognition of the global obesity epidemic. Int. J. Obes. 2008, 32, S120–S126. [Google Scholar] [CrossRef]
  2. Ward, Z.J.; Bleich, S.N.; Cradock, A.L.; Barrett, J.L.; Giles, C.M.; Flax, C.; Long, M.W.; Gortmaker, S.L. Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. N. Engl. J. Med. 2019, 381, 2440–2450. [Google Scholar] [CrossRef]
  3. Fruh, S.M. Obesity: Risk factors, complications, and strategies for sustainable long-term weight management. J. Am. Assoc. Nurse Pract. 2017, 29, S3–S14. [Google Scholar] [CrossRef]
  4. Goossens, G.H. The Metabolic Phenotype in Obesity: Fat Mass, Body Fat Distribution, and Adipose Tissue Function. Obes. Facts 2017, 10, 207–215. [Google Scholar] [CrossRef]
  5. Tremmel, M.; Gerdtham, U.G.; Nilsson, P.M.; Saha, S. Economic Burden of Obesity: A Systematic Literature Review. Int. J. Environ. Res. Public. Health 2017, 14, 435. [Google Scholar] [CrossRef] [PubMed]
  6. Kjellberg, J.; Tange Larsen, A.; Ibsen, R.; Højgaard, B. The Socioeconomic Burden of Obesity. Obes. Facts 2017, 10, 493–502. [Google Scholar] [CrossRef]
  7. Hammond, R.A.; Levine, R. The economic impact of obesity in the United States. Diabetes Metab. Syndr. Obes. 2010, 3, 285–295. [Google Scholar] [CrossRef] [PubMed]
  8. Rubino, F.; Cummings, D.E.; Eckel, R.H.; Cohen, R.V.; Wilding, J.P.H.; Brown, W.A.; Stanford, F.C.; Batterham, R.L.; Farooqi, I.S.; Farpour-Lambert, N.J.; et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol. 2025, 13, 221–262, Erratum in Lancet Diabetes Endocrinol. 2025, 13, e6. [Google Scholar] [CrossRef] [PubMed]
  9. Global, B.M.I.M.C.; Di Angelantonio, E.; Bhupathiraju Sh, N.; Wormser, D.; Gao, P.; Kaptoge, S.; Berrington de Gonzalez, A.; Cairns, B.J.; Huxley, R.; Jackson Ch, L.; et al. Body-mass index and all-cause mortality: Individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet 2016, 388, 776–786. [Google Scholar] [CrossRef]
  10. Heymsfield, S.B.; Peterson, C.M.; Thomas, D.M.; Heo, M.; Schuna, J.M., Jr. Why are there race/ethnic differences in adult body mass index-adiposity relationships? A quantitative critical review. Obes. Rev. 2016, 17, 262–275. [Google Scholar] [CrossRef]
  11. Humphreys, S. The unethical use of BMI in contemporary general practice. Br. J. Gen. Pract. 2010, 60, 696–697. [Google Scholar] [CrossRef] [PubMed]
  12. Mills, T.C.; Gallagher, D.; Wang, J.; Heshka, S. Modelling the relationship between body fat and the BMI. Int. J. Body Compos. Res. 2007, 5, 73–79. [Google Scholar]
  13. Janssen, I.; Katzmarzyk, P.T.; Ross, R. Waist circumference and not body mass index explains obesity-related health risk. Am. J. Clin. Nutr. 2004, 79, 379–384. [Google Scholar] [CrossRef]
  14. Ashwell, M.; Lejeune, S.; McPherson, K. Ratio of waist circumference to height may be better indicator of need for weight management. BMJ 1996, 312, 377. [Google Scholar] [CrossRef]
  15. Chen, L.; Peeters, A.; Magliano, D.J.; Shaw, J.E.; Welborn, T.A.; Wolfe, R.; Zimmet, P.Z.; Tonkin, A.M. Anthropometric measures and absolute cardiovascular risk estimates in the Australian Diabetes, Obesity and Lifestyle (AusDiab) Study. Eur. J. Cardiovasc. Prev. Rehabil. 2007, 14, 740–745. [Google Scholar] [CrossRef]
  16. Laddu, D.R.; Lee, V.R.; Blew, R.M.; Sato, T.; Lohman, T.G.; Going, S.B. Predicting visceral adipose tissue by MRI using DXA and anthropometry in adolescents and young adults. Int. J. Body Compos. Res. 2012, 10, 93–100. [Google Scholar]
  17. Kopelman, P.G. Obesity as a medical problem. Nature 2000, 404, 635–643. [Google Scholar] [CrossRef]
  18. Davis, C.D. The Gut Microbiome and Its Role in Obesity. Nutr. Today 2016, 51, 167–174. [Google Scholar] [CrossRef] [PubMed]
  19. Rakhra, V.; Galappaththy, S.L.; Bulchandani, S.; Cabandugama, P.K. Obesity and the Western Diet: How We Got Here. Mo. Med. 2020, 117, 536–538. [Google Scholar]
  20. Chaput, J.P.; McHill, A.W.; Cox, R.C.; Broussard, J.L.; Dutil, C.; da Costa, B.G.G.; Sampasa-Kanyinga, H.; Wright, K.P., Jr. The role of insufficient sleep and circadian misalignment in obesity. Nat. Rev. Endocrinol. 2023, 19, 82–97. [Google Scholar] [CrossRef] [PubMed]
  21. Raiman, L.; Amarnani, R.; Abdur-Rahman, M.; Marshall, A.; Mani-Babu, S. The role of physical activity in obesity: Let’s actively manage obesity. Clin. Med. 2023, 23, 311–317. [Google Scholar] [CrossRef]
  22. Kumar, R.; Rizvi, M.R.; Saraswat, S. Obesity and Stress: A Contingent Paralysis. Int. J. Prev. Med. 2022, 13, 95. [Google Scholar] [CrossRef]
  23. Viecelli, C.; Ewald, C.Y. The non-modifiable factors age, gender, and genetics influence resistance exercise. Front. Aging 2022, 3, 1005848. [Google Scholar] [CrossRef]
  24. Frayling, T.M.; Timpson, N.J.; Weedon, M.N.; Zeggini, E.; Freathy, R.M.; Lindgren, C.M.; Perry, J.R.; Elliott, K.S.; Lango, H.; Rayner, N.W.; et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007, 316, 889–894. [Google Scholar] [CrossRef]
  25. Yang, J.; Manolio, T.A.; Pasquale, L.R.; Boerwinkle, E.; Caporaso, N.; Cunningham, J.M.; de Andrade, M.; Feenstra, B.; Feingold, E.; Hayes, M.G.; et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nat. Genet. 2011, 43, 519–525. [Google Scholar] [CrossRef]
  26. Locke, A.E.; Kahali, B.; Berndt, S.I.; Justice, A.E.; Pers, T.H.; Day, F.R.; Powell, C.; Vedantam, S.; Buchkovich, M.L.; Yang, J.; et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 2015, 518, 197–206. [Google Scholar] [CrossRef]
  27. van Dijk, S.J.; Tellam, R.L.; Morrison, J.L.; Muhlhausler, B.S.; Molloy, P.L. Recent developments on the role of epigenetics in obesity and metabolic disease. Clin. Epigenet. 2015, 7, 66. [Google Scholar] [CrossRef]
  28. Kladnicka, I.; Bludovska, M.; Plavinova, I.; Muller, L.; Mullerova, D. Obesogens in Foods. Biomolecules 2022, 12, 680. [Google Scholar] [CrossRef] [PubMed]
  29. Engin, A. The Definition and Prevalence of Obesity and Metabolic Syndrome. Adv. Exp. Med. Biol. 2017, 960, 1–17. [Google Scholar] [CrossRef] [PubMed]
  30. Marcelin, G.; Chua, S., Jr. Contributions of adipocyte lipid metabolism to body fat content and implications for the treatment of obesity. Curr. Opin. Pharmacol. 2010, 10, 588–593. [Google Scholar] [CrossRef] [PubMed]
  31. Leitner, D.R.; Frühbeck, G.; Yumuk, V.; Schindler, K.; Micic, D.; Woodward, E.; Toplak, H. Obesity and Type 2 Diabetes: Two Diseases with a Need for Combined Treatment Strategies—EASO Can Lead the Way. Obes. Facts 2017, 10, 483–492. [Google Scholar] [CrossRef]
  32. Parto, P.; Lavie, C.J. Obesity and CardiovascularDiseases. Curr. Probl. Cardiol. 2017, 42, 376–394. [Google Scholar] [CrossRef]
  33. Nakamura, K.; Fuster, J.J.; Walsh, K. Adipokines: A link between obesity and cardiovascular disease. J. Cardiol. 2014, 63, 250–259. [Google Scholar] [CrossRef] [PubMed]
  34. Castoldi, A.; Naffah de Souza, C.; Câmara, N.O.; Moraes-Vieira, P.M. The Macrophage Switch in Obesity Development. Front. Immunol. 2015, 6, 637. [Google Scholar] [CrossRef]
  35. Cohen, P.; Spiegelman, B.M. Cell biology of fat storage. Mol. Biol. Cell 2016, 27, 2523–2527. [Google Scholar] [CrossRef] [PubMed]
  36. Redinger, R.N. The pathophysiology of obesity and its clinical manifestations. Gastroenterol. Hepatol. 2007, 3, 856–863. [Google Scholar]
  37. O’Brien, P.D.; Hinder, L.M.; Callaghan, B.C.; Feldman, E.L. Neurological consequences of obesity. Lancet Neurol. 2017, 16, 465–477. [Google Scholar] [CrossRef] [PubMed]
  38. Hurtado, A.M.; Acosta, A. Precision Medicine and Obesity. Gastroenterol. Clin. North. Am. 2021, 50, 127–139. [Google Scholar] [CrossRef]
  39. Huang, D.; Deng, M.; Kuang, S. Polymeric Carriers for Controlled Drug Delivery in Obesity Treatment. Trends Endocrinol. Metab. 2019, 30, 974–989. [Google Scholar] [CrossRef]
  40. Gostoli, S.; Raimondi, G.; Popa, A.P.; Giovannini, M.; Benasi, G.; Rafanelli, C. Behavioral Lifestyle Interventions for Weight Loss in Overweight or Obese Patients with Type 2 Diabetes: A Systematic Review of the Literature. Curr. Obes. Rep. 2024, 13, 224–241. [Google Scholar] [CrossRef]
  41. Unick, J.L.; Beavers, D.; Bond, D.S.; Clark, J.M.; Jakicic, J.M.; Kitabchi, A.E.; Knowler, W.C.; Wadden, T.A.; Wagenknecht, L.E.; Wing, R.R. The long-term effectiveness of a lifestyle intervention in severely obese individuals. Am. J. Med. 2013, 126, 236–242. [Google Scholar] [CrossRef]
  42. Wing, R.R.; Phelan, S. Long-term weight loss maintenance. Am. J. Clin. Nutr. 2005, 82, 222s–225s. [Google Scholar] [CrossRef] [PubMed]
  43. Cava, E.; Yeat, N.C.; Mittendorfer, B. Preserving Healthy Muscle during Weight Loss. Adv. Nutr. 2017, 8, 511–519. [Google Scholar] [CrossRef]
  44. Schmidt, S.K.; Hemmestad, L.; MacDonald, C.S.; Langberg, H.; Valentiner, L.S. Motivation and Barriers to Maintaining Lifestyle Changes in Patients with Type 2 Diabetes after an Intensive Lifestyle Intervention (The U-TURN Trial): A Longitudinal Qualitative Study. Int. J. Environ. Res. Public Health 2020, 17, 7454. [Google Scholar] [CrossRef] [PubMed]
  45. Wadden, T.A.; Tronieri, J.S.; Butryn, M.L. Lifestyle modification approaches for the treatment of obesity in adults. Am. Psychol. 2020, 75, 235–251. [Google Scholar] [CrossRef]
  46. Wadden, T.A.; West, D.S.; Neiberg, R.H.; Wing, R.R.; Ryan, D.H.; Johnson, K.C.; Foreyt, J.P.; Hill, J.O.; Trence, D.L.; Vitolins, M.Z. One-year weight losses in the Look AHEAD study: Factors associated with success. Obesity 2009, 17, 713–722. [Google Scholar] [CrossRef] [PubMed]
  47. Weiss, E.P.; Racette, S.B.; Villareal, D.T.; Fontana, L.; Steger-May, K.; Schechtman, K.B.; Klein, S.; Ehsani, A.A.; Holloszy, J.O. Lower extremity muscle size and strength and aerobic capacity decrease with caloric restriction but not with exercise-induced weight loss. J. Appl. Physiol. 2007, 102, 634–640. [Google Scholar] [CrossRef]
  48. Cooke, D.; Bloom, S. The obesity pipeline: Current strategies in the development of anti-obesity drugs. Nat. Rev. Drug Discov. 2006, 5, 919–931. [Google Scholar] [CrossRef]
  49. Sargent, B.J.; Moore, N.A. New central targets for the treatment of obesity. Br. J. Clin. Pharmacol. 2009, 68, 852–860. [Google Scholar] [CrossRef]
  50. de Andrade Mesquita, L.; Fagundes Piccoli, G.; Richter da Natividade, G.; Frison Spiazzi, B.; Colpani, V.; Gerchman, F. Is lorcaserin really associated with increased risk of cancer? A systematic review and meta-analysis. Obes. Rev. 2021, 22, e13170. [Google Scholar] [CrossRef]
  51. Pilitsi, E.; Farr, O.M.; Polyzos, S.A.; Perakakis, N.; Nolen-Doerr, E.; Papathanasiou, A.E.; Mantzoros, C.S. Pharmacotherapy of obesity: Available medications and drugs under investigation. Metabolism 2019, 92, 170–192. [Google Scholar] [CrossRef]
  52. Srivastava, G.; Apovian, C.M. Current pharmacotherapy for obesity. Nat. Rev. Endocrinol. 2018, 14, 12–24. [Google Scholar] [CrossRef]
  53. Gulinac, M.; Miteva, D.G.; Peshevska-Sekulovska, M.; Novakov, I.P.; Antovic, S.; Peruhova, M.; Snegarova, V.; Kabakchieva, P.; Assyov, Y.; Vasilev, G.; et al. Long-term effectiveness, outcomes and complications of bariatric surgery. World J. Clin. Cases 2023, 11, 4504–4512. [Google Scholar] [CrossRef]
  54. Lim, R.; Beekley, A.; Johnson, D.C.; Davis, K.A. Early and late complications of bariatric operation. Trauma. Surg. Acute Care Open 2018, 3, e000219. [Google Scholar] [CrossRef]
  55. Ashour, M.M.; Mabrouk, M.; Aboelnasr, M.A.; Beherei, H.H.; Tohamy, K.M.; Das, D.B. Anti-Obesity Drug Delivery Systems: Recent Progress and Challenges. Pharmaceutics 2023, 15, 2635. [Google Scholar] [CrossRef]
  56. Dombrowski, S.U.; Knittle, K.; Avenell, A.; Araújo-Soares, V.; Sniehotta, F.F. Long term maintenance of weight loss with non-surgical interventions in obese adults: Systematic review and meta-analyses of randomised controlled trials. BMJ 2014, 348, g2646. [Google Scholar] [CrossRef]
  57. Olateju, I.V.; Ogwu, D.; Owolabi, M.O.; Azode, U.; Osula, F.; Okeke, R.; Akabalu, I. Role of Behavioral Interventions in the Management of Obesity. Cureus 2021, 13, e18080. [Google Scholar] [CrossRef] [PubMed]
  58. Williams, K.V.; Mullen, M.L.; Kelley, D.E.; Wing, R.R. The effect of short periods of caloric restriction on weight loss and glycemic control in type 2 diabetes. Diabetes Care 1998, 21, 2–8. [Google Scholar] [CrossRef]
  59. Gadde, K.M. Current pharmacotherapy for obesity: Extrapolation of clinical trials data to practice. Expert. Opin. Pharmacother. 2014, 15, 809–822. [Google Scholar] [CrossRef] [PubMed]
  60. Vairavamurthy, J.; Cheskin, L.J.; Kraitchman, D.L.; Arepally, A.; Weiss, C.R. Current and cutting-edge interventions for the treatment of obese patients. Eur. J. Radiol. 2017, 93, 134–142. [Google Scholar] [CrossRef] [PubMed]
  61. Steenackers, N.; Van der Schueren, B.; Mertens, A.; Lannoo, M.; Grauwet, T.; Augustijns, P.; Matthys, C. Iron deficiency after bariatric surgery: What is the real problem? Proc. Nutr. Soc. 2018, 77, 445–455. [Google Scholar] [CrossRef]
  62. Fried, M.; Yumuk, V.; Oppert, J.M.; Scopinaro, N.; Torres, A.; Weiner, R.; Yashkov, Y.; Frühbeck, G. Interdisciplinary European guidelines on metabolic and bariatric surgery. Obes. Surg. 2014, 24, 42–55. [Google Scholar] [CrossRef] [PubMed]
  63. Mechanick, J.I.; Youdim, A.; Jones, D.B.; Garvey, W.T.; Hurley, D.L.; McMahon, M.M.; Heinberg, L.J.; Kushner, R.; Adams, T.D.; Shikora, S.; et al. Clinical practice guidelines for the perioperative nutritional, metabolic, and nonsurgical support of the bariatric surgery patient—2013 update: Cosponsored by American Association of Clinical Endocrinologists, The Obesity Society, and American Society for Metabolic & Bariatric Surgery. Obesity 2013, 21, 159–191. [Google Scholar] [CrossRef] [PubMed]
  64. Phillips, B.T.; Shikora, S.A. The history of metabolic and bariatric surgery: Development of standards for patient safety and efficacy. Metabolism 2018, 79, 97–107. [Google Scholar] [CrossRef]
  65. Hachuła, M.; Kosowski, M.; Zielańska, K.; Basiak, M.; Okopień, B. The Impact of Various Methods of Obesity Treatment on the Quality of Life and Mental Health—A Narrative Review. Int. J. Environ. Res. Public Health 2023, 20, 2122. [Google Scholar] [CrossRef] [PubMed]
  66. Ruban, A.; Stoenchev, K.; Ashrafian, H.; Teare, J. Current treatments for obesity. Clin. Med. 2019, 19, 205–212. [Google Scholar] [CrossRef]
  67. Bult, M.J.; van Dalen, T.; Muller, A.F. Surgical treatment of obesity. Eur. J. Endocrinol. 2008, 158, 135–145. [Google Scholar] [CrossRef]
  68. Benaiges, D.; Pedro-Botet, J.; Flores-Le Roux, J.A.; Climent, E.; Goday, A. Past, present and future of pharmacotherapy for obesity. Clin. Investig. Arterioscler. 2017, 29, 256–264. [Google Scholar] [CrossRef]
  69. Anderson, J.W.; Greenway, F.L.; Fujioka, K.; Gadde, K.M.; McKenney, J.; O’Neil, P.M. Bupropion SR enhances weight loss: A 48-week double-blind, placebo- controlled trial. Obes. Res. 2002, 10, 633–641. [Google Scholar] [CrossRef]
  70. Wadden, T.A.; Berkowitz, R.I.; Womble, L.G.; Sarwer, D.B.; Phelan, S.; Cato, R.K.; Hesson, L.A.; Osei, S.Y.; Kaplan, R.; Stunkard, A.J. Randomized trial of lifestyle modification and pharmacotherapy for obesity. N. Engl. J. Med. 2005, 353, 2111–2120. [Google Scholar] [CrossRef]
  71. Chen, K.Y.; Brychta, R.J.; Abdul Sater, Z.; Cassimatis, T.M.; Cero, C.; Fletcher, L.A.; Israni, N.S.; Johnson, J.W.; Lea, H.J.; Linderman, J.D.; et al. Opportunities and challenges in the therapeutic activation of human energy expenditure and thermogenesis to manage obesity. J. Biol. Chem. 2020, 295, 1926–1942. [Google Scholar] [CrossRef]
  72. Colman, E. Anorectics on trial: A half century of federal regulation of prescription appetite suppressants. Ann. Intern. Med. 2005, 143, 380–385. [Google Scholar] [CrossRef]
  73. Thompson, P.D. Valvular heart disease associated with fenfluramine-phentermine. N. Engl. J. Med. 1997, 337, 581–588. [Google Scholar] [CrossRef]
  74. Ma, P.; He, P.; Xu, C.Y.; Hou, B.Y.; Qiang, G.F.; Du, G.H. Recent developments in natural products for white adipose tissue browning. Chin. J. Nat. Med. 2020, 18, 803–817. [Google Scholar] [CrossRef]
  75. McClements, D.J. Advances in nanoparticle and microparticle delivery systems for increasing the dispersibility, stability, and bioactivity of phytochemicals. Biotechnol. Adv. 2020, 38, 107287. [Google Scholar] [CrossRef] [PubMed]
  76. Overgaard, R.V.; Navarria, A.; Ingwersen, S.H.; Bækdal, T.A.; Kildemoes, R.J. Clinical Pharmacokinetics of Oral Semaglutide: Analyses of Data from Clinical Pharmacology Trials. Clin. Pharmacokinet. 2021, 60, 1335–1348. [Google Scholar] [CrossRef] [PubMed]
  77. Angelidi, A.M.; Belanger, M.J.; Kokkinos, A.; Koliaki, C.C.; Mantzoros, C.S. Novel Noninvasive Approaches to the Treatment of Obesity: From Pharmacotherapy to Gene Therapy. Endocr. Rev. 2022, 43, 507–557. [Google Scholar] [CrossRef]
  78. Zhang, Y.; Liu, Q.; Yu, J.; Yu, S.; Wang, J.; Qiang, L.; Gu, Z. Locally Induced Adipose Tissue Browning by Microneedle Patch for Obesity Treatment. ACS Nano 2017, 11, 9223–9230. [Google Scholar] [CrossRef] [PubMed]
  79. Liao, Z.X.; Liu, M.C.; Kempson, I.M.; Fa, Y.C.; Huang, K.Y. Light-triggered methylcellulose gold nanoparticle hydrogels for leptin release to inhibit fat stores in adipocytes. Int. J. Nanomed. 2017, 12, 7603–7611. [Google Scholar] [CrossRef]
  80. Xue, Y.; Xu, X.; Zhang, X.Q.; Farokhzad, O.C.; Langer, R. Preventing diet-induced obesity in mice by adipose tissue transformation and angiogenesis using targeted nanoparticles. Proc. Natl. Acad. Sci. USA 2016, 113, 5552–5557. [Google Scholar] [CrossRef]
  81. Hossen, M.N.; Kajimoto, K.; Akita, H.; Hyodo, M.; Harashima, H. Vascular-targeted nanotherapy for obesity: Unexpected passive targeting mechanism to obese fat for the enhancement of active drug delivery. J. Control. Release 2012, 163, 101–110. [Google Scholar] [CrossRef] [PubMed]
  82. Huang, D.; Narayanan, N.; Cano-Vega, M.A.; Jia, Z.; Ajuwon, K.M.; Kuang, S.; Deng, M. Nanoparticle-Mediated Inhibition of Notch Signaling Promotes Mitochondrial Biogenesis and Reduces Subcutaneous Adipose Tissue Expansion in Pigs. iScience 2020, 23, 101167. [Google Scholar] [CrossRef]
  83. Jiang, C.; Cano-Vega, M.A.; Yue, F.; Kuang, L.; Narayanan, N.; Uzunalli, G.; Merkel, M.P.; Kuang, S.; Deng, M. Dibenzazepine-Loaded Nanoparticles Induce Local Browning of White Adipose Tissue to Counteract Obesity. Mol. Ther. 2017, 25, 1718–1729. [Google Scholar] [CrossRef]
  84. Thaker, V.V. Genetic and Epigenetic Causes of Obesity. Adolesc. Med. State Art. Rev. 2017, 28, 379–405. [Google Scholar] [PubMed]
  85. Gao, M.; Liu, D. Gene therapy for obesity: Progress and prospects. Discov. Med. 2014, 17, 319–328. [Google Scholar] [PubMed]
