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On the Role of Paraoxonase-1 and Chemokine Ligand 2 (C-C motif) in Metabolic Alterations Linked to Inflammation and Disease. A 2021 Update

Jordi Camps
Helena Castañé
Elisabet Rodríguez-Tomàs
Gerard Baiges-Gaya
Anna Hernández-Aguilera
Meritxell Arenas
Simona Iftimie
3 and
Jorge Joven
Unitat de Recerca Biomèdica, Hospital Universitari de Sant Joan, Institut d’Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43201 Reus, Spain
Department of Radiation Oncology, Hospital Universitari de Sant Joan, Institut d’Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43201 Reus, Spain
Department of Internal Medicine, Hospital Universitari de Sant Joan, Institut d’Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43201 Reus, Spain
Authors to whom correspondence should be addressed.
Biomolecules 2021, 11(7), 971;
Submission received: 31 May 2021 / Revised: 23 June 2021 / Accepted: 29 June 2021 / Published: 1 July 2021
(This article belongs to the Special Issue Chemokines in Infectious and Non-infectious Diseases)


Infectious and many non-infectious diseases share common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins, and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, both produce metabolic alterations that influence the pathogenesis of the disease. In this review, we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, inducing migration and infiltration of immune cells in target tissues and disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.

1. Oxidation, Inflammation and Disease

Tissues produce reactive oxygen species (ROS) as a metabolic by-product in response to environmental factors such as an imbalanced diet or an infectious process. ROS react with lipids, proteins, and nucleic acids and result in alterations in cell structure and function [1]. The organism has enzymatic and non-enzymatic antioxidants to block the harmful effects of ROS. However, these protective systems can be overwhelmed in disease states. An inflammatory reaction is generated when oxidative equilibrium is disrupted. For example, in infectious diseases, ROS production by host macrophages is an important part of the defense mechanism against infecting bacteria or viruses, and the imbalances produced can trigger an inflammatory reaction [2]. In turn, inflammation can lead to a further increase in oxidative stress and thus enter a vicious cycle that can aggravate the disease [3,4]. Independently of whether oxidative stress and inflammation represent the causes or the consequences of cellular alterations, an overwhelming amount of evidence indicates that both processes contribute to the pathogenesis of many diseases. The role played by macrophages and their polarization need to be considered in detail in the setting of chronic inflammatory diseases [5]. These diseases are associated with an increase in M1, or “classically activated” macrophages, and a decrease in M2, or “alternatively activated” macrophages [6,7,8]. Chemokines are involved in macrophage polarization, while directing the traffic of immune cells to sites of inflammation and activating the production and secretion of inflammatory cytokines [9]. Monocytes migrate to the site of inflammation and differentiate into macrophages when the chemokine (C-C motif) receptor (CCR2) interacts with the chemokine (C-C motif) ligand 2 (CCL2): a key process in the development of inflammatory diseases [10]. Recent studies indicate that other chemokines and chemokine receptors also play important roles. For example, the CCL5/CCR5 complex has been related to cancer and infection [11,12,13,14].

2. Paraoxonase-1 Is an Antioxidant Enzyme That Participates in the Innate Immune System

Paraoxonase-1 (PON1) belongs to an enzyme family composed of three members (PON1, PON2, and PON3), which are the protein products of a gene that evolved by duplication of a common precursor. They have high structural homology with each other [15,16], and the three genes are located in adjacent positions of chromosome 7 (7q21.3) [15,16]. PON1 is a lactonase and an esterase that catalyzes the hydrolysis of thiolactones, organophosphate esters, unsaturated aliphatic esters, aromatic carboxylic esters, and carbamates [17,18]. PON2 and PON3 do not degrade esters but have lactonase activity [19]. PON1 and PON3 degrade lipid peroxides in low-density lipoproteins (LDL) and high-density lipoproteins (HDL) [19]. In humans, PON1 and PON3 are mainly synthesized by the liver, and the enzymes are found in blood bound to HDL [20,21,22]. The enzymatic action of PON1 is exerted in the circulation within HDL particles, but they can also be transported from these particles to the cell membranes [23], especially of epithelial and endothelial cells [24,25,26]. Conversely, PON2 gene expression is exclusively intracellular [27].
In addition to degrading oxidized lipids, PON1 inhibits CCL2 synthesis [28,29]. In vitro treatment of oxidized LDL with purified PON1 reduces the degree of lipid oxidation and the ability of this lipoprotein to induce interactions between monocyte and endothelial cells [30]. Further experimental studies have shown that HDL particles obtained from PON1 deficient mice lacked the ability to protect LDL from peroxidation [31], and that PON1 and apolipoprotein-E double deficient mice had higher levels of lipid peroxidation products in vivo than the animals that were deficient in apolipoprotein-E alone [32].
PON1 can also protect the organism from bacterial biofilm formation through its lactonase activity [33]. A biofilm is an aggregation of bacteria, embedded within a matrix of polysaccharides, proteins, and DNA. Being embedded within biofilms provides bacteria with protection and, by developing antibiotic resistance, can make successful treatment difficult [34,35,36]. Quorum sensing is essential for the formation of biofilms. This phenomenon is defined as the coordination of bacterial behavior through the accumulation of signaling molecules, i.e., when the concentrations of signaling molecules reach a critical threshold, the result is modulation of certain target genes that trigger the formation of biofilms [37]. In Gram-negative bacteria, N-acyl-homoserine lactones (AHL) have been identified as the major signaling molecules in this communication system [38,39,40]. Considerable evidence suggests that PON1 plays an important role against biofilm formation. Lung epithelial cells and resident macrophages are important defense mechanisms against airborne microorganisms. PON1 protein is strongly expressed in lung epithelial cells and, as described above, it has lactonase activity [25,26]. Thus, it seems logical to infer that PON1 is able to hydrolyze AHL and interrupt quorum sensing signals. This hypothesis was demonstrated by investigators who found that a lactonase present in lung epithelial cells inactivates 3-oxo-C12-AHL [41,42,43,44]. These researchers also reported that wild-type mouse serum, rich in PON1, degraded 3-oxo-C12-AHL and decreased P. aeruginosa biofilm formation, and that this capacity was lost when serum from PON1 deficient mice was employed instead. In addition, adding purified PON1 to serum from PON1 deficient mice restored the ability to degrade 3-oxo-C12-AHL and inhibited biofilm growth [44]. These data demonstrate that PON1 efficiently degrades 3-oxo-C12-AHL and reduces the growth of bacterial biofilms. Currently, it is widely accepted that PON1 is an enzyme with multiple hydrolytic capacities causing lipoperoxide degradation and counteracting oxidative stress in the circulation and within cells. PON1 also inhibits the synthesis of CCL2 and the subsequent inflammatory reaction, and protects against the formation of bacterial biofilms. Overall, these results indicate that PON1 can be considered part of the organism’s innate immunity system [45].

3. The Protective Role of Paraoxonases on CCL2 Expression, Mitochondrial Function, and Metabolism

Several lines of research suggest that the PON family of enzymes play a prominent role in the protection of cells against mitochondrial dysfunction and metabolic alterations. Most studies in this field have been conducted on PON2 because the general consensus is that this is the major intracellular enzyme. For example, PON2 has been reported to reduce the unfolded protein response (UPR) accompanying oxidative stress and UPR-derived caspase activation in human vascular cells [27,46,47]. In addition, the expression of genes related to endoplasmic reticulum stress was increased in macrophages from apolipoprotein E and PON2 double deficient mice, compared to those that were only apolipoprotein E -deficient [48]. These authors observed that treatment of macrophages from apolipoprotein E and PON2 double deficient mice with an inducer of endoplasmic reticulum stress resulted in mitochondrial dysfunction, increased oxidative stress, and increased cell apoptosis. Further studies in several experimental models have added more evidence that PON2 protects mitochondrial function and prevents apoptosis [49,50,51].
From the above-mentioned data, it is inferred that PON2 does indeed play a protective role in mitochondrial function, but this is not so clear regarding PON1. Data suggest that this enzyme also protects cells from oxidation, and that this effect involves the inhibition of CCL2 synthesis. Studies from our research group have shown that PON1 deficient mice fed an atherogenic diet had increased hepatic fat depots and a marked depression of the tricarboxylic acid (TCA) cycle. In addition, the hepatic concentrations of several markers of oxidative stress and CCL2 expression were increased [52]. Further experimental data [53] showed that dietary fat caused liver steatosis, oxidative stress, and the accumulation of pro-inflammatory macrophages in the livers of LDL-receptor and PON1 double deficient mice, together with alterations in energy metabolism, in the methionine cycle, in the glutathione reduction pathway, and autophagy. Conversely, when we established a line of LDL-receptor, PON1, and CCL2 triple deficient mice, we observed that the deletion of this chemokine normalized the metabolic disturbances and increased lysosome-associated membrane protein 2 expression, which suggests enhanced chaperone-mediated autophagy. In humans, studies have observed that individuals with obesity have impaired PON1 activity and impaired mitochondrial function [54,55]. Our group has a special interest in evaluating the hepatic alterations in patients with morbid obesity treated with bariatric surgery and, as well, in observing the metabolic effects of the treatment. To date, results have shown that one-year post-surgery, the hepatic histology of all patients was improved, especially in those who had severe steatohepatitis, bridging fibrosis, and/or cirrhosis. Additionally, we observed pre-surgery differences in plasma and liver markers of oxidative stress and inflammation (including CCL2 and PON1), which were corrected one-year post-surgery [56]. In addition, patients with steatohepatitis presented pre-surgery alterations in energy metabolism, especially in plasma concentrations of α-ketoglutarate and oxaloacetate, which reverted one-year post-surgery [57]. Overall, these results suggest an entanglement of PON1 and CCL2 in the regulation of metabolism and mitochondrial function in the liver of experimental animals, and in humans (Figure 1).

4. Mechanism of Action of CCL2 in the Immune Response and Inflammation and Its Relationship with Multiple Metabolic Alterations

One of the proposed mechanisms by which oxidative stress would enhance the inflammatory response is the induction and assembly of multiprotein complexes called inflammasomes. ROS activate the NOD-like receptor Pyrin domain 3 (NLRP3) in macrophages, triggering the formation of inflammasomes and an immune reaction that involves the synthesis of pro-inflammatory chemokines, from which CCL2 is, probably, the most representative [58,59,60,61]. This chemokine is upregulated following tissue injury and is expressed by both inflammatory and stromal cells. CCL2 has been reported to promote endoplasmic reticulum (ER) stress and autophagy and to regulate NF-ĸB expression by catalyzing de-ubiquitination [62]. The main pathway triggering inflammation is, probably, the activation of pattern-recognition receptors (PRRs), which recognize pathogen-associated molecular patterns (PAMPs), synthesized as a response to pathogens, or damage-associated molecular patterns (DAMPs), which are products of damaged cells [63,64,65]. The binding of PAMP/DAMP to a PRR leads to NF-ĸB activation and the production of adhesion molecules and chemokines that lead to infiltration of immune cells into the sites of tissue damage [66]. Other alternative pathways also result in similar outcomes, particularly the phosphoinositide 3-kinase-related signaling pathway, the mitogen-activated protein kinase pathway, and the Janus kinase/signal transducers and activators of transcription signaling pathway [67,68,69]. These changes induce the UPR, essentially by three ER-related transmembrane proteins, i.e., the inositol-requiring enzyme 1, the protein kinase RNA-like endoplasmic reticulum kinase, and the activating transcription factor 6 [70,71,72,73]. CCL2 and other chemokines, together with oxidative stress, trigger ER stress. In addition, the UPR may regulate inflammation through several pathways, such as the regulation of oxidative stress or the upregulation of CCR2 expression [74]; the UPR links ER stress with cell death and autophagy [75]. When cell damage is moderate, autophagy helps cells survive the injury, allowing them to heal and thus preventing cell death by removing toxic protein aggregates. However, when cell damage is high, the result is a non-apoptotic form of cell death that can be detrimental. The role of autophagy in the maintenance of mitochondrial integrity seems to be paramount [76]. Mitophagy increases cell lifespan, while repression of autophagy reduces lifespan. Several studies have linked mitochondrial dysfunction, autophagy, and age-related diseases with the activity of the inflammasomes [77,78,79,80]. Taken together, these results define a clear relationship between oxidative stress, chemokines, and mitochondrial impairment, resulting in metabolic alterations and their involvement in diseases.
Activation of the immune response and chronic inflammation has been associated with aging and age-related diseases [81,82,83]. Senescent cells secrete chemokines, which influence the trafficking of immune cells [84,85]. Epidemiological studies have suggested that CCL2 levels are increased in older individuals, independently of metabolic alterations. Moreover, in vitro studies have shown that chemokines appear to confer senescence to neighboring normal cells in an autocrine and paracrine fashion [86,87,88]. A recent study by our research group in mice with accelerated aging is a good example of such relationships [89]. We crossbred mice that overexpressed CCL2 with progeroid mice bearing a mutation in the lamin A gene. Wild-type animals and progeroid mice not overexpressing CCL2 were used as controls. We observed that progeroid mice lost weight (relative to the wild-type animals) and developed lordokyphosis and lipodystrophy. The lifespan was significantly reduced in both strains of progeroid mice, but this reduction was higher in those overexpressing CCL2. These mice also presented specific characteristics of metabolic dysregulation in skeletal muscle, including alterations in the glucose and TCA cycles, and in one-carbon metabolism. These data suggest that mitochondrial metabolites play major roles in pathological aging. Consequently, we investigated the mitochondrial respiratory complexes in skeletal muscle, and observed that the expressions of complexes I and V were lower in mice overexpressing CCL2. In addition, the protein concentrations of translocase of outer membrane 20 (TOM20) and mitofusin 2 (MFN2) in the muscles of the progeroid mice were decreased, indicating alterations in the correct formation of the mitochondrial network. We also observed an increase in p53, which would indicate the triggering of aging through a p53-mediated transcriptional program involving the mechanistic target of rapamycin. Indeed, we found inhibition of phosphorylation of phosphoinositide 3-kinase, indicating a mechanistic target of rapamycin inhibition. Finally, the higher microtubule-associated proteins 1A/1B light chain 3B (LC3) II/I ratio, and lower lysosome-associated membrane protein 2 (LAMP2A) and sequestosome 1 (p62) expressions suggested the involvement of chaperone-mediated autophagy as a consequence of the CCL2 overexpression in the progeroid animals.
Following on from the actions described above, in many infectious and non-infectious diseases, the adaptive immunity deteriorates, whereas the innate immunity is more responsive to stimuli; the consequence is the development of an inflammatory reaction. Several studies have linked the activation of NLRP3, which is dependent on increased generation of free radical species by mitochondria, with metabolic disturbances [90,91,92]. Hence, it is of note that awareness of the origin of free radicals and the putative mechanisms of prevention (i.e., PON1) is critical when establishing possible therapeutic interventions in order to preempt an inflammatory reaction. Within this context, the interaction of PON1 with CCL2 can play a key role.
In the following sections we summarize the current knowledge on the roles that PON1, CCL2, and metabolic alterations play in some of the more frequently-occurring diseases.

