Search Results (2,141)

Background/Objectives: Metabolic syndrome (MetS) increases the risk of type 2 diabetes and cardiovascular disease. We aimed to identify the key metabolic predictors of MetS in a Central European cohort and to compare classical statistics with modern machine learning (ML) models. Methods: We analysed 956 adults from the Lower Silesia Healthy Donors cohort. Clinical, anthropometric, biochemical, and lifestyle variables were collected using standardised procedures. Group differences were tested with Mann–Whitney U tests and effect sizes. A multivariable logistic regression (outcome: binary MetS defined as ≥3 harmonised components, MetS_bin) estimated adjusted odds ratios. In parallel, ML models (logistic regression, Random Forest, XGBoost, LightGBM, CatBoost) were trained with stratified 5-fold cross-validation. Performance was evaluated by accuracy, F1-macro, and area under the receiver-operating characteristic curve (ROC AUC). Model interpretability used SHAP values. Results: Overweight/obese participants had higher fasting glucose (median 92.0 vs. 84.6 mg/dL), fasting insulin (9.9 vs. 6.6 µU/mL), and systolic blood pressure (134 vs. 121 mmHg) and lower HDL cholesterol (53 vs. 66 mg/dL) compared to normal-BMI individuals (all p < 0.001, r ≈ 0.39–0.41). Participants with a higher waist circumference also showed markedly increased HOMA-IR (2.16 vs. 1.34; p < 0.001). In multivariable logistic regression, waist circumference, BMI, triglycerides, HDL cholesterol, fasting glucose, and systolic blood pressure were independently associated with MetS, yielding a test ROC-AUC of 0.98 and PR-AUC of 0.88. Machine learning models further improved discrimination: Random Forest, XGBoost, LightGBM, and CatBoost all achieved very high performance (test ROC-AUC ≥ 0.99, PR-AUC ≥ 0.98), with CatBoost showing the best cross-validated PR-AUC (~0.99) and favourable calibration. SHAP analyses consistently highlighted fasting glucose, triglycerides, HDL cholesterol, waist circumference, and systolic blood pressure as the most influential predictors. Conclusions: Combining classical regression with modern gradient-boosting models substantially improves the identification of individuals at risk of MetS. CatBoost, XGBoost, and LightGBM delivered near-perfect discrimination in this Central European cohort while remaining explainable with SHAP. This framework supports clinically meaningful risk stratification—including a “subclinical” probability zone—and may inform targeted prevention strategies rather than purely reactive treatment. Full article

Metabolic syndrome (MetS) is a cluster of risk factors for cardiovascular diseases and type 2 diabetes. Gut microbiota dysbiosis has been implicated in the pathogenesis of MetS, but the mechanisms remain poorly understood. This study investigates gut microbiota interaction networks in MetS and explores their potential role in host metabolic regulation. In this population-based cross-sectional study, 221 MetS patients and 382 healthy controls were analyzed. Co-abundance network analysis was used to examine microbial interactions across the study. Significant differences in microbial co-abundance patterns were observed between MetS and healthy participants. In MetS, the gut microbiota displayed fewer and generally weaker co-abundance correlations compared with healthy controls. These changes appear to be more strongly associated with the synergistic effects of microbial interactions than solely with the abundance of individual taxa investigated here. Specific microbiota combinations were found to influence key metabolic functions, contributing to MetS development. The findings suggest that microbial interactions, rather than the abundance of individual bacteria, are associated with MetS. This study provides new insights into the role of disrupted gut microbiota networks in MetS pathogenesis. Full article