  86. Muzzin, P.; Eisensmith, R.C.; Copeland, K.C.; Woo, S.L. Correction of obesity and diabetes in genetically obese mice by leptin gene therapy. Proc. Natl. Acad. Sci. USA 1996, 93, 14804–14808. [Google Scholar] [CrossRef]
  87. Ueno, N.; Inui, A.; Kalra, P.S.; Kalra, S.P. Leptin transgene expression in the hypothalamus enforces euglycemia in diabetic, insulin-deficient nonobese Akita mice and leptin-deficient obese ob/ob mice. Peptides 2006, 27, 2332–2342. [Google Scholar] [CrossRef]
  88. Chung, J.Y.; Ain, Q.U.; Song, Y.; Yong, S.B.; Kim, Y.H. Targeted delivery of CRISPR interference system against Fabp4 to white adipocytes ameliorates obesity, inflammation, hepatic steatosis, and insulin resistance. Genome Res. 2019, 29, 1442–1452. [Google Scholar] [CrossRef]
  89. Matharu, N.; Rattanasopha, S.; Tamura, S.; Maliskova, L.; Wang, Y.; Bernard, A.; Hardin, A.; Eckalbar, W.L.; Vaisse, C.; Ahituv, N. CRISPR-mediated activation of a promoter or enhancer rescues obesity caused by haploinsufficiency. Science 2019, 363, eaau0629. [Google Scholar] [CrossRef]
  90. Puhl, D.L.; D’Amato, A.R.; Gilbert, R.J. Challenges of gene delivery to the central nervous system and the growing use of biomaterial vectors. Brain Res. Bull. 2019, 150, 216–230. [Google Scholar] [CrossRef]
  91. Age, F.A. FDA-Approved Drugs to Treat Overweight and Obesity. J. Psychosoc. Nurs. Ment. Health Serv. 2022, 60, 7–8. [Google Scholar] [CrossRef]
  92. Kim, K.K.; Cho, H.J.; Kang, H.C.; Youn, B.B.; Lee, K.R. Effects on weight reduction and safety of short-term phentermine administration in Korean obese people. Yonsei Med. J. 2006, 47, 614–625. [Google Scholar] [CrossRef] [PubMed]
  93. Heck, A.M.; Yanovski, J.A.; Calis, K.A. Orlistat, a new lipase inhibitor for the management of obesity. Pharmacotherapy 2000, 20, 270–279. [Google Scholar] [CrossRef]
  94. Gadde, K.M.; Martin, C.K.; Berthoud, H.R.; Heymsfield, S.B. Obesity: Pathophysiology and Management. J. Am. Coll. Cardiol. 2018, 71, 69–84. [Google Scholar] [CrossRef]
  95. Martin, C.K.; Redman, L.M.; Zhang, J.; Sanchez, M.; Anderson, C.M.; Smith, S.R.; Ravussin, E. Lorcaserin, a 5-HT(2C) receptor agonist, reduces body weight by decreasing energy intake without influencing energy expenditure. J. Clin. Endocrinol. Metab. 2011, 96, 837–845. [Google Scholar] [CrossRef]
  96. Fidler, M.C.; Sanchez, M.; Raether, B.; Weissman, N.J.; Smith, S.R.; Shanahan, W.R.; Anderson, C.M. A one-year randomized trial of lorcaserin for weight loss in obese and overweight adults: The BLOSSOM trial. J. Clin. Endocrinol. Metab. 2011, 96, 3067–3077. [Google Scholar] [CrossRef] [PubMed]
  97. Sharretts, J.; Galescu, O.; Gomatam, S.; Andraca-Carrera, E.; Hampp, C.; Yanoff, L. Cancer Risk Associated with Lorcaserin—The FDA’s Review of the CAMELLIA-TIMI 61 Trial. N. Engl. J. Med. 2020, 383, 1000–1002. [Google Scholar] [CrossRef]
  98. Van Can, J.; Sloth, B.; Jensen, C.B.; Flint, A.; Blaak, E.E.; Saris, W.H. Effects of the once-daily GLP-1 analog liraglutide on gastric emptying, glycemic parameters, appetite and energy metabolism in obese, non-diabetic adults. Int. J. Obes. 2014, 38, 784–793. [Google Scholar] [CrossRef]
  99. Daneschvar, H.L.; Aronson, M.D.; Smetana, G.W. FDA-Approved Anti-Obesity Drugs in the United States. Am. J. Med. 2016, 129, 879.e1–879.e6. [Google Scholar] [CrossRef]
  100. US Food and Drug Administration. FDA Approves New Drug Treatment for Chronic Weight Management, First Since 2014; Center for Drug Evaluation and Research: Washington, DC, USA, 2021. [Google Scholar]
  101. Rubino, D.M.; Greenway, F.L.; Khalid, U.; O’Neil, P.M.; Rosenstock, J.; Sørrig, R.; Wadden, T.A.; Wizert, A.; Garvey, W.T. Effect of Weekly Subcutaneous Semaglutide vs Daily Liraglutide on Body Weight in Adults With Overweight or Obesity Without Diabetes: The STEP 8 Randomized Clinical Trial. JAMA 2022, 327, 138–150. [Google Scholar] [CrossRef]
  102. Wilding, J.P.H.; Batterham, R.L.; Calanna, S.; Davies, M.; Van Gaal, L.F.; Lingvay, I.; McGowan, B.M.; Rosenstock, J.; Tran, M.T.D.; Wadden, T.A.; et al. Once-Weekly Semaglutide in Adults with Overweight or Obesity. N. Engl. J. Med. 2021, 384, 989–1002. [Google Scholar] [CrossRef] [PubMed]
  103. Richard, D.; Ferland, J.; Lalonde, J.; Samson, P.; Deshaies, Y. Influence of topiramate in the regulation of energy balance. Nutrition 2000, 16, 961–966. [Google Scholar] [CrossRef]
  104. Gadde, K.M.; Apolzan, J.W.; Berthoud, H.-R. Pharmacotherapy for patients with obesity. Clin. Chem. 2018, 64, 118–129. [Google Scholar] [CrossRef] [PubMed]
  105. Greenway, F.L.; Fujioka, K.; Plodkowski, R.A.; Mudaliar, S.; Guttadauria, M.; Erickson, J.; Kim, D.D.; Dunayevich, E. Effect of naltrexone plus bupropion on weight loss in overweight and obese adults (COR-I): A multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 2010, 376, 595–605, Erratum in Lancet 2010, 376, 594. Erratum in Lancet 2010, 376, 1392. [Google Scholar] [CrossRef]
  106. Cignarella, A.; Busetto, L.; Vettor, R. Pharmacotherapy of obesity: An update. Pharmacol. Res. 2021, 169, 105649. [Google Scholar] [CrossRef]
  107. Huynh, K.; Klose, M.; Krogsgaard, K.; Drejer, J.; Byberg, S.; Madsbad, S.; Magkos, F.; Aharaz, A.; Edsberg, B.; Tfelt-Hansen, J.; et al. Randomized controlled trial of Tesomet for weight loss in hypothalamic obesity. Eur. J. Endocrinol. 2022, 186, 687–700. [Google Scholar] [CrossRef]
  108. Ambery, P.; Parker, V.E.; Stumvoll, M.; Posch, M.G.; Heise, T.; Plum-Moerschel, L.; Tsai, L.F.; Robertson, D.; Jain, M.; Petrone, M.; et al. MEDI0382, a GLP-1 and glucagon receptor dual agonist, in obese or overweight patients with type 2 diabetes: A randomised, controlled, double-blind, ascending dose and phase 2a study. Lancet 2018, 391, 2607–2618. [Google Scholar] [CrossRef]
  109. Nahra, R.; Wang, T.; Gadde, K.M.; Oscarsson, J.; Stumvoll, M.; Jermutus, L.; Hirshberg, B.; Ambery, P. Effects of Cotadutide on Metabolic and Hepatic Parameters in Adults With Overweight or Obesity and Type 2 Diabetes: A 54-Week Randomized Phase 2b Study. Diabetes Care 2021, 44, 1433–1442, Erratum in Diabetes Care 2022, 45, 3112. [Google Scholar] [CrossRef]
  110. Tillner, J.; Posch, M.G.; Wagner, F.; Teichert, L.; Hijazi, Y.; Einig, C.; Keil, S.; Haack, T.; Wagner, M.; Bossart, M. A novel dual glucagon-like peptide and glucagon receptor agonist SAR425899: Results of randomized, placebo-controlled first-in-human and first-in-patient trials. Diabetes Obes. Metab. 2019, 21, 120–128. [Google Scholar] [CrossRef] [PubMed]
  111. Furihata, K.; Mimura, H.; Urva, S.; Oura, T.; Ohwaki, K.; Imaoka, T. A phase 1 multiple-ascending dose study of tirzepatide in Japanese participants with type 2 diabetes. Diabetes Obes. Metab. 2022, 24, 239–246. [Google Scholar] [CrossRef]
  112. Abdel-Malek, M.; Yang, L.; Miras, A.D. Pharmacotherapy for chronic obesity management: A look into the future. Intern. Emerg. Med. 2023, 18, 1019–1030. [Google Scholar] [CrossRef]
  113. Jastreboff, A.M.; Aronne, L.J.; Ahmad, N.N.; Wharton, S.; Connery, L.; Alves, B.; Kiyosue, A.; Zhang, S.; Liu, B.; Bunck, M.C.; et al. Tirzepatide Once Weekly for the Treatment of Obesity. N. Engl. J. Med. 2022, 387, 205–216. [Google Scholar] [CrossRef]
  114. Frias, J.P.; Nauck, M.A.; Van, J.; Kutner, M.E.; Cui, X.; Benson, C.; Urva, S.; Gimeno, R.E.; Milicevic, Z.; Robins, D.; et al. Efficacy and safety of LY3298176, a novel dual GIP and GLP-1 receptor agonist, in patients with type 2 diabetes: A randomised, placebo-controlled and active comparator-controlled phase 2 trial. Lancet 2018, 392, 2180–2193. [Google Scholar] [CrossRef]
  115. Mathiesen, D.S.; Bagger, J.I.; Knop, F.K. Long-acting amylin analogues for the management of obesity. Curr. Opin. Endocrinol. Diabetes Obes. 2022, 29, 183–190. [Google Scholar] [CrossRef]
  116. Lau, D.C.W.; Erichsen, L.; Francisco, A.M.; Satylganova, A.; le Roux, C.W.; McGowan, B.; Pedersen, S.D.; Pietiläinen, K.H.; Rubino, D.; Batterham, R.L. Once-weekly cagrilintide for weight management in people with overweight and obesity: A multicentre, randomised, double-blind, placebo-controlled and active-controlled, dose-finding phase 2 trial. Lancet 2021, 398, 2160–2172. [Google Scholar] [CrossRef] [PubMed]
  117. Enebo, L.B.; Berthelsen, K.K.; Kankam, M.; Lund, M.T.; Rubino, D.M.; Satylganova, A.; Lau, D.C.W. Safety, tolerability, pharmacokinetics, and pharmacodynamics of concomitant administration of multiple doses of cagrilintide with semaglutide 2·4 mg for weight management: A randomised, controlled, phase 1b trial. Lancet 2021, 397, 1736–1748. [Google Scholar] [CrossRef] [PubMed]
  118. Gómez-Zorita, S.; Trepiana, J.; González-Arceo, M.; Aguirre, L.; Milton-Laskibar, I.; González, M.; Eseberri, I.; Fernández-Quintela, A.; Portillo, M.P. Anti-Obesity Effects of Microalgae. Int. J. Mol. Sci. 2019, 21, 41. [Google Scholar] [CrossRef] [PubMed]
  119. Hernández-Lepe, M.A.; Wall-Medrano, A.; López-Díaz, J.A.; Juárez-Oropeza, M.A.; Hernández-Torres, R.P.; Ramos-Jiménez, A. Hypolipidemic Effect of Arthrospira (Spirulina) maxima Supplementation and a Systematic Physical Exercise Program in Overweight and Obese Men: A Double-Blind, Randomized, and Crossover Controlled Trial. Mar. Drugs 2019, 17, 270. [Google Scholar] [CrossRef]
  120. Fukasaka, Y.; Nambu, H.; Tanioka, H.; Obata, A.; Tonomura, M.; Okuno, T.; Yukioka, H. An insurmountable NPY Y5 receptor antagonist exhibits superior anti-obesity effects in high-fat diet-induced obese mice. Neuropeptides 2018, 70, 55–63. [Google Scholar] [CrossRef]
  121. Powell, A.G.; Apovian, C.M.; Aronne, L.J. New drug targets for the treatment of obesity. Clin. Pharmacol. Ther. 2011, 90, 40–51. [Google Scholar] [CrossRef]
  122. Ratemi, E.; Sultana Shaik, A.; Al Faraj, A.; Halwani, R. Alternative approaches for the treatment of airway diseases: Focus on nanoparticle medicine. Clin. Exp. Allergy 2016, 46, 1033–1042. [Google Scholar] [CrossRef] [PubMed]
  123. de Jesus Felismino, C.; Helal-Neto, E.; Portilho, F.L.; Rocha Pinto, S.; Sancenón, F.; Martínez-Máñez, R.; de Assis Ferreira, A.; da Silva, S.V.; Barja-Fidalgo, T.C.; Santos-Oliveira, R. Effect of obesity on biodistribution of nanoparticles. J. Control. Release 2018, 281, 11–18. [Google Scholar] [CrossRef]
  124. Sawie, H.G.; Khadrawy, Y.A.; El-Gizawy, M.M.; Mourad, H.H.; Omara, E.A.; Hosny, E.N. Effect of alpha-lipoic acid and caffeine-loaded chitosan nanoparticles on obesity and its complications in liver and kidney in rats. Naunyn Schmiedebergs Arch. Pharmacol. 2023, 396, 3017–3031. [Google Scholar] [CrossRef]
  125. Zu, Y.; Zhao, L.; Hao, L.; Mechref, Y.; Zabet-Moghaddam, M.; Keyel, P.A.; Abbasi, M.; Wu, D.; Dawson, J.A.; Zhang, R.; et al. Browning white adipose tissue using adipose stromal cell-targeted resveratrol-loaded nanoparticles for combating obesity. J. Control. Release 2021, 333, 339–351. [Google Scholar] [CrossRef]
  126. Hiradate, R.; Khalil, I.A.; Matsuda, A.; Sasaki, M.; Hida, K.; Harashima, H. A novel dual-targeted rosiglitazone-loaded nanoparticle for the prevention of diet-induced obesity via the browning of white adipose tissue. J. Control. Release 2021, 329, 665–675. [Google Scholar] [CrossRef]
  127. Di Mascolo, D.; Lyon, C.J.; Aryal, S.; Ramirez, M.R.; Wang, J.; Candeloro, P.; Guindani, M.; Hsueh, W.A.; Decuzzi, P. Rosiglitazone-loaded nanospheres for modulating macrophage-specific inflammation in obesity. J. Control. Release 2013, 170, 460–468. [Google Scholar] [CrossRef]
  128. Lacatusu, I.; Badea, N.; Udeanu, D.; Coc, L.; Pop, A.; Cioates Negut, C.; Tanase, C.; Stan, R.; Meghea, A. Improved anti-obesity effect of herbal active and endogenous lipids co-loaded lipid nanocarriers: Preparation, in vitro and in vivo evaluation. Mater. Sci. Eng. C 2019, 99, 12–24. [Google Scholar] [CrossRef]
  129. Toita, R.; Kawano, T.; Murata, M.; Kang, J.-H. Anti-obesity and anti-inflammatory effects of macrophage-targeted interleukin-10-conjugated liposomes in obese mice. Biomaterials 2016, 110, 81–88. [Google Scholar] [CrossRef] [PubMed]
  130. Liu, J.; Zhou, X.; Feng, C.; Zheng, W.; Chen, P.; Zhang, X.; Hou, P. Glucagon-modified Liposomes Delivering Thyroid Hormone for Anti-obesity Therapy. Arch. Med. Res. 2023, 54, 287–298. [Google Scholar] [CrossRef]
  131. Osinski, V.; Bauknight, D.K.; Dasa, S.S.K.; Harms, M.J.; Kroon, T.; Marshall, M.A.; Garmey, J.C.; Nguyen, A.T.; Hartman, J.; Upadhye, A.; et al. In vivo liposomal delivery of PPARα/γ dual agonist tesaglitazar in a model of obesity enriches macrophage targeting and limits liver and kidney drug effects. Theranostics 2020, 10, 585–601. [Google Scholar] [CrossRef] [PubMed]
  132. Sadeqi, A.; Kiaee, G.; Zeng, W.; Rezaei Nejad, H.; Sonkusale, S. Hard polymeric porous microneedles on stretchable substrate for transdermal drug delivery. Sci. Rep. 2022, 12, 1853. [Google Scholar] [CrossRef]
  133. Xie, Y.; Shao, R.; Lin, Y.; Wang, C.; Tan, Y.; Xie, W.; Sun, S. Improved Therapeutic Efficiency against Obesity through Transdermal Drug Delivery Using Microneedle Arrays. Pharmaceutics 2021, 13, 827. [Google Scholar] [CrossRef] [PubMed]
  134. Dangol, M.; Kim, S.; Li, C.G.; Fakhraei Lahiji, S.; Jang, M.; Ma, Y.; Huh, I.; Jung, H. Anti-obesity effect of a novel caffeine-loaded dissolving microneedle patch in high-fat diet-induced obese C57BL/6J mice. J. Control. Release 2017, 265, 41–47. [Google Scholar] [CrossRef] [PubMed]
  135. Bao, C.; Li, Z.; Liang, S.; Hu, Y.; Wang, X.; Fang, B.; Wang, P.; Chen, S.; Li, Y. Microneedle Patch Delivery of Capsaicin-Containing α-Lactalbumin Nanomicelles to Adipocytes Achieves Potent Anti-Obesity Effects. Adv. Funct. Mater. 2021, 31, 2011130. [Google Scholar] [CrossRef]
  136. Zhang, X.-Z.; Guan, J.; Cai, S.-L.; Du, Q.; Guo, M.-L. Polymeric in situ hydrogel implant of epigallocatechin gallate (EGCG) for prolonged and improved antihyperlipidemic and anti-obesity activity: Preparation and characterization. J. Biomater. Tissue Eng. 2015, 5, 813–817. [Google Scholar] [CrossRef]
  137. Jacob, S.; Nair, A.B.; Shah, J.; Sreeharsha, N.; Gupta, S.; Shinu, P. Emerging Role of Hydrogels in Drug Delivery Systems, Tissue Engineering and Wound Management. Pharmaceutics 2021, 13, 357. [Google Scholar] [CrossRef]
  138. Li, J.; Mooney, D.J. Designing hydrogels for controlled drug delivery. Nat. Rev. Mater. 2016, 1, 16071. [Google Scholar] [CrossRef]
  139. Ghasemiyeh, P.; Mohammadi-Samani, S. Hydrogels as drug delivery systems; pros and cons. Trends Pharm. Sci. 2019, 5, 7–24. [Google Scholar]
  140. Hoare, T.R.; Kohane, D.S. Hydrogels in drug delivery: Progress and challenges. Polymer 2008, 49, 1993–2007. [Google Scholar] [CrossRef]
  141. Gu, D.; O’Connor, A.J.; GH Qiao, G.; Ladewig, K. Hydrogels with smart systems for delivery of hydrophobic drugs. Expert. Opin. Drug Deliv. 2017, 14, 879–895. [Google Scholar] [CrossRef]
  142. Zhao, H.; Wu, M.; Tang, X.; Li, Q.; Yi, X.; Wang, S.; Jia, C.; Wei, Z.; Sun, X. Function of Chick Subcutaneous Adipose Tissue During the Embryonic and Posthatch Period. Front. Physiol. 2021, 12, 684426. [Google Scholar] [CrossRef] [PubMed]
  143. Cinti, S. The adipose organ. Prostaglandins Leukot. Essent. Fat. Acids 2005, 73, 9–15. [Google Scholar] [CrossRef]
  144. Barrett, P.; Mercer, J.G.; Morgan, P.J. Preclinical models for obesity research. Dis. Model. Mech. 2016, 9, 1245–1255. [Google Scholar] [CrossRef]
  145. Kissig, M.; Shapira, S.N.; Seale, P. SnapShot: Brown and Beige Adipose Thermogenesis. Cell 2016, 166, 258–258.e1. [Google Scholar] [CrossRef]
  146. Soler-Vazquez, M.C.; Mera, P.; Zagmutt, S.; Serra, D.; Herrero, L. New approaches targeting brown adipose tissue transplantation as a therapy in obesity. Biochem. Pharmacol. 2018, 155, 346–355. [Google Scholar] [CrossRef] [PubMed]
  147. Chusyd, D.E.; Wang, D.; Huffman, D.M.; Nagy, T.R. Relationships between Rodent White Adipose Fat Pads and Human White Adipose Fat Depots. Front. Nutr. 2016, 3, 10. [Google Scholar] [CrossRef] [PubMed]
  148. Cypess, A.M.; Lehman, S.; Williams, G.; Tal, I.; Rodman, D.; Goldfine, A.B.; Kuo, F.C.; Palmer, E.L.; Tseng, Y.H.; Doria, A.; et al. Identification and importance of brown adipose tissue in adult humans. N. Engl. J. Med. 2009, 360, 1509–1517. [Google Scholar] [CrossRef]
  149. Virtanen, K.A.; Lidell, M.E.; Orava, J.; Heglind, M.; Westergren, R.; Niemi, T.; Taittonen, M.; Laine, J.; Savisto, N.J.; Enerback, S.; et al. Functional brown adipose tissue in healthy adults. N. Engl. J. Med. 2009, 360, 1518–1525, Erratum in N. Engl. J. Med. 2009, 361, 1123. [Google Scholar] [CrossRef]
  150. Gerngross, C.; Schretter, J.; Klingenspor, M.; Schwaiger, M.; Fromme, T. Active Brown Fat During (18)F-FDG PET/CT Imaging Defines a Patient Group with Characteristic Traits and an Increased Probability of Brown Fat Redetection. J. Nucl. Med. 2017, 58, 1104–1110. [Google Scholar] [CrossRef]
  151. Sacks, H.; Symonds, M.E. Anatomical locations of human brown adipose tissue: Functional relevance and implications in obesity and type 2 diabetes. Diabetes 2013, 62, 1783–1790. [Google Scholar] [CrossRef]
  152. Giralt, M.; Villarroya, F. White, brown, beige/brite: Different adipose cells for different functions? Endocrinology 2013, 154, 2992–3000. [Google Scholar] [CrossRef]
  153. Orsso, C.E.; Colin-Ramirez, E.; Field, C.J.; Madsen, K.L.; Prado, C.M.; Haqq, A.M. Adipose Tissue Development and Expansion from the Womb to Adolescence: An Overview. Nutrients 2020, 12, 2735. [Google Scholar] [CrossRef]
  154. Park, A.; Kim, W.K.; Bae, K.H. Distinction of white, beige and brown adipocytes derived from mesenchymal stem cells. World J. Stem Cells 2014, 6, 33–42. [Google Scholar] [CrossRef]
  155. Cinti, S. Pink Adipocytes. Trends Endocrinol. Metab. 2018, 29, 651–666. [Google Scholar] [CrossRef]
  156. Diedrich, J.; Gusky, H.C.; Podgorski, I. Adipose tissue dysfunction and its effects on tumor metabolism. Horm. Mol. Biol. Clin. Investig. 2015, 21, 17–41. [Google Scholar] [CrossRef]
  157. Lecka-Czernik, B. Marrow fat metabolism is linked to the systemic energy metabolism. Bone 2012, 50, 534–539. [Google Scholar] [CrossRef]
  158. Laforest, S.; Michaud, A.; Paris, G.; Pelletier, M.; Vidal, H.; Geloen, A.; Tchernof, A. Comparative analysis of three human adipocyte size measurement methods and their relevance for cardiometabolic risk. Obesity 2017, 25, 122–131. [Google Scholar] [CrossRef]
  159. Honecker, J.; Weidlich, D.; Heisz, S.; Lindgren, C.M.; Karampinos, D.C.; Claussnitzer, M.; Hauner, H. A distribution-centered approach for analyzing human adipocyte size estimates and their association with obesity-related traits and mitochondrial function. Int. J. Obes. 2021, 45, 2108–2117. [Google Scholar] [CrossRef]