5. Obesity and the Associated Liver Disease

The prevalence of obesity has increased in recent decades, and the phenomenon constitutes a serious health problem worldwide [93]. Non-alcoholic fatty liver disease (NAFLD) is an important comorbidity of obesity. The most severe form of NAFLD is non-alcoholic steatohepatitis (NASH), which is often the main clinical reason for liver transplantation [94]. Excessive and unbalanced nutrient intake is a fundamental contributor to obesity, and related metabolic liver disease. Several mechanisms have been proposed to explain the metabolic alterations resulting from excessive food consumption and obesity. The capacity of adipose tissue to store and process lipids is limited and, when this limit is exceeded, adipocytes exhibit several signs of stress linked to metabolic dysfunction. Among these factors are: free radical production, mechanical stress, ER stress, hypoxia, mitochondrial dysfunction, altered chemokine and adipokine signaling, and inflammation [95,96]. Altered concentrations of circulating cytokines and chemokines are strongly associated with obesity [97,98,99,100,101]. In obese mice, all cell types within adipose tissue could, potentially, secrete cytokines. Increased expression of inflammatory mediators has been observed in the visceral fat of individuals with obesity [102,103]. Other metabolic tissues, apart from adipose tissue, contribute to the severity of the disease and, in consequence, to macrophage trafficking and infiltration mediated by chemokines [99,104,105]. Generally, the concept of abnormal nutrient intake should consider not only the total amount of calories consumed, but also their quality. Recently we reported that normal mice fed a high-fat diet develop hepatic steatosis, but if they were fed an isocaloric diet rich in fat and sucrose they developed NASH [106]. This derangement was accompanied by oxidative stress and an increase in the hepatic expression of CCL2. Additionally, we observed alterations in the TCA cycle, glycolysis, and amino acid and pentose-phosphate pathways in the liver, as well as an increase in autophagy. We concluded that, overall, the addition of sucrose to a high-fat diet promotes an oxidative and inflammatory environment, and also negates the ability to restore damaged hepatic mitochondria.
Abdominal obesity, whether in adults or children, is a risk factor for metabolic syndrome and, within which, is the reduction if serum PON1 activity [107,108], while exercise increases the activity [109,110,111]. In sedentary children and adolescents with obesity, we found that decreased PON1 activities were associated with hyperinsulinemia and insulin resistance, as well as higher triglycerides and lower HDL-cholesterol concentrations. This suggested that PON1 may be involved in the metabolic alterations leading to the future development of diabetes mellitus and/or cardiovascular disease [107]. Serum PON1 activity is low in chronic liver diseases [112]. Oxidative stress and decreased PON1 activity result in an increased production of pro-inflammatory cytokines such as CCL2 and tumor necrosis factor-α (TNF-α) [112]. In patients with liver impairment, the circulating levels of these cytokines correlate with the severity of the hepatic inflammation [113,114], while the pharmacological inhibition of CCL2 results in improved liver function [115]. The role of CCL2 in the development of liver disease is schematized in Figure 2.
In humans, body mass index correlates well with adipose tissue CCL2 expression [116,117]. CCL2 has been suggested to influence the function of adipocytes and to be the link between adipose tissue inflammation, insulin resistance, and liver impairment [99,118,119]. The inflammatory reaction induced by CCL2 could contribute to deterioration of cell homeostasis and energy requirements in metabolic organs [53,118]. A recent study reported that the overexpression of CCL2 in mice was associated with increased liver and decreased muscle weights and, as such, mimicked a phenotype frequently found in obesity, liver disease, and aging [120]. The animals also displayed distinct alterations in the liver and muscles, including concentrations of metabolites from energy and one-carbon metabolism, mitochondrial fusion, and autophagy. The study concluded that mice overexpressing CCL2 had an anabolic profile in the liver, with decoupling of oxidative phosphorylation components, and alterations in mitochondrial fusion; a phenomenon related to liver disease [121,122]. Of note is that skeletal muscle had a different, catabolic, profile, with increased expression of oxidative phosphorylation components and increased levels of lactate and ketone bodies, without alterations in mitochondrial fusion markers.
Bariatric surgery is a common treatment in patients with morbid obesity, and offers a unique opportunity to investigate the metabolic derangements associated with NAFLD, especially when comparing the data obtained from a peri-surgical liver biopsy with those obtained from a percutaneous biopsy obtained post-surgery [123]. Recent results from our research group [124,125,126,127] showed that, one year post-bariatric surgery (laparoscopic sleeve gastrectomy), the prevalence of diabetes, hypertension, and NAFLD significantly decreased in patients with pre-surgery morbid obesity; the improvements in hepatic histology and function were greater in patients with NASH. We found significant pre-surgery differences in liver markers of oxidative stress and inflammation (including CCL2 and PON1) between patients with, and those without, NASH, which suggested a regulatory role of mitogen-activated protein kinases. In addition, we observed an alteration in the mitochondrial function associated with a dysregulation of glutaminolysis and increased hepatic and plasma concentrations of α-ketoglutarate. Bariatric surgery was associated with consistent improvements in these parameters. These changes influenced the adenosine monophosphate-activated protein kinase/mammalian target of the rapamycin-driven pathways that modulated hepatocyte survival by coordinating apoptosis and autophagy. Finally, we reported that α-ketoglutarate and the associated metabolites affected methylation-related epigenomic remodeling enzymes. Integrative analysis of hepatic transcriptome signatures and differentially-methylated genomic regions distinguished patients with NASH from those without.

6. Cardiovascular Diseases

Atherosclerosis and cardiovascular diseases (CVD) are closely associated with obesity [128]. Perivascular inflammation plays a major role in the onset and development of atherosclerosis [129,130]. Indeed, experimental studies in apolipoprotein E-deficient mice reported that perivascular inflammation precedes oxidative stress and endothelial dysfunction [129]. This experimental model is characterized by increased production of chemokines such as CCL2 [131], macrophage inflammatory protein 1-α (MIP-1α or CCL3), and CCL5 [132]. A considerable body of evidence indicates that activation of the CCL2/CCR2 axis is important in the pathogenesis of atherosclerosis [133,134]. Lipid peroxides, interleukins, angiotensin II, homocysteine, activated platelets, and shear stress, among other mediators of atherosclerosis, induce CCL2 synthesis and secretion by endothelial cells and smooth muscle cells [134]. Increased CCL2 expression has been found in macrophage-rich atherosclerotic lesions [135]. Moreover, in autopsy-derived arterial specimens from patients, CCL2 was shown to be present in the early phases of atherosclerosis; the suggestion being that this chemokine contributes to the early influx of monocytes into the vessel wall [136]. In human carotid endarterectomy specimens, a high CCL2 expression was observed in macrophage-rich areas bordering the necrotic lipid core of the atheromatous plaque; the implication being that chronic monocyte infiltration and lipid accumulation promoted by CCL2 contribute to plaque vulnerability [137]. A study by our research group [138] showed that CCL2 (observed with immunohistochemical staining), was 9-fold higher in coronary arteries obtained by autopsy from patients with coronary artery disease, compared to those of healthy individuals who died in a traffic accident. CCL2 expression was observed in only 26% of normal arteries, and was mostly restricted to smooth muscle cells with an almost negligible staining in the intima and adventitia. Conversely, CCL2 was detected in all specimens of affected arteries, and in all arterial layers, particularly those of the adventitia. Moreover, the quantitative measurement of CCL2 expression discriminated healthy artery tissue samples from that of coronary artery disease samples in a mild, moderate, or severe state with >85% sensitivity and specificity. High plasma CCL2 concentrations have been shown to be associated with increased long-term risk of stroke [139,140], while CCL2 signaling pathways have been shown to be responsible for ischemic stroke progression and atrial fibrillation [141,142].
In the above sections, we have discussed the close relationships between increased concentrations of CCL2, oxidative stress and decreased PON1 activity. Low PON1 activities are known to increase oxidative stress as well as CCL2 synthesis and the generation of inflammatory processes. However, the opposite is also true. For example, chronic inflammation causes profound changes in the structure and in the circulating levels of HDL, among which are decreases in concentrations of PON1, apolipoprotein AI, lecithin:cholesterol acyltransferase, and cholesterol ester transfer protein, together with an increase in the concentration of serum amyloid A (Figure 3). All these changes influence the intracellular metabolism of cholesterol and increase the risk of CVD [143,144,145].
The mechanisms by which the decrease in PON1 concentrations associated with chronic inflammation can promote pro-atherogenic changes in the arterial system have received considerable research attention recently. The association of PON1 with HDL particles facilitates the binding of the particles to macrophages and, subsequently, the enzyme can hydrolyze membrane phospholipids to generate lysophosphatidylcholine, which regulates the expression of cholesterol transport proteins. Further, PON1 inhibits the formation of free radical species in macrophages by preventing the activation of NADPH oxidase and by stabilizing mitochondria. PON1 also promotes the differentiation of macrophages into an anti-inflammatory phenotype [146]. An interesting study [147] demonstrated that genetically reduced PON1 concentration induces proatherogenic changes in plasma proteomes in humans and mice. The study investigated the influence of the least efficient isoforms of PON1 genetic polymorphisms in humans and Pon1−/− genotype in mice and found that both genetic modifications induce changes in the plasma proteome that affect biological networks involving proteins participating in lipoprotein metabolism, in CVD in neurological diseases, in immune response, inflammatory response, in cell-to-cell signaling, and immune-cell trafficking. In general, clinical studies have found low circulating PON1 activities in patients with CVD [148,149,150,151,152]. However, its usefulness as a risk marker has not been clearly demonstrated. A recent trial (the Dutch PREVEND study) reported an association between low serum PON1 activities in 7766 subjects with high HDL and C-reactive protein levels [153], but this association was not sufficiently robust in the general population when adjusted for other confounding factors [154].
Metabolomics has enabled the identification of metabolic alterations in patients with CVD. In addition, associated comorbidities (diabetes, obesity, metabolic syndrome) can modify systemic and myocardial metabolism and worsen cardiac function [155,156,157,158]. The earliest study conducted almost 20 years ago was promising, but the low number of cases precluded definitive conclusions [157]. More recently, a lipidomics analyses in a population-based 10-year follow-up study in Sweden showed an association between CVD and lysophosphatidylcholine, monoglycerides, and sphingomyelin, independently of traditional risk factors. Of note is that these alterations were associated with biochemical markers of oxidative stress and inflammation [159]. Another lipidomics population-based study in Italy showed that eight lipid classes (cholesterol esters, lysophosphatidylcholines, lysophosphatidylethanolamines, phosphatidylcholines, phosphatidylethanolamines, phosphatidylserines, sphingomyelins, and triacylglycerols) predict future development of myocardial infarction, stroke, and sudden death [160]. Some patient-based studies have also been conducted. Shah et al. [161] studied 2023 consecutive patients undergoing cardiac catheterization and found that five different metabolite classes were independently associated with mortality; these were branched-chain amino acids (BCAA), dicarboxylacylcarnitines, fatty acids, long-chain dicarboxylacylcarnitines, and medium-chain acylcarnitines. Of those, three lipid profiles significantly predicted fatal events, independent of other standard predictors. More recent studies found that the serum concentrations of several energy balance-related metabolites are increased in patients with dilated cardiomyopathy [162], and alterations in NO metabolism were shown to be associated with severe aortic stenosis [163].
Our research group has paid special attention to investigating the potential utility of CCl2, PON1, and associated metabolic alterations as markers in the diagnosis of peripheral arterial disease (PAD) of the lower extremities. This disease is a frequent complication of diabetes mellitus and, if not treated expeditiously, may require amputation of the affected limb. Unfortunately, the disease progresses silently and, although preventive measures are effective in early stages, PAD is often under-diagnosed when asymptomatic and, consequently, prevention is either applied too late or not at all. Therefore, the search for laboratory-measured surrogates has an evident clinical interest. Furthermore, a characteristic of PAD is that the extent of the affected area is much greater than that of vascular diseases of the upper trunk, with which the biochemical alterations measured in the circulation are potentially greater [164]. Our studies showed that patients with PAD had decreased serum PON1 activities and increased CCL2 concentrations [165,166,167], together with significant alterations in energy metabolism, including decreased circulating levels of branched-chain amino acids and increased levels of glutamate, glutamine, and several metabolites of the TCA cycle. Additionally, we found that CCL2, isocitrate, and glutamate had a high diagnostic accuracy in predicting PAD, with areas under the curve of the receiver operating characteristics (AUROC) plots > 0.95 [168]. These studies not only served to illustrate the close relationships between PON1, CCL2, and energy metabolism in inflammatory diseases, but also served to highlight new biological markers for the early diagnosis of PAD.

7. Cancer

Obesity is a long-term risk factor for cancer, and both disorders share deviations in common metabolic pathways [169]. Cancer is associated with oxidative stress. Experimental studies have reported that increased production of ROS by cancerous cells can cause tumor proliferation, promotion of genetic instability, and alterations in cellular sensitivity to chemotherapy [170]. Currently, serum PON1 activity appears to be decreased in many types of cancers, and this topic has been the subject of a recent meta-analysis [171]. Our research group observed decreased PON1 activities in patients with cancers of the breast, lung, head and neck, and rectum who, fully or partially, recovered post-radiotherapy [172,173,174]. Some studies investigated the relationships between serum PON1 activities and tumor stage, and reported that local progress of the disease was associated with lower enzyme activities in patients with ovarian [175] and gastroesophageal cancers [176]. However, other studies did not find any significant differences in PON1 activities in relation to the presence/absence of metastases [176,177,178] and, as well, did not find any significant associations between PON1 concentrations and tumor histology stage or location [176,179,180].
Consistent with what has been highlighted in this review is that decreased serum PON1 activity is associated with inflammation in cancer. For instance, in gastroesophageal cancers, the decrease in PON1 activity correlates directly with the levels of circulating inflammation markers, including C-reactive protein and interleukin-6 [179,181]. Additionally, we have observed low serum PON1 activities and high CCL2 concentrations in patients with bladder cancer [182]. CCL2 and other pro-inflammatory cytokines and chemokines released from tumor or stromal cells act in autocrine and paracrine modes to induce changes in tumor cells, recruit bone marrow-derived cells, favor epithelial-mesenchymal-transition, and form an inflammatory milieu that favors metastatic cell growth [183]. For instance, interleukin-1β has been shown to promote migration and proliferation of HeLa cells by targeting the NF-κB/CCL-2 pathway [184], while CCL2 was reported as promoting prostate cancer metastasis [185]. Further, the CCL2/CCR2 axis has been associated with breast cancer (BC) progression [186], and miR-196a, which activates CCL2, also promotes the migration and invasion of the lung by cancer cells [187]. In addition, high plasma CCL2 concentrations are associated with poorer response to neoadjuvant radiochemotherapy in patients with colorectal cancer [188], and with increased risk of prostate cancer [189]. All these data suggest that the CCL2/CCR2 axis could be a promising target for cancer treatment and prevention.
Cancer cells also have profound changes in energy metabolism. Normal cells mainly produce energy via oxidative phosphorylation in the mitochondria. However, most cancer cells produce energy through an enhanced form of glycolysis, followed by lactic acid fermentation. Aerobic glycolysis is less efficient than oxidative phosphorylation in terms of ATP production, but aerobic glycolysis facilitates increased production of other metabolites that are required for the synthesis of lipids, proteins, and nucleic acids, which are factors in the proliferation of tumor cells [190]. This is termed the “Warburg effect” as a tribute to Otto Warburg who first described this phenomenon in 1956 [191]. Many studies have highlighted the importance of the glutaminolysis pathway in converting glutamine to glutamate and α-ketoglutarate for entry into the TCA cycle. Tumor cells convert 90% of glucose and 66% of glutamine into lactate and alanine. Glutamine and glutamate contribute to the carbon backbone in the TCA cycle, and this is relevant in conditions of carbon diversion to glycolysis [192,193]. The transfer of an amino group from glutamate to oxaloacetate via aspartate aminotransferase results in α-ketoglutarate and aspartate, whereas nitrogen transfer from glutamate to pyruvate via alanine aminotransferase results in α-ketoglutarate and alanine. Through these enzymatic modifications, glutamate activates several biochemical pathways that stimulate tumor development, including protein and nucleic acid syntheses, epigenetic changes, metabolite exchange between the mitochondria and the cytosol, and the stimulation of antioxidant defense mechanisms [194,195] (Figure 4).
Several studies have indicated that glutamate concentrations have a major impact on the fate of the tumor. For example, in mouse models of lung cancer (LC), the deletion of autophagy-related gene 7 (Atg7) decreases macroautophagy, suppresses tumor growth, and promotes cell death [196,197]. LC cells require autophagy to compensate for metabolic stress that is induced by the hypoxic tumor microenvironment, and autophagy promotes the degradation of intracellular components that are necessary for the syntheses of fatty acids, nucleotides, amino acids, and sugars [198]. However, although Atg7 deficiency decreases TCA cycle intermediates (such as glutamate, aspartate, and α-ketoglutarate), supplementations of glutamine or glutamate in the diets of these mice cause a restorative adaptation that increases the survival of LC cells [199]. In addition, NADPH oxidase 4, an enzyme that is highly expressed in LC tumors, promotes glutaminolysis, increases glutamate and glutathione concentrations, and contributes to the survival of LC cells [200]. Disturbances in energy metabolism in cancer cells are reflected in changes in plasma. We recently demonstrated that, in patients with LC or with head and neck cancer (HNC), plasma concentrations of glutamate are strongly increased, compared to those of the healthy population [201]. This study also reported that the measurement of plasma glutamate concentrations has a high diagnostic accuracy in differentiating between patients with LC or HNC and healthy individuals, so it could be a biomarker of these cancers. Another study reported that the plasma glutamate concentration has a high sensitivity and specificity in differentiating between LC and benign lung lesions [202]. Likewise, a high plasma glutamate concentration is associated with low survival [203], and with the presence of neurological complications in patients with LC [204]. Furthermore, glutamate and other glutaminolysis-related products have been proposed as biomarkers of chemotherapy efficacy in patients with oral squamous cell carcinoma [205]. The measurement of plasma concentrations of glutamate via metabolomics, either alone or in combination with other parameters, has demonstrated its usefulness as a biomarker in patients with pancreatic cancer as well [206].
Another alteration that is consistently observed in patients with various types of cancer is a decrease in the plasma concentrations of serine and branched-chain amino acids such as valine, leucine, and isoleucine [201,207,208]. This is due, probably, to an enhanced cellular demand for these amino acids related to increased glutaminolysis. These amino acids are the major nitrogen source for the biosynthesis of glutamine and glutamate [209]. The increased demand for glutamine by actively replicating tumor cells would explain the observed reduced serum concentrations of serine and branched-chain amino acids [210]. LC and HNC patients who had local tumor recurrences or who had died from the disease had higher plasma concentrations of branched-chain amino acids, serine, and other metabolites associated with glutaminolysis [201]. These findings could indicate that a poorer prognosis is associated with a deregulation of glutaminolysis. Several other metabolites have been observed to be related to the clinical characteristics of cancer patients, or to the molecular characteristics of their tumors. Preliminary results have indicated that LC patients with metastases have higher plasma concentrations of β-hydroxybutyrate, whereas those patients with local tumor recurrences had higher values of leucine, valine, and fumarate [201]. Very little is known about the relationships between these metabolites and prognosis of the cancer; β-hydroxybutyrate has been demonstrated to increase the expression of forkhead box O, and the mammalian target of rapamycin. Hence, this factor can stimulate cell growth, proliferation, and longevity [211]. This metabolite also induces the synthesis of metallothioneins, superoxide dismutase, and catalase, thus increasing the antioxidant capacities of cells [212]. Of note is that radiation therapy (RT) has been demonstrated to influence and, to some extent, correct these metabolic disturbances in patients as well as in experimental animals. In mice, RT decreased the hepatic concentrations of choline, O-phosphocholine, and trimethylamine N-oxide, while increasing the concentrations of glutamine, glutathione, malate, creatinine, phosphate, betaine, and 4-hydroxyphenylacetate [213]. A study in patients with glioblastoma demonstrated that post-RT concentrations of 28 metabolites were significantly altered from their pre-RT levels. However, the lack of a control group did not permit identification of the degree of pre-RT metabolic alterations in these patients, as well as whether the effects of treatment normalized or aggravated the alterations [214]. In patients with cervical cancer and radiation-induced acute intestinal symptoms, RT increased the fecal concentrations of α-ketobutyrate, valine, uracil, tyrosine, trimethylamine N-oxide, phenylalanine, lysine, isoleucine, glutamine, creatinine, creatine, bile acids, aminohippurate, and alanine, as well as being accompanied by reduced concentrations of α-glucose, n-butyrate, methylamine, and ethanol. The authors concluded that metabolomics may be a novel clinical tool for the diagnosis, or therapeutic monitoring, of radiation-induced acute intestinal symptoms [215].
In earlier studies we have reported that the plasma concentrations of the products of glycolysis, TCA cycle, and amino acid metabolism were considerably altered in women with BC, and that RT was associated with a partial rectification of these disturbances [207]. The metabolites that exhibited the strongest pre-RT decreases were serine, valine, leucine, isoleucine, succinate, α-ketoglutarate, glutamate, and malonyl coenzyme A. The parameters that exhibited the strongest increases were pyruvate, aspartate, and aconitate. The majority of these alterations were reversed following RT; the concentrations of lactate, alanine, valine, leucine, isoleucine, proline, malonyl coenzyme A, glycine, succinate, serine, and ketoglutarate were normalized post-RT. The same study also investigated the relationships between metabolic alterations and other concomitant treatments, as well as the clinical characteristics of BC patients. The study reported that adjuvant hormone therapy was associated with lower serum glycine concentrations, and that adjuvant chemotherapy was associated with lower lactate and glutamine concentrations, as well as higher oxaloacetate concentrations, post-RT. In addition, the post-RT plasma concentrations of leucine and isoleucine were significantly lower in estrogen receptor-positive patients than in estrogen receptor-negative patients, and these concentrations were higher in triple-negative patients, in comparison to luminal and Her2 subgroups. Another study in BC patients who received RT after neoadjuvant chemotherapy [208] reported that patients exhibited increased pre-RT concentrations of pyruvate, aspartate, aconitate, and citrate, in conjunction with decreased concentrations of lactate, alanine, valine, leucine, isoleucine, proline, malonyl coenzyme A, glycine, succinate, serine, ketoglutarate, and glutamate. RT largely corrected these alterations, and the improvement was significantly superior in patients who achieved a pathologically complete response than in those patients with partial responses, with serine, proline, and leucine being the parameters with the highest capacity to discriminate between the two groups. These effects of RT on energy metabolism in BC patients cannot be fully extrapolated to other types of cancers. For example, in H&N cancer patients, RT did not ameliorate metabolic alterations but, conversely, was associated with an increase in plasma glutamate and TCA cycle intermediates, such as malate, pyruvate, and succinate [201].