Background: Metabolic syndrome (MetS) comprises a cluster of metabolic abnormalities that increase the risk of type 2 diabetes mellitus (T2DM) and cardiometabolic morbidity. Although widely recognized, evidence on its documentation and follow-up in primary care is limited. This study aimed to evaluate the extent of MetS documentation in electronic medical records (EMRs), examine follow-up patterns and metabolic changes over time, and assess the incidence and predictors of new-onset T2DM according to baseline MetS severity. Methods: A retrospective cohort study was conducted on 8170 adults aged 30–50 years, insured by Clalit Health Services in Southern Israel, who met ATP III criteria for MetS in 2008 and were followed through 2015. MetS severity was classified as mild (three components), moderate (four), or severe (five). Changes in metabolic indices were assessed longitudinally, and predictors of T2DM were analyzed using Kaplan–Meier survival and multivariable Cox regression models. Results: Although all participants met the diagnostic criteria, only 1.6% had a recorded MetS diagnosis. Over the eight years of follow-up, 26% developed T2DM, with incidence increasing from 21% among those with mild MetS to 49% among those with severe MetS (p < 0.0001). Fasting plasma glucose rose significantly (median +13 mg/dL, p < 0.001), BMI remained stable, and modest improvements were observed in blood pressure and lipid levels. Elevated fasting glucose (HR 2.13, p < 0.001), higher BMI (HR 1.33, p = 0.010), and lower HDL (HR 1.26, p = 0.045) independently predicted diabetes onset. Conclusions: MetS remains markedly under-documented and insufficiently integrated into primary care follow-up. Despite regular clinical follow-up, improvements in metabolic indices were limited. These findings highlight the need for structured strategies to enhance MetS recognition and long-term management within routine practice. Full article

Insulin resistance is central in metabolic syndrome, but indices such as Homeostasis Model Assessment-estimated Insulin Resistance (HOMA-IR) require insulin assays that are costly and not always available. Non-insulin-based indices and refined anthropometric markers may offer simpler risk stratification in prediabetes and diabetes. Our objective was to compare insulin and non-insulin-based indices of insulin resistance, together with advanced anthropometric and lipid markers, between prediabetes (PreDM) and type 2 diabetes (T2DM) and across hypertension grades in metabolic syndrome. We conducted a cross-sectional study in 200 adults with metabolic syndrome, 80 with PreDM and 120 with T2DM. Clinical, anthropometric and biochemical parameters were recorded, and HOMA-IR, Homeostasis Model Assessment of Beta-cell function (HOMA%B), Metabolic Score for Insulin Resistance (METS-IR), triglyceride to glucose index (TyG), triglyceride-to-glucose index to high-density lipoprotein cholesterol ratio (TyG/HDL-c) and other derived indices were calculated. Group comparisons, correlations and multiple linear regression were performed. Compared with PreDM, T2DM showed higher glycemic indices and inflammation, but similar body mass index (BMI) and triglycerides. Across glycemic categories and hypertension grades, METS-IR, TyG and TyG/HDL-c increased and correlated strongly with body roundness index (BRI), abdominal volume index (AVI) and weight-adjusted waist index (WWI), while HOMA-IR contributed little independent information. In regression models, lipid adipose product (LAP) and WWI best explained METS-IR in prediabetes, whereas TyG and BRI were the main determinants of METS-IR in diabetes. In metabolic syndrome with PreDM or T2DM, METS-IR and TyG, particularly combined with BRI, AVI and WWI, outperformed traditional lipid ratios and added value beyond HOMA-IR. These composite indices appear useful for insulin resistance assessment when insulin measurement is unavailable or unreliable. Full article

Recently, a growing interest has been focused to the role of vitamin C in chronic diseases. Type 2 Diabetes Mellitus and the Metabolic Syndrome are complex, chronic disorders intrinsically linked by a common underlying element, such as chronic low-grade inflammation and excessive oxidative stress. Vitamin C, or ascorbic acid, is an essential water-soluble micronutrient and a highly potent non-enzymatic antioxidant that is critical for scavenging reactive oxygen species and maintaining cellular redox balance. It represents a cofactor for many enzymes, being involved in many biological functions, such as normal immune system functioning, catecholamine metabolism, dietary iron absorption, and collagen biosynthesis. Individuals with type 2 diabetes mellitus and metabolic syndrome frequently exhibit lower circulating and dietary vitamin C levels compared to healthy controls, a deficiency that may be associated with disease-related inflammation and higher body weight. In this sense, it has been shown that vitamin C improves skeletal muscle insulin sensitivity in experimental settings and modulates critical functions like vascular endothelial health. However, this potential is challenged by the fact that chronic hyperglycemia can interfere with the active cellular uptake and transport of vitamin C, potentially leading to relative intracellular deficiency in diabetic patients regardless of intake. It is interesting to note that different studies have demonstrated an inverse relationship between vitamin C concentrations and the prevalence of metabolic syndrome and type 2 diabetes. Vitamin C supplementation in people with diabetes and metabolic syndrome has controversial effects. While several studies indicate a significant reduction in fasting blood glucose or HbA1c, others revealed no significant effect on insulin resistance. This review aims to explore the pathophysiological role and therapeutic potential of vitamin C in type 2 diabetes and metabolic syndrome. Full article