  160. Fang, L.; Guo, F.; Zhou, L.; Stahl, R.; Grams, J. The cell size and distribution of adipocytes from subcutaneous and visceral fat is associated with type 2 diabetes mellitus in humans. Adipocyte 2015, 4, 273–279. [Google Scholar] [CrossRef]
  161. Suzuki, M.; Shinohara, Y.; Ohsaki, Y.; Fujimoto, T. Lipid droplets: Size matters. J. Electron. Microsc. 2011, 60, S101–S116. [Google Scholar] [CrossRef]
  162. Olzmann, J.A.; Carvalho, P. Dynamics and functions of lipid droplets. Nat. Rev. Mol. Cell Biol. 2019, 20, 137–155. [Google Scholar] [CrossRef]
  163. Song, Z.; Xiaoli, A.M.; Yang, F. Regulation and Metabolic Significance of De Novo Lipogenesis in Adipose Tissues. Nutrients 2018, 10, 1383. [Google Scholar] [CrossRef]
  164. Fujimoto, T.; Parton, R.G. Not just fat: The structure and function of the lipid droplet. Cold Spring Harb. Perspect. Biol. 2011, 3, a004838. [Google Scholar] [CrossRef]
  165. Ahmadian, M.; Duncan, R.E.; Jaworski, K.; Sarkadi-Nagy, E.; Sul, H.S. Triacylglycerol metabolism in adipose tissue. Future Lipidol. 2007, 2, 229–237. [Google Scholar] [CrossRef]
  166. Coleman, R.A.; Lee, D.P. Enzymes of triacylglycerol synthesis and their regulation. Prog. Lipid Res. 2004, 43, 134–176. [Google Scholar] [CrossRef]
  167. Cao, J.; Perez, S.; Goodwin, B.; Lin, Q.; Peng, H.; Qadri, A.; Zhou, Y.; Clark, R.W.; Perreault, M.; Tobin, J.F.; et al. Mice deleted for GPAT3 have reduced GPAT activity in white adipose tissue and altered energy and cholesterol homeostasis in diet-induced obesity. Am. J. Physiol. Endocrinol. Metab. 2014, 306, E1176–E1187. [Google Scholar] [CrossRef]
  168. Shan, D.; Li, J.L.; Wu, L.; Li, D.; Hurov, J.; Tobin, J.F.; Gimeno, R.E.; Cao, J. GPAT3 and GPAT4 are regulated by insulin-stimulated phosphorylation and play distinct roles in adipogenesis. J. Lipid Res. 2010, 51, 1971–1981. [Google Scholar] [CrossRef]
  169. Sim, M.F.M.; Persiani, E.; Talukder, M.M.U.; McIlroy, G.D.; Roumane, A.; Edwardson, J.M.; Rochford, J.J. Oligomers of the lipodystrophy protein seipin may co-ordinate GPAT3 and AGPAT2 enzymes to facilitate adipocyte differentiation. Sci. Rep. 2020, 10, 3259. [Google Scholar] [CrossRef]
  170. Patni, N.; Garg, A. Congenital generalized lipodystrophies--new insights into metabolic dysfunction. Nat. Rev. Endocrinol. 2015, 11, 522–534. [Google Scholar] [CrossRef]
  171. Araujo-Vilar, D.; Santini, F. Diagnosis and treatment of lipodystrophy: A step-by-step approach. J. Endocrinol. Investig. 2019, 42, 61–73. [Google Scholar] [CrossRef]
  172. Safar Zadeh, E.; Lungu, A.O.; Cochran, E.K.; Brown, R.J.; Ghany, M.G.; Heller, T.; Kleiner, D.E.; Gorden, P. The liver diseases of lipodystrophy: The long-term effect of leptin treatment. J. Hepatol. 2013, 59, 131–137. [Google Scholar] [CrossRef]
  173. Melvin, A.; O’Rahilly, S.; Savage, D.B. Genetic syndromes of severe insulin resistance. Curr. Opin. Genet. Dev. 2018, 50, 60–67. [Google Scholar] [CrossRef]
  174. Zhang, P.; Reue, K. Lipin proteins and glycerolipid metabolism: Roles at the ER membrane and beyond. Biochim. Biophys. Acta Biomembr. 2017, 1859, 1583–1595. [Google Scholar] [CrossRef]
  175. Phan, J.; Reue, K. Lipin, a lipodystrophy and obesity gene. Cell Metab. 2005, 1, 73–83. [Google Scholar] [CrossRef]
  176. Phan, J.; Peterfy, M.; Reue, K. Lipin expression preceding peroxisome proliferator-activated receptor-gamma is critical for adipogenesis in vivo and in vitro. J. Biol. Chem. 2004, 279, 29558–29564. [Google Scholar] [CrossRef] [PubMed]
  177. Nadra, K.; Medard, J.J.; Mul, J.D.; Han, G.S.; Gres, S.; Pende, M.; Metzger, D.; Chambon, P.; Cuppen, E.; Saulnier-Blache, J.S.; et al. Cell autonomous lipin 1 function is essential for development and maintenance of white and brown adipose tissue. Mol. Cell Biol. 2012, 32, 4794–4810. [Google Scholar] [CrossRef]
  178. Zhang, W.; Zhong, W.; Sun, Q.; Sun, X.; Zhou, Z. Adipose-specific lipin1 overexpression in mice protects against alcohol-induced liver injury. Sci. Rep. 2018, 8, 408. [Google Scholar] [CrossRef] [PubMed]
  179. Pelosi, M.; Testet, E.; Le Lay, S.; Dugail, I.; Tang, X.; Mabilleau, G.; Hamel, Y.; Madrange, M.; Blanc, T.; Odent, T.; et al. Normal human adipose tissue functions and differentiation in patients with biallelic LPIN1 inactivating mutations. J. Lipid Res. 2017, 58, 2348–2364. [Google Scholar] [CrossRef]
  180. Croce, M.A.; Eagon, J.C.; LaRiviere, L.L.; Korenblat, K.M.; Klein, S.; Finck, B.N. Hepatic lipin 1beta expression is diminished in insulin-resistant obese subjects and is reactivated by marked weight loss. Diabetes 2007, 56, 2395–2399. [Google Scholar] [CrossRef]
  181. Yao-Borengasser, A.; Rasouli, N.; Varma, V.; Miles, L.M.; Phanavanh, B.; Starks, T.N.; Phan, J.; Spencer, H.J., 3rd; McGehee, R.E., Jr.; Reue, K.; et al. Lipin expression is attenuated in adipose tissue of insulin-resistant human subjects and increases with peroxisome proliferator-activated receptor gamma activation. Diabetes 2006, 55, 2811–2818. [Google Scholar] [CrossRef] [PubMed][Green Version]
  182. Yen, C.L.; Stone, S.J.; Koliwad, S.; Harris, C.; Farese, R.V., Jr. Thematic review series: Glycerolipids. DGAT enzymes and triacylglycerol biosynthesis. J. Lipid Res. 2008, 49, 2283–2301. [Google Scholar] [CrossRef]
  183. Harris, C.A.; Haas, J.T.; Streeper, R.S.; Stone, S.J.; Kumari, M.; Yang, K.; Han, X.; Brownell, N.; Gross, R.W.; Zechner, R.; et al. DGAT enzymes are required for triacylglycerol synthesis and lipid droplets in adipocytes. J. Lipid Res. 2011, 52, 657–667. [Google Scholar] [CrossRef]
  184. Stone, S.J.; Myers, H.M.; Watkins, S.M.; Brown, B.E.; Feingold, K.R.; Elias, P.M.; Farese, R.V., Jr. Lipopenia and skin barrier abnormalities in DGAT2-deficient mice. J. Biol. Chem. 2004, 279, 11767–11776. [Google Scholar] [CrossRef]
  185. Chitraju, C.; Walther, T.C.; Farese, R.V., Jr. The triglyceride synthesis enzymes DGAT1 and DGAT2 have distinct and overlapping functions in adipocytes. J. Lipid Res. 2019, 60, 1112–1120. [Google Scholar] [CrossRef]
  186. Chitraju, C.; Mejhert, N.; Haas, J.T.; Diaz-Ramirez, L.G.; Grueter, C.A.; Imbriglio, J.E.; Pinto, S.; Koliwad, S.K.; Walther, T.C.; Farese, R.V., Jr. Triglyceride Synthesis by DGAT1 Protects Adipocytes from Lipid-Induced ER Stress during Lipolysis. Cell Metab. 2017, 26, 407–418. [Google Scholar] [CrossRef]
  187. Smith, S.J.; Cases, S.; Jensen, D.R.; Chen, H.C.; Sande, E.; Tow, B.; Sanan, D.A.; Raber, J.; Eckel, R.H.; Farese, R.V., Jr. Obesity resistance and multiple mechanisms of triglyceride synthesis in mice lacking Dgat. Nat. Genet. 2000, 25, 87–90. [Google Scholar] [CrossRef]
  188. Chen, H.C.; Smith, S.J.; Ladha, Z.; Jensen, D.R.; Ferreira, L.D.; Pulawa, L.K.; McGuire, J.G.; Pitas, R.E.; Eckel, R.H.; Farese, R.V., Jr. Increased insulin and leptin sensitivity in mice lacking acyl CoA:diacylglycerol acyltransferase 1. J. Clin. Investig. 2002, 109, 1049–1055. [Google Scholar] [CrossRef]
  189. Chen, H.C.; Ladha, Z.; Farese, R.V., Jr. Deficiency of acyl coenzyme a:diacylglycerol acyltransferase 1 increases leptin sensitivity in murine obesity models. Endocrinology 2002, 143, 2893–2898. [Google Scholar] [CrossRef]
  190. Schweiger, M.; Schreiber, R.; Haemmerle, G.; Lass, A.; Fledelius, C.; Jacobsen, P.; Tornqvist, H.; Zechner, R.; Zimmermann, R. Adipose triglyceride lipase and hormone-sensitive lipase are the major enzymes in adipose tissue triacylglycerol catabolism. J. Biol. Chem. 2006, 281, 40236–40241. [Google Scholar] [CrossRef]
  191. Li, Y.; Li, Z.; Ngandiri, D.A.; Llerins Perez, M.; Wolf, A.; Wang, Y. The Molecular Brakes of Adipose Tissue Lipolysis. Front. Physiol. 2022, 13, 826314. [Google Scholar] [CrossRef]
  192. Lafontan, M.; Langin, D. Lipolysis and lipid mobilization in human adipose tissue. Prog. Lipid Res. 2009, 48, 275–297. [Google Scholar] [CrossRef] [PubMed]
  193. Grabner, G.F.; Xie, H.; Schweiger, M.; Zechner, R. Lipolysis: Cellular mechanisms for lipid mobilization from fat stores. Nat. Metab. 2021, 3, 1445–1465. [Google Scholar] [CrossRef]
  194. Coleman, R.A.; Mashek, D.G. Mammalian triacylglycerol metabolism: Synthesis, lipolysis, and signaling. Chem. Rev. 2011, 111, 6359–6386. [Google Scholar] [CrossRef]
  195. Haemmerle, G.; Lass, A.; Zimmermann, R.; Gorkiewicz, G.; Meyer, C.; Rozman, J.; Heldmaier, G.; Maier, R.; Theussl, C.; Eder, S.; et al. Defective lipolysis and altered energy metabolism in mice lacking adipose triglyceride lipase. Science 2006, 312, 734–737. [Google Scholar] [CrossRef]
  196. Fischer, J.; Lefevre, C.; Morava, E.; Mussini, J.M.; Laforet, P.; Negre-Salvayre, A.; Lathrop, M.; Salvayre, R. The gene encoding adipose triglyceride lipase (PNPLA2) is mutated in neutral lipid storage disease with myopathy. Nat. Genet. 2007, 39, 28–30. [Google Scholar] [CrossRef] [PubMed]
  197. Li, M.; Hirano, K.I.; Ikeda, Y.; Higashi, M.; Hashimoto, C.; Zhang, B.; Kozawa, J.; Sugimura, K.; Miyauchi, H.; Suzuki, A.; et al. Triglyceride deposit cardiomyovasculopathy: A rare cardiovascular disorder. Orphanet J. Rare Dis. 2019, 14, 134. [Google Scholar] [CrossRef] [PubMed]
  198. Wu, J.W.; Wang, S.P.; Casavant, S.; Moreau, A.; Yang, G.S.; Mitchell, G.A. Fasting energy homeostasis in mice with adipose deficiency of desnutrin/adipose triglyceride lipase. Endocrinology 2012, 153, 2198–2207. [Google Scholar] [CrossRef]
  199. Haemmerle, G.; Zimmermann, R.; Hayn, M.; Theussl, C.; Waeg, G.; Wagner, E.; Sattler, W.; Magin, T.M.; Wagner, E.F.; Zechner, R. Hormone-sensitive lipase deficiency in mice causes diglyceride accumulation in adipose tissue, muscle, and testis. J. Biol. Chem. 2002, 277, 4806–4815. [Google Scholar] [CrossRef]
  200. Harada, K.; Shen, W.J.; Patel, S.; Natu, V.; Wang, J.; Osuga, J.; Ishibashi, S.; Kraemer, F.B. Resistance to high-fat diet-induced obesity and altered expression of adipose-specific genes in HSL-deficient mice. Am. J. Physiol. Endocrinol. Metab. 2003, 285, E1182–E1195. [Google Scholar] [CrossRef]
  201. Sekiya, M.; Osuga, J.; Okazaki, H.; Yahagi, N.; Harada, K.; Shen, W.J.; Tamura, Y.; Tomita, S.; Iizuka, Y.; Ohashi, K.; et al. Absence of hormone-sensitive lipase inhibits obesity and adipogenesis in Lep ob/ob mice. J. Biol. Chem. 2004, 279, 15084–15090. [Google Scholar] [CrossRef]
  202. Shen, W.J.; Yu, Z.; Patel, S.; Jue, D.; Liu, L.F.; Kraemer, F.B. Hormone-sensitive lipase modulates adipose metabolism through PPARgamma. Biochim. Biophys. Acta 2011, 1811, 9–16. [Google Scholar] [CrossRef]
  203. Zhang, Y.; Proenca, R.; Maffei, M.; Barone, M.; Leopold, L.; Friedman, J.M. Positional cloning of the mouse obese gene and its human homologue. Nature 1994, 372, 425–432. [Google Scholar] [CrossRef]
  204. Ingalls, A.M.; Dickie, M.M.; Snell, G.D. Obese, a new mutation in the house mouse. J. Hered. 1950, 41, 317–318. [Google Scholar] [CrossRef]
  205. Hummel, K.P.; Dickie, M.M.; Coleman, D.L. Diabetes, a new mutation in the mouse. Science 1966, 153, 1127–1128. [Google Scholar] [CrossRef]
  206. Pico, C.; Palou, M.; Pomar, C.A.; Rodriguez, A.M.; Palou, A. Leptin as a key regulator of the adipose organ. Rev. Endocr. Metab. Disord. 2022, 23, 13–30. [Google Scholar] [CrossRef]
  207. Obradovic, M.; Sudar-Milovanovic, E.; Soskic, S.; Essack, M.; Arya, S.; Stewart, A.J.; Gojobori, T.; Isenovic, E.R. Leptin and Obesity: Role and Clinical Implication. Front. Endocrinol. 2021, 12, 585887. [Google Scholar] [CrossRef] [PubMed]
  208. Kaboli, M.; Nakhjavani, M.; Rabizadeh, S.; Gholamzadeh, M.; Najafizadeh, S.R. The impact of anti-TNF-alpha therapy on leptin and inflammatory markers in rheumatoid arthritis patients: A case-control study. BMC Rheumatol. 2025, 9, 22. [Google Scholar] [CrossRef] [PubMed]
  209. Crowson, C.S.; Matteson, E.L.; Davis, J.M., 3rd; Gabriel, S.E. Contribution of obesity to the rise in incidence of rheumatoid arthritis. Arthritis Care Res. 2013, 65, 71–77. [Google Scholar] [CrossRef]
  210. Iikuni, N.; Lam, Q.L.; Lu, L.; Matarese, G.; La Cava, A. Leptin and Inflammation. Curr. Immunol. Rev. 2008, 4, 70–79. [Google Scholar] [CrossRef] [PubMed]
  211. Sinkiewicz-Darol, E.; Adamczyk, I.; Lubiech, K.; Pilarska, G.; Twaruzek, M. Leptin in Human Milk-One of the Key Regulators of Nutritional Programming. Molecules 2022, 27, 3581. [Google Scholar] [CrossRef]
  212. Pico, C.; Palou, M. Leptin and Metabolic Programming. Nutrients 2021, 14, 114. [Google Scholar] [CrossRef]
  213. Qiao, J.; Dai, L.J.; Zhang, Q.; Ouyang, Y.Q. A Meta-Analysis of the Association Between Breastfeeding and Early Childhood Obesity. J. Pediatr. Nurs. 2020, 53, 57–66. [Google Scholar] [CrossRef]
  214. Yan, J.; Liu, L.; Zhu, Y.; Huang, G.; Wang, P.P. The association between breastfeeding and childhood obesity: A meta-analysis. BMC Public. Health 2014, 14, 1267. [Google Scholar] [CrossRef]
  215. Palou, M.; Pico, C.; Palou, A. Leptin as a breast milk component for the prevention of obesity. Nutr. Rev. 2018, 76, 875–892. [Google Scholar] [CrossRef]
  216. Oliver, P.; Pico, C.; De Matteis, R.; Cinti, S.; Palou, A. Perinatal expression of leptin in rat stomach. Dev. Dyn. 2002, 223, 148–154. [Google Scholar] [CrossRef]
  217. Sanchez, J.; Oliver, P.; Miralles, O.; Ceresi, E.; Pico, C.; Palou, A. Leptin orally supplied to neonate rats is directly uptaken by the immature stomach and may regulate short-term feeding. Endocrinology 2005, 146, 2575–2582. [Google Scholar] [CrossRef] [PubMed]
  218. Pico, C.; Oliver, P.; Sanchez, J.; Miralles, O.; Caimari, A.; Priego, T.; Palou, A. The intake of physiological doses of leptin during lactation in rats prevents obesity in later life. Int. J. Obes. 2007, 31, 1199–1209. [Google Scholar] [CrossRef] [PubMed]
  219. Collden, G.; Caron, E.; Bouret, S.G. Neonatal leptin antagonism improves metabolic programming of postnatally overnourished mice. Int. J. Obes. 2022, 46, 1138–1144. [Google Scholar] [CrossRef] [PubMed]
  220. Makki, K.; Froguel, P.; Wolowczuk, I. Adipose tissue in obesity-related inflammation and insulin resistance: Cells, cytokines, and chemokines. ISRN Inflamm. 2013, 2013, 139239. [Google Scholar] [CrossRef]
  221. Scherer, P.E.; Williams, S.; Fogliano, M.; Baldini, G.; Lodish, H.F. A novel serum protein similar to C1q, produced exclusively in adipocytes. J. Biol. Chem. 1995, 270, 26746–26749. [Google Scholar] [CrossRef]
  222. Lihn, A.S.; Pedersen, S.B.; Richelsen, B. Adiponectin: Action, regulation and association to insulin sensitivity. Obes. Rev. 2005, 6, 13–21. [Google Scholar] [CrossRef]
  223. Berg, A.H.; Combs, T.P.; Du, X.; Brownlee, M.; Scherer, P.E. The adipocyte-secreted protein Acrp30 enhances hepatic insulin action. Nat. Med. 2001, 7, 947–953. [Google Scholar] [CrossRef]
  224. Yamauchi, T.; Kamon, J.; Waki, H.; Terauchi, Y.; Kubota, N.; Hara, K.; Mori, Y.; Ide, T.; Murakami, K.; Tsuboyama-Kasaoka, N.; et al. The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat. Med. 2001, 7, 941–946. [Google Scholar] [CrossRef]
  225. Choi, H.M.; Doss, H.M.; Kim, K.S. Multifaceted Physiological Roles of Adiponectin in Inflammation and Diseases. Int. J. Mol. Sci. 2020, 21, 1219. [Google Scholar] [CrossRef] [PubMed]
  226. Pham, D.V.; Park, P.H. Tumor Metabolic Reprogramming by Adipokines as a Critical Driver of Obesity-Associated Cancer Progression. Int. J. Mol. Sci. 2021, 22, 1444. [Google Scholar] [CrossRef] [PubMed]
  227. Yanai, H.; Yoshida, H. Beneficial Effects of Adiponectin on Glucose and Lipid Metabolism and Atherosclerotic Progression: Mechanisms and Perspectives. Int. J. Mol. Sci. 2019, 20, 1190. [Google Scholar] [CrossRef] [PubMed]
  228. Wang, Z.V.; Scherer, P.E. Adiponectin, cardiovascular function, and hypertension. Hypertension 2008, 51, 8–14. [Google Scholar] [CrossRef]
  229. Nigro, E.; Scudiero, O.; Monaco, M.L.; Palmieri, A.; Mazzarella, G.; Costagliola, C.; Bianco, A.; Daniele, A. New insight into adiponectin role in obesity and obesity-related diseases. Biomed. Res. Int. 2014, 2014, 658913. [Google Scholar] [CrossRef]
  230. Frankenberg, A.D.V.; Reis, A.F.; Gerchman, F. Relationships between adiponectin levels, the metabolic syndrome, and type 2 diabetes: A literature review. Arch. Endocrinol. Metab. 2017, 61, 614–622. [Google Scholar] [CrossRef]
  231. Lei, X.; Qiu, S.; Yang, G.; Wu, Q. Adiponectin and metabolic cardiovascular diseases: Therapeutic opportunities and challenges. Genes. Dis. 2023, 10, 1525–1536. [Google Scholar] [CrossRef]
  232. Han, Y.; Sun, Q.; Chen, W.; Gao, Y.; Ye, J.; Chen, Y.; Wang, T.; Gao, L.; Liu, Y.; Yang, Y. New advances of adiponectin in regulating obesity and related metabolic syndromes. J. Pharm. Anal. 2024, 14, 100913. [Google Scholar] [CrossRef]
  233. Zhao, S.; Kusminski, C.M.; Scherer, P.E. Adiponectin, Leptin and Cardiovascular Disorders. Circ. Res. 2021, 128, 136–149. [Google Scholar] [CrossRef]
  234. McTernan, P.G.; McTernan, C.L.; Chetty, R.; Jenner, K.; Fisher, F.M.; Lauer, M.N.; Crocker, J.; Barnett, A.H.; Kumar, S. Increased resistin gene and protein expression in human abdominal adipose tissue. J. Clin. Endocrinol. Metab. 2002, 87, 2407. [Google Scholar] [CrossRef] [PubMed]
  235. Steppan, C.M.; Bailey, S.T.; Bhat, S.; Brown, E.J.; Banerjee, R.R.; Wright, C.M.; Patel, H.R.; Ahima, R.S.; Lazar, M.A. The hormone resistin links obesity to diabetes. Nature 2001, 409, 307–312. [Google Scholar] [CrossRef]
  236. Rajala, M.W.; Obici, S.; Scherer, P.E.; Rossetti, L. Adipose-derived resistin and gut-derived resistin-like molecule-beta selectively impair insulin action on glucose production. J. Clin. Investig. 2003, 111, 225–230. [Google Scholar] [CrossRef]
  237. Rangwala, S.M.; Rich, A.S.; Rhoades, B.; Shapiro, J.S.; Obici, S.; Rossetti, L.; Lazar, M.A. Abnormal glucose homeostasis due to chronic hyperresistinemia. Diabetes 2004, 53, 1937–1941. [Google Scholar] [CrossRef] [PubMed]
  238. Pravenec, M.; Kazdova, L.; Landa, V.; Zidek, V.; Mlejnek, P.; Jansa, P.; Wang, J.; Qi, N.; Kurtz, T.W. Transgenic and recombinant resistin impair skeletal muscle glucose metabolism in the spontaneously hypertensive rat. J. Biol. Chem. 2003, 278, 45209–45215. [Google Scholar] [CrossRef] [PubMed]
  239. Park, H.K.; Ahima, R.S. Resistin in rodents and humans. Diabetes Metab. J. 2013, 37, 404–414. [Google Scholar] [CrossRef]
  240. Patel, L.; Buckels, A.C.; Kinghorn, I.J.; Murdock, P.R.; Holbrook, J.D.; Plumpton, C.; Macphee, C.H.; Smith, S.A. Resistin is expressed in human macrophages and directly regulated by PPAR gamma activators. Biochem. Biophys. Res. Commun. 2003, 300, 472–476. [Google Scholar] [CrossRef]