8. Infectious Diseases

Bacterial or viral infections cause oxidative stress, inflammation, and metabolic alterations linked to mitochondrial dysfunction as the body’s defense systems respond directly against external agents, or against the interference of these agents in cell homeostasis. Infectious diseases trigger a cascade of reactions in the host, known as the acute-phase response. This response is associated with, amongst others, structural and functional changes in HDL particles that lose their antioxidant and anti-inflammatory properties [216,217,218]. Many studies have identified decreased serum PON1 activities and increased CCL2 concentrations in infectious diseases. A proteomic study reported decreased PON1 expression in patients with sepsis, compared to healthy individuals [219]. We recently observed that hospitalized patients carrying an indwelling central venous catheter [220] or a urinary catheter, with catheter-associated asymptomatic bacteriuria [221] had decreased serum PON1 activities and increased CCL2 concentrations. Based on our findings, we proposed the measurement of the circulating levels of these molecules as useful markers of acute concomitant infection. We found similar alterations in patients with severe sepsis admitted to the Intensive Care Unit; the alterations tended to normalize when the sepsis was corrected [222,223]. Serum PON1 activity was found to be low in several studies in patients infected with Helicobacter pylori; this alteration may play a role in the high predisposition of these patients to develop atherosclerosis and CVD [224,225,226,227,228]. Decreased serum PON1 activities were also observed in patients infected by Brucella [229], or Mycobacterium tuberculosis [230], together with increased release of pro-inflammatory cytokines.
Viral infections are associated with similar disruptions. Patients with human immunodeficiency virus (HIV) infection have decreased circulating levels of HDL-cholesterol and PON1 activity, and increased CCL2 [231,232,233,234,235,236]. These patients often develop pro-atherogenic metabolic alterations, which can be explained by the infection itself, or by the effects of antiretroviral therapies [237,238,239]. Higher PON1 activities and lower CCL2 concentrations have been related to higher CD4+ T lymphocyte counts, which indicate a better immunological status [233]. Recent studies observed that CCL2 participates in the onset and development of neurocognitive disorders in HIV-infected patients [240,241,242,243]. Similar alterations in PON1 and CCL2 levels have been reported in patients with hepatitis B [244,245,246], hepatitis C [247,248], and dengue [249]. Although data on alterations in energy metabolism in HIV infection are scarce, some studies using metabolomic methods showed significant associations between CCL2, sphingomyelins, phospholipids, and triglycerides [250], Additionally, the alterations in glutaminolysis and pro-inflammatory molecules appear to be the metabolomic signature of late immune recovery post-treatment [251]. Moreover, increased plasma glutamine levels have been found to be related to CVD in these patients [252].
In this article, which has “A 2021 update” in the title, we must not miss the opportunity of commenting on the special circumstances in which we currently find ourselves, i.e., the COVID-19 pandemic. Available data on this issue are very preliminary. A proteomic study found decreased PON1 expression in the HDL of COVID-19 patients [253]; the role of PON1 in COVID-19 may be different depending on whether the enzyme is present in the circulation or within the cells. Purified native HDL with intact PON1 elicits a potent antiviral effect against SARS-CoV-2 in cultured monocyte cells, while glycated HDL, with inactive PON1, lost its antiviral activity [254]. However, an in silico study reported that PON1 enhances the action of ACE2, the main cell receptor of SARS-CoV-2 [255], and the inhibition of PON1 activity has been described as being a potent inhibitor of vaccinia virus early protein synthesis and viral mRNA methylation in mice [256], suggesting that intracellular PON1 is important in limiting the translation of viral proteins and virus replication. High CCL2 concentrations have been observed in the circulation [257,258,259,260,261,262] in bronchoalveolar lavage fluid [263], and in lung tissue of COVID-19 patients [264]. One study reported that CCL2 expression increases rapidly in the early acute phase of infection and then progressively decreases as the disease advances [265]. The effects of this infection on mitochondrial function and energy metabolism deserve further research, because preliminary data suggest they could be very clinically relevant [266,267].

9. Final Remarks

We make no pretense at an exhaustive review of all the articles that demonstrate a participation of PON1, CCL2, and metabolic alterations in all known diseases. We have not addressed neurological, autoimmune, or kidney diseases, or conditions caused by food poisoning or xenobiotics. Nor have we mentioned the alterations produced in these parameters by surgical procedures, nor the successful (or unsuccessful) attempts to modulate these pathways through dietary or pharmacological interventions. Indeed, such a task is beyond the remit of a review article. Rather, we sought to highlight some of the common pathophysiological mechanisms of many communicable and/or non-communicable diseases, particularly with respect to the important roles that PON1 and CCL2 play in metabolic changes linked to mitochondrial dysfunction. Our goal has been to encourage interested readers to undertake their own research in a field that we believe will have transformational scientific and clinical implications in the near future.


This study was supported by a grant from the Fundació la Marató de TV3 (201807-10), Barcelona, Spain and by the CERCA Programme, Generalitat de Catalunya, Barcelona, Spain.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.


Studies from our group reported in this paper were supported by the Instituto de Investigación Carlos III, Madrid, Spain (Grants PI15/00285, PI18/00921, PI18/01590, and CPII/00023), the Generalitat de Catalunya, Barcelona, Spain (SGR1227), Fundació La Marató de TV3, Barcelona, Spain (60/U/2016), and Ministry of Science, Innovation and Universities, Madrid, Spain (PGC2018-096244-B-I00).

Conflicts of Interest

The authors declare no conflict of interest.