Gestational obesity, defined as obesity during pregnancy or a pre-pregnancy BMI ≥30, is a growing global health challenge with profound implications for both maternal and offspring health. This narrative review synthesizes current evidence on the mechanistic pathways by which maternal obesity affects pregnancy outcomes and intergenerational health trajectories. For mothers, gestational obesity increases the risk of gestational diabetes, hypertensive disorders, cesarean delivery, and postpartum weight retention. Offspring exposed to maternal obesity face higher risks of obesity, metabolic syndrome, cardiovascular disease, and neurodevelopmental disorders, many of which persist across the lifespan. The underlying mechanisms include metabolic dysregulation, insulin resistance, chronic inflammation, oxidative stress, and alterations in placental function. Epigenetic modifications, such as DNA methylation, histone changes, and non-coding RNA expression, play central roles in fetal programming, while maternal gut dysbiosis and alterations in breast milk microbiota further shape infant health outcomes. Importantly, maternal obesity not only influences pregnancy and early life but also perpetuates an intergenerational cycle of obesity and related comorbidities. Preventive strategies targeting preconception and prenatal health, combined with interventions to optimize lactation and maternal diet, may mitigate long-term risks. Future research should prioritize longitudinal and mechanistic studies to refine interventions aimed at disrupting the transmission of obesity-related disease across generations. Full article

Background/Objectives: This study investigated the association between physical activity (PA) levels and the risk of chronic diseases in Korean adults with sleep deficiency (SD). Methods: Data were obtained from the Korea National Health and Nutrition Examination Survey (2016–2021; n = 31,338). SD was defined as less than 7 h of sleep per night. The PA levels were categorized as low, moderate, or high. Multivariable logistic regression was used to estimate odds ratios (OR) with 95% confidence intervals (CI) for various chronic diseases, adjusting for demographic and lifestyle covariates. Results: High PA levels were associated with lower odds of abdominal obesity (OR = 0.855, 95% CI = 0.782–0.934, p < 0.001), hypertension (OR = 0.787, 95% CI = 0.657–0.942, p < 0.01), diabetes mellitus (OR = 0.743, 95% CI = 0.622–0.887, p < 0.01), and metabolic syndrome (OR = 0.706, 95% CI = 0.586–0.850, p < 0.001). Moderate PA showed similar but weaker associations. Conversely, high PA levels were associated with higher odds of depression (OR = 1.474, 95% CI = 1.123–1.935, p < 0.01). Subgroup analyses indicated that the protective effects of PA were stronger among women, non-smokers, and individuals with obesity. Conclusions: Among adults with SD, moderate-to-vigorous PA is associated with a lower odds of several metabolic disorders, including abdominal obesity, diabetes, and metabolic syndrome. This highlights the importance of regular PA in maintaining metabolic health. However, a positive association between high PA and depression should warrant further investigation, as reverse causality or residual confounding may explain this association. Full article