  241. Lu, S.C.; Shieh, W.Y.; Chen, C.Y.; Hsu, S.C.; Chen, H.L. Lipopolysaccharide increases resistin gene expression in vivo and in vitro. FEBS Lett. 2002, 530, 158–162. [Google Scholar] [CrossRef]
  242. Kunnari, A.M.; Savolainen, E.R.; Ukkola, O.H.; Kesaniemi, Y.A.; Jokela, M.A. The expression of human resistin in different leucocyte lineages is modulated by LPS and TNFalpha. Regul. Pept. 2009, 157, 57–63. [Google Scholar] [CrossRef] [PubMed]
  243. Bokarewa, M.; Nagaev, I.; Dahlberg, L.; Smith, U.; Tarkowski, A. Resistin, an adipokine with potent proinflammatory properties. J. Immunol. 2005, 174, 5789–5795. [Google Scholar] [CrossRef] [PubMed]
  244. Esteve Rafols, M. Adipose tissue: Cell heterogeneity and functional diversity. Endocrinol. Nutr. 2014, 61, 100–112. [Google Scholar] [CrossRef]
  245. Schwartz, D.R.; Lazar, M.A. Human resistin: Found in translation from mouse to man. Trends Endocrinol. Metab. 2011, 22, 259–265. [Google Scholar] [CrossRef]
  246. Yang, R.Z.; Lee, M.J.; Hu, H.; Pray, J.; Wu, H.B.; Hansen, B.C.; Shuldiner, A.R.; Fried, S.K.; McLenithan, J.C.; Gong, D.W. Identification of omentin as a novel depot-specific adipokine in human adipose tissue: Possible role in modulating insulin action. Am. J. Physiol. Endocrinol. Metab. 2006, 290, E1253–E1261. [Google Scholar] [CrossRef]
  247. Zabetian-Targhi, F.; Mirzaei, K.; Keshavarz, S.A.; Hossein-Nezhad, A. Modulatory Role of Omentin-1 in Inflammation: Cytokines and Dietary Intake. J. Am. Coll. Nutr. 2016, 35, 670–678. [Google Scholar] [CrossRef]
  248. de Souza Batista, C.M.; Yang, R.Z.; Lee, M.J.; Glynn, N.M.; Yu, D.Z.; Pray, J.; Ndubuizu, K.; Patil, S.; Schwartz, A.; Kligman, M.; et al. Omentin plasma levels and gene expression are decreased in obesity. Diabetes 2007, 56, 1655–1661. [Google Scholar] [CrossRef]
  249. Pan, H.Y.; Guo, L.; Li, Q. Changes of serum omentin-1 levels in normal subjects and in patients with impaired glucose regulation and with newly diagnosed and untreated type 2 diabetes. Diabetes Res. Clin. Pract. 2010, 88, 29–33. [Google Scholar] [CrossRef] [PubMed]
  250. Pan, X.; Kaminga, A.C.; Wen, S.W.; Acheampong, K.; Liu, A. Omentin-1 in diabetes mellitus: A systematic review and meta-analysis. PLoS ONE 2019, 14, e0226292. [Google Scholar] [CrossRef]
  251. Kukla, M.; Menzyk, T.; Dembinski, M.; Winiarski, M.; Garlicki, A.; Bociaga-Jasik, M.; Skonieczna, M.; Hudy, D.; Maziarz, B.; Kusnierz-Cabala, B.; et al. Anti-inflammatory adipokines: Chemerin, vaspin, omentin concentrations and SARS-CoV-2 outcomes. Sci. Rep. 2021, 11, 21514. [Google Scholar] [CrossRef]
  252. Sena, C.M. Omentin: A Key Player in Glucose Homeostasis, Atheroprotection, and Anti-Inflammatory Potential for Cardiovascular Health in Obesity and Diabetes. Biomedicines 2024, 12, 284. [Google Scholar] [CrossRef]
  253. Xie, Y.; Xu, E.; Bowe, B.; Al-Aly, Z. Long-term cardiovascular outcomes of COVID-19. Nat. Med. 2022, 28, 583–590. [Google Scholar] [CrossRef]
  254. Wurfel, M.; Bluher, M.; Stumvoll, M.; Ebert, T.; Kovacs, P.; Tonjes, A.; Breitfeld, J. Adipokines as Clinically Relevant Therapeutic Targets in Obesity. Biomedicines 2023, 11, 1427. [Google Scholar] [CrossRef]
  255. Ozkan, B.; Zhang, S.; Echouffo-Tcheugui, J.B.; Florido, R.; Nambi, V.; Michos, E.D.; Abushamat, L.A.; Matsushita, K.; Gerstenblith, G.; Blumenthal, R.S.; et al. Adipokines and Transitions in Metabolic Health Over Time: The Atherosclerosis Risk In Communities (ARIC) Study. J. Clin. Endocrinol. Metab. 2025, 110, e2939–e2945. [Google Scholar] [CrossRef] [PubMed]
  256. Gao, D.; Bing, C.; Griffiths, H.R. Disrupted adipokine secretion and inflammatory responses in human adipocyte hypertrophy. Adipocyte 2025, 14, 2485927. [Google Scholar] [CrossRef] [PubMed]
  257. Kirichenko, T.V.; Markina, Y.V.; Bogatyreva, A.I.; Tolstik, T.V.; Varaeva, Y.R.; Starodubova, A.V. The Role of Adipokines in Inflammatory Mechanisms of Obesity. Int. J. Mol. Sci. 2022, 23, 14982. [Google Scholar] [CrossRef]
  258. Gu, X.; Wang, L.; Liu, S.; Shan, T. Adipose tissue adipokines and lipokines: Functions and regulatory mechanism in skeletal muscle development and homeostasis. Metabolism 2023, 139, 155379. [Google Scholar] [CrossRef]
  259. Cao, H.; Gerhold, K.; Mayers, J.R.; Wiest, M.M.; Watkins, S.M.; Hotamisligil, G.S. Identification of a lipokine, a lipid hormone linking adipose tissue to systemic metabolism. Cell 2008, 134, 933–944. [Google Scholar] [CrossRef]
  260. Trico, D.; Mengozzi, A.; Nesti, L.; Hatunic, M.; Gabriel Sanchez, R.; Konrad, T.; Lalic, K.; Lalic, N.M.; Mari, A.; Natali, A.; et al. Circulating palmitoleic acid is an independent determinant of insulin sensitivity, beta cell function and glucose tolerance in non-diabetic individuals: A longitudinal analysis. Diabetologia 2020, 63, 206–218. [Google Scholar] [CrossRef]
  261. Yore, M.M.; Syed, I.; Moraes-Vieira, P.M.; Zhang, T.; Herman, M.A.; Homan, E.A.; Patel, R.T.; Lee, J.; Chen, S.; Peroni, O.D.; et al. Discovery of a class of endogenous mammalian lipids with anti-diabetic and anti-inflammatory effects. Cell 2014, 159, 318–332. [Google Scholar] [CrossRef] [PubMed]
  262. Aryal, P.; Syed, I.; Lee, J.; Patel, R.; Nelson, A.T.; Siegel, D.; Saghatelian, A.; Kahn, B.B. Distinct biological activities of isomers from several families of branched fatty acid esters of hydroxy fatty acids (FAHFAs). J. Lipid Res. 2021, 62, 100108. [Google Scholar] [CrossRef]
  263. Pflimlin, E.; Bielohuby, M.; Korn, M.; Breitschopf, K.; Lohn, M.; Wohlfart, P.; Konkar, A.; Podeschwa, M.; Barenz, F.; Pfenninger, A.; et al. Acute and Repeated Treatment with 5-PAHSA or 9-PAHSA Isomers Does Not Improve Glucose Control in Mice. Cell Metab. 2018, 28, 217–227. [Google Scholar] [CrossRef]
  264. Hu, M.; Han, Y.; Zhang, X.; Tian, S.; Shang, Z.; Yuan, Z.; He, L. Extracellular vesicles for targeted drug delivery: Advances in surface modification strategies and therapeutic applications. J. Transl. Med. 2025, 23, 1028. [Google Scholar] [CrossRef]
  265. An, Y.; Lin, S.; Tan, X.; Zhu, S.; Nie, F.; Zhen, Y.; Gu, L.; Zhang, C.; Wang, B.; Wei, W.; et al. Exosomes from adipose-derived stem cells and application to skin wound healing. Cell Prolif. 2021, 54, e12993. [Google Scholar] [CrossRef]
  266. Liu, W.; Liu, T.; Zhao, Q.; Ma, J.; Jiang, J.; Shi, H. Adipose Tissue-Derived Extracellular Vesicles: A Promising Biomarker and Therapeutic Strategy for Metabolic Disorders. Stem Cells Int. 2023, 2023, 9517826. [Google Scholar] [CrossRef]
  267. Moraes, J.A.; Encarnacao, C.; Franco, V.A.; Xavier Botelho, L.G.; Rodrigues, G.P.; Ramos-Andrade, I.; Barja-Fidalgo, C.; Renovato-Martins, M. Adipose Tissue-Derived Extracellular Vesicles and the Tumor Microenvironment: Revisiting the Hallmarks of Cancer. Cancers 2021, 13, 3328. [Google Scholar] [CrossRef]
  268. Ramos, C.C.; Pires, J.; Gonzalez, E.; Garcia-Vallicrosa, C.; Reis, C.A.; Falcon-Perez, J.M.; Freitas, D. Extracellular vesicles in tumor-adipose tissue crosstalk: Key drivers and therapeutic targets in cancer cachexia. Extracell. Vesicles Circ. Nucl. Acids 2024, 5, 371–396. [Google Scholar] [CrossRef] [PubMed]
  269. Zhang, Z.; Shao, M.; Hepler, C.; Zi, Z.; Zhao, S.; An, Y.A.; Zhu, Y.; Ghaben, A.L.; Wang, M.Y.; Li, N.; et al. Dermal adipose tissue has high plasticity and undergoes reversible dedifferentiation in mice. J. Clin. Investig. 2019, 129, 5327–5342. [Google Scholar] [CrossRef] [PubMed]
  270. Chen, S.X.; Zhang, L.J.; Gallo, R.L. Dermal White Adipose Tissue: A Newly Recognized Layer of Skin Innate Defense. J. Investig. Dermatol. 2019, 139, 1002–1009. [Google Scholar] [CrossRef] [PubMed]
  271. Driskell, R.R.; Jahoda, C.A.; Chuong, C.M.; Watt, F.M.; Horsley, V. Defining dermal adipose tissue. Exp. Dermatol. 2014, 23, 629–631. [Google Scholar] [CrossRef]
  272. Kasza, I.; Suh, Y.; Wollny, D.; Clark, R.J.; Roopra, A.; Colman, R.J.; MacDougald, O.A.; Shedd, T.A.; Nelson, D.W.; Yen, M.I.; et al. Syndecan-1 is required to maintain intradermal fat and prevent cold stress. PLoS Genet. 2014, 10, e1004514. [Google Scholar] [CrossRef]
  273. Chung, H.; Multhaupt, H.A.; Oh, E.S.; Couchman, J.R. Minireview: Syndecans and their crucial roles during tissue regeneration. FEBS Lett. 2016, 590, 2408–2417. [Google Scholar] [CrossRef] [PubMed]
  274. Kasza, I.; Kuhn, J.P.; Volzke, H.; Hernando, D.; Xu, Y.G.; Siebert, J.W.; Gibson, A.L.F.; Yen, C.E.; Nelson, D.W.; MacDougald, O.A.; et al. Contrasting recruitment of skin-associated adipose depots during cold challenge of mouse and human. J. Physiol. 2022, 600, 847–868. [Google Scholar] [CrossRef] [PubMed]
  275. Zhang, L.J.; Guerrero-Juarez, C.F.; Hata, T.; Bapat, S.P.; Ramos, R.; Plikus, M.V.; Gallo, R.L. Innate immunity. Dermal adipocytes protect against invasive Staphylococcus aureus skin infection. Science 2015, 347, 67–71. [Google Scholar] [CrossRef]
  276. McLafferty, E.; Hendry, C.; Alistair, F. The integumentary system: Anatomy, physiology and function of skin. Nurs. Stand. 2012, 27, 35–42. [Google Scholar] [CrossRef]
  277. Gushiken, L.F.S.; Beserra, F.P.; Bastos, J.K.; Jackson, C.J.; Pellizzon, C.H. Cutaneous Wound Healing: An Update from Physiopathology to Current Therapies. Life 2021, 11, 665. [Google Scholar] [CrossRef]
  278. Shook, B.A.; Wasko, R.R.; Mano, O.; Rutenberg-Schoenberg, M.; Rudolph, M.C.; Zirak, B.; Rivera-Gonzalez, G.C.; Lopez-Giraldez, F.; Zarini, S.; Rezza, A.; et al. Dermal Adipocyte Lipolysis and Myofibroblast Conversion Are Required for Efficient Skin Repair. Cell Stem Cell 2020, 26, 880–895. [Google Scholar] [CrossRef]
  279. Schmidt, B.A.; Horsley, V. Intradermal adipocytes mediate fibroblast recruitment during skin wound healing. Development 2013, 140, 1517–1527. [Google Scholar] [CrossRef] [PubMed]
  280. Lahav, Y.; Kfir, A.; Gepner, Y. The paradox of obesity with normal weight; a cross-sectional study. Front. Nutr. 2023, 10, 1173488. [Google Scholar] [CrossRef]
  281. Rasmussen, A. The so-called hibernating gland. J. Morphol. 2005, 38, 147–205. [Google Scholar] [CrossRef]
  282. Ballinger, M.A.; Andrews, M.T. Nature’s fat-burning machine: Brown adipose tissue in a hibernating mammal. J. Exp. Biol. 2018, 221, jeb162586. [Google Scholar] [CrossRef]
  283. Hindle, A.G.; Martin, S.L. Intrinsic circannual regulation of brown adipose tissue form and function in tune with hibernation. Am. J. Physiol. Endocrinol. Metab. 2014, 306, E284–E299. [Google Scholar] [CrossRef]
  284. Osilla, E.V.; Marsidi, J.L.; Shumway, K.R.; Sharma, S. Physiology, Temperature Regulation; StatPearls: Treasure Island, FL, USA, 2024. [Google Scholar]
  285. Nowack, J.; Giroud, S.; Arnold, W.; Ruf, T. Muscle Non-shivering Thermogenesis and Its Role in the Evolution of Endothermy. Front. Physiol. 2017, 8, 889. [Google Scholar] [CrossRef]
  286. Lidell, M.E. Brown Adipose Tissue in Human Infants. In Brown Adipose Tissue; Handbook of Experimental Pharmacology; Springer: New York, NY, USA, 2019; Volume 251, pp. 107–123. [Google Scholar] [CrossRef]
  287. Hammarlund, K.; Nilsson, G.E.; Oberg, P.A.; Sedin, G. Transepidermal water loss in newborn infants. V. Evaporation from the skin and heat exchange during the first hours of life. Acta Paediatr. Scand. 1980, 69, 385–392. [Google Scholar] [CrossRef] [PubMed]
  288. Asakura, H. Fetal and neonatal thermoregulation. J. Nippon. Med. Sch. 2004, 71, 360–370. [Google Scholar] [CrossRef] [PubMed]
  289. Dang, R.; Patel, A.I.; Weng, Y.; Schroeder, A.R.; Lee, H.C.; Aby, J.; Frymoyer, A. Incidence of Neonatal Hypothermia in the Newborn Nursery and Associated Factors. JAMA Netw. Open 2023, 6, e2331011. [Google Scholar] [CrossRef]
  290. Zhang, W.; Bi, S. Hypothalamic Regulation of Brown Adipose Tissue Thermogenesis and Energy Homeostasis. Front. Endocrinol. 2015, 6, 136. [Google Scholar] [CrossRef] [PubMed]
  291. Zhao, Z.D.; Yang, W.Z.; Gao, C.; Fu, X.; Zhang, W.; Zhou, Q.; Chen, W.; Ni, X.; Lin, J.K.; Yang, J.; et al. A hypothalamic circuit that controls body temperature. Proc. Natl. Acad. Sci. USA 2017, 114, 2042–2047, Erratum in Proc. Natl. Acad. Sci. USA 2017, 114, E1755. [Google Scholar] [CrossRef]
  292. Bartness, T.J.; Vaughan, C.H.; Song, C.K. Sympathetic and sensory innervation of brown adipose tissue. Int. J. Obes. 2010, 34, S36–S42. [Google Scholar] [CrossRef]
  293. Leiva, M.; Matesanz, N.; Pulgarín-Alfaro, M.; Nikolic, I.; Sabio, G. Uncovering the Role of p38 Family Members in Adipose Tissue Physiology. Front. Endocrinol. 2020, 11, 572089. [Google Scholar] [CrossRef]
  294. Cao, W.; Daniel, K.W.; Robidoux, J.; Puigserver, P.; Medvedev, A.V.; Bai, X.; Floering, L.M.; Spiegelman, B.M.; Collins, S. p38 mitogen-activated protein kinase is the central regulator of cyclic AMP-dependent transcription of the brown fat uncoupling protein 1 gene. Mol. Cell Biol. 2004, 24, 3057–3067. [Google Scholar] [CrossRef]
  295. Nedergaard, J.; Cannon, B. [3H]GDP binding and thermogenin amount in brown adipose tissue mitochondria from cold-exposed rats. Am. J. Physiol. 1985, 248, C365–C371. [Google Scholar] [CrossRef]
  296. Lee, J.H.; Park, A.; Oh, K.J.; Lee, S.C.; Kim, W.K.; Bae, K.H. The Role of Adipose Tissue Mitochondria: Regulation of Mitochondrial Function for the Treatment of Metabolic Diseases. Int. J. Mol. Sci. 2019, 20, 4924. [Google Scholar] [CrossRef] [PubMed]
  297. Bertholet, A.M.; Kirichok, Y. UCP1: A transporter for H(+) and fatty acid anions. Biochimie 2017, 134, 28–34. [Google Scholar] [CrossRef]
  298. Fedorenko, A.; Lishko, P.V.; Kirichok, Y. Mechanism of fatty-acid-dependent UCP1 uncoupling in brown fat mitochondria. Cell 2012, 151, 400–413. [Google Scholar] [CrossRef]
  299. Bertholet, A.M.; Kirichok, Y. The Mechanism FA-Dependent H(+) Transport by UCP1. In Brown Adipose Tissue; Handbook of Experimental Pharmacology; Springer: New York, NY, USA, 2019; Volume 251, pp. 143–159. [Google Scholar] [CrossRef]
  300. Chouchani, E.T.; Kazak, L.; Spiegelman, B.M. New Advances in Adaptive Thermogenesis: UCP1 and Beyond. Cell Metab. 2019, 29, 27–37. [Google Scholar] [CrossRef] [PubMed]
  301. Roesler, A.; Kazak, L. UCP1-independent thermogenesis. Biochem. J. 2020, 477, 709–725. [Google Scholar] [CrossRef]
  302. Hofmann, W.E.; Liu, X.; Bearden, C.M.; Harper, M.E.; Kozak, L.P. Effects of genetic background on thermoregulation and fatty acid-induced uncoupling of mitochondria in UCP1-deficient mice. J. Biol. Chem. 2001, 276, 12460–12465. [Google Scholar] [CrossRef] [PubMed]
  303. Ikeda, K.; Yamada, T. UCP1 Dependent and Independent Thermogenesis in Brown and Beige Adipocytes. Front. Endocrinol. 2020, 11, 498. [Google Scholar] [CrossRef]
  304. Bal, N.C.; Singh, S.; Reis, F.C.G.; Maurya, S.K.; Pani, S.; Rowland, L.A.; Periasamy, M. Both brown adipose tissue and skeletal muscle thermogenesis processes are activated during mild to severe cold adaptation in mice. J. Biol. Chem. 2017, 292, 16616–16625. [Google Scholar] [CrossRef]
  305. Liu, M.; Zhang, X.Y.; Wang, C.Z.; Wang, D.H. Recruitment of Muscle Genes as an Effect of Brown Adipose Tissue Ablation in Cold-Acclimated Brandt’s Voles (Lasiopodomys brandtii). Int. J. Mol. Sci. 2022, 24, 342. [Google Scholar] [CrossRef]
  306. Villarroya, J.; Cereijo, R.; Gavaldà-Navarro, A.; Peyrou, M.; Giralt, M.; Villarroya, F. New insights into the secretory functions of brown adipose tissue. J. Endocrinol. 2019, 243, R19–R27. [Google Scholar] [CrossRef]
  307. Yang, F.T.; Stanford, K.I. Batokines: Mediators of Inter-Tissue Communication (a Mini-Review). Curr. Obes. Rep. 2022, 11, 1–9. [Google Scholar] [CrossRef] [PubMed]
  308. Ziqubu, K.; Dludla, P.V.; Mabhida, S.E.; Jack, B.U.; Keipert, S.; Jastroch, M.; Mazibuko-Mbeje, S.E. Brown adipose tissue-derived metabolites and their role in regulating metabolism. Metabolism 2024, 150, 155709. [Google Scholar] [CrossRef] [PubMed]
  309. Ghesmati, Z.; Rashid, M.; Fayezi, S.; Gieseler, F.; Alizadeh, E.; Darabi, M. An update on the secretory functions of brown, white, and beige adipose tissue: Towards therapeutic applications. Rev. Endocr. Metab. Disord. 2024, 25, 279–308. [Google Scholar] [CrossRef] [PubMed]
  310. Nishimura, T.; Nakatake, Y.; Konishi, M.; Itoh, N. Identification of a novel FGF, FGF-21, preferentially expressed in the liver. Biochim. Biophys. Acta 2000, 1492, 203–206. [Google Scholar] [CrossRef]
  311. Klein Hazebroek, M.; Keipert, S. Adapting to the Cold: A Role for Endogenous Fibroblast Growth Factor 21 in Thermoregulation? Front. Endocrinol. 2020, 11, 389. [Google Scholar] [CrossRef]
  312. Zingaretti, M.C.; Crosta, F.; Vitali, A.; Guerrieri, M.; Frontini, A.; Cannon, B.; Nedergaard, J.; Cinti, S. The presence of UCP1 demonstrates that metabolically active adipose tissue in the neck of adult humans truly represents brown adipose tissue. FASEB J. 2009, 23, 3113–3120. [Google Scholar] [CrossRef]
  313. Chartoumpekis, D.V.; Habeos, I.G.; Ziros, P.G.; Psyrogiannis, A.I.; Kyriazopoulou, V.E.; Papavassiliou, A.G. Brown adipose tissue responds to cold and adrenergic stimulation by induction of FGF21. Mol. Med. 2011, 17, 736–740. [Google Scholar] [CrossRef]
  314. Hondares, E.; Rosell, M.; Gonzalez, F.J.; Giralt, M.; Iglesias, R.; Villarroya, F. Hepatic FGF21 expression is induced at birth via PPARalpha in response to milk intake and contributes to thermogenic activation of neonatal brown fat. Cell Metab. 2010, 11, 206–212. [Google Scholar] [CrossRef]
  315. Hondares, E.; Iglesias, R.; Giralt, A.; Gonzalez, F.J.; Giralt, M.; Mampel, T.; Villarroya, F. Thermogenic activation induces FGF21 expression and release in brown adipose tissue. J. Biol. Chem. 2011, 286, 12983–12990. [Google Scholar] [CrossRef]
  316. Ameka, M.; Markan, K.R.; Morgan, D.A.; BonDurant, L.D.; Idiga, S.O.; Naber, M.C.; Zhu, Z.; Zingman, L.V.; Grobe, J.L.; Rahmouni, K.; et al. Liver Derived FGF21 Maintains Core Body Temperature During Acute Cold Exposure. Sci. Rep. 2019, 9, 630. [Google Scholar] [CrossRef]
  317. Abu-Odeh, M.; Zhang, Y.; Reilly, S.M.; Ebadat, N.; Keinan, O.; Valentine, J.M.; Hafezi-Bakhtiari, M.; Ashayer, H.; Mamoun, L.; Zhou, X.; et al. FGF21 promotes thermogenic gene expression as an autocrine factor in adipocytes. Cell Rep. 2021, 35, 109331. [Google Scholar] [CrossRef]
  318. Kharitonenkov, A.; Shiyanova, T.L.; Koester, A.; Ford, A.M.; Micanovic, R.; Galbreath, E.J.; Sandusky, G.E.; Hammond, L.J.; Moyers, J.S.; Owens, R.A.; et al. FGF-21 as a novel metabolic regulator. J. Clin. Investig. 2005, 115, 1627–1635. [Google Scholar] [CrossRef]
  319. Woo, Y.C.; Xu, A.; Wang, Y.; Lam, K.S. Fibroblast growth factor 21 as an emerging metabolic regulator: Clinical perspectives. Clin. Endocrinol. 2013, 78, 489–496. [Google Scholar] [CrossRef]