  1. Pizzino, G.; Irrera, N.; Cucinotta, M.; Pallio, G.; Mannino, F.; Arcoraci, V.; Squadrito, F.; Altavilla, D.; Bitto, A. Oxidative stress: Harms and benefits for human health. Oxid. Med. Cell. Longev. 2017, 2017, 8416763. [Google Scholar] [CrossRef] [PubMed]
  2. Masud, S.; Torraca, V.; Meijer, A.H. Modeling infectious diseases in the context of a developing immune system. Curr. Top. Dev. Biol. 2017, 124, 277–329. [Google Scholar] [CrossRef] [Green Version]
  3. He, J.; Liu, J.; Huang, Y.; Tang, X.; Xiao, H.; Hu, Z. Oxidative Stress, inflammation, and autophagy: Potential targets of mesenchymal stem cells-based therapies in ischemic stroke. Front. Neurosci. 2021, 15, 641157. [Google Scholar] [CrossRef] [PubMed]
  4. Kibel, A.; Lukinac, A.M.; Dambic, V.; Juric, I.; Relatic, K.S. Oxidative stress in ischemic heart disease. Oxid. Med. Cell. Longev. 2020, 2020, 6627144. [Google Scholar] [CrossRef]
  5. Atri, C.; Guerfali, F.Z.; Laouini, D. Role of human macrophage polarization in inflammation during infectious diseases. Int. J. Mol. Sci. 2018, 19, 1801. [Google Scholar] [CrossRef] [Green Version]
  6. Parisi, L.; Gini, E.; Baci, D.; Tremolati, M.; Fanuli, M.; Bassani, B.; Farronato, G.; Bruno, A.; Mortara, L. Macrophage polarization in chronic inflammatory diseases: Killers or builders? J. Immunol. Res. 2018, 2018, 8917804. [Google Scholar] [CrossRef]
  7. Poltavets, A.S.; Vishnyakova, P.A.; Elchaninov, A.V.; Sukhikh, G.T.; Fatkhudinov, T.K. Macrophage modification strategies for efficient cell therapy. Cells 2020, 9, 1535. [Google Scholar] [CrossRef] [PubMed]
  8. Viola, A.; Munari, F.; Sánchez-Rodríguez, R.; Scolaro, T.; Castegna, A. The metabolic signature of macrophage responses. Front. Immunol. 2019, 10, 1462. [Google Scholar] [CrossRef] [Green Version]
  9. Turner, M.D.; Nedjai, B.; Hurst, T.; Pennington, D.J. Cytokines and chemokines: At the crossroads of cell signalling and inflammatory disease. Biochim. Biophys. Acta 2014, 1843, 2563–2582. [Google Scholar] [CrossRef] [Green Version]
  10. Gschwandtner, M.; Derler, R.; Midwood, K.S. More than just attractive: How CCL2 influences myeloid cell behavior beyond chemotaxis. Front. Immunol. 2019, 10, 2759. [Google Scholar] [CrossRef] [Green Version]
  11. Huang, R.; Guo, L.; Gao, M.; Li, J.; Xiang, S. Research trends and regulation of CCL5 in prostate cancer. Onco. Targets Ther. 2021, 14, 1417–1427. [Google Scholar] [CrossRef]
  12. Agresti, N.; Lalezari, J.P.; Amodeo, P.P.; Mody, K.; Mosher, S.F.; Seethamraju, H.; Kelly, S.A.; Pourhassan, N.Z.; Sudduth, C.D.; Bovinet, C.; et al. Disruption of CCR5 signaling to treat COVID-19-associated cytokine storm: Case series of four critically ill patients treated with leronlimab. J. Transl. Autoimmun. 2021, 4, 100083. [Google Scholar] [CrossRef] [PubMed]
  13. Yao, X.; Matosevic, S. Chemokine networks modulating natural killer cell trafficking to solid tumors. Cytokine Growth Factor Rev. 2021, 36–45. [Google Scholar] [CrossRef] [PubMed]
  14. Necula, D.; Riviere-Cazaux, C.; Shen, Y.; Zhou, M. Insight into the roles of CCR5 in learning and memory in normal and disordered states. Brain Behav. Immun. 2021, 92, 1–9. [Google Scholar] [CrossRef] [PubMed]
  15. Taler-Verčič, A.; Goličnik, M.; Bavec, A. The structure and function of paraoxonase-1 and its comparison to paraoxonase-2 and -3. Molecules 2020, 25, 5980. [Google Scholar] [CrossRef]
  16. Levy, D.; Reichert, C.O.; Bydlowski, S.P. Paraoxonases activities and polymorphisms in elderly and old-age diseases: An overview. Antioxidants 2019, 8, 118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Camps, J.; Marsillach, J.; Joven, J. The paraoxonases: Role in human diseases and methodological difficulties in measurement. Crit. Rev. Clin. Lab. Sci. 2009, 46, 83–106. [Google Scholar] [CrossRef]
  18. Costa, L.G.; Cole, T.B.; Vitalone, A.; Furlong, C.E. Measurement of paraoxonase (PON1) status as a potential biomarker of susceptibility to organophosphate toxicity. Clin. Chim. Acta 2005, 352, 37–47. [Google Scholar] [CrossRef]
  19. Draganov, D.I.; Teiber, J.F.; Speelman, A.; Osawa, Y.; Sunahara, R.; La Du, B.N. Human paraoxonases (PON1, PON2, and PON3) are lactonases with overlapping and distinct substrate specificities. J. Lipid Res. 2005, 46, 1239–1247. [Google Scholar] [CrossRef] [Green Version]
  20. Jaouad, L.; de Guise, C.; Berrougui, H.; Cloutier, M.; Isabelle, M.; Fulop, T.; Payette, H.; Khalil, A. Age-related decrease in high-density lipoproteins antioxidant activity is due to an alteration in the PON1′s free sulfhydryl groups. Atherosclerosis 2006, 185, 191–200. [Google Scholar] [CrossRef]
  21. Leviev, I.; Negro, F.; James, R.W. Two alleles of the human paraoxonase gene produce different amounts of mRNA. An explanation for differences in serum concentrations of paraoxonase associated with the (Leu-Met54) polymorphism. Arterioscler. Thromb. Vasc. Biol. 1997, 17, 2935–2939. [Google Scholar] [CrossRef] [PubMed]
  22. Sierksma, A.; van der Gaag, M.S.; van Tol, A.; James, R.W.; Hendriks, H.F. Kinetics of HDL cholesterol and paraoxonase activity in moderate alcohol consumers. Alcohol. Clin. Exp. Res. 2002, 26, 1430–1435. [Google Scholar] [CrossRef]
  23. Deakin, S.P.; Bioletto, S.; Bochaton-Piallat, M.L.; James, R.W. HDL-associated paraoxonase-1 can redistribute to cell membranes and influence sensitivity to oxidative stress. Free Radic. Biol. Med. 2011, 50, 102–109. [Google Scholar] [CrossRef] [Green Version]
  24. Marsillach, J.; Camps, J.; Beltran-Debón, R.; Rull, A.; Aragones, G.; Maestre-Martínez, C.; Sabench, F.; Hernández, M.; Castillo, D.D.; Joven, J.; et al. Immunohistochemical analysis of paraoxonases-1 and 3 in human atheromatous plaques. Eur. J. Clin. Investig. 2011, 41, 308–314. [Google Scholar] [CrossRef]
  25. Marsillach, J.; Mackness, B.; Mackness, M.; Riu, F.; Beltrán, R.; Joven, J.; Camps, J. Immunohistochemical analysis of paraoxonases-1, 2, and 3 expression in normal mouse tissues. Free Radic. Biol. Med. 2008, 45, 146–157. [Google Scholar] [CrossRef]
  26. Rodríguez-Sanabria, F.; Rull, A.; Beltrán-Debón, R.; Aragonès, G.; Camps, J.; Mackness, B.; Mackness, M.; Joven, J. Tissue distribution and expression of paraoxonases and chemokines in mouse: The ubiquitous and joint localisation suggest a systemic and coordinated role. J. Mol. Histol. 2010, 41, 379–386. [Google Scholar] [CrossRef]
  27. Manco, G.; Porzio, E.; Carusone, T.M. Human paraoxonase-2 (PON2): Protein functions and modulation. Antioxidants 2021, 10, 256. [Google Scholar] [CrossRef] [PubMed]
  28. Mackness, B.; Hine, D.; Liu, Y.; Mastorikou, M.; Mackness, M. Paraoxonase-1 inhibits oxidised LDL-induced MCP-1 production by endothelial cells. Biochem. Biophys. Res. Commun. 2004, 318, 680–683. [Google Scholar] [CrossRef] [PubMed]
  29. Camps, J.; Rodríguez-Gallego, E.; García-Heredia, A.; Triguero, I.; Riera-Borrull, M.; Hernández-Aguilera, A.; Luciano-Mateo, F.; Fernández-Arroyo, S.; Joven, J. Paraoxonases and chemokine (C-C motif) ligand-2 in noncommunicable diseases. Adv. Clin. Chem. 2014, 63, 247–308. [Google Scholar] [CrossRef]
  30. Watson, A.D.; Berliner, J.A.; Hama, S.Y.; La Du, B.N.; Faull, K.F.; Fogelman, A.M.; Navab, M. Protective effect of high density lipoprotein associated paraoxonase. Inhibition of the biological activity of minimally oxidized low density lipoprotein. J. Clin. Investig. 1995, 96, 2882–2891. [Google Scholar] [CrossRef] [PubMed]
  31. Shih, D.M.; Gu, L.; Xia, Y.R.; Navab, M.; Li, W.F.; Hama, S.; Castellani, L.W.; Furlong, C.E.; Costa, L.G.; Fogelman, A.M.; et al. Mice lacking serum paraoxonase are susceptible to organophosphate toxicity and atherosclerosis. Nature 1998, 394, 284–287. [Google Scholar] [CrossRef]
  32. Rozenberg, O.; Rosenblat, M.; Coleman, R.; Shih, D.M.; Aviram, M. Paraoxonase (PON1) deficiency is associated with increased macrophage oxidative stress: Studies in PON1-knockout mice. Free Radic. Biol. Med. 2003, 34, 774–784. [Google Scholar] [CrossRef]
  33. Mackness, M.; Mackness, B. Human paraoxonase-1 (PON1): Gene structure and expression, promiscuous activities and multiple physiological roles. Gene 2015, 567, 12–21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Singh, S.; Singh, S.K.; Chowdhury, I.; Singh, R. Understanding the mechanism of bacterial biofilms resistance to antimicrobial agents. Open Microbiol. J. 2017, 11, 53–62. [Google Scholar] [CrossRef] [Green Version]
  35. Gebreyohannes, G.; Nyerere, A.; Bii, C.; Sbhatu, D.B. Challenges of intervention, treatment, and antibiotic resistance of biofilm-forming microorganisms. Heliyon 2019, 5, e02192. [Google Scholar] [CrossRef] [Green Version]
  36. Balaure, P.C.; Grumezescu, A.M. Recent advances in surface nanoengineering for biofilm prevention and control. Part I: Molecular basis of biofilm recalcitrance. Passive anti-biofouling nanocoatings. Nanomaterials 2020, 10, 1230. [Google Scholar] [CrossRef]
  37. Camps, J.; Iftimie, S.; García-Heredia, A.; Castro, A.; Joven, J. Paraoxonases and infectious diseases. Clin. Biochem. 2017, 50, 804–811. [Google Scholar] [CrossRef]
  38. Coquant, G.; Grill, J.P.; Seksik, P. Impact of N-acyl-homoserine lactones, quorum sensing molecules, on gut immunity. Front. Immunol. 2020, 11, 1827. [Google Scholar] [CrossRef] [PubMed]
  39. Billot, R.; Plener, L.; Jacquet, P.; Elias, M.; Chabrière, E.; Daudé, D. Engineering acyl-homoserine lactone-interfering enzymes toward bacterial control. J. Biol. Chem. 2020, 295, 12993–13007. [Google Scholar] [CrossRef] [PubMed]
  40. Sharma, A.; Singh, P.; Sarmah, B.K.; Nandi, S.P. Quorum sensing: Its role in microbial social networking. Res. Microbiol. 2020, 171, 159–164. [Google Scholar] [CrossRef] [PubMed]
  41. Chun, C.K.; Ozer, E.A.; Welsh, M.J.; Zabner, J.; Greenberg, E.P. Inactivation of a Pseudomonas aeruginosa quorum-sensing signal by human airway epithelia. Proc. Natl. Acad. Sci. USA 2004, 101, 3587–3590. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Stoltz, D.A.; Ozer, E.A.; Zabner, J. Paraoxonases, quorum sensing, and Pseudomonas aeruginosa. In The Paraoxonases: Their Role in Disease Development and Xenobiotic Metabolism; Mackness, B., Mackness, M., Aviram, M., Paragh, G., Eds.; Springer: Dordrecht, The Netherlands, 2008; pp. 307–319. [Google Scholar]
  43. Chen, F.; Gao, Y.; Chen, X.; Yu, Z.; Li, X. Quorum quenching enzymes and their application in degrading signal molecules to block quorum sensing-dependent infection. Int. J. Mol. Sci. 2013, 14, 17477–17500. [Google Scholar] [CrossRef]
  44. Ozer, E.A.; Pezzulo, A.; Shih, D.M.; Chun, C.; Furlong, C.; Lusis, A.J.; Greenberg, E.P.; Zabner, J. Human and murine paraoxonase 1 are host modulators of Pseudomonas aeruginosa quorum-sensing. FEMS Microbiol. Lett. 2005, 253, 29–37. [Google Scholar] [CrossRef] [Green Version]
  45. Richter, R.J.; Jarvik, G.P.; Furlong, C.E. Paraoxonase 1 status as a risk factor for disease or exposure. Adv. Exp. Med. Biol. 2010, 660, 29–35. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Horke, S.; Witte, I.; Wilgenbus, P.; Krüger, M.; Strand, D.; Förstermann, U. Paraoxonase-2 reduces oxidative stress in vascular cells and decreases endoplasmic reticulum stress-induced caspase activation. Circulation 2007, 115, 2055–2064. [Google Scholar] [CrossRef] [PubMed]
  47. Horke, S.; Witte, I.; Wilgenbus, P.; Altenhöfer, S.; Krüger, M.; Li, H.; Förstermann, U. Protective effect of paraoxonase-2 against endoplasmic reticulum stress-induced apoptosis is lost upon disturbance of calcium homoeostasis. Biochem. J. 2008, 416, 395–405. [Google Scholar] [CrossRef] [Green Version]
  48. Devarajan, A.; Grijalva, V.R.; Bourquard, N.; Meriwether, D.; Imaizumi, S.; Shin, B.C.; Devaskar, S.U.; Reddy, S.T. Macrophage paraoxonase 2 regulates calcium homeostasis and cell survival under endoplasmic reticulum stress conditions and is sufficient to prevent the development of aggravated atherosclerosis in paraoxonase 2 deficiency/apoE-/- mice on a Western diet. Mol. Genet. Metab. 2012, 107, 416–427. [Google Scholar] [CrossRef] [Green Version]
  49. Sulaiman, D.; Li, J.; Devarajan, A.; Cunningham, C.M.; Li, M.; Fishbein, G.A.; Fogelman, A.M.; Eghbali, M.; Reddy, S.T. Paraoxonase 2 protects against acute myocardial ischemia-reperfusion injury by modulating mitochondrial function and oxidative stress via the PI3K/Akt/GSK-3β RISK pathway. J. Mol. Cell. Cardiol. 2019, 129, 154–164. [Google Scholar] [CrossRef]
  50. Tao, S.; Niu, L.; Cai, L.; Geng, Y.; Hua, C.; Ni, Y.; Zhao, R. N-(3-oxododecanoyl)-l-homoserine lactone modulates mitochondrial function and suppresses proliferation in intestinal goblet cells. Life Sci. 2018, 201, 81–88. [Google Scholar] [CrossRef]
  51. Tao, S.; Luo, Y.; Bin, H.; Liu, J.; Qian, X.; Ni, Y.; Zhao, R. Paraoxonase 2 modulates a proapoptotic function in LS174T cells in response to quorum sensing molecule N-(3-oxododecanoyl)-L-homoserine lactone. Sci. Rep. 2016, 6, 28778. [Google Scholar] [CrossRef]
  52. García-Heredia, A.; Kensicki, E.; Mohney, R.P.; Rull, A.; Triguero, I.; Marsillach, J.; Tormos, C.; Mackness, B.; Mackness, M.; Shih, D.M.; et al. Paraoxonase-1 deficiency is associated with severe liver steatosis in mice fed a high-fat high-cholesterol diet: A metabolomic approach. J. Proteome Res. 2013, 12, 1946–1955. [Google Scholar] [CrossRef] [PubMed]
  53. Luciano-Mateo, F.; Cabré, N.; Fernández-Arroyo, S.; Baiges-Gaya, G.; Hernández- Aguilera, A.; Rodríguez-Tomàs, E.; Mercado-Gómez, M.; Menendez, J.A.; Camps, J.; Joven, J. Chemokine (C-C motif) ligand 2 gene ablation protects low-density lipoprotein and paraoxonase-1 double deficient mice from liver injury, oxidative stress and inflammation. Biochim. Biophys. Acta Mold Basis Dis. 2019, 1865, 1555–1566. [Google Scholar] [CrossRef] [PubMed]
  54. Meneses, M.J.; Silvestre, R.; Sousa-Lima, I.; Macedo, M.P. Paraoxonase-1 as a regulator of glucose and lipid homeostasis: Impact on the onset and progression of metabolic disorders. Int. J. Mol. Sci. 2019, 20, 4049. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Calvo, N.; Beltrán-Debón, R.; Rodríguez-Gallego, E.; Hernández-Aguilera, A.; Guirro, M.; Mariné-Casadó, R.; Millá, L.; Alegret, J.M.; Sabench, F.; del Castillo, D.; et al. Liver fat deposition and mitochondrial dysfunction in morbid obesity: An approach combining metabolomics with liver imaging and histology. World J. Gastroenterol. 2015, 21, 7529–7544. [Google Scholar] [CrossRef]
  56. Cabré, N.; Luciano-Mateo, F.; Fernández-Arroyo, S.; Baiges-Gayà, G.; Hernández-Aguilera, A.; Fibla, M.; Fernández-Julià, R.; París, M.; Sabench, F.; Castillo, D.D.; et al. Laparoscopic sleeve gastrectomy reverses non-alcoholic fatty liver disease modulating oxidative stress and inflammation. Metabolism 2019, 99, 81–89. [Google Scholar] [CrossRef] [PubMed]
  57. Cabré, N.; Luciano-Mateo, F.; Baiges-Gayà, G.; Fernández-Arroyo, S.; Rodríguez-Tomàs, E.; Hernández-Aguilera, A.; París, M.; Sabench, F.; Del Castillo, D.; López-Miranda, J.; et al. Plasma metabolic alterations in patients with severe obesity and non-alcoholic steatohepatitis. Aliment. Pharmacol. Ther. 2020, 51, 374–387. [Google Scholar] [CrossRef] [PubMed]
  58. Kurihara, C.; Lecuona, E.; Wu, Q.; Yang, W.; Núñez-Santana, F.L.; Akbarpour, M.; Liu, X.; Ren, Z.; Li, W.; Querrey, M.; et al. Crosstalk between nonclassical monocytes and alveolar macrophages mediates transplant ischemia-reperfusion injury through classical monocyte recruitment. JCI Insight 2021, 6, 147282. [Google Scholar] [CrossRef] [PubMed]
  59. Mohammed, S.; Nicklas, E.H.; Thadathil, N.; Selvarani, R.; Royce, G.H.; Kinter, M.; Richardson, A.; Deepa, S.S. Role of necroptosis in chronic hepatic inflammation and fibrosis in a mouse model of increased oxidative stress. Free Radic. Biol. Med. 2021, 164, 315–328. [Google Scholar] [CrossRef] [PubMed]