Background and Objectives: Cardiovascular–kidney–metabolic (CKM) syndrome reflects the interconnection between metabolic risk factors, chronic kidney disease (CKD), and cardiovascular disease (CVD). Despite increasing awareness, population-based data on CKM syndrome are limited, particularly in Europe. This study assessed the prevalence of CKM syndrome and the use of renal and cardiac biomarkers in Lithuania. Materials and Methods: Health records of 923,329 adults aged ≥40 years from the national Electronic Health Services and Cooperation Infrastructure Information System were analyzed. CKM-associated conditions (prediabetes/type 2 diabetes, obesity, CKD) and cardiovascular outcomes (atherosclerotic CVD, peripheral vascular disease, stroke, heart failure, atrial fibrillation) were identified. CKM stages were defined as stage 0 (no CKM conditions), stages 1–3 (at least one CKM condition), and stage 4 (at least one CVD diagnosis). The use of estimated glomerular filtration rate (eGFR), albumin-to-creatinine ratio (ACR) and N-terminal pro–B-type natriuretic peptide (NT-proBNP) testing was evaluated. Results: Overall, 34.8% of adults met criteria for stage 4 CKM syndrome, and 23.4% were classified as stage 1–3. Obesity (21.2%) and type 2 diabetes (17.2%) were the most common CKM-associated conditions. Heart failure (25.4%) and atrial fibrillation (14.0%) were the most common cardiovascular outcomes, with ≥2 CVD diagnoses present in 15.4% of patients. Among stage 1–3 patients, eGFR, ACR, and NT-proBNP were measured in 53.5%, 9.0%, and 4.9%, respectively. Conclusions: A third of Lithuanian adults aged ≥40 years had stage 4 CKM syndrome. The underuse of biomarker testing highlights missed opportunities for early detection. Broader implementation of biomarker testing and integrated care is warranted to slow progression of CKM syndrome and reduce cardiovascular risk. Full article

The prevalence of maternal obesity is rapidly increasing, which represents a major public health concern worldwide. Currently more than 50% of all adult women are overweight or obese, and this trend is reflected in women of child-bearing age. Maternal obesity is characterized by metabolic dysfunction and chronic inflammation, and is associated with health problems in both the mother and the offspring. Intrauterine programming occurs during embryonic and fetal development, a critical period not only for the formation of tissues and organs but also for the etiology of diseases later in life. The principal mechanisms underlying fetal programming in the offspring of obese mothers appear to involve DNA methylation and chromatin remodeling within progenitor cells. Aberrant DNA methylation patterns have been identified in genes involved in insulin signaling, lipid metabolism, and appetite regulation in the placenta and fetal tissues. Histone modifications, such as acetylation and methylation of histone tails, may also play a crucial role in modulating chromatin structure and accessibility of transcriptional machinery to DNA. The persistence of such modifications throughout life, and potentially across generations, can lead to permanent alterations in gene expression, thereby contributing to the intergenerational transmission of metabolic disorders. The aim of this paper is to present an overview of the current knowledge regarding the effects of maternal obesity on fetal development and the occurrence of fetal complications, as well as long-term complications observed in adulthood related to intrauterine exposure to maternal obesity, including hypertension and cardiovascular diseases, impaired insulin secretion and resistance, diabetes mellitus, and metabolic syndrome. The mechanisms underlying fetal programming are also discussed. Full article

Objective: The genetic causes of obesity are complex and include diabetes and obesity monogenic syndromes like autosomal recessive Bardet–Biedl syndrome (BBS). Other clinical manifestations of this syndrome include metabolic disorders, polydactyly, retinal dystrophy, and endocrine, urological, and neurological abnormalities. Moreover, isolated clinical manifestations have been described in carriers of heterozygous mutations in BBS genes. On the other hand, Fahr’s disease is characterized by the accumulation of calcium deposits in various areas within the brain, leading to neurodegeneration, and the course of the disease is variable. Case presentation: We present the case of a 21-year-old female with severe obesity, diagnosed at the age of six years. The patient also experienced hypertension, hyperlipidemia, insulin resistance, and polycystic ovarian syndrome. During an MRI examination, hyperintensity in the region of the dentate nuclei and hyperintensity in the globus pallidus were described. NGS (next-generation sequencing) results showed a heterozygous variant in the TMEM67 gene, which revealed the patient to be a carrier of BBS, and a homozygotic variant in the MYORG gene, leading to a Fahr’s disease diagnosis. However, due to an insufficient number of phenotypic criteria and only one causative variant in the TMEM67 gene, the diagnosis of BBS could not be established. Conclusions: Attempts to identify the cause of obesity can lead to unexpected results, which can be resolved through collaboration between clinicians of different specialties and the use of NGS molecular testing. The status of being a BBS carrier, which coexists with Fahr’s disease, may be a potential contributing factor to severe obesity and metabolic disorders in the patient. Full article