  320. Kliewer, S.A.; Mangelsdorf, D.J. A Dozen Years of Discovery: Insights into the Physiology and Pharmacology of FGF21. Cell Metab. 2019, 29, 246–253. [Google Scholar] [CrossRef] [PubMed]
  321. Lee, P.; Brychta, R.J.; Linderman, J.; Smith, S.; Chen, K.Y.; Celi, F.S. Mild cold exposure modulates fibroblast growth factor 21 (FGF21) diurnal rhythm in humans: Relationship between FGF21 levels, lipolysis, and cold-induced thermogenesis. J. Clin. Endocrinol. Metab. 2013, 98, E98–E102. [Google Scholar] [CrossRef] [PubMed]
  322. Hanssen, M.J.; Broeders, E.; Samms, R.J.; Vosselman, M.J.; van der Lans, A.A.; Cheng, C.C.; Adams, A.C.; van Marken Lichtenbelt, W.D.; Schrauwen, P. Serum FGF21 levels are associated with brown adipose tissue activity in humans. Sci. Rep. 2015, 5, 10275. [Google Scholar] [CrossRef] [PubMed]
  323. Lee, P.; Linderman, J.D.; Smith, S.; Brychta, R.J.; Wang, J.; Idelson, C.; Perron, R.M.; Werner, C.D.; Phan, G.Q.; Kammula, U.S.; et al. Irisin and FGF21 are cold-induced endocrine activators of brown fat function in humans. Cell Metab. 2014, 19, 302–309. [Google Scholar] [CrossRef]
  324. Mendez-Gutierrez, A.; Aguilera, C.M.; Cereijo, R.; Osuna-Prieto, F.J.; Martinez-Tellez, B.; Rico, M.C.; Sanchez-Infantes, D.; Villarroya, F.; Ruiz, J.R.; Sanchez-Delgado, G. Cold exposure modulates potential brown adipokines in humans, but only FGF21 is associated with brown adipose tissue volume. Obesity 2024, 32, 560–570. [Google Scholar] [CrossRef]
  325. Moure, R.; Cairo, M.; Moron-Ros, S.; Quesada-Lopez, T.; Campderros, L.; Cereijo, R.; Hernaez, A.; Villarroya, F.; Giralt, M. Levels of beta-klotho determine the thermogenic responsiveness of adipose tissues: Involvement of the autocrine action of FGF21. Am. J. Physiol. Endocrinol. Metab. 2021, 320, E822–E834. [Google Scholar] [CrossRef]
  326. Samms, R.J.; Cheng, C.C.; Kharitonenkov, A.; Gimeno, R.E.; Adams, A.C. Overexpression of beta-Klotho in Adipose Tissue Sensitizes Male Mice to Endogenous FGF21 and Provides Protection From Diet-Induced Obesity. Endocrinology 2016, 157, 1467–1480. [Google Scholar] [CrossRef]
  327. Blázquez-Medela, A.M.; Jumabay, M.; Boström, K.I. Beyond the bone: Bone morphogenetic protein signaling in adipose tissue. Obes. Rev. 2019, 20, 648–658. [Google Scholar] [CrossRef]
  328. Ahrens, M.; Ankenbauer, T.; Schröder, D.; Hollnagel, A.; Mayer, H.; Gross, G. Expression of human bone morphogenetic proteins-2 or -4 in murine mesenchymal progenitor C3H10T1/2 cells induces differentiation into distinct mesenchymal cell lineages. DNA Cell Biol. 1993, 12, 871–880. [Google Scholar] [CrossRef] [PubMed]
  329. Tseng, Y.H.; Kokkotou, E.; Schulz, T.J.; Huang, T.L.; Winnay, J.N.; Taniguchi, C.M.; Tran, T.T.; Suzuki, R.; Espinoza, D.O.; Yamamoto, Y.; et al. New role of bone morphogenetic protein 7 in brown adipogenesis and energy expenditure. Nature 2008, 454, 1000–1004, Erratum in Nature 2009, 459, 122. [Google Scholar] [CrossRef] [PubMed]
  330. Xue, R.; Wan, Y.; Zhang, S.; Zhang, Q.; Ye, H.; Li, Y. Role of bone morphogenetic protein 4 in the differentiation of brown fat-like adipocytes. Am. J. Physiol. Endocrinol. Metab. 2014, 306, E363–E372. [Google Scholar] [CrossRef] [PubMed]
  331. Elsen, M.; Raschke, S.; Tennagels, N.; Schwahn, U.; Jelenik, T.; Roden, M.; Romacho, T.; Eckel, J. BMP4 and BMP7 induce the white-to-brown transition of primary human adipose stem cells. Am. J. Physiol. Cell Physiol. 2014, 306, C431–C440. [Google Scholar] [CrossRef]
  332. Gustafson, B.; Smith, U. The WNT inhibitor Dickkopf 1 and bone morphogenetic protein 4 rescue adipogenesis in hypertrophic obesity in humans. Diabetes 2012, 61, 1217–1224. [Google Scholar] [CrossRef]
  333. Boon, M.R.; van den Berg, S.A.; Wang, Y.; van den Bossche, J.; Karkampouna, S.; Bauwens, M.; De Saint-Hubert, M.; van der Horst, G.; Vukicevic, S.; de Winther, M.P.; et al. BMP7 activates brown adipose tissue and reduces diet-induced obesity only at subthermoneutrality. PLoS ONE 2013, 8, e74083. [Google Scholar] [CrossRef]
  334. Martins, L.; Seoane-Collazo, P.; Contreras, C.; Gonzalez-Garcia, I.; Martinez-Sanchez, N.; Gonzalez, F.; Zalvide, J.; Gallego, R.; Dieguez, C.; Nogueiras, R.; et al. A Functional Link between AMPK and Orexin Mediates the Effect of BMP8B on Energy Balance. Cell Rep. 2016, 16, 2231–2242. [Google Scholar] [CrossRef]
  335. Whittle, A.J.; Carobbio, S.; Martins, L.; Slawik, M.; Hondares, E.; Vazquez, M.J.; Morgan, D.; Csikasz, R.I.; Gallego, R.; Rodriguez-Cuenca, S.; et al. BMP8B increases brown adipose tissue thermogenesis through both central and peripheral actions. Cell 2012, 149, 871–885. [Google Scholar] [CrossRef]
  336. Pellegrinelli, V.; Peirce, V.J.; Howard, L.; Virtue, S.; Turei, D.; Senzacqua, M.; Frontini, A.; Dalley, J.W.; Horton, A.R.; Bidault, G.; et al. Adipocyte-secreted BMP8b mediates adrenergic-induced remodeling of the neuro-vascular network in adipose tissue. Nat. Commun. 2018, 9, 4974. [Google Scholar] [CrossRef]
  337. Urisarri, A.; Gonzalez-Garcia, I.; Estevez-Salguero, A.; Pata, M.P.; Milbank, E.; Lopez, N.; Mandia, N.; Grijota-Martinez, C.; Salgado, C.A.; Nogueiras, R.; et al. BMP8 and activated brown adipose tissue in human newborns. Nat. Commun. 2021, 12, 5274. [Google Scholar] [CrossRef]
  338. Whittle, A.J.; Jiang, M.; Peirce, V.; Relat, J.; Virtue, S.; Ebinuma, H.; Fukamachi, I.; Yamaguchi, T.; Takahashi, M.; Murano, T.; et al. Soluble LR11/SorLA represses thermogenesis in adipose tissue and correlates with BMI in humans. Nat. Commun. 2015, 6, 8951. [Google Scholar] [CrossRef]
  339. Lu, H.C.; Mackie, K. An Introduction to the Endogenous Cannabinoid System. Biol. Psychiatry 2016, 79, 516–525. [Google Scholar] [CrossRef] [PubMed]
  340. Krott, L.M.; Piscitelli, F.; Heine, M.; Borrino, S.; Scheja, L.; Silvestri, C.; Heeren, J.; Di Marzo, V. Endocannabinoid regulation in white and brown adipose tissue following thermogenic activation. J. Lipid Res. 2016, 57, 464–473. [Google Scholar] [CrossRef] [PubMed]
  341. Boon, M.R.; Kooijman, S.; van Dam, A.D.; Pelgrom, L.R.; Berbee, J.F.; Visseren, C.A.; van Aggele, R.C.; van den Hoek, A.M.; Sips, H.C.; Lombes, M.; et al. Peripheral cannabinoid 1 receptor blockade activates brown adipose tissue and diminishes dyslipidemia and obesity. FASEB J. 2014, 28, 5361–5375. [Google Scholar] [CrossRef] [PubMed]
  342. Fournier, B.; Murray, B.; Gutzwiller, S.; Marcaletti, S.; Marcellin, D.; Bergling, S.; Brachat, S.; Persohn, E.; Pierrel, E.; Bombard, F.; et al. Blockade of the activin receptor IIb activates functional brown adipogenesis and thermogenesis by inducing mitochondrial oxidative metabolism. Mol. Cell Biol. 2012, 32, 2871–2879. [Google Scholar] [CrossRef]
  343. Kim, W.K.; Choi, H.R.; Park, S.G.; Ko, Y.; Bae, K.H.; Lee, S.C. Myostatin inhibits brown adipocyte differentiation via regulation of Smad3-mediated beta-catenin stabilization. Int. J. Biochem. Cell Biol. 2012, 44, 327–334. [Google Scholar] [CrossRef]
  344. Prestwich, T.C.; Macdougald, O.A. Wnt/beta-catenin signaling in adipogenesis and metabolism. Curr. Opin. Cell Biol. 2007, 19, 612–617. [Google Scholar] [CrossRef]
  345. Kang, S.; Bajnok, L.; Longo, K.A.; Petersen, R.K.; Hansen, J.B.; Kristiansen, K.; MacDougald, O.A. Effects of Wnt signaling on brown adipocyte differentiation and metabolism mediated by PGC-1alpha. Mol. Cell Biol. 2005, 25, 1272–1282. [Google Scholar] [CrossRef] [PubMed]
  346. Cypess, A.M.; Kahn, C.R. The role and importance of brown adipose tissue in energy homeostasis. Curr. Opin. Pediatr. 2010, 22, 478–484. [Google Scholar] [CrossRef] [PubMed]
  347. Lowell, B.B.; Spiegelman, B.M. Towards a molecular understanding of adaptive thermogenesis. Nature 2000, 404, 652–660. [Google Scholar] [CrossRef]
  348. Marette, A.; Bukowiecki, L.J. Stimulation of glucose transport by insulin and norepinephrine in isolated rat brown adipocytes. Am. J. Physiol. 1989, 257, C714–C721. [Google Scholar] [CrossRef]
  349. Vallerand, A.L.; Perusse, F.; Bukowiecki, L.J. Stimulatory effects of cold exposure and cold acclimation on glucose uptake in rat peripheral tissues. Am. J. Physiol. 1990, 259, R1043–R1049. [Google Scholar] [CrossRef] [PubMed]
  350. Shimizu, Y.; Nikami, H.; Saito, M. Sympathetic activation of glucose utilization in brown adipose tissue in rats. J. Biochem. 1991, 110, 688–692. [Google Scholar] [CrossRef] [PubMed]
  351. Nedergaard, J.; Bengtsson, T.; Cannon, B. Unexpected evidence for active brown adipose tissue in adult humans. Am. J. Physiol. Endocrinol. Metab. 2007, 293, E444–E452. [Google Scholar] [CrossRef]
  352. Wijers, S.L.; Saris, W.H.; van Marken Lichtenbelt, W.D. Individual thermogenic responses to mild cold and overfeeding are closely related. J. Clin. Endocrinol. Metab. 2007, 92, 4299–4305. [Google Scholar] [CrossRef]
  353. Fischer, J.G.W.; Maushart, C.I.; Becker, A.S.; Muller, J.; Madoerin, P.; Chirindel, A.; Wild, D.; Ter Voert, E.; Bieri, O.; Burger, I.; et al. Comparison of [(18)F]FDG PET/CT with magnetic resonance imaging for the assessment of human brown adipose tissue activity. EJNMMI Res. 2020, 10, 85. [Google Scholar] [CrossRef]
  354. Chen, K.Y.; Cypess, A.M.; Laughlin, M.R.; Haft, C.R.; Hu, H.H.; Bredella, M.A.; Enerback, S.; Kinahan, P.E.; Lichtenbelt, W.; Lin, F.I.; et al. Brown Adipose Reporting Criteria in Imaging STudies (BARCIST 1.0): Recommendations for Standardized FDG-PET/CT Experiments in Humans. Cell Metab. 2016, 24, 210–222. [Google Scholar] [CrossRef]
  355. van Marken Lichtenbelt, W.D.; Vanhommerig, J.W.; Smulders, N.M.; Drossaerts, J.M.; Kemerink, G.J.; Bouvy, N.D.; Schrauwen, P.; Teule, G.J. Cold-activated brown adipose tissue in healthy men. N. Engl. J. Med. 2009, 360, 1500–1508, Erratum in N. Engl. J. Med. 2009, 60, 1917. [Google Scholar] [CrossRef]
  356. Saito, M.; Okamatsu-Ogura, Y.; Matsushita, M.; Watanabe, K.; Yoneshiro, T.; Nio-Kobayashi, J.; Iwanaga, T.; Miyagawa, M.; Kameya, T.; Nakada, K.; et al. High incidence of metabolically active brown adipose tissue in healthy adult humans: Effects of cold exposure and adiposity. Diabetes 2009, 58, 1526–1531. [Google Scholar] [CrossRef]
  357. Saari, T.J.; Raiko, J.; U-Din, M.; Niemi, T.; Taittonen, M.; Laine, J.; Savisto, N.; Haaparanta-Solin, M.; Nuutila, P.; Virtanen, K.A. Basal and cold-induced fatty acid uptake of human brown adipose tissue is impaired in obesity. Sci. Rep. 2020, 10, 14373. [Google Scholar] [CrossRef]
  358. Ouellet, V.; Labbe, S.M.; Blondin, D.P.; Phoenix, S.; Guerin, B.; Haman, F.; Turcotte, E.E.; Richard, D.; Carpentier, A.C. Brown adipose tissue oxidative metabolism contributes to energy expenditure during acute cold exposure in humans. J. Clin. Investig. 2012, 122, 545–552. [Google Scholar] [CrossRef]
  359. Blondin, D.P.; Labbe, S.M.; Tingelstad, H.C.; Noll, C.; Kunach, M.; Phoenix, S.; Guerin, B.; Turcotte, E.E.; Carpentier, A.C.; Richard, D.; et al. Increased brown adipose tissue oxidative capacity in cold-acclimated humans. J. Clin. Endocrinol. Metab. 2014, 99, E438–E446. [Google Scholar] [CrossRef]
  360. Blondin, D.P.; Daoud, A.; Taylor, T.; Tingelstad, H.C.; Bezaire, V.; Richard, D.; Carpentier, A.C.; Taylor, A.W.; Harper, M.E.; Aguer, C.; et al. Four-week cold acclimation in adult humans shifts uncoupling thermogenesis from skeletal muscles to brown adipose tissue. J. Physiol. 2017, 595, 2099–2113. [Google Scholar] [CrossRef] [PubMed]
  361. Lee, P.; Zhao, J.T.; Swarbrick, M.M.; Gracie, G.; Bova, R.; Greenfield, J.R.; Freund, J.; Ho, K.K. High prevalence of brown adipose tissue in adult humans. J. Clin. Endocrinol. Metab. 2011, 96, 2450–2455. [Google Scholar] [CrossRef] [PubMed]
  362. Li, Y.; Fromme, T. Uncoupling Protein 1 Does Not Produce Heat without Activation. Int. J. Mol. Sci. 2022, 23, 2406. [Google Scholar] [CrossRef]
  363. Wang, H.; Willershäuser, M.; Li, Y.; Fromme, T.; Schnabl, K.; Bast-Habersbrunner, A.; Ramisch, S.; Mocek, S.; Klingenspor, M. Uncoupling protein-1 expression does not protect mice from diet-induced obesity. Am. J. Physiol. Endocrinol. Metab. 2021, 320, E333–E345. [Google Scholar] [CrossRef]
  364. Porter, C. Quantification of UCP1 function in human brown adipose tissue. Adipocyte 2017, 6, 167–174. [Google Scholar] [CrossRef] [PubMed]
  365. Porter, C.; Herndon, D.N.; Chondronikola, M.; Chao, T.; Annamalai, P.; Bhattarai, N.; Saraf, M.K.; Capek, K.D.; Reidy, P.T.; Daquinag, A.C.; et al. Human and Mouse Brown Adipose Tissue Mitochondria Have Comparable UCP1 Function. Cell Metab. 2016, 24, 246–255. [Google Scholar] [CrossRef]
  366. U-Din, M.; de Mello, V.D.; Tuomainen, M.; Raiko, J.; Niemi, T.; Fromme, T.; Klavus, A.; Gautier, N.; Haimilahti, K.; Lehtonen, M.; et al. Cold-stimulated brown adipose tissue activation is related to changes in serum metabolites relevant to NAD(+) metabolism in humans. Cell Rep. 2023, 42, 113131. [Google Scholar] [CrossRef]
  367. Jequier, E. Thermogenic responses induced by nutrients in man: Their importance in energy balance regulation. Exp. Suppl. 1983, 44, 26–44. [Google Scholar] [CrossRef]
  368. Westerterp, K.R. Diet induced thermogenesis. Nutr. Metab. 2004, 1, 5. [Google Scholar] [CrossRef] [PubMed]
  369. Din, M.U.; Saari, T.; Raiko, J.; Kudomi, N.; Maurer, S.F.; Lahesmaa, M.; Fromme, T.; Amri, E.Z.; Klingenspor, M.; Solin, O.; et al. Postprandial Oxidative Metabolism of Human Brown Fat Indicates Thermogenesis. Cell Metab. 2018, 28, 207–216.e203. [Google Scholar] [CrossRef]
  370. Himms-Hagen, J. Role of thermogenesis in the regulation of energy balance in relation to obesity. Can. J. Physiol. Pharmacol. 1989, 67, 394–401. [Google Scholar] [CrossRef] [PubMed]
  371. Glick, Z.; Teague, R.J.; Bray, G.A. Brown adipose tissue: Thermic response increased by a single low protein, high carbohydrate meal. Science 1981, 213, 1125–1127. [Google Scholar] [CrossRef]
  372. Saito, M.; Minokoshi, Y.; Shimazu, T. Metabolic and sympathetic nerve activities of brown adipose tissue in tube-fed rats. Am. J. Physiol. 1989, 257, E374–E378. [Google Scholar] [CrossRef]
  373. Lupien, J.R.; Glick, Z.; Saito, M.; Bray, G.A. Guanosine diphosphate binding to brown adipose tissue mitochondria is increased after single meal. Am. J. Physiol. 1985, 249, R694–R698. [Google Scholar] [CrossRef]
  374. Von Essen, G.; Lindsund, E.; Cannon, B.; Nedergaard, J. Adaptive facultative diet-induced thermogenesis in wild-type but not in UCP1-ablated mice. Am. J. Physiol. Endocrinol. Metab. 2017, 313, E515–E527. [Google Scholar] [CrossRef]
  375. Feldmann, H.M.; Golozoubova, V.; Cannon, B.; Nedergaard, J. UCP1 ablation induces obesity and abolishes diet-induced thermogenesis in mice exempt from thermal stress by living at thermoneutrality. Cell Metab. 2009, 9, 203–209. [Google Scholar] [CrossRef]
  376. Luijten, I.H.N.; Feldmann, H.M.; von Essen, G.; Cannon, B.; Nedergaard, J. In the absence of UCP1-mediated diet-induced thermogenesis, obesity is augmented even in the obesity-resistant 129S mouse strain. Am. J. Physiol. Endocrinol. Metab. 2019, 316, E729–E740. [Google Scholar] [CrossRef]
  377. Hibi, M.; Oishi, S.; Matsushita, M.; Yoneshiro, T.; Yamaguchi, T.; Usui, C.; Yasunaga, K.; Katsuragi, Y.; Kubota, K.; Tanaka, S.; et al. Brown adipose tissue is involved in diet-induced thermogenesis and whole-body fat utilization in healthy humans. Int. J. Obes. 2016, 40, 1655–1661. [Google Scholar] [CrossRef]
  378. Loeliger, R.C.; Maushart, C.I.; Gashi, G.; Senn, J.R.; Felder, M.; Becker, A.S.; Muller, J.; Balaz, M.; Wolfrum, C.; Burger, I.A.; et al. Relation of diet-induced thermogenesis to brown adipose tissue activity in healthy men. Am. J. Physiol. Endocrinol. Metab. 2021, 320, E93–E101. [Google Scholar] [CrossRef] [PubMed]
  379. Heenan, K.A.; Carrillo, A.E.; Fulton, J.L.; Ryan, E.J.; Edsall, J.R.; Rigopoulos, D.; Markofski, M.M.; Flouris, A.D.; Dinas, P.C. Effects of Nutrition/Diet on Brown Adipose Tissue in Humans: A Systematic Review and Meta-Analysis. Nutrients 2020, 12, 2752. [Google Scholar] [CrossRef] [PubMed]
  380. Ho, K.K.Y. Diet-induced thermogenesis: Fake friend or foe? J. Endocrinol. 2018, 238, R185–R191. [Google Scholar] [CrossRef]
  381. Kozak, L.P. Brown fat and the myth of diet-induced thermogenesis. Cell Metab. 2010, 11, 263–267. [Google Scholar] [CrossRef] [PubMed]
  382. Enerback, S.; Jacobsson, A.; Simpson, E.M.; Guerra, C.; Yamashita, H.; Harper, M.E.; Kozak, L.P. Mice lacking mitochondrial uncoupling protein are cold-sensitive but not obese. Nature 1997, 387, 90–94. [Google Scholar] [CrossRef]
  383. Melnyk, A.; Harper, M.E.; Himms-Hagen, J. Raising at thermoneutrality prevents obesity and hyperphagia in BAT-ablated transgenic mice. Am. J. Physiol. 1997, 272, R1088–R1093. [Google Scholar] [CrossRef]
  384. Liu, X.; Rossmeisl, M.; McClaine, J.; Riachi, M.; Harper, M.E.; Kozak, L.P. Paradoxical resistance to diet-induced obesity in UCP1-deficient mice. J. Clin. Investig. 2003, 111, 399–407. [Google Scholar] [CrossRef]
  385. Anunciado-Koza, R.; Ukropec, J.; Koza, R.A.; Kozak, L.P. Inactivation of UCP1 and the glycerol phosphate cycle synergistically increases energy expenditure to resist diet-induced obesity. J. Biol. Chem. 2008, 283, 27688–27697. [Google Scholar] [CrossRef]
  386. Tzeravini, E.; Anastasios, T.; Alexander, K.; Nikolaos, T.; Nikolaos, K. Diet induced thermogenesis, older and newer data with emphasis on obesity and diabetes mellitus—A narrative review. Metabol. Open 2024, 22, 100291. [Google Scholar] [CrossRef]
  387. Granneman, J.G.; Burnazi, M.; Zhu, Z.; Schwamb, L.A. White adipose tissue contributes to UCP1-independent thermogenesis. Am. J. Physiol. Endocrinol. Metab. 2003, 285, E1230–E1236. [Google Scholar] [CrossRef] [PubMed]
  388. Ukropec, J.; Anunciado, R.P.; Ravussin, Y.; Hulver, M.W.; Kozak, L.P. UCP1-independent thermogenesis in white adipose tissue of cold-acclimated Ucp1−/− mice. J. Biol. Chem. 2006, 281, 31894–31908. [Google Scholar] [CrossRef] [PubMed]
  389. Meyer, C.W.; Willershauser, M.; Jastroch, M.; Rourke, B.C.; Fromme, T.; Oelkrug, R.; Heldmaier, G.; Klingenspor, M. Adaptive thermogenesis and thermal conductance in wild-type and UCP1-KO mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2010, 299, R1396–R1406. [Google Scholar] [CrossRef]
  390. Young, P.; Arch, J.R.; Ashwell, M. Brown adipose tissue in the parametrial fat pad of the mouse. FEBS Lett. 1984, 167, 10–14. [Google Scholar] [CrossRef]
  391. Schirinzi, V.; Poli, C.; Berteotti, C.; Leone, A. Browning of Adipocytes: A Potential Therapeutic Approach to Obesity. Nutrients 2023, 15, 2229. [Google Scholar] [CrossRef] [PubMed]
  392. Scheel, A.K.; Espelage, L.; Chadt, A. Many Ways to Rome: Exercise, Cold Exposure and Diet-Do They All Affect BAT Activation and WAT Browning in the Same Manner? Int. J. Mol. Sci. 2022, 23, 4759. [Google Scholar] [CrossRef]