  60. Zhu, F.; Willette-Brown, J.; Zhang, J.; Ferre, E.M.N.; Sun, Z.; Wu, X.; Lionakis, M.S.; Hu, Y. NLRP3 inhibition ameliorates severe cutaneous autoimmune manifestations in a mouse model of autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy-like disease. J. Investig. Dermatol. 2020, 141, 1404–1415. [Google Scholar] [CrossRef]
  61. McKnight, A.H.; Katzenberger, D.R.; Britnell, S.R. Colchicine in acute coronary syndrome: A systematic review. Ann. Pharmacother. 2021, 55, 187–197. [Google Scholar] [CrossRef]
  62. Kolattukudy, P.E.; Niu, J. Inflammation, endoplasmic reticulum stress, autophagy, and the monocyte chemoattractant protein-1/CCR2 pathway. Circ. Res. 2012, 110, 174–189. [Google Scholar] [CrossRef]
  63. Pandey, E.; Nour, A.S.; Harris, E.N. Prominent receptors of liver sinusoidal endothelial cells in liver homeostasis and disease. Front. Physiol. 2020, 11, 873. [Google Scholar] [CrossRef]
  64. Andersson, U.; Ottestad, W.; Tracey, K.J. Extracellular HMGB1: A therapeutic target in severe pulmonary inflammation including COVID-19? Mol. Med. 2020, 26, 42. [Google Scholar] [CrossRef] [PubMed]
  65. Shamilov, R.; Ackley, T.W.; Aneskievich, B.J. Enhanced wound healing- and inflammasome-associated gene expression in TNFAIP3-interacting protein 1-(TNIP1-) deficient HaCaT keratinocytes parallels reduced reepithelialization. Mediat. Inflamm. 2020, 2020, 5919150. [Google Scholar] [CrossRef] [PubMed]
  66. Relja, B.; Land, W.G. Damage-associated molecular patterns in trauma. Eur. J. Trauma. Emerg. Surg. 2020, 46, 751–775. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Afrose, S.S.; Junaid, M.; Akter, Y.; Tania, M.; Zheng, M.; Khan, M.A. Targeting kinases with thymoquinone: A molecular approach to cancer therapeutics. Drug Discov. Today. 2020, 25, 2294–2306. [Google Scholar] [CrossRef] [PubMed]
  68. Dantonio, P.M.; Klein, M.O.; Freire, M.R.V.B.; Araujo, C.N.; Chiacetti, A.C.; Correa, R.G. Exploring major signaling cascades in melanomagenesis: A rationale route for targetted skin cancer therapy. Biosci. Rep. 2018, 38, BSR20180511. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Stawski, L.; Trojanowska, M. Oncostatin M and its role in fibrosis. Connect. Tissue Res. 2019, 60, 40–49. [Google Scholar] [CrossRef]
  70. Slaine, P.D.; Kleer, M.; Duguay, B.A.; Pringle, E.S.; Kadijk, E.; Ying, S.; Balgi, A.; Roberge, M.; McCormick, C.; Khaperskyy, D.A. Thiopurines activate an antiviral unfolded protein response that blocks influenza A virus glycoprotein accumulation. J. Virol. 2021, 95, e00453-21. [Google Scholar] [CrossRef] [PubMed]
  71. Féral, K.; Jaud, M.; Philippe, C.; Di Bella, D.; Pyronnet, S.; Rouault-Pierre, K.; Mazzolini, L.; Touriol, C. ER Stress and unfolded protein response in leukemia: Friend, foe, or both? Biomolecules 2021, 11, 199. [Google Scholar] [CrossRef]
  72. Huang, J.; Pan, H.; Wang, J.; Wang, T.; Huo, X.; Ma, Y.; Lu, Z.; Sun, B.; Jiang, H. Unfolded protein response in colorectal cancer. Cell. Biosci. 2021, 11, 26. [Google Scholar] [CrossRef] [PubMed]
  73. Robinson, C.M.; Talty, A.; Logue, S.E.; Mnich, K.; Gorman, A.M.; Samali, A. An emerging role for the unfolded protein response in pancreatic cancer. Cancers 2021, 13, 261. [Google Scholar] [CrossRef]
  74. Morris, G.; Puri, B.K.; Walder, K.; Berk, M.; Stubbs, B.; Maes, M.; Carvalho, A.F. The endoplasmic reticulum stress response in neuroprogressive diseases: Emerging pathophysiological role and translational implications. Mol. Neurobiol. 2018, 55, 8765–8787. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Rashid, H.O.; Yadav, R.K.; Kim, H.R.; Chae, H.J. ER stress: Autophagy induction, inhibition and selection. Autophagy 2015, 11, 1956–1977. [Google Scholar] [CrossRef] [PubMed]
  76. Dymkowska, D. The involvement of autophagy in the maintenance of endothelial homeostasis: The role of mitochondria. Mitochondrion 2021, 57, 131–147. [Google Scholar] [CrossRef]
  77. Picca, A.; Calvani, R.; Coelho-Junior, H.J.; Marzetti, E. Cell death and inflammation: The role of mitochondria in health and disease. Cells 2021, 10, 537. [Google Scholar] [CrossRef]
  78. Su, Y.J.; Wang, P.W.; Weng, S.W. The role of mitochondria in immune-cell-mediated tissue regeneration and ageing. Int. J. Mol Sci. 2021, 22, 2668. [Google Scholar] [CrossRef] [PubMed]
  79. Jang, J.Y.; Blum, A.; Liu, J.; Finkel, T. The role of mitochondria in aging. J. Clin. Investig. 2018, 128, 3662–3670. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  80. Meyers, A.K.; Zhu, X. The NLRP3 Inflammasome: Metabolic regulation and contribution to inflammaging. Cells 2020, 9, 1808. [Google Scholar] [CrossRef] [PubMed]
  81. López-Otín, C.; Blasco, M.A.; Partridge, L.; Serrano, M.; Kroemer, G. The hallmarks of aging. Cell 2013, 153, 1194–1217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Fulop, T.; Witkowski, J.M.; Olivieri, F.; Larbi, A. The integration of inflammaging in age-related diseases. Semin. Immunol. 2018, 40, 17–35. [Google Scholar] [CrossRef]
  83. Hotamisligil, G.S. Endoplasmic reticulum stress and the inflammatory basis of metabolic disease. Cell 2010, 140, 900–917. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Berent-Maoz, B.; Montecino-Rodriguez, E.; Signer, R.A.; Dorshkind, K. Fibroblast growth factor-7 partially reverses murine thymocyte progenitor aging by repression of Ink4a. Blood 2012, 119, 5715–5721. [Google Scholar] [CrossRef] [Green Version]
  85. Sierra-Filardi, E.; Nieto, C.; Domínguez-Soto, A.; Barroso, R.; Sánchez-Mateos, P.; Puig-Kroger, A.; López-Bravo, M.; Joven, J.; Ardavín, C.; Rodríguez-Fernández, J.L.; et al. CCL2 shapes macrophage polarization by GM-CSF and M-CSF: Identification of CCL2/CCR2-dependent gene expression profile. J. Immunol. 2014, 192, 3858–3867. [Google Scholar] [CrossRef] [Green Version]
  86. Yousefzadeh, M.J.; Schafer, M.J.; Noren Hooten, N.; Atkinson, E.J.; Evans, M.K.; Baker, D.J.; Quarles, E.K.; Robbins, P.D.; Ladiges, W.C.; LeBrasseur, N.K.; et al. Circulating levels of monocyte chemoattractant protein-1 as a potential measure of biological age in mice and frailty in humans. Aging Cell 2018, 17, e12706. [Google Scholar] [CrossRef] [PubMed]
  87. Acosta, J.C.; Banito, A.; Wuestefeld, T.; Georgilis, A.; Janich, P.; Morton, J.P.; Athineos, D.; Kang, T.W.; Lasitschka, F.; Andrulis, M.; et al. A complex secretory program orchestrated by the inflammasome controls paracrine senescence. Nat. Cell. Biol. 2013, 15, 978–990. [Google Scholar] [CrossRef] [PubMed]
  88. Lee, J.Y.; Yu, K.R.; Lee, B.C.; Kang, I.; Kim, J.J.; Jung, E.J.; Kim, H.S.; Seo, Y.; Choi, S.W.; Kang, K.S. GATA4-dependent regulation of the secretory phenotype via MCP-1 underlies lamin a-mediated human mesenchymal stem cell aging. Exp. Mol. Med. 2018, 50, 1–12. [Google Scholar] [CrossRef] [Green Version]
  89. Luciano-Mateo, F.; Cabré, N.; Baiges-Gaya, G.; Fernández-Arroyo, S.; Hernández-Aguilera, A.; Rodríguez-Tomàs, E.; Arenas, M.; Camps, J.; Menéndez, J.A.; Joven, J. Systemic overexpression of C-C motif chemokine ligand 2 promotes metabolic dysregulation and premature death in mice with accelerated aging. Aging 2020, 12, 20001–20023. [Google Scholar] [CrossRef] [PubMed]
  90. Hoyt, L.R.; Randall, M.J.; Ather, J.L.; DePuccio, D.P.; Landry, C.C.; Qian, X.; Janssen-Heininger, Y.M.; van der Vliet, A.; Dixon, A.E.; Amiel, E.; et al. Mitochondrial ROS induced by chronic ethanol exposure promote hyper-activation of the NLRP3 inflammasome. Redox. Biol. 2017, 12, 883–896. [Google Scholar] [CrossRef]
  91. Lavallard, V.; Cottet-Dumoulin, D.; Wassmer, C.H.; Rouget, C.; Parnaud, G.; Brioudes, E.; Lebreton, F.; Bellofatto, K.; Berishvili, E.; Berney, T.; et al. NLRP3 inflammasome is activated in rat pancreatic islets by transplantation and hypoxia. Sci. Rep. 2020, 10, 7011. [Google Scholar] [CrossRef]
  92. Fusco, R.; Gugliandolo, E.; Siracusa, R.; Scuto, M.; Cordaro, M.; D’Amico, R.; Evangelista, M.; Peli, A.; Peritore, A.F.; Impellizzeri, D.; et al. Formyl peptide receptor 1 signaling in acute inflammation and neural differentiation induced by traumatic brain injury. Biology 2020, 9, 238. [Google Scholar] [CrossRef]
  93. González-Muniesa, P.; Mártinez-González, M.A.; Hu, F.B.; Després, J.P.; Matsuzawa, Y.; Loos, R.J.F.; Moreno, L.A.; Bray, G.A.; Martinez, J.A. Obesity. Nat. Rev. Dis. Primers. 2017, 15, 17034. [Google Scholar] [CrossRef]
  94. Friedman, S.L.; Neuschwander-Tetri, B.A.; Rinella, M.; Sanyal, A.J. Mechanisms of NAFLD development and therapeutic strategies. Nat. Med. 2018, 24, 908–922. [Google Scholar] [CrossRef]
  95. You, K.; Wang, L.; Chou, C.H.; Liu, K.; Nakata, T.; Jaiswal, A.; Yao, J.; Lefkovith, A.; Omar, A.; Perrigoue, J.G.; et al. QRICH1 dictates the outcome of ER stress through transcriptional control of proteostasis. Science 2021, 371, eabb6896. [Google Scholar] [CrossRef] [PubMed]
  96. Lee, J.M.; Park, S.; Lee, D.; Ginting, R.P.; Lee, M.R.; Lee, M.W.; Han, J. Reduction in endoplasmic reticulum stress activates beige adipocytes differentiation and alleviates high fat diet-induced metabolic phenotypes. Biochim. Biophys. Acta Mol. Basis Dis. 2021, 1867, 166099. [Google Scholar] [CrossRef] [PubMed]
  97. Scully, T.; Ettela, A.; LeRoith, D.; Gallagher, E.J. Obesity, type 2 diabetes, and cancer risk. Front. Oncol. 2021, 10, 615375. [Google Scholar] [CrossRef] [PubMed]
  98. Srinivas, A.N.; Suresh, D.; Santhekadur, P.K.; Suvarna, D.; Kumar, D.P. Extracellular vesicles as inflammatory drivers in NAFLD. Front. Immunol. 2021, 11, 627424. [Google Scholar] [CrossRef] [PubMed]
  99. Dommel, S.; Blüher, M. Does C-C motif chemokine ligand 2 (CCL2) link obesity to a pro-inflammatory State? Int. J. Mol. Sci. 2021, 22, 1500. [Google Scholar] [CrossRef]
  100. Vieira, E.; Mirizio, G.G.; Barin, G.R.; de Andrade, R.V.; Nimer, N.F.S.; La Sala, L. Clock genes, inflammation and the immune system-implications for diabetes, obesity and neurodegenerative diseases. Int. J. Mol. Sci. 2020, 21, 9743. [Google Scholar] [CrossRef]
  101. Kawai, T.; Autieri, M.V.; Scalia, R. Adipose tissue inflammation and metabolic dysfunction in obesity. Am. J. Physiol. Cell. Physiol. 2021, 320, C375–C391. [Google Scholar] [CrossRef]
  102. Michailidou, Z.; Gomez-Salazar, M.; Alexaki, V.I. Innate immune cells in the adipose tissue in health and metabolic disease. J. Innate Immun. 2021, 13, 1–27. [Google Scholar] [CrossRef]
  103. Ruggiero, A.D.; Key, C.C.; Kavanagh, K. Adipose tissue macrophage polarization in healthy and unhealthy obesity. Front. Nutr. 2021, 8, 625331. [Google Scholar] [CrossRef]
  104. Kwaifa, I.K.; Bahari, H.; Yong, Y.K.; Noor, S.M. Endothelial dsfunction in obesity-induced inflammation: Molecular mechanisms and clinical implications. Biomolecules 2020, 10, 291. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Ni, Y.; Ni, L.; Zhuge, F.; Xu, L.; Fu, Z.; Ota, T. Adipose tissue macrophage phenotypes and characteristics: The key to insulin resistance in obesity and metabolic disorders. Obesity 2020, 28, 225–234. [Google Scholar] [CrossRef]
  106. Baiges-Gaya, G.; Fernández-Arroyo, S.; Luciano-Mateo, F.; Cabré, N.; Rodríguez-Tomàs, E.; Hernández-Aguilera, A.; Castañé, H.; Romeu, M.; Nogués, M.R.; Camps, J.; et al. Hepatic metabolic adaptation and adipose tissue expansion are altered in mice with steatohepatitis induced by high-fat high sucrose diet. J. Nutr. Biochem. 2021, 89, 108559. [Google Scholar] [CrossRef]
  107. Ferré, N.; Feliu, A.; García-Heredia, A.; Marsillach, J.; París, N.; Zaragoza-Jordana, M.; Mackness, B.; Mackness, M.; Escribano, J.; Closa-Monasterolo, R.; et al. Impaired paraoxonase-1 status in obese children. Relationships with insulin resistance and metabolic syndrome. Clin. Biochem. 2013, 46, 1830–1836. [Google Scholar] [CrossRef]
  108. Luciano-Mateo, F.; Cabré, N.; Nadal, M.; García-Heredia, A.; Baiges-Gaya, G.; Hernández-Aguilera, A.; Camps, J.; Joven, J.; Domingo, J.L. Serum concentrations of trace elements and their relationships with paraoxonase-1 in morbidly obese women. J. Trace Elem. Med. Biol. 2018, 48, 8–15. [Google Scholar] [CrossRef] [PubMed]
  109. Sureda, A.; Mestre-Alfaro, A.; Banquells, M.; Riera, J.; Drobnic, F.; Camps, J.; Joven, J.; Tur., J.A.; Pons, A. Exercise in a hot environment influences plasma anti-inflammatory and antioxidant status in well-trained athletes. J. Therm. Biol. 2015, 47, 91–98. [Google Scholar] [CrossRef]
  110. Ferré, N.; Camps, J.; Fernández-Ballart, J.; Arija, V.; Murphy, M.M.; Ceruelo, S.; Biarnés, E.; Vilella, E.; Tous, M.; Joven, J. Regulation of serum paraoxonase activity by genetic, nutritional, and lifestyle factors in the general population. Clin. Chem. 2003, 49, 1491–1497. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  111. Kupczyk, D.; Bilski, R.; Sokołowski, K.; Pawłowska, M.; Woźniak, A.; Szewczyk-Golec, K. Paraoxonase 1: The lectin-like oxidized LDL receptor type I and oxidative stress in the blood of men with type II obesity. Dis. Mark. 2019, 2019, 6178017. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  112. Camps, J.; Joven, J. Chemokine ligand 2 and paraoxonase-1 in non-alcoholic fatty liver disease: The search for alternative causative factors. World J. Gastroenterol. 2015, 21, 2875–2882. [Google Scholar] [CrossRef] [PubMed]
  113. Camps, J.; Hernandez-Aguilera, A.; Garcia-Heredia, A.; Cabre, N.; Luciano-Mateo, F.; Arenas, M.; Joven, J. Relationships between metformin, paraoxonase-1 and the chemokine (C-C Motif) ligand 2. Curr. Clin. Pharmacol. 2016, 11, 250–258. [Google Scholar] [CrossRef]
  114. Marsillach, J.; Bertran, N.; Camps, J.; Ferré, N.; Riu, F.; Tous, M.; Coll, B.; Alonso- Villaverde, C.; Joven, J. The role of circulating monocyte chemoattractant protein-1 as a marker of hepatic inflammation in patients with chronic liver disease. Clin. Biochem. 2005, 38, 1138–1140. [Google Scholar] [CrossRef]
  115. Diaz Soto, M.P.; Lim, J.K. Evaluating the therapeutic potential of cenicriviroc in the treatment of nonalcoholic steatohepatitis with fibrosis: A brief report on emerging data. Hepat. Med. 2020, 12, 115–123. [Google Scholar] [CrossRef]
  116. Samaan, M.C.; Obeid, J.; Nguyen, T.; Thabane, L.; Timmons, B.W. Chemokine (C-C motif) Ligand 2 is a potential biomarker of inflammation & physical fitness in obese children: A cross-sectional study. BMC Pediatr. 2013, 13, 47. [Google Scholar] [CrossRef] [Green Version]
  117. Bodo, M.J.; Jimenez, E.Y.; Conn, C.; Dye, A.; Pomo, P.; Kolkmeyer, D.; Orlando, R.; Kong, A.S. Association between circulating CCL2 levels and modifiable behaviors in overweight and obese adolescents: A cross-sectional pilot study. J. Pediatr. Endocrinol. Metab. 2016, 29, 441–449. [Google Scholar] [CrossRef]
  118. Rull, A.; Camps, J.; Alonso-Villaverde, C.; Joven, J. Insulin resistance, inflammation, and obesity: Role of monocyte chemoattractant protein-1 (or CCL2) in the regulation of metabolism. Mediat. Inflamm. 2010, 2010, 326580. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  119. Zhao, L.; Fan, M.; Zhao, L.; Yun, H.; Yang, Y.; Wang, C.; Qin, D. Fibroblast growth factor 1 ameliorates adipose tissue inflammation and systemic insulin resistance via enhancing adipocyte mTORC2/Rictor signal. J. Cell. Mol. Med. 2020, 24, 12813–12825. [Google Scholar] [CrossRef] [PubMed]
  120. Luciano-Mateo, F.; Cabré, N.; Fernández-Arroyo, S.; Baiges-Gaya, G.; Hernández- Aguilera, A.; Rodríguez-Tomàs, E.; Muñoz-Pinedo, C.; Menéndez, J.A.; Camps, J.; Joven, J. Chemokine C-C motif ligand 2 overexpression drives tissue-specific metabolic responses in the liver and muscle of mice. Sci. Rep. 2020, 10, 11954. [Google Scholar] [CrossRef] [PubMed]
  121. Mato, J.M.; Lu, S.C. Role of S-adenosyl-L-methionine in liver health and injury. Hepatology 2007, 45, 1306–1312. [Google Scholar] [CrossRef] [PubMed]