Background/Objectives: The aim of this study was to investigate rates of self-reported Polycystic Ovary Syndrome (PCOS), metabolic abnormalities and age of menarche in girls with a history of Premature Adrenarche (PA) and the association of baseline characteristics with these outcomes. Methods: A retrospective chart review of girls with PA seen between 2005 and 2015 was conducted. Eligible patients (or their mothers in girls <18 years of age) were surveyed by telephone to query whether they had developed PCOS, diabetes, pre-diabetes, hypertension or dyslipidemia as well as their age of menarche. Associations of baseline characteristics with PCOS or metabolic abnormalities were analyzed. Results: A total of 359 patients with PA were identified, of whom 118 completed a telephone survey. At baseline, the average age of girls with PA was 6.7 ± 1.4 years, of whom 55% were White. At follow-up, the average age of girls was 17 ± 3.5 years. Among the respondents, 19.5% reported a diagnosis of PCOS, 5.1% reported diabetes, 8.5% pre-diabetes, 7.6% hypertension and 6% hyperlipidemia. Major risk factors for PCOS included a maternal history of PCOS (p = 0.005, OR 4.1) and increased BMI at baseline (p = 0.03, OR 1.69). Additionally, girls with history of PA had an earlier age of menarche compared to their mothers (11.3 ± 1.6 years vs. 11.9 ± 1.5 years, p = 0.002). Conclusions: Our results suggest that maternal history of PCOS poses the greatest risk for future development of self-reported PCOS in girls with a history of PA followed by increased BMI. Prospective studies using objective diagnostic criteria are needed to corroborate these findings, as our outcomes were based on self-reported data. Full article

Background: Throughout the course of the COVID-19 pandemic, clinicians recognized that individuals with metabolic syndrome, including elevated body mass index (BMI) and type 2 diabetes, have increased clinical care requirements and worsened outcomes during COVID-19 infection. With the availability of COVID-19 vaccines, it was unknown whether vaccination could mitigate the clinical outcomes among patients with metabolic syndrome. In this study, we sought to determine whether BMI and hemoglobin A1c are associated with a risk of breakthrough infection and increased clinical needs among patients who have been fully vaccinated against COVID-19. Methods: We conducted a retrospective cohort study of patients in the Veterans Affairs healthcare system who were vaccinated against COVID-19 between 1 December 2020 and 22 August 2021. We sampled a random subset of 549,344 patients from a total of over 1 million de-identified patients greater than age 18 who were vaccinated between 1 December 2020 and 22 August 2021, without a prior positive COVID-19 test in the VA healthcare system data warehouse. The primary study outcomes were breakthrough COVID-19 infections after vaccination and hospitalization due to breakthrough COVID-19 infections. Results: We identified 480,129 patients with available BMI and hemoglobin A1c data; of these, all had data available for the covariates of race, ethnicity, sex, and age, and 467,283 had data available for district as well. Adjusting for those covariates, Cox proportional hazards modeling for time from vaccination until breakthrough infection demonstrated that higher BMI (HR per unit 1.015, p < 0.001) and hemoglobin A1c were associated with an increased risk of infection (HR per unit 1.063, p < 0.001). The number of patients from this set who developed breakthrough infections within the study period was 8903 (9146 if those with missing district data were included). The average age of fully vaccinated patients with breakthrough COVID-19 infection within six months of full vaccination was 64.5. The average BMI was 31.2 ± 6.2 and the average A1c was 6.34 ± 1.5. Adjusting for the above covariates, multivariable logistic regression trends towards significance, with an increased risk of hospitalization due to breakthrough COVID-19 infection with increased BMI (HR per unit 1.010, p = 0.052), and was statistically significant for increased hemoglobin A1c (HR per unit 1.150, p < 0.010). Conclusions: This study identifies BMI and hemoglobin A1c as risk factors for breakthrough COVID-19 infection among fully vaccinated patients in the US veteran population. Full article