  393. Kawate, R.; Talan, M.I.; Engel, B.T. Sympathetic nervous activity to brown adipose tissue increases in cold-tolerant mice. Physiol. Behav. 1994, 55, 921–925. [Google Scholar] [CrossRef]
  394. Kirov, S.A.; Talan, M.I.; Engel, B.T. Sympathetic outflow to interscapular brown adipose tissue in cold acclimated mice. Physiol. Behav. 1996, 59, 231–235. [Google Scholar] [CrossRef]
  395. Murano, I.; Barbatelli, G.; Giordano, A.; Cinti, S. Noradrenergic parenchymal nerve fiber branching after cold acclimatisation correlates with brown adipocyte density in mouse adipose organ. J. Anat. 2009, 214, 171–178. [Google Scholar] [CrossRef] [PubMed]
  396. Barbatelli, G.; Murano, I.; Madsen, L.; Hao, Q.; Jimenez, M.; Kristiansen, K.; Giacobino, J.P.; De Matteis, R.; Cinti, S. The emergence of cold-induced brown adipocytes in mouse white fat depots is determined predominantly by white to brown adipocyte transdifferentiation. Am. J. Physiol. Endocrinol. Metab. 2011, 298, E1244–E1253. [Google Scholar] [CrossRef]
  397. Danysz, W.; Han, Y.; Li, F.; Nicoll, J.; Buch, P.; Hengl, T.; Ruitenberg, M.; Parsons, C. Browning of white adipose tissue induced by the ss3 agonist CL-316,243 after local and systemic treatment—PK-PD relationship. Biochim. Biophys. Acta Mol. Basis Dis. 2018, 1864, 2972–2982. [Google Scholar] [CrossRef]
  398. Hartimath, S.V.; Khanapur, S.; Boominathan, R.; Jiang, L.; Cheng, P.; Yong, F.F.; Tan, P.W.; Robins, E.G.; Goggi, J.L. Imaging adipose tissue browning using the TSPO-18kDa tracer [(18)F]FEPPA. Mol. Metab. 2019, 25, 154–158. [Google Scholar] [CrossRef]
  399. Goggi, J.L.; Hartimath, S.; Khanapur, S.; Ramasamy, B.; Tang, J.R.; Cheng, P.; Barron, A.M.; Tsukada, H.; Robins, E.G. Imaging Adipose Tissue Browning using Mitochondrial Complex-I Tracer [(18)F]BCPP-EF. Contrast Media Mol. Imaging 2022, 2022, 6113660. [Google Scholar] [CrossRef]
  400. Jimenez, M.; Barbatelli, G.; Allevi, R.; Cinti, S.; Seydoux, J.; Giacobino, J.P.; Muzzin, P.; Preitner, F. Beta 3-adrenoceptor knockout in C57BL/6J mice depresses the occurrence of brown adipocytes in white fat. Eur. J. Biochem. 2003, 270, 699–705. [Google Scholar] [CrossRef]
  401. Tyagi, P.; Tyagi, V.; Chancellor, M. Mirabegron: A safety review. Expert. Opin. Drug Saf. 2011, 10, 287–294. [Google Scholar] [CrossRef]
  402. O’Kane, M.; Robinson, D.; Cardozo, L.; Wagg, A.; Abrams, P. Mirabegron in the Management of Overactive Bladder Syndrome. Int. J. Womens Health 2022, 14, 1337–1350. [Google Scholar] [CrossRef]
  403. Finlin, B.S.; Memetimin, H.; Zhu, B.; Confides, A.L.; Vekaria, H.J.; El Khouli, R.H.; Johnson, Z.R.; Westgate, P.M.; Chen, J.; Morris, A.J.; et al. The beta3-adrenergic receptor agonist mirabegron improves glucose homeostasis in obese humans. J. Clin. Investig. 2020, 130, 2319–2331. [Google Scholar] [CrossRef] [PubMed]
  404. Bel, J.S.; Tai, T.C.; Khaper, N.; Lees, S.J. Mirabegron: The most promising adipose tissue beiging agent. Physiol. Rep. 2021, 9, e14779. [Google Scholar] [CrossRef] [PubMed]
  405. Sun, X.; Sui, W.; Mu, Z.; Xie, S.; Deng, J.; Li, S.; Seki, T.; Wu, J.; Jing, X.; He, X.; et al. Mirabegron displays anticancer effects by globally browning adipose tissues. Nat. Commun. 2023, 14, 7610. [Google Scholar] [CrossRef] [PubMed]
  406. Phiri, K.; Hallas, J.; Linder, M.; Margulis, A.; Suehs, B.; Arana, A.; Bahmanyar, S.; Hoffman, V.; Enger, C.; Horter, L.; et al. A study of cancer occurrence in users of mirabegron and antimuscarinic treatments for overactive bladder. Curr. Med. Res. Opin. 2021, 37, 867–877. [Google Scholar] [CrossRef]
  407. Park, J.S.; Lee, M.E.; Jang, W.S.; Kim, J.; Shin, G.; Ham, W.S. Association between β3-adrenergic receptor agonist use and risk of kidney cancer among patients with overactive bladder. J. Clin. Oncol. 2024, 42, 456. [Google Scholar] [CrossRef]
  408. Sui, W.; Li, H.; Yang, Y.; Jing, X.; Xue, F.; Cheng, J.; Dong, M.; Zhang, M.; Pan, H.; Chen, Y.; et al. Bladder drug mirabegron exacerbates atherosclerosis through activation of brown fat-mediated lipolysis. Proc. Natl. Acad. Sci. USA 2019, 116, 10937–10942. [Google Scholar] [CrossRef]
  409. Ying, Z.; van Eenige, R.; Beerepoot, R.; Boon, M.R.; Kloosterhuis, N.J.; van de Sluis, B.; Bartelt, A.; Rensen, P.C.N.; Kooijman, S. Mirabegron-induced brown fat activation does not exacerbate atherosclerosis in mice with a functional hepatic ApoE-LDLR pathway. Pharmacol. Res. 2023, 187, 106634. [Google Scholar] [CrossRef]
  410. Loh, R.K.C.; Formosa, M.F.; La Gerche, A.; Reutens, A.T.; Kingwell, B.A.; Carey, A.L. Acute metabolic and cardiovascular effects of mirabegron in healthy individuals. Diabetes Obes. Metab. 2019, 21, 276–284. [Google Scholar] [CrossRef]
  411. Nahon, K.J.; Janssen, L.G.M.; Sardjoe Mishre, A.S.D.; Bilsen, M.P.; van der Eijk, J.A.; Botani, K.; Overduin, L.A.; Ruiz, J.R.; Burakiewicz, J.; Dzyubachyk, O.; et al. The effect of mirabegron on energy expenditure and brown adipose tissue in healthy lean South Asian and Europid men. Diabetes Obes. Metab. 2020, 22, 2032–2044. [Google Scholar] [CrossRef]
  412. Ma, L.; Xiong, L.; Huang, G. Effects of mirabegron on brown adipose tissue and metabolism in humans: A systematic review and meta-analysis. Eur. J. Clin. Pharmacol. 2024, 80, 317–333. [Google Scholar] [CrossRef] [PubMed]
  413. Dehvari, N.; da Silva Junior, E.D.; Bengtsson, T.; Hutchinson, D.S. Mirabegron: Potential off target effects and uses beyond the bladder. Br. J. Pharmacol. 2018, 175, 4072–4082. [Google Scholar] [CrossRef]
  414. Wang, Y.; Ashokan, K. Physical Exercise: An Overview of Benefits From Psychological Level to Genetics and Beyond. Front. Physiol. 2021, 12, 731858. [Google Scholar] [CrossRef]
  415. Severinsen, M.C.K.; Scheele, C.; Pedersen, B.K. Exercise and browning of white adipose tissue—A translational perspective. Curr. Opin. Pharmacol. 2020, 52, 18–24. [Google Scholar] [CrossRef]
  416. Bostrom, P.; Wu, J.; Jedrychowski, M.P.; Korde, A.; Ye, L.; Lo, J.C.; Rasbach, K.A.; Bostrom, E.A.; Choi, J.H.; Long, J.Z.; et al. A PGC1-alpha-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature 2012, 481, 463–468. [Google Scholar] [CrossRef]
  417. Xiong, Y.; Wu, Z.; Zhang, B.; Wang, C.; Mao, F.; Liu, X.; Hu, K.; Sun, X.; Jin, W.; Kuang, S. Fndc5 loss-of-function attenuates exercise-induced browning of white adipose tissue in mice. FASEB J. 2019, 33, 5876–5886. [Google Scholar] [CrossRef]
  418. Tiano, J.P.; Springer, D.A.; Rane, S.G. SMAD3 negatively regulates serum irisin and skeletal muscle FNDC5 and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1alpha) during exercise. J. Biol. Chem. 2015, 290, 11431. [Google Scholar] [CrossRef]
  419. Oguri, Y.; Shinoda, K.; Kim, H.; Alba, D.L.; Bolus, W.R.; Wang, Q.; Brown, Z.; Pradhan, R.N.; Tajima, K.; Yoneshiro, T.; et al. CD81 Controls Beige Fat Progenitor Cell Growth and Energy Balance via FAK Signaling. Cell 2020, 182, 563–577. [Google Scholar] [CrossRef]
  420. Pekkala, S.; Wiklund, P.K.; Hulmi, J.J.; Ahtiainen, J.P.; Horttanainen, M.; Pollanen, E.; Makela, K.A.; Kainulainen, H.; Hakkinen, K.; Nyman, K.; et al. Are skeletal muscle FNDC5 gene expression and irisin release regulated by exercise and related to health? J. Physiol. 2013, 591, 5393–5400. [Google Scholar] [CrossRef]
  421. Timmons, J.A.; Baar, K.; Davidsen, P.K.; Atherton, P.J. Is irisin a human exercise gene? Nature 2012, 488, E9–E10. [Google Scholar] [CrossRef] [PubMed]
  422. Norheim, F.; Langleite, T.M.; Hjorth, M.; Holen, T.; Kielland, A.; Stadheim, H.K.; Gulseth, H.L.; Birkeland, K.I.; Jensen, J.; Drevon, C.A. The effects of acute and chronic exercise on PGC-1alpha, irisin and browning of subcutaneous adipose tissue in humans. FEBS J. 2014, 281, 739–749. [Google Scholar] [CrossRef] [PubMed]
  423. Mendez-Gutierrez, A.; Aguilera, C.M.; Osuna-Prieto, F.J.; Martinez-Tellez, B.; Rico Prados, M.C.; Acosta, F.M.; Llamas-Elvira, J.M.; Ruiz, J.R.; Sanchez-Delgado, G. Exercise-induced changes on exerkines that might influence brown adipose tissue metabolism in young sedentary adults. Eur. J. Sport. Sci. 2023, 23, 625–636. [Google Scholar] [CrossRef] [PubMed]
  424. Cuevas-Ramos, D.; Mehta, R.; Aguilar-Salinas, C.A. Fibroblast Growth Factor 21 and Browning of White Adipose Tissue. Front. Physiol. 2019, 10, 37. [Google Scholar] [CrossRef]
  425. Cuevas-Ramos, D.; Almeda-Valdes, P.; Meza-Arana, C.E.; Brito-Cordova, G.; Gomez-Perez, F.J.; Mehta, R.; Oseguera-Moguel, J.; Aguilar-Salinas, C.A. Exercise increases serum fibroblast growth factor 21 (FGF21) levels. PLoS ONE 2012, 7, e38022. [Google Scholar] [CrossRef]
  426. Li, H.; Dong, M.; Liu, W.; Gao, C.; Jia, Y.; Zhang, X.; Xiao, X.; Liu, Q.; Lin, H. Peripheral IL-6/STAT3 signaling promotes beiging of white fat. Biochim. Biophys. Acta Mol. Cell Res. 2021, 1868, 119080. [Google Scholar] [CrossRef]
  427. Larsuphrom, P.; Latunde-Dada, G.O. Association of Serum Hepcidin Levels with Aerobic and Resistance Exercise: A Systematic Review. Nutrients 2021, 13, 393. [Google Scholar] [CrossRef] [PubMed]
  428. Kleinert, M.; Clemmensen, C.; Sjoberg, K.A.; Carl, C.S.; Jeppesen, J.F.; Wojtaszewski, J.F.P.; Kiens, B.; Richter, E.A. Exercise increases circulating GDF15 in humans. Mol. Metab. 2018, 9, 187–191. [Google Scholar] [CrossRef]
  429. Laurens, C.; Parmar, A.; Murphy, E.; Carper, D.; Lair, B.; Maes, P.; Vion, J.; Boulet, N.; Fontaine, C.; Marques, M.; et al. Growth and differentiation factor 15 is secreted by skeletal muscle during exercise and promotes lipolysis in humans. JCI Insight 2020, 5, e131870. [Google Scholar] [CrossRef] [PubMed]
  430. Chachay, V.S.; Kirkpatrick, C.M.; Hickman, I.J.; Ferguson, M.; Prins, J.B.; Martin, J.H. Resveratrol—Pills to replace a healthy diet? Br. J. Clin. Pharmacol. 2011, 72, 27–38. [Google Scholar] [CrossRef]
  431. Ciccone, L.; Piragine, E.; Brogi, S.; Camodeca, C.; Fucci, R.; Calderone, V.; Nencetti, S.; Martelli, A.; Orlandini, E. Resveratrol-like Compounds as SIRT1 Activators. Int. J. Mol. Sci. 2022, 23, 15105. [Google Scholar] [CrossRef]
  432. Cao, D.; Wang, M.; Qiu, X.; Liu, D.; Jiang, H.; Yang, N.; Xu, R.M. Structural basis for allosteric, substrate-dependent stimulation of SIRT1 activity by resveratrol. Genes. Dev. 2015, 29, 1316–1325. [Google Scholar] [CrossRef]
  433. Qiang, L.; Wang, L.; Kon, N.; Zhao, W.; Lee, S.; Zhang, Y.; Rosenbaum, M.; Zhao, Y.; Gu, W.; Farmer, S.R.; et al. Brown remodeling of white adipose tissue by SirT1-dependent deacetylation of Ppargamma. Cell 2012, 150, 620–632. [Google Scholar] [CrossRef]
  434. Harms, M.J.; Ishibashi, J.; Wang, W.; Lim, H.W.; Goyama, S.; Sato, T.; Kurokawa, M.; Won, K.J.; Seale, P. Prdm16 is required for the maintenance of brown adipocyte identity and function in adult mice. Cell Metab. 2014, 19, 593–604. [Google Scholar] [CrossRef]
  435. Wang, S.; Liang, X.; Yang, Q.; Fu, X.; Rogers, C.J.; Zhu, M.; Rodgers, B.D.; Jiang, Q.; Dodson, M.V.; Du, M. Resveratrol induces brown-like adipocyte formation in white fat through activation of AMP-activated protein kinase (AMPK) alpha1. Int. J. Obes. 2015, 39, 967–976. [Google Scholar] [CrossRef] [PubMed]
  436. Wang, S.; Liang, X.; Yang, Q.; Fu, X.; Zhu, M.; Rodgers, B.D.; Jiang, Q.; Dodson, M.V.; Du, M. Resveratrol enhances brown adipocyte formation and function by activating AMP-activated protein kinase (AMPK) alpha1 in mice fed high-fat diet. Mol. Nutr. Food Res. 2017, 61, 1600746. [Google Scholar] [CrossRef]
  437. Andrade, J.M.O.; Barcala-Jorge, A.S.; Batista-Jorge, G.C.; Paraiso, A.F.; Freitas, K.M.; Lelis, D.F.; Guimaraes, A.L.S.; de Paula, A.M.B.; Santos, S.H.S. Effect of resveratrol on expression of genes involved thermogenesis in mice and humans. Biomed. Pharmacother. 2019, 112, 108634. [Google Scholar] [CrossRef]
  438. Chen, S.; Zhao, X.; Ran, L.; Wan, J.; Wang, X.; Qin, Y.; Shu, F.; Gao, Y.; Yuan, L.; Zhang, Q.; et al. Resveratrol improves insulin resistance, glucose and lipid metabolism in patients with non-alcoholic fatty liver disease: A randomized controlled trial. Dig. Liver Dis. 2015, 47, 226–232. [Google Scholar] [CrossRef]
  439. Zheng, J.; Zheng, S.; Feng, Q.; Zhang, Q.; Xiao, X. Dietary capsaicin and its anti-obesity potency: From mechanism to clinical implications. Biosci. Rep. 2017, 37, BSR20170286. [Google Scholar] [CrossRef] [PubMed]
  440. Baskaran, P.; Krishnan, V.; Ren, J.; Thyagarajan, B. Capsaicin induces browning of white adipose tissue and counters obesity by activating TRPV1 channel-dependent mechanisms. Br. J. Pharmacol. 2016, 173, 2369–2389. [Google Scholar] [CrossRef]
  441. Zhang, Q.; He, C.X.; Wang, L.Y.; Qian, D.; Tang, D.D.; Jiang, S.N.; Chen, W.W.; Wu, C.J.; Peng, W. Hydroxy-alpha-sanshool from the fruits of Zanthoxylum bungeanum Maxim. promotes browning of white fat by activating TRPV1 to induce PPAR-gamma deacetylation. Phytomedicine 2023, 121, 155113. [Google Scholar] [CrossRef] [PubMed]
  442. Baskaran, P.; Covington, K.; Bennis, J.; Mohandass, A.; Lehmann, T.; Thyagarajan, B. Binding Efficacy and Thermogenic Efficiency of Pungent and Nonpungent Analogs of Capsaicin. Molecules 2018, 23, 3198. [Google Scholar] [CrossRef]
  443. Lund, J.; Larsen, L.H.; Lauritzen, L. Fish oil as a potential activator of brown and beige fat thermogenesis. Adipocyte 2018, 7, 88–95. [Google Scholar] [CrossRef]
  444. Kim, M.; Goto, T.; Yu, R.; Uchida, K.; Tominaga, M.; Kano, Y.; Takahashi, N.; Kawada, T. Fish oil intake induces UCP1 upregulation in brown and white adipose tissue via the sympathetic nervous system. Sci. Rep. 2015, 5, 18013. [Google Scholar] [CrossRef]
  445. Bargut, T.C.; Souza-Mello, V.; Mandarim-de-Lacerda, C.A.; Aguila, M.B. Fish oil diet modulates epididymal and inguinal adipocyte metabolism in mice. Food Funct. 2016, 7, 1468–1476. [Google Scholar] [CrossRef]
  446. Yamazaki, T.; Li, D.; Ikaga, R. Fish Oil Increases Diet-Induced Thermogenesis in Mice. Mar. Drugs 2021, 19, 278. [Google Scholar] [CrossRef] [PubMed]
  447. Choi, Y.; Yu, L. Natural Bioactive Compounds as Potential Browning Agents in White Adipose Tissue. Pharm. Res. 2021, 38, 549–567. [Google Scholar] [CrossRef] [PubMed]
  448. Kaisanlahti, A.; Glumoff, T. Browning of white fat: Agents and implications for beige adipose tissue to type 2 diabetes. J. Physiol. Biochem. 2019, 75, 1–10. [Google Scholar] [CrossRef]
  449. Hankir, M.K.; Cowley, M.A.; Fenske, W.K. A BAT-Centric Approach to the Treatment of Diabetes: Turn on the Brain. Cell Metab. 2016, 24, 31–40. [Google Scholar] [CrossRef]
  450. Pilkington, A.C.; Paz, H.A.; Wankhade, U.D. Beige Adipose Tissue Identification and Marker Specificity—Overview. Front. Endocrinol. 2021, 12, 599134. [Google Scholar] [CrossRef] [PubMed]
  451. Schulz, T.J.; Huang, T.L.; Tran, T.T.; Zhang, H.; Townsend, K.L.; Shadrach, J.L.; Cerletti, M.; McDougall, L.E.; Giorgadze, N.; Tchkonia, T.; et al. Identification of inducible brown adipocyte progenitors residing in skeletal muscle and white fat. Proc. Natl. Acad. Sci. USA 2011, 108, 143–148. [Google Scholar] [CrossRef]
  452. Jespersen, N.Z.; Larsen, T.J.; Peijs, L.; Daugaard, S.; Homoe, P.; Loft, A.; de Jong, J.; Mathur, N.; Cannon, B.; Nedergaard, J.; et al. A classical brown adipose tissue mRNA signature partly overlaps with brite in the supraclavicular region of adult humans. Cell Metab. 2013, 17, 798–805. [Google Scholar] [CrossRef]
  453. Himms-Hagen, J.; Melnyk, A.; Zingaretti, M.C.; Ceresi, E.; Barbatelli, G.; Cinti, S. Multilocular fat cells in WAT of CL-316243-treated rats derive directly from white adipocytes. Am. J. Physiol. Cell Physiol. 2000, 279, C670–C681. [Google Scholar] [CrossRef]
  454. Nijhawan, P.; Behl, T.; Bungau, S.; Uddin, M.S.; Zengin, G.; Arora, S. Molecular insights into therapeutic promise of targeting of Wnt/β-catenin signaling pathway in obesity. Mol. Biol. Rep. 2020, 47, 8091–8100. [Google Scholar] [CrossRef]
  455. Keipert, S.; Jastroch, M. Brite/beige fat and UCP1—Is it thermogenesis? Biochim. Biophys. Acta 2014, 1837, 1075–1082. [Google Scholar] [CrossRef]
  456. Harms, M.; Seale, P. Brown and beige fat: Development, function and therapeutic potential. Nat. Med. 2013, 19, 1252–1263. [Google Scholar] [CrossRef] [PubMed]
  457. Wu, J.; Bostrom, P.; Sparks, L.M.; Ye, L.; Choi, J.H.; Giang, A.H.; Khandekar, M.; Virtanen, K.A.; Nuutila, P.; Schaart, G.; et al. Beige adipocytes are a distinct type of thermogenic fat cell in mouse and human. Cell 2012, 150, 366–376. [Google Scholar] [CrossRef]
  458. Sharp, L.Z.; Shinoda, K.; Ohno, H.; Scheel, D.W.; Tomoda, E.; Ruiz, L.; Hu, H.; Wang, L.; Pavlova, Z.; Gilsanz, V.; et al. Human BAT possesses molecular signatures that resemble beige/brite cells. PLoS ONE 2012, 7, e49452. [Google Scholar] [CrossRef]
  459. Ku, H.C.; Chan, T.Y.; Chung, J.F.; Kao, Y.H.; Cheng, C.F. The ATF3 inducer protects against diet-induced obesity via suppressing adipocyte adipogenesis and promoting lipolysis and browning. Biomed. Pharmacother. 2022, 145, 112440. [Google Scholar] [CrossRef]
  460. Seale, P.; Bjork, B.; Yang, W.; Kajimura, S.; Chin, S.; Kuang, S.; Scimè, A.; Devarakonda, S.; Conroe, H.M.; Erdjument-Bromage, H.; et al. PRDM16 controls a brown fat/skeletal muscle switch. Nature 2008, 454, 961–967. [Google Scholar] [CrossRef]
  461. Ohno, H.; Shinoda, K.; Spiegelman, B.M.; Kajimura, S. PPARgamma agonists induce a white-to-brown fat conversion through stabilization of PRDM16 protein. Cell Metab. 2012, 15, 395–404. [Google Scholar] [CrossRef]
  462. Petrovic, N.; Walden, T.B.; Shabalina, I.G.; Timmons, J.A.; Cannon, B.; Nedergaard, J. Chronic peroxisome proliferator-activated receptor gamma (PPARgamma) activation of epididymally derived white adipocyte cultures reveals a population of thermogenically competent, UCP1-containing adipocytes molecularly distinct from classic brown adipocytes. J. Biol. Chem. 2010, 285, 7153–7164. [Google Scholar] [PubMed]
  463. De Jong, J.M.; Larsson, O.; Cannon, B.; Nedergaard, J. A stringent validation of mouse adipose tissue identity markers. Am. J. Physiol. Endocrinol. Metab. 2015, 308, E1085–E1105. [Google Scholar] [CrossRef]
  464. Nahmgoong, H.; Jeon, Y.G.; Park, E.S.; Choi, Y.H.; Han, S.M.; Park, J.; Ji, Y.; Sohn, J.H.; Han, J.S.; Kim, Y.Y.; et al. Distinct properties of adipose stem cell subpopulations determine fat depot-specific characteristics. Cell Metab. 2022, 34, 458–472. [Google Scholar] [CrossRef] [PubMed]
  465. Vegiopoulos, A.; Muller-Decker, K.; Strzoda, D.; Schmitt, I.; Chichelnitskiy, E.; Ostertag, A.; Berriel Diaz, M.; Rozman, J.; Hrabe de Angelis, M.; Nusing, R.M.; et al. Cyclooxygenase-2 controls energy homeostasis in mice by de novo recruitment of brown adipocytes. Science 2010, 328, 1158–1161. [Google Scholar] [CrossRef]