  122. Hernández-Alvarez, M.I.; Sebastián, D.; Vives, S.; Ivanova, S.; Bartoccioni, P.; Kakimoto, P.; Plana, N.; Veiga, S.R.; Hernández, V.; Vasconcelos, N.; et al. Deficient endoplasmic reticulum-mitochondrial phosphatidylserine transfer causes liver disease. Cell 2019, 177, 881–895.e17. [Google Scholar] [CrossRef] [PubMed]
  123. Rodríguez-Gallego, E.; Guirro, M.; Riera-Borrull, M.; Hernández-Aguilera, A.; Mariné-Casadó, R.; Fernández-Arroyo, S.; Beltrán-Debón, R.; Sabench, F.; Hernández, M.; del Castillo, D.; et al. Mapping of the circulating metabolome reveals α-ketoglutarate as a predictor of morbid obesity-associated non-alcoholic fatty liver disease. Int. J. Obes. 2015, 39, 279–287. [Google Scholar] [CrossRef]
  124. Hernández-Aguilera, A.; Casacuberta, N.; Castañé, H.; Fibla, M.; Fernández-Arroyo, S.; Fort-Gallifa, I.; París, M.; Sabench, F.; Del Castillo, D.; Baiges-Gaya, G.; et al. Nonalcoholic steatohepatitis modifies serum iron-related variables in patients with morbid obesity. Biol. Trace Elem. Res. 2021. [Google Scholar] [CrossRef] [PubMed]
  125. Auguet, T.; Bertran, L.; Binetti, J.; Aguilar, C.; Martínez, S.; Sabench, F.; Lopez-Dupla, J.M.; Porras, J.A.; Riesco, D.; Del Castillo, D.; et al. Relationship between IL-8 circulating levels and TLR2 hepatic expression in women with morbid obesity and nonalcoholic steatohepatitis. Int. J. Mol. Sci. 2020, 21, 4189. [Google Scholar] [CrossRef]
  126. Cabré, N.; Gil, M.; Amigó, N.; Luciano-Mateo, F.; Baiges-Gaya, G.; Fernández-Arroyo, S.; Rodríguez-Tomàs, E.; Hernández-Aguilera, A.; Castañé, H.; París, M.; et al. Laparoscopic sleeve gastrectomy alters 1H-NMR-measured lipoprotein and glycoprotein profile in patients with severe obesity and nonalcoholic fatty liver disease. Sci. Rep. 2021, 11, 1343. [Google Scholar] [CrossRef]
  127. Cabré, N.; Luciano-Mateo, F.; Chapski, D.J.; Baiges-Gaya, G.; Fernández-Arroyo, S.; Hernández-Aguilera, A.; Castañé, H.; Rodríguez-Tomàs, E.; París, M.; Sabench, F.; et al. Glutaminolysis-induced mTORC1 activation drives non-alcoholic steatohepatitis progression. J. Hepatol. 2021. Epub ahead of print. [Google Scholar] [CrossRef]
  128. Roth, C.L.; Molica, F.; Kwak, B.R. Browning of white adipose tissue as a therapeutic tool in the fight against atherosclerosis. Metabolites 2021, 11, 319. [Google Scholar] [CrossRef]
  129. Skiba, D.S.; Nosalski, R.; Mikolajczyk, T.P.; Siedlinski, M.; Rios, F.J.; Montezano, A.C.; Jawien, J.; Olszanecki, R.; Korbut, R.; Czesnikiewicz-Guzik, M.; et al. Anti-atherosclerotic effect of the angiotensin 1-7 mimetic AVE0991 is mediated by inhibition of perivascular and plaque inflammation in early atherosclerosis. Br. J. Pharmacol. 2017, 174, 4055–4069. [Google Scholar] [CrossRef] [PubMed]
  130. Nosalski, R.; Guzik, T.J. Perivascular adipose tissue inflammation in vascular disease. Br. J. Pharmacol. 2017, 174, 3496–3513. [Google Scholar] [CrossRef] [Green Version]
  131. Ravindran, D.; Ridiandries, A.; Vanags, L.Z.; Henriquez, R.; Cartland, S.; Tan, J.T.; Bursill, C.A. Chemokine binding protein ‘M3’ limits atherosclerosis in apolipoprotein E-/- mice. PLoS ONE 2017, 12, e0173224. [Google Scholar] [CrossRef] [PubMed]
  132. Braunersreuther, V.; Pellieux, C.; Pelli, G.; Burger, F.; Steffens, S.; Montessuit, C.; Weber, C.; Proudfoot, A.; Mach, F.; Arnaud, C. Chemokine CCL5/RANTES inhibition reduces myocardial reperfusion injury in atherosclerotic mice. J. Mol. Cell. Cardiol. 2010, 48, 789–798. [Google Scholar] [CrossRef]
  133. França, C.N.; Izar, M.C.O.; Hortêncio, M.N.S.; do Amaral, J.B.; Ferreira, C.E.S.; Tuleta, I.D.; Fonseca, F.A.H. Monocyte subtypes and the CCR2 chemokine receptor in cardiovascular disease. Clin. Sci. 2017, 131, 1215–1224. [Google Scholar] [CrossRef] [Green Version]
  134. Bianconi, V.; Sahebkar, A.; Atkin, S.L.; Pirro, M. The regulation and importance of monocyte chemoattractant protein-1. Curr. Opin. Hematol. 2018, 25, 44–51. [Google Scholar] [CrossRef]
  135. Hartmann, P.; Schober, A.; Weber, C. Chemokines and microRNAs in atherosclerosis. Cell. Mol. Life Sci. 2015, 72, 3253–3266. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  136. Takeya, M.; Yoshimura, T.; Leonard, E.J.; Takahashi, K. Detection of monocyte chemoattractant protein-1 in human atherosclerotic lesions by an anti-monocyte chemoattractant protein-1 monoclonal antibody. Hum. Pathol. 1993, 24, 534–539. [Google Scholar] [CrossRef]
  137. Nelken, N.A.; Coughlin, S.R.; Gordon, D.; Wilcox, J.N. Monocyte chemoattractant protein-1 in human atheromatous plaques. J. Clin. Investig. 1991, 88, 1121–1127. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  138. Hernández-Aguilera, A.; Fibla, M.; Cabré, N.; Luciano-Mateo, F.; Camps, J.; Fernández-Arroyo, S.; Martín-Paredero, V.; Menendez, J.A.; Sirvent, J.J.; Joven, J. Chemokine (C-C motif) ligand 2 and coronary artery disease: Tissue expression of functional and atypical receptors. Cytokine 2020, 126, 154923. [Google Scholar] [CrossRef]
  139. Georgakis, M.K.; Malik, R.; Björkbacka, H.; Pana, T.A.; Demissie, S.; Ayers, C.; Elhadad, M.A.; Fornage, M.; Beiser, A.S.; Benjamin, E.J.; et al. Circulating monocyte chemoattractant protein-1 and risk of stroke: Meta-analysis of population-based studies involving 17180 Individuals. Circ. Res. 2019, 125, 773–782. [Google Scholar] [CrossRef] [Green Version]
  140. Georgakis, M.K.; Gill, D.; Rannikmäe, K.; Traylor, M.; Anderson, C.D.; Lee, J.M.; Kamatani, Y.; Hopewell, J.C.; Worrall, B.B.; Bernhagen, J.; et al. Genetically determined levels of circulating cytokines and risk of stroke. Circulation 2019, 139, 256–268. [Google Scholar] [CrossRef] [PubMed]
  141. Savelieva, I.; Camm, A.J. A new biomarker in atrial fibrillation: Monocyte chemoattractant protein-1-induced protein. Cardiology 2019, 144, 122–124. [Google Scholar] [CrossRef] [PubMed]
  142. Li, L.; Lou, W.; Li, H.; Zhu, Y.; Huang, X. Upregulated C-C motif chemokine ligand 2 promotes ischemic stroke via chemokine signaling pathway. Ann. Vasc. Surg. 2020, 68, 476–486. [Google Scholar] [CrossRef]
  143. Feingold, K.R.; Grunfeld, C. Effect of inflammation on HDL structure and function. Curr. Opin. Lipidol. 2016, 27, 521–530. [Google Scholar] [CrossRef] [PubMed]
  144. Cervellati, C.; Vigna, G.B.; Trentini, A.; Sanz, J.M.; Zimetti, F.; Dalla Nora, E.; Morieri, M.L.; Zuliani, G.; Passaro, A. Paraoxonase-1 activities in individuals with different HDL circulating levels: Implication in reverse cholesterol transport and early vascular damage. Atherosclerosis 2019, 285, 64–70. [Google Scholar] [CrossRef]
  145. Vaisar, T.; Kanter, J.E.; Wimberger, J.; Irwin, A.D.; Gauthier, J.; Wolfson, E.; Bahnam, V.; Wu, I.H.; Shah, H.; Keenan, H.A.; et al. High concentration of medium-sized HDL particles and enrichment in HDL paraoxonase 1 associate with protection from vascular complications in people with long-standing type 1 diabetes. Diabetes Care 2020, 43, 178–186. [Google Scholar] [CrossRef] [PubMed]
  146. White, C.R.; Anantharamaiah, G.M. Cholesterol reduction and macrophage function: Role of paraoxonases. Curr. Opin. Lipidol. 2017, 28, 397–402. [Google Scholar] [CrossRef]
  147. Sikora, M.; Bretes, E.; Perła-Kaján, J.; Lewandowska, I.; Marczak, Ł.; Jakubowski, H. Genetic attenuation of paraoxonase 1 activity induces proatherogenic changes in plasma proteomes of mice and humans. Antioxidants 2020, 9, 1198. [Google Scholar] [CrossRef]
  148. Çetin, M.; Tunçdemir, P.; Karaman, K.; Yel, S.; Karaman, E.; Özgökçe, M.; Kömüroğlu, A.U. Cardiovascular evaluation and serum paraoxonase-1 levels in adolescents with polycystic ovary syndrome. J. Obstet. Gynaecol. 2020, 40, 90–95. [Google Scholar] [CrossRef] [PubMed]
  149. Shokri, Y.; Variji, A.; Nosrati, M.; Khonakdar-Tarsi, A.; Kianmehr, A.; Kashi, Z.; Bahar, A.; Bagheri, A.; Mahrooz, A. Importance of paraoxonase 1 (PON1) as an antioxidant and antiatherogenic enzyme in the cardiovascular complications of type 2 diabetes: Genotypic and phenotypic evaluation. Diabetes Res. Clin. Pract. 2020, 161, 108067. [Google Scholar] [CrossRef]
  150. Khalil, A.; Fulop, T.; Berrougui, H. Role of paraoxonase1 in the regulation of high-density lipoprotein functionality and in cardiovascular protection. Antioxid. Redox Signal. 2021, 34, 191–200. [Google Scholar] [CrossRef]
  151. Khosravi, M.; Poursaleh, A.; Ghasempour, G.; Farhad, S.; Najafi, M. The effects of oxidative stress on the development of atherosclerosis. Biol. Chem. 2019, 400, 711–732. [Google Scholar] [CrossRef]
  152. Ponce-Ruiz, N.; Murillo-González, F.E.; Rojas-García, A.E.; Barrón-Vivanco, B.S.; Bernal-Hernández, Y.Y.; González-Arias, C.A.; Ortega-Cervantes, L.; Ponce-Gallegos, J.; López-Guarnido, O.; Medina-Díaz, I.M. PON1 status and homocysteine levels as potential biomarkers for cardiovascular disease. Exp. Gerontol. 2020, 140, 111062. [Google Scholar] [CrossRef]
  153. Corsetti, J.P.; Sparks, C.E.; James, R.W.; Bakker, S.J.L.; Dullaart, R.P.F. Low serum paraoxonase-1 activity associates with incident cardiovascular disease risk in subjects with concurrently high levels of high-density lipoprotein cholesterol and C-reactive protein. J. Clin. Med. 2019, 8, 1357. [Google Scholar] [CrossRef] [Green Version]
  154. Kunutsor, S.K.; Bakker, S.J.; James, R.W.; Dullaart, R.P. Serum paraoxonase-1 activity and risk of incident cardiovascular disease: The PREVEND study and meta-analysis of prospective population studies. Atherosclerosis 2016, 245, 143–154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  155. Lent-Schochet, D.; McLaughlin, M.; Ramakrishnan, N.; Jialal, I. Exploratory metabolomics of metabolic syndrome: A status report. World J. Diabetes 2019, 10, 23–36. [Google Scholar] [CrossRef]
  156. Reddy, P.; Lent-Schochet, D.; Ramakrishnan, N.; McLaughlin, M.; Jialal, I. Metabolic syndrome is an inflammatory disorder: A conspiracy between adipose tissue and phagocytes. Clin. Chim. Acta 2019, 496, 35–44. [Google Scholar] [CrossRef] [PubMed]
  157. Pouralijan Amiri, M.; Khoshkam, M.; Salek, R.M.; Madadi, R.; Faghanzadeh Ganji, G.; Ramazani, A. Metabolomics in early detection and prognosis of acute coronary syndrome. Clin. Chim. Acta 2019, 495, 43–53. [Google Scholar] [CrossRef] [PubMed]
  158. Iida, M.; Harada, S.; Takebayashi, T. Application of metabolomics to epidemiological studies of atherosclerosis and cardiovascular disease. J. Atheroscler. Thromb. 2019, 26, 747–757. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  159. Ganna, A.; Salihovic, S.; Sundström, J.; Broeckling, C.D.; Hedman, A.K.; Magnusson, P.K.; Pedersen, N.L.; Larsson, A.; Siegbahn, A.; Zilmer, M.; et al. Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease. PLoS Genet. 2014, 10, e1004801. [Google Scholar] [CrossRef]
  160. Stegemann, C.; Pechlaner, R.; Willeit, P.; Langley, S.R.; Mangino, M.; Mayr, U.; Menni, C.; Moayyeri, A.; Santer, P.; Rungger, G.; et al. Lipidomics profiling and risk of cardiovascular disease in the prospective population-based Bruneck study. Circulation 2014, 129, 1821–1831. [Google Scholar] [CrossRef] [Green Version]
  161. Shah, S.H.; Sun, J.L.; Stevens, R.D.; Bain, J.R.; Muehlbauer, M.J.; Pieper, K.S.; Haynes, C.; Hauser, E.R.; Kraus, W.E.; Granger, C.B.; et al. Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease. Am. Heart J. 2012, 163, 844–850.e1. [Google Scholar] [CrossRef]
  162. Haas, J.; Frese, K.S.; Sedaghat-Hamedani, F.; Kayvanpour, E.; Tappu, R.; Nietsch, R.; Tugrul, O.F.; Wisdom, M.; Dietrich, C.; Amr, A.; et al. Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy. Int. J. Mol. Sci. 2021, 22, 1999. [Google Scholar] [CrossRef]
  163. Van Driel, B.O.; Schuldt, M.; Algül, S.; Levin, E.; Güclü, A.; Germans, T.; Rossum, A.C.V.; Pei, J.; Harakalova, M.; Baas, A.; et al. Metabolomics in Severe Aortic Stenosis Reveals Intermediates of Nitric Oxide Synthesis as Most Distinctive Markers. Int. J. Mol. Sci. 2021, 22, 3569. [Google Scholar] [CrossRef]
  164. Rull, A.; Hernandez-Aguilera, A.; Fibla, M.; Sepulveda, J.; Rodríguez-Gallego, E.; Riera-Borrull, M.; Sirvent, J.J.; Martín-Paredero, V.; Menendez, J.A.; Camps, J.; et al. Understanding the role of circulating chemokine (C-C motif) ligand 2 in patients with chronic ischemia threatening the lower extremities. Vasc. Med. 2014, 19, 442–451. [Google Scholar] [CrossRef] [PubMed]
  165. Fort-Gallifa, I.; García-Heredia, A.; Hernández-Aguilera, A.; Simó, J.M.; Sepúlveda, J.; Martín-Paredero, V.; Camps, J.; Joven, J. Biochemical indices of oxidative stress and inflammation in the evaluation of peripheral artery disease. Free Radic. Biol. Med. 2016, 97, 568–576. [Google Scholar] [CrossRef]
  166. Fort-Gallifa, I.; Hernández-Aguilera, A.; García-Heredia, A.; Cabré, N.; Luciano-Mateo, F.; Simó, J.M.; Martín-Paredero, V.; Camps, J.; Joven, J. Galectin-3 in peripheral artery disease. Relationships with markers of oxidative stress and inflammation. Int. J. Mol Sci. 2017, 18, 973. [Google Scholar] [CrossRef]
  167. Cabré, N.; Luciano-Mateo, F.; Arenas, M.; Nadal, M.; Baiges-Gaya, G.; Hernández-Aguilera, A.; Fort-Gallifa, I.; Rodríguez, E.; Riu, F.; Camps, J.; et al. Trace element concentrations in breast cancer patients. Breast 2018, 42, 142–149. [Google Scholar] [CrossRef]
  168. Hernández-Aguilera, A.; Fernández-Arroyo, S.; Cabre, N.; Luciano-Mateo, F.; Baiges-Gaya, G.; Fibla, M.; Martín-Paredero, V.; Menendez, J.A.; Camps, J.; Joven, J. Plasma energy-balance metabolites discriminate asymptomatic patients with peripheral artery disease. Mediat. Inflamm. 2018, 2018, 2760272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  169. Brown, K.A. Metabolic pathways in obesity-related breast cancer. Nat. Rev. Endocrinol. 2021, 17, 350–363. [Google Scholar] [CrossRef]
  170. Michalak, S.; Szubert, S.; Moszynski, R.; Sajdak, S.; Szpurek, D. Serum arylesterase and paraoxonase activities in patients with ovarian tumors. Taiwan J. Obstet. Gynecol. 2014, 53, 490–493. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  171. Arenas, M.; Rodríguez, E.; Sahebkar, A.; Sabater, S.; Rizo, D.; Pallisé, O.; Hernández, M.; Riu, F.; Camps, J.; Joven, J. Paraoxonase-1 activity in patients with cancer: A systematic review and meta-analysis. Crit. Rev. Oncol. Hematol. 2018, 127, 6–14. [Google Scholar] [CrossRef] [PubMed]
  172. Arenas, M.; García-Heredia, A.; Cabré, N.; Luciano-Mateo, F.; Hernández-Aguilera, A.; Sabater, S.; Bonet, M.; Gascón, M.; Fernández-Arroyo, S.; Fort-Gallifa, I.; et al. Effect of radiotherapy on activity and concentration of serum paraoxonase-1 in breast cancer patients. PLoS ONE 2017, 12, e0188633. [Google Scholar] [CrossRef] [Green Version]
  173. Rodríguez-Tomàs, E.; Murcia, M.; Arenas, M.; Arguís, M.; Gil, M.; Amigó, N.; Correig, X.; Torres, L.; Sabater, S.; Baiges-Gayà, G.; et al. Serum paraoxonase-1-related variables and lipoprotein profile in patients with lung or head and neck cancer: Effect of radiotherapy. Antioxidants 2019, 8, 213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  174. Rodríguez-Tomàs, E.; Arenas, M.; Gómez, J.; Acosta, J.; Trilla, J.; López, Y.; Árquez, M.; Torres, L.; Araguas, P.; Hernández-Aguilera, A.; et al. Identification of potential metabolic biomarkers of rectal cancer and of the effect of neoadjuvant radiochemotherapy. PLoS ONE 2021, 16, e0250453. [Google Scholar] [CrossRef]
  175. Camuzcuoglu, H.; Arioz, D.T.; Toy, H.; Kurt, S.; Celik, H.; Erel, O. Serum paraoxonase and arylesterase activities in patients with epithelial ovarian cancer. Gynecol. Oncol. 2009, 112, 481–485. [Google Scholar] [CrossRef] [PubMed]
  176. Krzystek-Korpacka, M.; Boehm, D.; Matusiewicz, M.; Diakowska, D.; Grabowski, K.; Gamian, A. Paraoxonase 1 (PON1) status in gastroesophageal malignancies and associated paraneoplastic syndromes-connection with inflammation. Clin. Biochem. 2008, 41, 804–811. [Google Scholar] [CrossRef]
  177. Afsar, C.U.; Gunaldı, M.; Okuturlar, Y.; Gedikbası, A.; Tiken, E.E.; Kahraman, S.; Karaca, F.; Ercolak, V.; Karabulut, M. Paraoxonase-1 and arylesterase activities in patients with colorectal cancer. Int. J. Clin. Exp. Med. 2015, 8, 21599–21604. [Google Scholar] [PubMed]
  178. Balci, H.; Genc, H.; Papila, C.; Can, G.; Papila, B.; Yanardag, H.; Uzun, H. Serum lipid hydroperoxide levels and paraoxonase activity in patients with lung, breast, and colorectal cancer. J. Clin. Lab. Anal. 2012, 26, 155–160. [Google Scholar] [CrossRef]
  179. Sehitogulları, A.; Aslan, M.; Sayır, F.; Kahraman, A.; Demir, H. Serum paraoxonase-1 enzyme activities and oxidative stress levels in patients with esophageal squamous cell carcinoma. Redox Rep. 2014, 19, 199–205. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  180. Bulbuller, N.; Eren, E.; Ellidag, H.Y.; Oner, O.Z.; Sezer, C.; Aydin, O.; Yılmaz, N. Diagnostic value of thiols, paraoxonase 1, arylesterase and oxidative balance in colorectal cancer in human. Neoplasma 2013, 60, 419–424. [Google Scholar] [CrossRef] [Green Version]
  181. Malik, U.U.; Siddiqui, I.A.; Hashim, Z.; Zarina, S. Measurement of serum paraoxonase activity and MDA concentrations in patients suffering with oral squamous cell carcinoma. Clin. Chim. Acta. 2014, 430, 38–42. [Google Scholar] [CrossRef]
  182. Iftimie, S.; García-Heredia, A.; Pujol-Bosch, F.; Pont-Salvadó, A.; López-Azcona, A.F.; Hernández-Aguilera, A.; Cabré, N.; Luciano-Mateo, F.; Fort-Gallifa, I.; Castro, A.; et al. Serum paraoxonase-1 concentration as a potential predictor of urinary bladder cancer recurrence. A five year follow-up study. Arch. Med. Res. 2018, 49, 119–122. [Google Scholar] [CrossRef]
  183. Li, R.; Wen, A.; Lin, J. Pro-inflammatory cytokines in the formation of the pre-metastatic niche. Cancers 2020, 12, 3752. [Google Scholar] [CrossRef]
  184. Tao, L.; Liu, S.; Xiong, J.; Yang, H.; Wu, Y.; Xu, A.; Gong, Y. IL-1β promotes cervical cancer through activating NF-κB/CCL-2. Int. J. Clin. Exp. Pathol. 2021, 14, 426–433. [Google Scholar] [PubMed]
  185. Adekoya, T.O.; Richardson, R.M. Cytokines and chemokines as mediators of prostate cancer metastasis. Int. J. Mol. Sci. 2020, 21, 4449. [Google Scholar] [CrossRef] [PubMed]
  186. Fang, W.B.; Sofia Acevedo, D.; Smart, C.; Zinda, B.; Alissa, N.; Warren, K.; Fraga, G.; Huang, L.C.; Shyr, Y.; Li, W.; et al. Expression of CCL2/CCR2 signaling proteins in breast carcinoma cells is associated with invasive progression. Sci. Rep. 2021, 11, 8708. [Google Scholar] [CrossRef] [PubMed]
  187. Lee, S.; Hong, J.H.; Kim, J.S.; Yoon, J.S.; Chun, S.H.; Hong, S.A.; Kim, E.J.; Kang, K.; Lee Kang, J.; Ko, Y.H.; et al. Cancer-associated fibroblasts activated by miR-196a promote the migration and invasion of lung cancer cells. Cancer Lett. 2021, 508, 92–103. [Google Scholar] [CrossRef]
  188. Liu, X.; Zheng, S.; Peng, Y.; Zhuang, J.; Yang, Y.; Xu, Y.; Guan, G. Construction of the prediction model for locally advanced rectal cancer following neoadjuvant chemoradiotherapy based on pretreatment tumor-infiltrating macrophage-associated biomarkers. Onco. Targets Ther. 2021, 14, 2599–2610. [Google Scholar] [CrossRef]
  189. Sun, X.; Ye, D.; Du, L.; Qian, Y.; Jiang, X.; Mao, Y. Genetically predicted levels of circulating cytokines and prostate cancer risk: A Mendelian randomization study. Int. J. Cancer 2020, 147, 2469–2478. [Google Scholar] [CrossRef] [PubMed]
  190. Vander Heiden, M.G.; Cantley, L.C.; Thompson, C.B. Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science 2009, 324, 1029–1033. [Google Scholar] [CrossRef] [Green Version]
  191. Warburg, O. On the origin of cancer cells. Science 1956, 123, 309–314. [Google Scholar] [CrossRef] [PubMed]
  192. Bott, A.J.; Maimouni, S.; Zong, W.X. The pleiotropic effects of glutamine metabolism in cancer. Cancers 2019, 11, 770. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  193. Trilla-Fuertes, L.; Gámez-Pozo, A.; López-Camacho, E.; Prado-Vázquez, G.; Zapater- Moros, A.; López-Vacas, R.; Arevalillo, J.M.; Díaz-Almirón, M.; Navarro, H.; Maín, P.; et al. Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer. BMC Cancer 2020, 20, 307. [Google Scholar] [CrossRef] [Green Version]
  194. Nguyen, T.; Kirsch, B.J.; Asaka, R.; Nabi, K.; Quinones, A.; Tan, J.; Antonio, M.J.; Camelo, F.; Li, T.; Nguyen, S.; et al. Uncovering the role of N-acetyl-aspartyl-glutamate as a glutamate reservoir in cancer. Cell Rep. 2019, 27, 491–501.e6. [Google Scholar] [CrossRef] [Green Version]
  195. Udupa, S.; Nguyen, S.; Hoang, G.; Nguyen, T.; Quinones, A.; Pham, K.; Asaka, R.; Nguyen, K.; Zhang, C.; Elgogary, A.; et al. Upregulation of the glutaminase II pathway contributes to glutamate production upon glutaminase 1 inhibition in pancreatic cancer. Proteomics 2019, 19, e1800451. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  196. Karsli-Uzunbas, G.; Guo, J.Y.; Price, S.; Teng, X.; Laddha, S.V.; Khor, S.; Kalaany, N.Y.; Jacks, T.; Chan, C.S.; Rabinowitz, J.D.; et al. Autophagy is required for glucose homeostasis and lung tumor maintenance. Cancer Discov. 2014, 4, 914–927. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  197. Guo, J.Y.; Teng, X.; Laddha, S.V.; Ma, S.; Van Nostrand, S.C.; Yang, Y.; Khor, S.; Chan, C.S.; Rabinowitz, J.D.; White, E. Autophagy provides metabolic substrates to maintain energy charge and nucleotide pools in Ras-driven lung cancer cells. Genes Dev. 2016, 30, 1704–1717. [Google Scholar] [CrossRef] [Green Version]
  198. Rabinowitz, J.D.; White, E. Autophagy and metabolism. Science 2010, 330, 1344–1348. [Google Scholar] [CrossRef] [Green Version]
  199. Sappington, D.R.; Siegel, E.R.; Hiatt, G.; Desai, A.; Penney, R.B.; Jamshidi-Parsian, A.; Griffin, R.J.; Boysen, G. Glutamine drives glutathione synthesis and contributes to radiation sensitivity of A549 and H460 lung cancer cell lines. Biochim. Biophys. Acta 2016, 1860, 836–843. [Google Scholar] [CrossRef] [Green Version]
  200. Zeng, C.; Wu, Q.; Wang, J.; Yao, B.; Ma, L.; Yang, Z.; Li, J.; Liu, B. NOX4 supports glycolysis and promotes glutamine metabolism in non-small cell lung cancer cells. Free Radic. Biol. Med. 2016, 101, 236–248. [Google Scholar] [CrossRef]
  201. Rodríguez-Tomàs, E.; Arguís, M.; Arenas, M.; Fernández-Arroyo, S.; Murcia, M.; Sabater, S.; Torres, L.; Baiges-Gayà, G.; Hernández-Aguilera, A.; Camps, J.; et al. Alterations in plasma concentrations of energy-balance-related metabolites in patients with lung, or head & neck, cancers: Effects of radiotherapy. J. Proteom. 2020, 213, 103605. [Google Scholar] [CrossRef]
  202. Vanhove, K.; Giesen, P.; Owokotomo, O.E.; Mesotten, L.; Louis, E.; Shkedy, Z.; Thomeer, M.; Adriaensens, P. The plasma glutamate concentration as a complementary tool to differentiate benign PET-positive lung lesions from lung cancer. BMC Cancer 2018, 18, 868. [Google Scholar] [CrossRef]
  203. Berker, Y.; Vandergrift, L.A.; Wagner, I.; Su, L.; Kurth, J.; Schuler, A.; Dinges, S.S.; Habbel, P.; Nowak, J.; Mark, E.; et al. Magnetic resonance spectroscopy-based metabolomic biomarkers for typing, staging, and survival estimation of early-stage human lung cancer. Sci. Rep. 2019, 9, 10319. [Google Scholar] [CrossRef] [Green Version]
  204. Michalak, S.; Rybacka-Mossakowska, J.; Ambrosius, W.; Gazdulska, J.; Gołda-Gocka, I.; Kozubski, W.; Ramlau, R. The markers of glutamate metabolism in peripheral blood mononuclear cells and neurological complications in lung cancer patients. Dis. Mark. 2016, 2016, 2895972. [Google Scholar] [CrossRef] [Green Version]
  205. Ye, G.; Liu, Y.; Yin, P.; Zeng, Z.; Huang, Q.; Kong, H.; Lu, X.; Zhong, L.; Zhang, Z.; Xu, G. Study of induction chemotherapy efficacy in oral squamous cell carcinoma using pseudotargeted metabolomics. J. Proteome Res. 2014, 13, 1994–2004. [Google Scholar] [CrossRef] [PubMed]
  206. Long, N.P.; Yoon, S.J.; Anh, N.H.; Nghi, T.D.; Lim, D.K.; Hong, Y.J.; Hong, S.S.; Kwon, S.W. A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer. Metabolomics 2018, 14, 109. [Google Scholar] [CrossRef]
  207. Arenas, M.; Rodríguez, E.; García-Heredia, A.; Fernández-Arroyo, S.; Sabater, S.; Robaina, R.; Gascón, M.; Rodríguez-Pla, M.; Cabré, N.; Luciano-Mateo, F.; et al. Metabolite normalization with local radiotherapy following breast tumor resection. PLoS ONE 2018, 13, e0207474. [Google Scholar] [CrossRef]
  208. Arenas, M.; Fernández-Arroyo, S.; Rodríguez-Tomàs, E.; Sabater, S.; Murria, Y.; Gascón, M.; Amillano, K.; Melé, M.; Camps, J.; Joven, J. Effects of radiotherapy on plasma energy metabolites in patients with breast cancer who received neoadjuvant chemotherapy. Clin. Transl. Oncol. 2020, 22, 1078–1085. [Google Scholar] [CrossRef] [PubMed]
  209. Holecek, M. Relation between glutamine, branched-chain amino acids, and protein metabolism. Nutrition 2002, 18, 130–133. [Google Scholar] [CrossRef]
  210. Hensley, C.T.; Wasti, A.T.; DeBerardinis, R.J. Glutamine and cancer: Cell biology, physiology, and clinical opportunities. J. Clin. Investig. 2013, 123, 3678–3684. [Google Scholar] [CrossRef] [Green Version]
  211. Miller, V.J.; Villamena, F.A.; Volek, J.S. Nutritional ketosis and mitohormesis: Potential implications for mitochondrial function and human health. J. Nutr. Metab. 2018, 8, 5157645. [Google Scholar] [CrossRef] [Green Version]
  212. Shimazu, T.; Hirschey, M.D.; Newman, J.; He, W.; Shirakawa, K.; Le Moan, N.; Grueter, C.A.; Lim, H.; Saunders, L.R.; Stevens, R.D.; et al. Suppression of oxidative stress by β-hydroxybutyrate, an endogenous histone deacetylase inhibitor. Science 2013, 339, 211–214. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  213. Xiao, X.; Hu, M.; Zhang, X.; Hu, J.Z. NMR-based metabolomics analysis of liver from C57BL/6 mouse exposed to ionizing radiation. Radiat. Res. 2017, 188, 44–55. [Google Scholar] [CrossRef]
  214. Mörén, L.; Wibom, C.; Bergström, P.; Johansson, M.; Antti, H.; Bergenheim, A.T. Characterization of the serum metabolome following radiation treatment in patients with high-grade gliomas. Radiat. Oncol. 2016, 11, 51. [Google Scholar] [CrossRef] [Green Version]
  215. Chai, Y.; Wang, J.; Wang, T.; Yang, Y.; Su, J.; Shi, F.; Wang, J.; Zhou, X.; He, B.; Ma, H.; et al. Application of 1H NMR spectroscopy-based metabonomics to feces of cervical cancer patients with radiation-induced acute intestinal symptoms. Radiother. Oncol. 2015, 117, 294–301. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  216. Webb, N.R. High-density lipoproteins and serum amyloid A (SAA). Curr. Atheroscler. Rep. 2021, 23, 7. [Google Scholar] [CrossRef]
  217. Namiri-Kalantari, R.; Gao, F.; Chattopadhyay, A.; Wheeler, A.A.; Navab, K.D.; Farias-Eisner, R.; Reddy, S.T. The dual nature of HDL: Anti-inflammatory and pro-inflammatory. Biofactors 2015, 41, 153–159. [Google Scholar] [CrossRef]
  218. Birner-Gruenberger, R.; Schittmayer, M.; Holzer, M.; Marsche, G. Understanding high-density lipoprotein function in disease: Recent advances in proteomics unravel the complexity of its composition and biology. Prog. Lipid Res. 2014, 56, 36–46. [Google Scholar] [CrossRef] [Green Version]
  219. Sharma, N.K.; Ferreira, B.L.; Tashima, A.K.; Brunialti, M.K.C.; Torquato, R.J.S.; Bafi, A.; Assuncao, M.; Azevedo, L.C.P.; Salomao, R. Lipid metabolism impairment in patients withsepsis secondary to hospital acquired pneumonia, a proteomic analysis. Clin. Proteom. 2019, 16, 29. [Google Scholar] [CrossRef] [PubMed]
  220. Iftimie, S.; García-Heredia, A.; Pujol, I.; Ballester, F.; Fort-Gallifa, I.; Simó, J.M.; Joven, J.; Castro, A.; Camps, J. A preliminary study of paraoxonase-1 in infected patients with an indwelling central venous catheter. Clin. Biochem. 2016, 49, 449–457. [Google Scholar] [CrossRef]
  221. Iftimie, S.; García-Heredia, A.; Pujol, I.; Ballester, F.; Fort-Gallifa, I.; Simó, J.M.; Joven, J.; Camps, J.; Castro, A. Preliminary study on serum paraoxonase-1 status and chemokine (C-C motif) ligand 2 in hospitalized elderly patients with catheter-associated asymptomatic bacteriuria. Eur. J. Clin. Microbiol. Infect. Dis. 2016, 35, 1417–1424. [Google Scholar] [CrossRef]
  222. Sans, T.; Rull, A.; Luna, J.; Mackness, B.; Mackness, M.; Joven, J.; Ibañez, M.; Pariente, R.; Rodriguez, M.; Ortin, X.; et al. Monocyte chemoattractant protein-1 and paraoxonase-1 and 3 levels in patients with sepsis treated in an intensive care unit: A preliminary report. Clin. Chem. Lab. Med. 2012, 50, 1409–1415. [Google Scholar] [CrossRef] [PubMed]
  223. Garrido, P.; Rovira, C.; Cueto, P.; Fort-Gallifa, I.; Hernández-Aguilera, A.; Cabré, N.; Luciano-Mateo, F.; García-Heredia, A.; Camps, J.; Joven, J.; et al. Effect of continuous renal-replacement therapy on paraoxonase-1-related variables in patients with acute renal failure caused by septic shock. Clin. Biochem. 2018, 61, 1–6. [Google Scholar] [CrossRef]
  224. Kucukazman, M.; Yeniova, O.; Dal, K.; Yavuz, B. Helicobacter pylori and cardiovascular disease. Eur. Rev. Med. Pharmacol. Sci. 2015, 19, 3731–3741. [Google Scholar] [PubMed]
  225. Vijayvergiya, R.; Vadivelu, R. Role of Helicobacter pylori infection in pathogenesis of atherosclerosis. World J. Cardiol. 2015, 7, 134–143. [Google Scholar] [CrossRef] [PubMed]
  226. He, C.; Yang, Z.; Lu, N.H. Helicobacter pylori: An infectious risk factor for atherosclerosis? J. Atheroscler. Thromb. 2014, 21, 1229–1242. [Google Scholar] [CrossRef] [Green Version]
  227. Aslan, M.; Nazligul, Y.; Horoz, M.; Bolukbas, C.; Bolukbas, F.F.; Gur, M.; Celik, H.; Erel, O. Serum paraoxonase-1 activity in Helicobacter pylori infected subjects. Atherosclerosis 2008, 196, 270–274. [Google Scholar] [CrossRef]
  228. Akbas, H.S.; Basyigit, S.; Suleymanlar, I.; Kemaloglu, D.; Koc, S.; Davran, F.; Demir, I.; Suleymanlar, G. The assessment of carotid intima media thickness and serum paraoxonase-1 activity in Helicobacter pylori positive subjects. Lipids Health Dis. 2010, 9, 92. [Google Scholar] [CrossRef] [Green Version]
  229. Demirpençe, O.; Sevim, B.; Yıldırım, M.; Ayan Nurlu, N.; Mert, D.; Evliyaoğlu, O. Serum paraoxonase, TAS, TOS and ceruloplasmin in brucellosis. Int. J. Clin. Exp. Med. 2014, 7, 1592–1597. [Google Scholar]
  230. Selek, S.; Cosar, N.; Kocyigit, A.; Erel, O.; Aksoy, N.; Gencer, M.; Gunak, F.; Aslan, M. PON1 activity and total oxidant status in patients with active pulmonary tuberculosis. Clin. Biochem. 2008, 41, 140–144. [Google Scholar] [CrossRef]
  231. Coll, B.; van Wijk, J.P.; Parra, S.; Castro Cabezas, M.; Hoepelman, I.M.; Alonso-Villaverde, C.; de Koning, E.J.; Camps, J.; Ferre, N.; Rabelink, T.J.; et al. Effects of rosiglitazone and metformin on postprandial paraoxonase-1 and monocyte chemoattractant protein-1 in human immunodeficiency virus-infected patients with lipodystrophy. Eur. J. Pharmacol. 2006, 544, 104–110. [Google Scholar] [CrossRef] [PubMed]
  232. Parra, S.; Marsillach, J.; Aragonès, G.; Rull, A.; Beltrán-Debón, R.; Alonso-Villaverde, C.; Joven, J.; Camps, J. Methodological constraints in interpreting serum paraoxonase-1 activity measurements: An example from a study in HIV-infected patients. Lipids Health Dis. 2010, 9, 32. [Google Scholar] [CrossRef] [Green Version]
  233. Parra, S.; Alonso-Villaverde, C.; Coll, B.; Ferré, N.; Marsillach, J.; Aragonès, G.; Mackness, M.; Mackness, B.; Masana, L.; Joven, J.; et al. Serum paraoxonase-1 activity and concentration are influenced by human immunodeficiency virus infection. Atherosclerosis 2007, 194, 175–181. [Google Scholar] [CrossRef]