Background/Objectives: Metabolic syndrome (MS) impacts 25% of the adult population worldwide and elevates the risk of colorectal cancer by 40%. Microsatellite instability (MSI) resulting from impaired DNA mismatch repair serves as a critical biomarker for selecting patients for immunotherapy. Methods: This single-center pilot study examined the correlations between MS and MSI in 157 individuals with surgically treated colorectal cancer. Patients were categorized according to the International Diabetes Federation Metabolic Syndrome criteria. The MSI status was assessed using immunohistochemical investigation of mismatch repair proteins. The statistical analysis encompassed chi-square tests and the computation of odds ratios. Results: Patients with MS exhibited a substantially greater prevalence of MSI compared to controls (15.5% vs. 9.8%, p < 0.05) corresponding to a 1.63-fold increase in odds. The co-occurrence of MSI and hepatic steatosis displayed a strong association within the MS group (OR: 5.81), indicating a 2.6-fold increased prevalence relative to controls. Conclusions: This pilot investigation offers initial evidence associating MS with a heightened frequency of MSI in colorectal cancer. The strong association with hepatic steatosis indicates common metabolic-genomic pathways. The findings advocate for the incorporation of metabolic assessment into precision oncology for the selection of immunotherapy, necessitating multicenter validation studies. Full article

Liposomal nano-systems and hydrogels are two types of nano-technological systems that have promising applications in the prevention and treatment of metabolic diseases (diabetes, obesity, dyslipidemias, and metabolic syndrome), which are a major public health concern worldwide. Advances in nanotechnology and biomaterials have enabled the development of new platforms for the controlled delivery of nutrients or bioactive compounds in order to solve these issues. This review compares the characteristics, advantages, and limitations of these two systems, with a focus on their applicability in the prevention and treatment of metabolic diseases. Full article

Adiponectin, an adipokine secreted by adipocytes with anti-inflammatory and insulin-sensitizing properties, circulates in several isoforms, of which total and high-molecular-weight (HMW) adiponectin are the most physiologically relevant. While adiponectin has been inversely associated with obesity and metabolic syndrome (MetS), evidence from Latin American populations remains scarce. To explore its role in this context, we conducted a case–control study in 310 Panamanian adults, including 77 individuals with MetS and 233 controls, diagnosed according to the Latin American Diabetes Association (ALAD) criteria. Serum adiponectin, lipid profile, glucose, HbA1c, and body composition were evaluated, with adiponectin quantified by chemiluminescent immunoassay (CLIA). Correlations with metabolic parameters were analyzed using GraphPad Prism 10.5. Participants with MetS exhibited significantly lower adiponectin concentrations compared with controls (7.75 ± 2.58 µg/mL vs. 9.53 ± 3.31 µg/mL, p = 0.0030). Adiponectin levels were significantly lower in males than in females (p = 0.0083) and showed inverse correlations with visceral fat (r = −0.26, p < 0.001), triglycerides (r = −0.25, p = 0.0062), insulin (r = −0.31, p < 0.0001), and HbA1c (r = −0.11, p = 0.046). Conversely, a positive association was observed with HDL cholesterol (r = 0.37, p < 0.0001). Individuals with HbA1c ≥ 6.5% or insulin ≥ 15 µU/mL exhibited markedly reduced adiponectin concentrations (p = 0.0006 and p < 0.0001, respectively). The ROC analysis yielded an AUC of 0.69, indicating a moderate discriminatory ability of adiponectin for identifying MetS in this population. These findings confirm that adiponectin is inversely associated with several metabolic risk factors, supporting its potential utility as a biomarker for early detection and risk stratification of metabolic syndrome in the Panamanian population. Full article