  466. Lee, P.; Werner, C.D.; Kebebew, E.; Celi, F.S. Functional thermogenic beige adipogenesis is inducible in human neck fat. Int. J. Obes. 2014, 38, 170–176. [Google Scholar] [CrossRef]
  467. Di Franco, A.; Guasti, D.; Mazzanti, B.; Ercolino, T.; Francalanci, M.; Nesi, G.; Bani, D.; Forti, G.; Mannelli, M.; Valeri, A.; et al. Dissecting the origin of inducible brown fat in adult humans through a novel adipose stem cell model from adipose tissue surrounding pheochromocytoma. J. Clin. Endocrinol. Metab. 2014, 99, E1903–E1912. [Google Scholar] [CrossRef] [PubMed]
  468. Vergnes, L.; Davies, G.R.; Lin, J.Y.; Yeh, M.W.; Livhits, M.J.; Harari, A.; Symonds, M.E.; Sacks, H.S.; Reue, K. Adipocyte Browning and Higher Mitochondrial Function in Periadrenal But Not SC Fat in Pheochromocytoma. J. Clin. Endocrinol. Metab. 2016, 101, 4440–4448. [Google Scholar] [CrossRef] [PubMed]
  469. Scheller, E.L.; Doucette, C.R.; Learman, B.S.; Cawthorn, W.P.; Khandaker, S.; Schell, B.; Wu, B.; Ding, S.Y.; Bredella, M.A.; Fazeli, P.K.; et al. Region-specific variation in the properties of skeletal adipocytes reveals regulated and constitutive marrow adipose tissues. Nat. Commun. 2015, 6, 7808, Erratum in Nat. Commun. 2016, 7, 13775. [Google Scholar] [CrossRef]
  470. Scheller, E.L.; Burr, A.A.; MacDougald, O.A.; Cawthorn, W.P. Inside out: Bone marrow adipose tissue as a source of circulating adiponectin. Adipocyte 2016, 5, 251–269. [Google Scholar] [CrossRef] [PubMed]
  471. Li, Q.; Wu, Y.; Kang, N. Marrow Adipose Tissue: Its Origin, Function, and Regulation in Bone Remodeling and Regeneration. Stem Cells Int. 2018, 2018, 7098456. [Google Scholar] [CrossRef]
  472. Cawthorn, W.P.; Scheller, E.L. Editorial: Bone Marrow Adipose Tissue: Formation, Function, and Impact on Health and Disease. Front. Endocrinol. 2017, 8, 112. [Google Scholar] [CrossRef]
  473. Li, Z.; Hardij, J.; Bagchi, D.P.; Scheller, E.L.; MacDougald, O.A. Development, regulation, metabolism and function of bone marrow adipose tissues. Bone 2018, 110, 134–140. [Google Scholar] [CrossRef]
  474. Craft, C.S.; Robles, H.; Lorenz, M.R.; Hilker, E.D.; Magee, K.L.; Andersen, T.L.; Cawthorn, W.P.; MacDougald, O.A.; Harris, C.A.; Scheller, E.L. Bone marrow adipose tissue does not express UCP1 during development or adrenergic-induced remodeling. Sci. Rep. 2019, 9, 17427. [Google Scholar] [CrossRef]
  475. Craft, C.S.; Scheller, E.L. Evolution of the Marrow Adipose Tissue Microenvironment. Calcif. Tissue Int. 2017, 100, 461–475. [Google Scholar] [CrossRef]
  476. Gunaratnam, K.; Vidal, C.; Gimble, J.M.; Duque, G. Mechanisms of palmitate-induced lipotoxicity in human osteoblasts. Endocrinology 2014, 155, 108–116. [Google Scholar] [CrossRef]
  477. Kajimura, D.; Lee, H.W.; Riley, K.J.; Arteaga-Solis, E.; Ferron, M.; Zhou, B.; Clarke, C.J.; Hannun, Y.A.; DePinho, R.A.; Guo, X.E.; et al. Adiponectin regulates bone mass via opposite central and peripheral mechanisms through FoxO1. Cell Metab. 2013, 17, 901–915. [Google Scholar] [CrossRef] [PubMed]
  478. Mattiucci, D.; Maurizi, G.; Izzi, V.; Cenci, L.; Ciarlantini, M.; Mancini, S.; Mensa, E.; Pascarella, R.; Vivarelli, M.; Olivieri, A.; et al. Bone marrow adipocytes support hematopoietic stem cell survival. J. Cell Physiol. 2018, 233, 1500–1511. [Google Scholar] [CrossRef] [PubMed]
  479. Thomas, T.; Gori, F.; Khosla, S.; Jensen, M.D.; Burguera, B.; Riggs, B.L. Leptin acts on human marrow stromal cells to enhance differentiation to osteoblasts and to inhibit differentiation to adipocytes. Endocrinology 1999, 140, 1630–1638. [Google Scholar] [CrossRef]
  480. Yokota, T.; Meka, C.S.; Kouro, T.; Medina, K.L.; Igarashi, H.; Takahashi, M.; Oritani, K.; Funahashi, T.; Tomiyama, Y.; Matsuzawa, Y.; et al. Adiponectin, a fat cell product, influences the earliest lymphocyte precursors in bone marrow cultures by activation of the cyclooxygenase-prostaglandin pathway in stromal cells. J. Immunol. 2003, 171, 5091–5099. [Google Scholar] [CrossRef] [PubMed]
  481. Ambrosi, T.H.; Scialdone, A.; Graja, A.; Gohlke, S.; Jank, A.M.; Bocian, C.; Woelk, L.; Fan, H.; Logan, D.W.; Schurmann, A.; et al. Adipocyte Accumulation in the Bone Marrow during Obesity and Aging Impairs Stem Cell-Based Hematopoietic and Bone Regeneration. Cell Stem Cell 2017, 20, 771–784. [Google Scholar] [CrossRef]
  482. Fan, Y.; Hanai, J.I.; Le, P.T.; Bi, R.; Maridas, D.; DeMambro, V.; Figueroa, C.A.; Kir, S.; Zhou, X.; Mannstadt, M.; et al. Parathyroid Hormone Directs Bone Marrow Mesenchymal Cell Fate. Cell Metab. 2017, 25, 661–672. [Google Scholar] [CrossRef]
  483. Hardaway, A.L.; Herroon, M.K.; Rajagurubandara, E.; Podgorski, I. Marrow adipocyte-derived CXCL1 and CXCL2 contribute to osteolysis in metastatic prostate cancer. Clin. Exp. Metastasis 2015, 32, 353–368. [Google Scholar] [CrossRef]
  484. Luo, Y.; Chen, G.L.; Hannemann, N.; Ipseiz, N.; Kronke, G.; Bauerle, T.; Munos, L.; Wirtz, S.; Schett, G.; Bozec, A. Microbiota from Obese Mice Regulate Hematopoietic Stem Cell Differentiation by Altering the Bone Niche. Cell Metab. 2015, 22, 886–894. [Google Scholar] [CrossRef]
  485. Naveiras, O.; Nardi, V.; Wenzel, P.L.; Hauschka, P.V.; Fahey, F.; Daley, G.Q. Bone-marrow adipocytes as negative regulators of the haematopoietic microenvironment. Nature 2009, 460, 259–263. [Google Scholar] [CrossRef]
  486. Takeshita, S.; Fumoto, T.; Naoe, Y.; Ikeda, K. Age-related marrow adipogenesis is linked to increased expression of RANKL. J. Biol. Chem. 2014, 289, 16699–16710. [Google Scholar] [CrossRef]
  487. Lecka-Czernik, B.; Baroi, S.; Stechschulte, L.A.; Chougule, A.S. Marrow Fat-a New Target to Treat Bone Diseases? Curr. Osteoporos. Rep. 2018, 16, 123–129. [Google Scholar] [CrossRef]
  488. Calo, E.; Quintero-Estades, J.A.; Danielian, P.S.; Nedelcu, S.; Berman, S.D.; Lees, J.A. Rb regulates fate choice and lineage commitment in vivo. Nature 2010, 466, 1110–1114. [Google Scholar] [CrossRef]
  489. Fernandez-Marcos, P.J.; Auwerx, J. pRb, a switch between bone and brown fat. Dev. Cell 2010, 19, 360–362. [Google Scholar] [CrossRef] [PubMed][Green Version]
  490. Nuttall, M.E.; Shah, F.; Singh, V.; Thomas-Porch, C.; Frazier, T.; Gimble, J.M. Adipocytes and the regulation of bone remodeling: A balancing act. Calcif. Tissue Int. 2014, 94, 78–87. [Google Scholar] [CrossRef]
  491. Kfoury, Y.; Scadden, D.T. Mesenchymal cell contributions to the stem cell niche. Cell Stem Cell 2015, 16, 239–253. [Google Scholar] [CrossRef] [PubMed]
  492. Lecka-Czernik, B.; Stechschulte, L.A.; Czernik, P.J.; Sherman, S.B.; Huang, S.; Krings, A. Marrow Adipose Tissue: Skeletal Location, Sexual Dimorphism, and Response to Sex Steroid Deficiency. Front. Endocrinol. 2017, 8, 188. [Google Scholar] [CrossRef] [PubMed]
  493. Cawthorn, W.P.; Scheller, E.L.; Learman, B.S.; Parlee, S.D.; Simon, B.R.; Mori, H.; Ning, X.; Bree, A.J.; Schell, B.; Broome, D.T.; et al. Bone marrow adipose tissue is an endocrine organ that contributes to increased circulating adiponectin during caloric restriction. Cell Metab. 2014, 20, 368–375. [Google Scholar] [CrossRef]
  494. Sulston, R.J.; Learman, B.S.; Zhang, B.; Scheller, E.L.; Parlee, S.D.; Simon, B.R.; Mori, H.; Bree, A.J.; Wallace, R.J.; Krishnan, V.; et al. Increased Circulating Adiponectin in Response to Thiazolidinediones: Investigating the Role of Bone Marrow Adipose Tissue. Front. Endocrinol. 2016, 7, 128. [Google Scholar] [CrossRef]
  495. Deng, P.; Yuan, Q.; Cheng, Y.; Li, J.; Liu, Z.; Liu, Y.; Li, Y.; Su, T.; Wang, J.; Salvo, M.E.; et al. Loss of KDM4B exacerbates bone-fat imbalance and mesenchymal stromal cell exhaustion in skeletal aging. Cell Stem Cell 2021, 28, 1057–1073. [Google Scholar] [CrossRef] [PubMed]
  496. Yu, B.; Huo, L.; Liu, Y.; Deng, P.; Szymanski, J.; Li, J.; Luo, X.; Hong, C.; Lin, J.; Wang, C.Y. PGC-1alpha Controls Skeletal Stem Cell Fate and Bone-Fat Balance in Osteoporosis and Skeletal Aging by Inducing TAZ. Cell Stem Cell 2018, 23, 193–209. [Google Scholar] [CrossRef]
  497. Velickovic, K.; Lugo Leija, H.A.; Bloor, I.; Law, J.; Sacks, H.; Symonds, M.; Sottile, V. Low temperature exposure induces browning of bone marrow stem cell derived adipocytes in vitro. Sci. Rep. 2018, 8, 4974. [Google Scholar] [CrossRef]
  498. Li, Z.; Bowers, E.; Zhu, J.; Yu, H.; Hardij, J.; Bagchi, D.P.; Mori, H.; Lewis, K.T.; Granger, K.; Schill, R.L.; et al. Lipolysis of bone marrow adipocytes is required to fuel bone and the marrow niche during energy deficits. Elife 2022, 11, e78496. [Google Scholar] [CrossRef]
  499. Pop, L.M.; Lingvay, I.; Yuan, Q.; Li, X.; Adams-Huet, B.; Maalouf, N.M. Impact of pioglitazone on bone mineral density and bone marrow fat content. Osteoporos. Int. 2017, 28, 3261–3269. [Google Scholar] [CrossRef]
  500. Grey, A.; Beckley, V.; Doyle, A.; Fenwick, S.; Horne, A.; Gamble, G.; Bolland, M. Pioglitazone increases bone marrow fat in type 2 diabetes: Results from a randomized controlled trial. Eur. J. Endocrinol. 2012, 166, 1087–1091. [Google Scholar] [CrossRef]
  501. Billington, E.O.; Grey, A.; Bolland, M.J. The effect of thiazolidinediones on bone mineral density and bone turnover: Systematic review and meta-analysis. Diabetologia 2015, 58, 2238–2246. [Google Scholar] [CrossRef]
  502. Kirk, A.B.; Michelsen-Correa, S.; Rosen, C.; Martin, C.F.; Blumberg, B. PFAS and Potential Adverse Effects on Bone and Adipose Tissue Through Interactions With PPARgamma. Endocrinology 2021, 162, bqab194. [Google Scholar] [CrossRef]
  503. Bredella, M.A.; Torriani, M.; Ghomi, R.H.; Thomas, B.J.; Brick, D.J.; Gerweck, A.V.; Rosen, C.J.; Klibanski, A.; Miller, K.K. Vertebral bone marrow fat is positively associated with visceral fat and inversely associated with IGF-1 in obese women. Obesity 2011, 19, 49–53. [Google Scholar] [CrossRef] [PubMed]
  504. Hardaway, A.L.; Herroon, M.K.; Rajagurubandara, E.; Podgorski, I. Bone marrow fat: Linking adipocyte-induced inflammation with skeletal metastases. Cancer Metastasis Rev. 2014, 33, 527–543. [Google Scholar] [CrossRef] [PubMed]
  505. Hwang, S.; Panicek, D.M. Magnetic resonance imaging of bone marrow in oncology, Part 1. Skelet. Radiol. 2007, 36, 913–920. [Google Scholar] [CrossRef]
  506. Shen, W.; Chen, J.; Gantz, M.; Punyanitya, M.; Heymsfield, S.B.; Gallagher, D.; Albu, J.; Engelson, E.; Kotler, D.; Pi-Sunyer, X.; et al. Ethnic and sex differences in bone marrow adipose tissue and bone mineral density relationship. Osteoporos. Int. 2012, 23, 2293–2301. [Google Scholar] [CrossRef]
  507. McCabe, L.R.; Irwin, R.; Tekalur, A.; Evans, C.; Schepper, J.D.; Parameswaran, N.; Ciancio, M. Exercise prevents high fat diet-induced bone loss, marrow adiposity and dysbiosis in male mice. Bone 2019, 118, 20–31, Erratum in Bone 2019, 127, 677–678.. [Google Scholar] [CrossRef]
  508. Ermetici, F.; Briganti, S.; Delnevo, A.; Cannao, P.; Leo, G.D.; Benedini, S.; Terruzzi, I.; Sardanelli, F.; Luzi, L. Bone marrow fat contributes to insulin sensitivity and adiponectin secretion in premenopausal women. Endocrine 2018, 59, 410–418. [Google Scholar] [CrossRef]
  509. Dib, L.H.; Ortega, M.T.; Fleming, S.D.; Chapes, S.K.; Melgarejo, T. Bone marrow leptin signaling mediates obesity-associated adipose tissue inflammation in male mice. Endocrinology 2014, 155, 40–46. [Google Scholar] [CrossRef] [PubMed]
  510. Kim, T.Y.; Schafer, A.L. Diabetes and Bone Marrow Adiposity. Curr. Osteoporos. Rep. 2016, 14, 337–344. [Google Scholar] [CrossRef]
  511. Slade, J.M.; Coe, L.M.; Meyer, R.A.; McCabe, L.R. Human bone marrow adiposity is linked with serum lipid levels not T1-diabetes. J. Diabetes Complicat. 2012, 26, 1–9. [Google Scholar] [CrossRef]
  512. Abdalrahaman, N.; McComb, C.; Foster, J.E.; McLean, J.; Lindsay, R.S.; McClure, J.; McMillan, M.; Drummond, R.; Gordon, D.; McKay, G.A.; et al. Deficits in Trabecular Bone Microarchitecture in Young Women With Type 1 Diabetes Mellitus. J. Bone Miner. Res. 2015, 30, 1386–1393. [Google Scholar] [CrossRef]
  513. Botolin, S.; McCabe, L.R. Bone loss and increased bone adiposity in spontaneous and pharmacologically induced diabetic mice. Endocrinology 2007, 148, 198–205. [Google Scholar] [CrossRef] [PubMed]
  514. Botolin, S.; Faugere, M.C.; Malluche, H.; Orth, M.; Meyer, R.; McCabe, L.R. Increased bone adiposity and peroxisomal proliferator-activated receptor-gamma2 expression in type I diabetic mice. Endocrinology 2005, 146, 3622–3631. [Google Scholar] [CrossRef] [PubMed]
  515. Martin, L.M.; McCabe, L.R. Type I diabetic bone phenotype is location but not gender dependent. Histochem. Cell Biol. 2007, 128, 125–133. [Google Scholar] [CrossRef]
  516. Motyl, K.J.; Raetz, M.; Tekalur, S.A.; Schwartz, R.C.; McCabe, L.R. CCAAT/enhancer binding protein beta-deficiency enhances type 1 diabetic bone phenotype by increasing marrow adiposity and bone resorption. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2011, 300, R1250–R1260. [Google Scholar] [CrossRef]
  517. Fowlkes, J.L.; Bunn, R.C.; Liu, L.; Wahl, E.C.; Coleman, H.N.; Cockrell, G.E.; Perrien, D.S.; Lumpkin, C.K., Jr.; Thrailkill, K.M. Runt-related transcription factor 2 (RUNX2) and RUNX2-related osteogenic genes are down-regulated throughout osteogenesis in type 1 diabetes mellitus. Endocrinology 2008, 149, 1697–1704. [Google Scholar] [CrossRef]
  518. Botolin, S.; McCabe, L.R. Inhibition of PPARgamma prevents type I diabetic bone marrow adiposity but not bone loss. J. Cell Physiol. 2006, 209, 967–976. [Google Scholar] [CrossRef]
  519. Yu, E.W.; Greenblatt, L.; Eajazi, A.; Torriani, M.; Bredella, M.A. Marrow adipose tissue composition in adults with morbid obesity. Bone 2017, 97, 38–42. [Google Scholar] [CrossRef]
  520. Sheu, Y.; Amati, F.; Schwartz, A.V.; Danielson, M.E.; Li, X.; Boudreau, R.; Cauley, J.A.; The Osteoporotic Fractures in Men (MrOS) Research Group. Vertebral bone marrow fat, bone mineral density and diabetes: The Osteoporotic Fractures in Men (MrOS) study. Bone 2017, 97, 299–305. [Google Scholar] [CrossRef] [PubMed]
  521. Harslof, T.; Wamberg, L.; Moller, L.; Stodkilde-Jorgensen, H.; Ringgaard, S.; Pedersen, S.B.; Langdahl, B.L. Rosiglitazone decreases bone mass and bone marrow fat. J. Clin. Endocrinol. Metab. 2011, 96, 1541–1548. [Google Scholar] [CrossRef] [PubMed][Green Version]
  522. de Araujo, I.M.; Salmon, C.E.; Nahas, A.K.; Nogueira-Barbosa, M.H.; Elias, J., Jr.; de Paula, F.J. Marrow adipose tissue spectrum in obesity and type 2 diabetes mellitus. Eur. J. Endocrinol. 2017, 176, 21–30. [Google Scholar] [CrossRef] [PubMed]
  523. Baum, T.; Yap, S.P.; Karampinos, D.C.; Nardo, L.; Kuo, D.; Burghardt, A.J.; Masharani, U.B.; Schwartz, A.V.; Li, X.; Link, T.M. Does vertebral bone marrow fat content correlate with abdominal adipose tissue, lumbar spine bone mineral density, and blood biomarkers in women with type 2 diabetes mellitus? J. Magn. Reson. Imaging 2012, 35, 117–124. [Google Scholar] [CrossRef]
  524. Devlin, M.J.; Van Vliet, M.; Motyl, K.; Karim, L.; Brooks, D.J.; Louis, L.; Conlon, C.; Rosen, C.J.; Bouxsein, M.L. Early-onset type 2 diabetes impairs skeletal acquisition in the male TALLYHO/JngJ mouse. Endocrinology 2014, 155, 3806–3816. [Google Scholar] [CrossRef]
  525. Bornstein, S.; Moschetta, M.; Kawano, Y.; Sacco, A.; Huynh, D.; Brooks, D.; Manier, S.; Fairfield, H.; Falank, C.; Roccaro, A.M.; et al. Metformin Affects Cortical Bone Mass and Marrow Adiposity in Diet-Induced Obesity in Male Mice. Endocrinology 2017, 158, 3369–3385. [Google Scholar] [CrossRef] [PubMed]
  526. Sato, K.; Feng, X.; Chen, J.; Li, J.; Muranski, P.; Desierto, M.J.; Keyvanfar, K.; Malide, D.; Kajigaya, S.; Young, N.S. PPARgamma antagonist attenuates mouse immune-mediated bone marrow failure by inhibition of T cell function. Haematologica 2016, 101, 57–67. [Google Scholar] [CrossRef] [PubMed]
  527. Tavassoli, M.; Maniatis, A.; Crosby, W.H. Induction of sustained hemopoiesis in fatty marrow. Blood 1974, 43, 33–38. [Google Scholar] [CrossRef]
  528. Harada, K.; Yahata, T.; Onizuka, M.; Ibrahim, A.A.; Kikkawa, E.; Miyata, T.; Ando, K. Plasminogen activator inhibitor type-1 is a negative regulator of hematopoietic regeneration in the adipocyte-rich bone marrow microenvironment. Biochem. Biophys. Res. Commun. 2021, 557, 180–186. [Google Scholar] [CrossRef]
  529. Tratwal, J.; Rojas-Sutterlin, S.; Bataclan, C.; Blum, S.; Naveiras, O. Bone marrow adiposity and the hematopoietic niche: A historical perspective of reciprocity, heterogeneity, and lineage commitment. Best. Pract. Res. Clin. Endocrinol. Metab. 2021, 35, 101564. [Google Scholar] [CrossRef]
  530. Sillen, M.; Declerck, P.J. Targeting PAI-1 in Cardiovascular Disease: Structural Insights Into PAI-1 Functionality and Inhibition. Front. Cardiovasc. Med. 2020, 7, 622473. [Google Scholar] [CrossRef]
  531. Yahata, T.; Ibrahim, A.A.; Muguruma, Y.; Eren, M.; Shaffer, A.M.; Watanabe, N.; Kaneko, S.; Nakabayashi, T.; Dan, T.; Hirayama, N.; et al. TGF-beta-induced intracellular PAI-1 is responsible for retaining hematopoietic stem cells in the niche. Blood 2017, 130, 2283–2294. [Google Scholar] [CrossRef]
  532. Kaji, H. Adipose Tissue-Derived Plasminogen Activator Inhibitor-1 Function and Regulation. Compr. Physiol. 2016, 6, 1873–1896. [Google Scholar] [CrossRef]
  533. Veldhuis-Vlug, A.G.; Rosen, C.J. Mechanisms of marrow adiposity and its implications for skeletal health. Metabolism 2017, 67, 106–114. [Google Scholar] [CrossRef]
  534. Verma, S.; Rajaratnam, J.H.; Denton, J.; Hoyland, J.A.; Byers, R.J. Adipocytic proportion of bone marrow is inversely related to bone formation in osteoporosis. J. Clin. Pathol. 2002, 55, 693–698. [Google Scholar] [CrossRef] [PubMed]
  535. Justesen, J.; Stenderup, K.; Ebbesen, E.N.; Mosekilde, L.; Steiniche, T.; Kassem, M. Adipocyte tissue volume in bone marrow is increased with aging and in patients with osteoporosis. Biogerontology 2001, 2, 165–171. [Google Scholar] [CrossRef]
  536. Li, J.; Chen, X.; Lu, L.; Yu, X. The relationship between bone marrow adipose tissue and bone metabolism in postmenopausal osteoporosis. Cytokine Growth Factor. Rev. 2020, 52, 88–98. [Google Scholar] [CrossRef]
  537. Paccou, J.; Penel, G.; Chauveau, C.; Cortet, B.; Hardouin, P. Marrow adiposity and bone: Review of clinical implications. Bone 2019, 118, 8–15. [Google Scholar] [CrossRef]
  538. Woods, G.N.; Ewing, S.K.; Schafer, A.L.; Gudnason, V.; Sigurdsson, S.; Lang, T.; Hue, T.F.; Kado, D.M.; Vittinghoff, E.; Rosen, C.; et al. Saturated and Unsaturated Bone Marrow Lipids Have Distinct Effects on Bone Density and Fracture Risk in Older Adults. J. Bone Miner. Res. 2022, 37, 700–710. [Google Scholar] [CrossRef]