  234. Parra, S.; Marsillach, J.; Aragonés, G.; Beltrán, R.; Montero, M.; Coll, B.; Mackness, B.; Mackness, M.; Alonso-Villaverde, C.; Joven, J.; et al. Paraoxonase-1 gene haplotypes are associated with metabolic disturbances, atherosclerosis, and immunologic outcome in HIV-infected patients. J. Infect. Dis. 2010, 201, 627–634. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  235. Viladés, C.; Broch, M.; Plana, M.; Domingo, P.; Alonso-Villaverde, C.; Pedrol, E.; Knobel, H.; Dalmau, D.; Peraire, J.; Gutiérrez, C.; et al. Effect of genetic variants of CCR2 and CCL2 on the natural history of HIV-1 infection: CCL2-2518GG is overrepresented in a cohort of Spanish HIV-1-infected subjects. J. Acquir. Immune Defic. Syndr. 2007, 44, 132–138. [Google Scholar] [CrossRef] [PubMed]
  236. Alonso-Villaverde, C.; Aragonès, G.; Beltrán-Debón, R.; Fernández-Sender, L.; Rull, A.; Rodríguez-Sanabria, F.; Marsillach, J.; Pardo-Reche, P.; Camps, J.; Joven, J. Host—Pathogen interactions in the development of metabolic disturbances and atherosclerosis in HIV infection: The role of CCL2 genetic variants. Cytokine 2010, 51, 251–258. [Google Scholar] [CrossRef]
  237. Aragonès, G.; Beltrán-Debón, R.; Rull, A.; Rodríguez-Sanabria, F.; Fernández-Sender, L.; Camps, J.; Joven, J.; Alonso-Villaverde, C. Human immunodeficiency virus-infection induces major changes in high-density lipoprotein particle size distribution and composition: The effect of antiretroviral treatment and disease severity. Clin. Chem. Lab. Med. 2010, 48, 1147–1152. [Google Scholar] [CrossRef] [PubMed]
  238. Coll, B.; Parra, S.; Alonso-Villaverde, C.; Aragonés, G.; Montero, M.; Camps, J.; Joven, J.; Masana, L. The role of immunity and inflammation in the progression of atherosclerosis in patients with HIV infection. Stroke 2007, 38, 2477–2484. [Google Scholar] [CrossRef] [Green Version]
  239. Joven, J.; Coll, B.; Tous, M.; Ferré, N.; Alonso-Villaverde, C.; Parra, S.; Camps, J. The influence of HIV infection on the correlation between plasma concentrations of monocyte chemoattractant protein-1 and carotid atherosclerosis. Clin. Chim. Acta. 2006, 368, 114–119. [Google Scholar] [CrossRef]
  240. Williams, M.E.; Joska, J.A.; Amod, A.R.; Paul, R.H.; Stein, D.J.; Ipser, J.C.; Naudé, P.J.W. The association of peripheral immune markers with brain cortical thickness and surface area in South African people living with HIV. J. Neurovirol. 2020, 26, 908–919. [Google Scholar] [CrossRef] [PubMed]
  241. Force, G.; Ghout, I.; Ropers, J.; Carcelain, G.; Marigot-Outtandy, D.; Hahn, V.; Darchy, N.; Defferriere, H.; Bouaziz-Amar, E.; Carlier, R.; et al. Improvement of HIV-associated neurocognitive disorders after antiretroviral therapy intensification: The Neuro+3 study. J. Antimicrob. Chemother. 2021, 76, 743–752. [Google Scholar] [CrossRef]
  242. Zhang, J.; Gong, X.; Xiong, H. Significant higher-level C-C motif chemokine ligand 2/3 and chemotactic power in cerebral white matter than grey matter in rat and human. Eur. J. Neurosci. 2021. [Google Scholar] [CrossRef]
  243. Hermes, D.J.; Yadav-Samudrala, B.J.; Xu, C.; Paniccia, J.E.; Meeker, R.B.; Armstrong, M.L.; Reisdorph, N.; Cravatt, B.F.; Mackie, K.; Lichtman, A.H.; et al. GPR18 drives FAAH inhibition-induced neuroprotection against HIV-1 Tat-induced neurodegeneration. Exp. Neurol. 2021, 341, 113699. [Google Scholar] [CrossRef]
  244. Karsen, H.; Binici, I.; Sunnetcioglu, M.; Baran, A.I.; Ceylan, M.R.; Selek, S.; Celik, H. Association of paraoxonase activity and atherosclerosis in patients with chronic hepatitis B. Afr. Health Sci. 2012, 12, 114–118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  245. Duygu, F.; Tekin Koruk, S.; Aksoy, N. Serum paraoxonase and arylesterase activities in various forms of hepatitis B virus infection. J. Clin. Lab. Anal. 2011, 25, 311–316. [Google Scholar] [CrossRef] [PubMed]
  246. Schulpis, K.H.; Barzeliotou, A.; Papadakis, M.; Rodolakis, A.; Antsaklis, A.; Papassotiriou, I.; Vlachos, G.D. Maternal chronic hepatitis B virus is implicated with low neonatal paraoxonase/arylesterase activities. Clin. Biochem. 2008, 41, 282–287. [Google Scholar] [CrossRef]
  247. Ferré, N.; Marsillach, J.; Camps, J.; Rull, A.; Coll, B.; Tous, M.; Joven, J. Genetic association of paraoxonase-1 polymorphisms and chronic hepatitis C virus infection. Clin. Chim. Acta. 2005, 361, 206–210. [Google Scholar] [CrossRef]
  248. Ali, E.M.; Shehata, H.H.; Ali-Labib, R.; Esmail Zahra, L.M. Oxidant and antioxidant of arylesterase and paraoxonase as biomarkers in patients with hepatitis C virus. Clin. Biochem. 2009, 42, 1394–1400. [Google Scholar] [CrossRef]
  249. Chandrasena, L.G.; Peiris, H.; Kamani, J.; Wanigasuriya, P.; Jayaratne, S.D.; Wijayasiri, W.A.; Wijesekara, G.U. Antioxidants in patients with dengue viral infection. Southeast Asian J. Trop. Med. Public Health 2014, 45, 1015–1022. [Google Scholar]
  250. Peltenburg, N.C.; Schoeman, J.C.; Hou, J.; Mora, F.; Harms, A.C.; Lowe, S.H.; Bierau, J.; Bakker, J.A.; Verbon, A.; Hankemeier, T.; et al. Persistent metabolic changes in HIV-infected patients during the first year of combination antiretroviral therapy. Sci. Rep. 2018, 8, 16947. [Google Scholar] [CrossRef] [Green Version]
  251. Rodríguez-Gallego, E.; Gómez, J.; Domingo, P.; Ferrando-Martínez, S.; Peraire, J.; Viladés, C.; Veloso, S.; López-Dupla, M.; Beltrán-Debón, R.; Alba, V.; et al. Circulating metabolomic profile can predict dyslipidemia in HIV patients undergoing antiretroviral therapy. Atherosclerosis 2018, 273, 28–36. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  252. Okeke, N.L.; Craig, D.M.; Muehlbauer, M.J.; Ilkayeva, O.; Clement, M.E.; Naggie, S.; Shah, S.H. Metabolites predict cardiovascular disease events in persons living with HIV: A pilot case-control study. Metabolomics 2018, 14, 23. [Google Scholar] [CrossRef]
  253. Begue, F.; Tanaka, S.; Mouktadi, Z.; Rondeau, P.; Veeren, B.; Diotel, N.; Tran-Dinh, A.; Robert, T.; Vélia, E.; Mavingui, P.; et al. Altered high-density lipoprotein composition and functions during severe COVID-19. Sci. Rep. 2021, 11, 2291. [Google Scholar] [CrossRef] [PubMed]
  254. Cho, K.H.; Kim, J.R.; Lee, I.C.; Kwon, H.J. Native high-density lipoproteins (HDL) with higher paraoxonase exerts a potent antiviral effect against SARS-CoV-2 (COVID-19), while glycated HDL lost the antiviral activity. Antioxidants 2021, 10, 209. [Google Scholar] [CrossRef]
  255. Cava, C.; Bertoli, G.; Castiglioni, I. In silico discovery of candidate drugs against Covid-19. Viruses 2020, 12, 404. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  256. Keller, B.T.; Borchardt, R.T. Adenosine dialdehyde: A potent inhibitor of vaccinia virus multiplication in mouse L929 cells. Mol. Pharmacol. 1987, 31, 485–492. [Google Scholar] [PubMed]
  257. Haljasmägi, L.; Salumets, A.; Rumm, A.P.; Jürgenson, M.; Krassohhina, E.; Remm, A.; Sein, H.; Kareinen, L.; Vapalahti, O.; Sironen, T.; et al. Longitudinal proteomic profiling reveals increased early inflammation and sustained apoptosis proteins in severe COVID-19. Sci. Rep. 2020, 10, 20533. [Google Scholar] [CrossRef] [PubMed]
  258. Jøntvedt Jørgensen, M.; Holter, J.C.; Christensen, E.E.; Schjalm, C.; Tonby, K.; Pischke, S.E.; Jenum, S.; Skeie, L.G.; Nur, S.; Lind, A.; et al. Increased interleukin-6 and macrophage chemoattractant protein-1 are associated with respiratory failure in COVID-19. Sci. Rep. 2020, 10, 21697. [Google Scholar] [CrossRef]
  259. Li, S.; Jiang, L.; Li, X.; Lin, F.; Wang, Y.; Li, B.; Jiang, T.; An, W.; Liu, S.; Liu, H.; et al. Clinical and pathological investigation of patients with severe COVID-19. JCI Insight 2020, 5, e138070. [Google Scholar] [CrossRef]
  260. Xi, X.; Guo, Y.; Zhu, M.; Wei, Y.; Li, G.; Du, B.; Wang, Y. Higher expression of monocyte chemotactic protein 1 in mild COVID-19 patients might be correlated with inhibition of Type I IFN signaling. Virol. J. 2021, 18, 12. [Google Scholar] [CrossRef] [PubMed]
  261. Zhang, F.; Mears, J.R.; Shakib, L.; Beynor, J.I.; Shanaj, S.; Korsunsky, I.; Nathan, A.; Donlin, L.T.; Raychaudhuri, S.; Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium. IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation. Genome Med. 2021, 13, 64. [Google Scholar] [CrossRef]
  262. Chi, Y.; Ge, Y.; Wu, B.; Zhang, W.; Wu, T.; Wen, T.; Liu, J.; Guo, X.; Huang, C.; Jiao, Y.; et al. Serum cytokine and chemokine profile in relation to the severity of coronavirus disease 2019 in China. J. Infect. Dis. 2020, 222, 746–754. [Google Scholar] [CrossRef]
  263. Xiong, Y.; Liu, Y.; Cao, L.; Wang, D.; Guo, M.; Jiang, A.; Guo, D.; Hu, W.; Yang, J.; Tang, Z.; et al. Transcriptomic characteristics of bronchoalveolar lavage fluid and peripheral blood mononuclear cells in COVID-19 patients. Emerg. Microbes Infect. 2020, 9, 761–770. [Google Scholar] [CrossRef] [PubMed]
  264. Chu, H.; Chan, J.F.; Wang, Y.; Yuen, T.T.; Chai, Y.; Hou, Y.; Shuai, H.; Yang, D.; Hu, B.; Huang, X.; et al. Comparative replication and immune activation profiles of SARS-CoV-2 and SARS-CoV in human lungs: An ex vivo study with implications for the pathogenesis of COVID-19. Clin. Infect. Dis. 2020, 71, 1400–1409. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  265. Lin, L.; Lu, L.; Cao, W.; Li, T. Hypothesis for potential pathogenesis of SARS-CoV-2 infection-a review of immune changes in patients with viral pneumonia. Emerg. Microbes Infect. 2020, 9, 727–732. [Google Scholar] [CrossRef] [Green Version]
  266. Ferraro, E.; Germanò, M.; Mollace, R.; Mollace, V.; Malara, N. HIF-1, the Warburg effect, and macrophage/microglia polarization potential role in COVID-19 pathogenesis. Oxid. Med. Cell. Longev. 2021, 2021, 8841911. [Google Scholar] [CrossRef] [PubMed]
  267. Burtscher, J.; Burtscher, M.; Millet, G.P. The central role of mitochondrial fitness on antiviral defenses: An advocacy for physical activity during the COVID-19 pandemic. Redox Biol. 2021, 43, 101976. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Oxidation, inflammation, and disturbances in energy metabolism are closely related. To date, the evidence reported suggests that excessive production of reactive oxygen species (ROS) would inhibit paraoxonase-1 (PON1) activity in high-density lipoprotein (HDL) particles and in the mitochondrial membranes of somatic cells. At the same time, it would stimulate the synthesis of chemokine (C-C motif) ligand 2 (CCL2) through several pathways, notably that of pathogen-associated molecular patterns/damage-associated molecular patterns/pattern-recognition receptors (PAMP/DAMP/PRR). The decrease in PON1 activity and the increase in CCl2 would cause alterations in mitochondrial metabolism and an inhibition of autophagy. At the same time, CCL2 would interact with its receptor (CRR2) and present on monocytes, promoting their migration to sites of injury, their differentiation to macrophages, and their synthesis of new ROS, producing a vicious circle that would trigger and aggravate the disease.
Figure 1. Oxidation, inflammation, and disturbances in energy metabolism are closely related. To date, the evidence reported suggests that excessive production of reactive oxygen species (ROS) would inhibit paraoxonase-1 (PON1) activity in high-density lipoprotein (HDL) particles and in the mitochondrial membranes of somatic cells. At the same time, it would stimulate the synthesis of chemokine (C-C motif) ligand 2 (CCL2) through several pathways, notably that of pathogen-associated molecular patterns/damage-associated molecular patterns/pattern-recognition receptors (PAMP/DAMP/PRR). The decrease in PON1 activity and the increase in CCl2 would cause alterations in mitochondrial metabolism and an inhibition of autophagy. At the same time, CCL2 would interact with its receptor (CRR2) and present on monocytes, promoting their migration to sites of injury, their differentiation to macrophages, and their synthesis of new ROS, producing a vicious circle that would trigger and aggravate the disease.
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Figure 2. Role of the chemokine (C-C motif) ligand 2 (CCL2) in the development of liver disease. Reactive oxygen species (ROS) and decreased paraoxonase-1 (PON1) activity increase the synthesis of CCL2, which activates monocytes that cross the endothelial barrier by diapedesis and differentiate into macrophages. These cells synthesize pro-inflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin 1β (IL-1β), and interleukin 6 (IL-6), contributing to fat accumulation and apoptosis of hepatocytes. Further, monocytes and macrophages synthesize tumor growth factor-β (TGF-β) that induces differentiation of stellate cells into myofibroblasts that synthesize collagen.
Figure 2. Role of the chemokine (C-C motif) ligand 2 (CCL2) in the development of liver disease. Reactive oxygen species (ROS) and decreased paraoxonase-1 (PON1) activity increase the synthesis of CCL2, which activates monocytes that cross the endothelial barrier by diapedesis and differentiate into macrophages. These cells synthesize pro-inflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin 1β (IL-1β), and interleukin 6 (IL-6), contributing to fat accumulation and apoptosis of hepatocytes. Further, monocytes and macrophages synthesize tumor growth factor-β (TGF-β) that induces differentiation of stellate cells into myofibroblasts that synthesize collagen.
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Figure 3. Changes in the structure of high-density lipoproteins (HDL) produced by inflammation. Chronic inflammatory processes cause a decrease in the content of paraoxnase-1 (PON1), apolipoprotein AI (Apo AI), lecithin:cholesterol acyltransferase (LCAT), and cholesterol ester transfer protein (CETP), and an increase in the concentration of serum amyloid A (SAA).
Figure 3. Changes in the structure of high-density lipoproteins (HDL) produced by inflammation. Chronic inflammatory processes cause a decrease in the content of paraoxnase-1 (PON1), apolipoprotein AI (Apo AI), lecithin:cholesterol acyltransferase (LCAT), and cholesterol ester transfer protein (CETP), and an increase in the concentration of serum amyloid A (SAA).
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Figure 4. Glutaminolysis in cancer. Cancer cells require glutamine from the circulation to convert it into glutamate and α-ketoglutarate, (α-KG) which enter the tricarboxylic acid (TCA) cycle. These metabolites induce the synthesis of proteins, glutathione, and fatty acids, as well as epigenetic changes and metabolite exchange between the mitochondria and the cytosol.
Figure 4. Glutaminolysis in cancer. Cancer cells require glutamine from the circulation to convert it into glutamate and α-ketoglutarate, (α-KG) which enter the tricarboxylic acid (TCA) cycle. These metabolites induce the synthesis of proteins, glutathione, and fatty acids, as well as epigenetic changes and metabolite exchange between the mitochondria and the cytosol.
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Camps, J.; Castañé, H.; Rodríguez-Tomàs, E.; Baiges-Gaya, G.; Hernández-Aguilera, A.; Arenas, M.; Iftimie, S.; Joven, J. On the Role of Paraoxonase-1 and Chemokine Ligand 2 (C-C motif) in Metabolic Alterations Linked to Inflammation and Disease. A 2021 Update. Biomolecules 2021, 11, 971.

AMA Style

Camps J, Castañé H, Rodríguez-Tomàs E, Baiges-Gaya G, Hernández-Aguilera A, Arenas M, Iftimie S, Joven J. On the Role of Paraoxonase-1 and Chemokine Ligand 2 (C-C motif) in Metabolic Alterations Linked to Inflammation and Disease. A 2021 Update. Biomolecules. 2021; 11(7):971.

Chicago/Turabian Style

Camps, Jordi, Helena Castañé, Elisabet Rodríguez-Tomàs, Gerard Baiges-Gaya, Anna Hernández-Aguilera, Meritxell Arenas, Simona Iftimie, and Jorge Joven. 2021. "On the Role of Paraoxonase-1 and Chemokine Ligand 2 (C-C motif) in Metabolic Alterations Linked to Inflammation and Disease. A 2021 Update" Biomolecules 11, no. 7: 971.

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