  539. Yeung, D.K.; Griffith, J.F.; Antonio, G.E.; Lee, F.K.; Woo, J.; Leung, P.C. Osteoporosis is associated with increased marrow fat content and decreased marrow fat unsaturation: A proton MR spectroscopy study. J. Magn. Reson. Imaging 2005, 22, 279–285. [Google Scholar] [CrossRef]
  540. Li, X.; Shet, K.; Xu, K.; Rodriguez, J.P.; Pino, A.M.; Kurhanewicz, J.; Schwartz, A.; Rosen, C.J. Unsaturation level decreased in bone marrow fat of postmenopausal women with low bone density using high resolution magic angle spinning (HRMAS) (1)H NMR spectroscopy. Bone 2017, 105, 87–92. [Google Scholar] [CrossRef] [PubMed]
  541. Fazeli, P.K.; Bredella, M.A.; Misra, M.; Meenaghan, E.; Rosen, C.J.; Clemmons, D.R.; Breggia, A.; Miller, K.K.; Klibanski, A. Preadipocyte factor-1 is associated with marrow adiposity and bone mineral density in women with anorexia nervosa. J. Clin. Endocrinol. Metab. 2010, 95, 407–413. [Google Scholar] [CrossRef] [PubMed]
  542. Yakar, S.; Rosen, C.J.; Beamer, W.G.; Ackert-Bicknell, C.L.; Wu, Y.; Liu, J.L.; Ooi, G.T.; Setser, J.; Frystyk, J.; Boisclair, Y.R.; et al. Circulating levels of IGF-1 directly regulate bone growth and density. J. Clin. Investig. 2002, 110, 771–781. [Google Scholar] [CrossRef]
  543. Conover, C.A.; Johnstone, E.W.; Turner, R.T.; Evans, G.L.; John Ballard, F.J.; Doran, P.M.; Khosla, S. Subcutaneous administration of insulin-like growth factor (IGF)-II/IGF binding protein-2 complex stimulates bone formation and prevents loss of bone mineral density in a rat model of disuse osteoporosis. Growth Horm. IGF Res. 2002, 12, 178–183. [Google Scholar] [CrossRef]
  544. Reid, I.R.; Baldock, P.A.; Cornish, J. Effects of Leptin on the Skeleton. Endocr. Rev. 2018, 39, 938–959. [Google Scholar] [CrossRef] [PubMed]
  545. Choi, H.S.; Kim, S.W.; Cho, E.H. Serum Preadipocyte Factor 1 Levels Are Not Associated with Bone Mineral Density among Healthy Postmenopausal Korean Women. Endocrinol. Metab. 2017, 32, 124–128. [Google Scholar] [CrossRef]
  546. Bredella, M.A.; Fazeli, P.K.; Freedman, L.M.; Calder, G.; Lee, H.; Rosen, C.J.; Klibanski, A. Young women with cold-activated brown adipose tissue have higher bone mineral density and lower Pref-1 than women without brown adipose tissue: A study in women with anorexia nervosa, women recovered from anorexia nervosa, and normal-weight women. J. Clin. Endocrinol. Metab. 2012, 97, E584–E590. [Google Scholar] [CrossRef]
  547. Aronis, K.N.; Kilim, H.; Chamberland, J.P.; Breggia, A.; Rosen, C.; Mantzoros, C.S. Preadipocyte factor-1 levels are higher in women with hypothalamic amenorrhea and are associated with bone mineral content and bone mineral density through a mechanism independent of leptin. J. Clin. Endocrinol. Metab. 2011, 96, E1634–E1639. [Google Scholar] [CrossRef]
  548. Hudak, C.S.; Sul, H.S. Pref-1, a gatekeeper of adipogenesis. Front. Endocrinol. 2013, 4, 79. [Google Scholar] [CrossRef] [PubMed]
  549. Cinti, S. Transdifferentiation properties of adipocytes in the adipose organ. Am. J. Physiol. Endocrinol. Metab. 2009, 297, E977–E986. [Google Scholar] [CrossRef]
  550. Morroni, M.; Giordano, A.; Zingaretti, M.C.; Boiani, R.; De Matteis, R.; Kahn, B.B.; Nisoli, E.; Tonello, C.; Pisoschi, C.; Luchetti, M.M.; et al. Reversible transdifferentiation of secretory epithelial cells into adipocytes in the mammary gland. Proc. Natl. Acad. Sci. USA 2004, 101, 16801–16806. [Google Scholar] [CrossRef] [PubMed]
  551. Giordano, A.; Smorlesi, A.; Frontini, A.; Barbatelli, G.; Cinti, S. White, brown and pink adipocytes: The extraordinary plasticity of the adipose organ. Eur. J. Endocrinol. 2014, 170, R159–R171. [Google Scholar] [CrossRef] [PubMed]
  552. Hennighausen, L.; Robinson, G.W. Information networks in the mammary gland. Nat. Rev. Mol. Cell Biol. 2005, 6, 715–725. [Google Scholar] [CrossRef]
  553. Gjorevski, N.; Nelson, C.M. Integrated morphodynamic signalling of the mammary gland. Nat. Rev. Mol. Cell Biol. 2011, 12, 581–593. [Google Scholar] [CrossRef]
  554. Stingl, J.; Eirew, P.; Ricketson, I.; Shackleton, M.; Vaillant, F.; Choi, D.; Li, H.I.; Eaves, C.J. Purification and unique properties of mammary epithelial stem cells. Nature 2006, 439, 993–997. [Google Scholar] [CrossRef]
  555. Li, L.; Li, B.; Li, M.; Niu, C.; Wang, G.; Li, T.; Król, E.; Jin, W.; Speakman, J.R. Brown adipocytes can display a mammary basal myoepithelial cell phenotype in vivo. Mol. Metab. 2017, 6, 1198–1211. [Google Scholar] [CrossRef]
  556. Hovey, R.C.; Trott, J.F. Morphogenesis of mammary gland development. Adv. Exp. Med. Biol. 2004, 554, 219–228. [Google Scholar] [CrossRef] [PubMed]
  557. Richert, M.M.; Schwertfeger, K.L.; Ryder, J.W.; Anderson, S.M. An atlas of mouse mammary gland development. J. Mammary Gland. Biol. Neoplasia 2000, 5, 227–241. [Google Scholar] [CrossRef] [PubMed]
  558. Robinson, G.W.; McKnight, R.A.; Smith, G.H.; Hennighausen, L. Mammary epithelial cells undergo secretory differentiation in cycling virgins but require pregnancy for the establishment of terminal differentiation. Development 1995, 121, 2079–2090. [Google Scholar] [CrossRef]
  559. Giordano, A.; Perugini, J.; Kristensen, D.M.; Sartini, L.; Frontini, A.; Kajimura, S.; Kristiansen, K.; Cinti, S. Mammary alveolar epithelial cells convert to brown adipocytes in post-lactating mice. J. Cell Physiol. 2017, 232, 2923–2928. [Google Scholar] [CrossRef]
  560. Warren, J.L.; Warren, J.S. The Case for Understanding Interdisciplinary Relationships in Health Care. Ochsner J. 2023, 23, 94–97. [Google Scholar] [CrossRef]
  561. Wang, J.Y.; Wang, Q.W.; Yang, X.Y.; Yang, W.; Li, D.R.; Jin, J.Y.; Zhang, H.C.; Zhang, X.F. GLP-1 receptor agonists for the treatment of obesity: Role as a promising approach. Front. Endocrinol. 2023, 14, 1085799. [Google Scholar] [CrossRef]
  562. Jensterle, M.; Rizzo, M.; Haluzik, M.; Janez, A. Efficacy of GLP-1 RA Approved for Weight Management in Patients With or Without Diabetes: A Narrative Review. Adv. Ther. 2022, 39, 2452–2467. [Google Scholar] [CrossRef]
  563. Iorga, R.A.; Bacalbasa, N.; Carsote, M.; Bratu, O.G.; Stanescu, A.M.A.; Bungau, S.; Pantis, C.; Diaconu, C.C. Metabolic and cardiovascular benefits of GLP-1 agonists, besides the hypoglycemic effect (Review). Exp. Ther. Med. 2020, 20, 2396–2400. [Google Scholar] [CrossRef]
  564. Sposito, A.C.; Berwanger, O.; de Carvalho, L.S.F.; Saraiva, J.F.K. GLP-1RAs in type 2 diabetes: Mechanisms that underlie cardiovascular effects and overview of cardiovascular outcome data. Cardiovasc. Diabetol. 2018, 17, 157. [Google Scholar] [CrossRef] [PubMed]
  565. Tanday, N.; Flatt, P.R.; Irwin, N. Metabolic responses and benefits of glucagon-like peptide-1 (GLP-1) receptor ligands. Br. J. Pharmacol. 2022, 179, 526–541. [Google Scholar] [CrossRef]
  566. Hropot, T.; Herman, R.; Janez, A.; Lezaic, L.; Jensterle, M. Brown Adipose Tissue: A New Potential Target for Glucagon-like Peptide 1 Receptor Agonists in the Treatment of Obesity. Int. J. Mol. Sci. 2023, 24, 8592. [Google Scholar] [CrossRef]
  567. Beiroa, D.; Imbernon, M.; Gallego, R.; Senra, A.; Herranz, D.; Villarroya, F.; Serrano, M.; Fernø, J.; Salvador, J.; Escalada, J.; et al. GLP-1 agonism stimulates brown adipose tissue thermogenesis and browning through hypothalamic AMPK. Diabetes 2014, 63, 3346–3358. [Google Scholar] [CrossRef]
  568. Zhao, L.; Zhu, C.; Lu, M.; Chen, C.; Nie, X.; Abudukerimu, B.; Zhang, K.; Ning, Z.; Chen, Y.; Cheng, J.; et al. The key role of a glucagon-like peptide-1 receptor agonist in body fat redistribution. J. Endocrinol. 2019, 240, 271–286. [Google Scholar] [CrossRef]
  569. Zhao, L.; Li, W.; Zhang, P.; Wang, D.; Yang, L.; Yuan, G. Liraglutide induced browning of visceral white adipose through regulation of miRNAs in high-fat-diet-induced obese mice. Endocrine 2024, 85, 222–232. [Google Scholar] [CrossRef]
  570. Xu, F.; Lin, B.; Zheng, X.; Chen, Z.; Cao, H.; Xu, H.; Liang, H.; Weng, J. GLP-1 receptor agonist promotes brown remodelling in mouse white adipose tissue through SIRT1. Diabetologia 2016, 59, 1059–1069. [Google Scholar] [CrossRef] [PubMed]
  571. Kulterer, O.C.; Herz, C.T.; Prager, M.; Schmöltzer, C.; Langer, F.B.; Prager, G.; Marculescu, R.; Kautzky-Willer, A.; Hacker, M.; Haug, A.R.; et al. Brown Adipose Tissue Prevalence Is Lower in Obesity but Its Metabolic Activity Is Intact. Front. Endocrinol. 2022, 13, 858417. [Google Scholar] [CrossRef] [PubMed]
  572. Ziqubu, K.; Dludla, P.V.; Mthembu, S.X.H.; Nkambule, B.B.; Mabhida, S.E.; Jack, B.U.; Nyambuya, T.M.; Mazibuko-Mbeje, S.E. An insight into brown/beige adipose tissue whitening, a metabolic complication of obesity with the multifactorial origin. Front. Endocrinol. 2023, 14, 1114767. [Google Scholar] [CrossRef]
  573. Gorgojo-Martinez, J.J.; Mezquita-Raya, P.; Carretero-Gomez, J.; Castro, A.; Cebrian-Cuenca, A.; de Torres-Sanchez, A.; Garcia-de-Lucas, M.D.; Nunez, J.; Obaya, J.C.; Soler, M.J.; et al. Clinical Recommendations to Manage Gastrointestinal Adverse Events in Patients Treated with Glp-1 Receptor Agonists: A Multidisciplinary Expert Consensus. J. Clin. Med. 2022, 12, 145. [Google Scholar] [CrossRef] [PubMed]
  574. Bettge, K.; Kahle, M.; Abd El Aziz, M.S.; Meier, J.J.; Nauck, M.A. Occurrence of nausea, vomiting and diarrhoea reported as adverse events in clinical trials studying glucagon-like peptide-1 receptor agonists: A systematic analysis of published clinical trials. Diabetes Obes. Metab. 2017, 19, 336–347. [Google Scholar] [CrossRef]
  575. Samms, R.J.; Coghlan, M.P.; Sloop, K.W. How May GIP Enhance the Therapeutic Efficacy of GLP-1? Trends Endocrinol. Metab. 2020, 31, 410–421. [Google Scholar] [CrossRef]
  576. Baggio, L.L.; Drucker, D.J. Glucagon-like peptide-1 receptor co-agonists for treating metabolic disease. Mol. Metab. 2021, 46, 101090. [Google Scholar] [CrossRef]
  577. Borner, T.; Geisler, C.E.; Fortin, S.M.; Cosgrove, R.; Alsina-Fernandez, J.; Dogra, M.; Doebley, S.; Sanchez-Navarro, M.J.; Leon, R.M.; Gaisinsky, J.; et al. GIP Receptor Agonism Attenuates GLP-1 Receptor Agonist-Induced Nausea and Emesis in Preclinical Models. Diabetes 2021, 70, 2545–2553. [Google Scholar] [CrossRef]
  578. Fisman, E.Z.; Tenenbaum, A. The dual glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist tirzepatide: A novel cardiometabolic therapeutic prospect. Cardiovasc. Diabetol. 2021, 20, 225. [Google Scholar] [CrossRef] [PubMed]
  579. Coskun, T.; Sloop, K.W.; Loghin, C.; Alsina-Fernandez, J.; Urva, S.; Bokvist, K.B.; Cui, X.; Briere, D.A.; Cabrera, O.; Roell, W.C.; et al. LY3298176, a novel dual GIP and GLP-1 receptor agonist for the treatment of type 2 diabetes mellitus: From discovery to clinical proof of concept. Mol. Metab. 2018, 18, 3–14. [Google Scholar] [CrossRef] [PubMed]
  580. Scheen, A.J. Dual GIP/GLP-1 receptor agonists: New advances for treating type-2 diabetes. Ann. Endocrinol. 2023, 84, 316–321. [Google Scholar] [CrossRef]
  581. Dowker-Key, P.D.; Jadi, P.K.; Gill, N.B.; Hubbard, K.N.; Elshaarrawi, A.; Alfatlawy, N.D.; Bettaieb, A. A Closer Look into White Adipose Tissue Biology and the Molecular Regulation of Stem Cell Commitment and Differentiation. Genes 2024, 15, 1017. [Google Scholar] [CrossRef] [PubMed]
  582. Bluher, M. Metabolically Healthy Obesity. Endocr. Rev. 2020, 41, bnaa004. [Google Scholar] [CrossRef]
  583. Gomez-Garcia, I.; Trepiana, J.; Fernandez-Quintela, A.; Giralt, M.; Portillo, M.P. Sexual Dimorphism in Brown Adipose Tissue Activation and White Adipose Tissue Browning. Int. J. Mol. Sci. 2022, 23, 8250. [Google Scholar] [CrossRef]
  584. Bloor, I.D.; Symonds, M.E. Sexual dimorphism in white and brown adipose tissue with obesity and inflammation. Horm. Behav. 2014, 66, 95–103. [Google Scholar] [CrossRef]
Figure 1. Limitations of Current Approaches to Treat Obesity. The first-line approach to obesity management involves lifestyle modifications, such as adopting low-calorie diets and increasing physical activity, which can achieve weight loss and improve health outcomes [40,41,42,43,44,45,46,47]. However, their effectiveness is often limited by adherence challenges. Pharmacotherapy is recommended for those who do not meet weight loss goals through lifestyle changes alone and is typically used in combination to enhance appetite control and satiety [48,49]. Despite its benefits, drug therapy is often constrained by side effects and safety concerns [50,51,52]. Bariatric surgery, reserved for individuals with severe obesity (BMI ≥40 kg/m2), can significantly improve metabolic and cardiovascular parameters but carries postoperative risks and limited eligibility [53,54]. Given these constraints, emerging strategies such as advanced DDSs aim to enhance therapeutic efficacy and minimize adverse effects, though issues of safety and efficacy remain [55]. Created in BioRender. Dowker, P. (2026) https://BioRender.com/r25o517 (Accessed on 10 February 2026). Footnotes and abbreviations: Body mass index (BMI); Drug delivery systems (DDSs); Food and Drug Administration (FDA); Lorcaserin (Belviq XR).
Figure 1. Limitations of Current Approaches to Treat Obesity. The first-line approach to obesity management involves lifestyle modifications, such as adopting low-calorie diets and increasing physical activity, which can achieve weight loss and improve health outcomes [40,41,42,43,44,45,46,47]. However, their effectiveness is often limited by adherence challenges. Pharmacotherapy is recommended for those who do not meet weight loss goals through lifestyle changes alone and is typically used in combination to enhance appetite control and satiety [48,49]. Despite its benefits, drug therapy is often constrained by side effects and safety concerns [50,51,52]. Bariatric surgery, reserved for individuals with severe obesity (BMI ≥40 kg/m2), can significantly improve metabolic and cardiovascular parameters but carries postoperative risks and limited eligibility [53,54]. Given these constraints, emerging strategies such as advanced DDSs aim to enhance therapeutic efficacy and minimize adverse effects, though issues of safety and efficacy remain [55]. Created in BioRender. Dowker, P. (2026) https://BioRender.com/r25o517 (Accessed on 10 February 2026). Footnotes and abbreviations: Body mass index (BMI); Drug delivery systems (DDSs); Food and Drug Administration (FDA); Lorcaserin (Belviq XR).
Ijms 27 01925 g001
Figure 2. Relevance of yellow adipose tissue. YAT, also referred to as BMAT or MAT, is an emerging adipose tissue type under investigation due to its proposed impact on human health and disease [472,473]. In panel (A), we briefly summarize the maturation of premature yellow adipose from multipotent stem cells (MSCs) to fully differentiated yellow adipocytes. In panels (B,C), both the beneficial [469,474,475,476,477,478,479,480] and pathological [481,482,483,484,485,486] effects of YAT are outlined. Created in BioRender. Dowker, P. (2026) https://BioRender.com/f40i747 (Accessed on 10 February 2026). Footnotes & abbreviations: Bone marrow adipose tissue (BMAT), CCAAT/enhancer-binding protein beta (C/EBPβ), CCAAT/enhancer-binding protein delta (C/EBPδ), cluster of differentiation 24 (CD24), cluster of differentiation 31 (CD31; platelet endothelial cell adhesion molecule-1 or PECAM-1), cluster of differentiation 45 (CD45; leukocyte common antigen), C-X-C motif chemokine ligand 1 (CXCL1; keratinocyte chemoattractant in mice), C-X-C motif chemokine ligand 2 (CXCL2; macrophage inflammatory protein-2 or MIP-2 in mice), mesenchymal stem cell (MSC), peroxisome proliferator-activated receptor gamma (PPARγ), preadipocyte factor 1 (PREF-1; also known as DLK1), receptor activator of nuclear factor kappa-B ligand (RANKL), stem cell antigen 1 (SCA1; Ly6A/E in mice), zinc finger protein 423 (Zfp423).
Figure 2. Relevance of yellow adipose tissue. YAT, also referred to as BMAT or MAT, is an emerging adipose tissue type under investigation due to its proposed impact on human health and disease [472,473]. In panel (A), we briefly summarize the maturation of premature yellow adipose from multipotent stem cells (MSCs) to fully differentiated yellow adipocytes. In panels (B,C), both the beneficial [469,474,475,476,477,478,479,480] and pathological [481,482,483,484,485,486] effects of YAT are outlined. Created in BioRender. Dowker, P. (2026) https://BioRender.com/f40i747 (Accessed on 10 February 2026). Footnotes & abbreviations: Bone marrow adipose tissue (BMAT), CCAAT/enhancer-binding protein beta (C/EBPβ), CCAAT/enhancer-binding protein delta (C/EBPδ), cluster of differentiation 24 (CD24), cluster of differentiation 31 (CD31; platelet endothelial cell adhesion molecule-1 or PECAM-1), cluster of differentiation 45 (CD45; leukocyte common antigen), C-X-C motif chemokine ligand 1 (CXCL1; keratinocyte chemoattractant in mice), C-X-C motif chemokine ligand 2 (CXCL2; macrophage inflammatory protein-2 or MIP-2 in mice), mesenchymal stem cell (MSC), peroxisome proliferator-activated receptor gamma (PPARγ), preadipocyte factor 1 (PREF-1; also known as DLK1), receptor activator of nuclear factor kappa-B ligand (RANKL), stem cell antigen 1 (SCA1; Ly6A/E in mice), zinc finger protein 423 (Zfp423).
Ijms 27 01925 g002
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Dowker-Key, P.D.; Jadi, P.K.; Alfatlawi, R.; Giannone, R.J.; Bettaieb, A. Reexamining Fat: Exploring Diversity, Plasticity, Development, Functional Implication, and Therapeutic Options. Int. J. Mol. Sci. 2026, 27, 1925. https://doi.org/10.3390/ijms27041925

AMA Style

Dowker-Key PD, Jadi PK, Alfatlawi R, Giannone RJ, Bettaieb A. Reexamining Fat: Exploring Diversity, Plasticity, Development, Functional Implication, and Therapeutic Options. International Journal of Molecular Sciences. 2026; 27(4):1925. https://doi.org/10.3390/ijms27041925

Chicago/Turabian Style

Dowker-Key, Presley D., Praveen Kumar Jadi, Rawon Alfatlawi, Richard J. Giannone, and Ahmed Bettaieb. 2026. "Reexamining Fat: Exploring Diversity, Plasticity, Development, Functional Implication, and Therapeutic Options" International Journal of Molecular Sciences 27, no. 4: 1925. https://doi.org/10.3390/ijms27041925

APA Style

Dowker-Key, P. D., Jadi, P. K., Alfatlawi, R., Giannone, R. J., & Bettaieb, A. (2026). Reexamining Fat: Exploring Diversity, Plasticity, Development, Functional Implication, and Therapeutic Options. International Journal of Molecular Sciences, 27(4), 1925. https://doi.org/10.3390/ijms27041925

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop