ABSTRACT
Growing evidences showed that heavy metals exposure may be associated with metabolic diseases. Nevertheless, the mechanism underlying arsenic (As) exposure and metabolic syndrome (MetS) risk has not been fully elucidated. So we aimed to prospectively investigate the role of serum uric acid (SUA) on the association between blood As exposure and incident MetS. A sample of 1045 older participants in a community in China was analyzed. We determined As at baseline and SUA concentration at follow-up in the Yiwu Elderly Cohort. MetS events were defined according to the criteria of the International Diabetes Federation (IDF). Generalized linear model with log-binominal regression model was applied to estimate the association of As with incident MetS. To investigate the role of SUA in the association between As and MetS, a mediation analysis was conducted. In the fully adjusted log-binominal model, per interquartile range increment of As, the risk of MetS increased 1.25-fold. Compared with the lowest quartile of As, the adjusted relative risk (RR) of MetS in the highest quartile was 1.42 (95% confidence interval, CI: 1.03, 2.00). Additionally, blood As was positively associated with SUA, while SUA had significant association with MetS risk. Further mediation analysis demonstrated that the association of As and MetS risk was mediated by SUA, with the proportion of 15.7%. Our study found higher As was remarkably associated with the elevated risk of MetS in the Chinese older adults population. Mediation analysis indicated that SUA might be a mediator in the association between As exposure and MetS.
Subject(s)
Arsenic , Environmental Exposure , Metabolic Syndrome , Uric Acid , Aged , Female , Humans , Male , Middle Aged , Arsenic/blood , Arsenic/toxicity , China/epidemiology , East Asian People , Environmental Exposure/adverse effects , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Metabolic Syndrome/blood , Uric Acid/bloodABSTRACT
Polychlorinated biphenyls (PCBs) and dioxin are persistent endocrine disrupting chemicals (EDCs) and have been associated with an increased risk of metabolic syndrome (MetS). The aim of this systematic review and meta-analysis was to assess the associations of PCBs and dioxin with MetS and its risk factors, including obesity, hypertriglyceridaemia (HTG), hypertension (HTN) and diabetes mellitus (DM). We searched three electronic databases for epidemiological studies concerning PCBs and dioxin with MetS published up to the end of 2023. Meta-analysis was performed for MetS itself and each of the MetS risks based on a random-effects meta-analysis model, and odds ratios (ORs) with 95% confidence intervals (CIs) were obtained. Publication bias was assessed based on Egger's test. Eleven studies were included from three databases up to 2023. There were 40,528 participants aged 18-89, where 18-100% of them were males, included in our meta-analysis. The meta-analysis results showed a strong association between PCB exposure and DM (OR = 3.593, 95% CI 2.566, 5.031), while most of the risk factors for MetS, including obesity (OR = 1.875, 95% CI 0.883, 3.979), HTN (OR = 1.335, 95% CI 0.902, 1.976) and HTG (OR = 1.611, 95% CI 0.981, 2.643), were weakly associated with PCB. Furthermore, both PCBs (OR = 1.162, 95% CI 0.994, 1.357) and dioxin (OR = 2.742, 95% CI 1.936, 3.883) were found to be weakly and strongly associated with MetS, respectively. Meta-regression analysis showed that DM in the Asian population is associated with PCB exposure, while HTG in the Northern American population is associated with PCB exposure. Our meta-analysis has demonstrated a strong relationship between DM and PCBs, while the relationship between PCBs with MetS and other risk factors is less pronounced. Additionally, MetS is weakly associated with dioxin exposure. To improve primary care outcomes, healthcare providers should consider incorporating the assessment of patients' risk of exposure to PCBs and dioxins into their evaluation procedures for more targeted medical interventions.
Subject(s)
Dioxins , Metabolic Syndrome , Polychlorinated Biphenyls , Humans , Metabolic Syndrome/chemically induced , Metabolic Syndrome/epidemiology , Polychlorinated Biphenyls/adverse effects , Dioxins/adverse effects , Risk Factors , Female , Male , Adult , Obesity/chemically induced , Middle Aged , Environmental Exposure/adverse effects , Aged , Adolescent , Hypertension/chemically induced , Hypertension/epidemiologyABSTRACT
AIM: To explore the effect of mixed exposure to per- and polyfluoroalkyl substances (PFAS) on metabolic syndrome (MetS). METHODS: This cross-sectional study used data from the Korean National Environmental Health Survey Cycle 4 (2018-2020). The serum concentrations of five PFAS (perfluorooctanoic acid [PFOA], perfluorooctanesulfonic acid [PFOS], perfluorohexanesulfonic acid, perfluorononanoic acid [PFNA], and perfluorodecanoic acid [PFDeA]) were measured, and the relative potency factor approach was employed for the mixture of PFAS (Cmix) assessment. MetS was diagnosed if the patient satisfied three of five criteria: central obesity, elevated triglycerides, reduced high-density lipoprotein cholesterol, elevated blood pressure (BP), and elevated glycated hemoglobin (HbA1c). Age, sex, smoking, drinking, and exercise status were considered as covariates. The risk of MetS for single and mixed exposure to PFAS was analyzed using binomial regression and Bayesian kernel machine regression (BKMR). RESULTS: A total of 2984 (male:female = 1:1.3; age range, 19-80 years) adults were enrolled. The prevalence of MetS was 45.6%. Each PFAS and Cmix levels were higher in participants with MetS than in those without MetS. Cmix increased the risk of elevated BP and HbA1c, and eventually MetS (odds ratio [OR] = 2.00, 95% confidence interval [CI] 1.11-3.60 per log10Cmix; OR = 1.57, 95% CI 1.07-2.31 in the highest quartile of Cmix [Q4] vs. the lowest [Q1]). Sex-specific analyses revealed that the impact of Cmix was valid in females but not in males (Cmix Q4 vs. Q1: OR = 1.01, 95% CI 0.57-1.8 in males; OR = 2.30, 95% CI 1.38-3.84 in females). In the BKMR analysis, mixed exposure to PFAS dose-dependently increased the risk of MetS, particularly in females. Among single exposures, PFNA contributed significantly to the cumulative effect. CONCLUSION: Mixed exposure to PFAS was associated with a higher risk of MetS in females. Further studies on potential health concerns associated with PFAS mixtures are warranted.
Subject(s)
Alkanesulfonic Acids , Environmental Exposure , Environmental Pollutants , Fluorocarbons , Metabolic Syndrome , Humans , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Fluorocarbons/blood , Republic of Korea/epidemiology , Male , Female , Middle Aged , Adult , Environmental Pollutants/blood , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Alkanesulfonic Acids/blood , Health Surveys , Aged , Cross-Sectional Studies , Caprylates/blood , Young AdultABSTRACT
BACKGROUND: The prevalence of metabolic syndrome (MetS) in American adults increased from 37.6% in the 2011-12 period to 41.8% in 2017-2018. Environmental exposure, particularly to common compounds such as glyphosate, has drawn increasing attention as a potential risk factor. METHODS: We employed three cycles of data (2013-2018) from the National Health and Nutrition Examination Survey (NHANES) in a cross-sectional study to examine potential associations between urine glyphosate measurements and MetS incidence. We first created a MetS score using exploratory factor analysis (EFA) of the International Diabetes Federation (IDF) criteria for MetS, with data drawn from the 2013-2018 NHANES cycles, and validated this score independently on an additional associated metric, the albumin-to-creatinine (ACR) ratio. The score was validated via a machine learning approach in predicting the ACR score via binary classification and then used in multivariable regression to test the association between quartile-categorized glyphosate exposure and the MetS score. RESULTS: In adjusted multivariable regressions, regressions between quartile-categorized glyphosate exposure and MetS score showed a significant inverted U-shaped or saturating doseâresponse profile, often with the largest effect for exposures in quartile 3. Exploration of potential effect modification by sex, race, and age category revealed significant differences by race and age, with older people (aged > 65 years) and non-Hispanic African American participants showing larger effect sizes for all exposure quartiles. CONCLUSIONS: We found that urinary glyphosate concentration is significantly associated with a statistical score designed to predict MetS status and that dose-response coefficient is nonlinear, with advanced age and non-Hispanic African American, Mexican American and other Hispanic participants exhibiting greater effect sizes.
Subject(s)
Glycine , Glyphosate , Herbicides , Nutrition Surveys , Humans , Glycine/analogs & derivatives , Glycine/urine , Cross-Sectional Studies , Male , Female , Middle Aged , Adult , Herbicides/urine , Aged , Metabolic Syndrome/urine , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , United States/epidemiology , Environmental Exposure/analysis , Young Adult , Risk Factors , Environmental Pollutants/urineABSTRACT
The utilization of atypical antipsychotics (AAPs) often leads to metabolic syndrome (MetS) in schizophrenia (SZ) patients. Macrophage migration inhibitory factor (MIF) is an important MetS-related cytokine. To investigate the potential association between the MIF-794 CATT5-8 polymorphism and AAP-induced MetS in SZ patients, data from 375 chronic SZ patients who received AAP treatment for a minimum of one year were included. MIF-794 CATT polymorphism genotyping and plasma MIF quantification was performed. The metabolism status of all patients was assessed according to the NCEP-ATP III criteria. Individuals who displayed at least three of the five risk factors (waist circumference, high-density lipoprotein cholesterol, triglycerides, fasting glucose levels, and blood pressure) were diagnosed with MetS. The prevalence of MetS in SZ patients with MIF CATT >5/6 was significantly higher than in those with CATT 5/5-5/6. In female patients, MIF CATT >5/6 was associated with an elevated risk of AAP-induced MetS after adjusting for covariates, particularly regarding abdominal obesity, and the mediating effect of plasma MIF levels was significant. In conclusion, MIF CATT >5/6 increased the risk of AAP-induced MetS among females with chronic SZ. The MIF-794 CATT5-8 microsatellite polymorphism may be a unique indicator for AAP-induced metabolic adverse effects in female SZ patients.
Subject(s)
Antipsychotic Agents , Intramolecular Oxidoreductases , Macrophage Migration-Inhibitory Factors , Metabolic Syndrome , Schizophrenia , Humans , Schizophrenia/drug therapy , Schizophrenia/blood , Female , Macrophage Migration-Inhibitory Factors/blood , Macrophage Migration-Inhibitory Factors/genetics , Metabolic Syndrome/chemically induced , Metabolic Syndrome/epidemiology , Metabolic Syndrome/blood , Antipsychotic Agents/adverse effects , Adult , Male , Intramolecular Oxidoreductases/blood , Intramolecular Oxidoreductases/genetics , Middle Aged , Chronic DiseaseABSTRACT
BACKGROUND: Metabolic Syndrome (MetS) is a widely observed metabolic disorder that is increasingly prevalent worldwide, leading to substantial societal consequences. Previous studies have conducted two separate meta-analyses to investigate the relationship between MetS and air pollutants. However, these studies yielded conflicting results, necessitating a thorough systematic review and meta-analysis to reassess the link between different air pollutants and the risk of developing MetS. METHODS: We conducted a comprehensive search of relevant literature in databases including PubMed, Embase, Cochrane Library, and Web of Science up to October 9, 2023. The search was specifically restricted to publications in the English language. Following the screening of studies investigating the correlation between air pollution and MetS, we utilized random-effects models to calculate pooled effect sizes along with their respective 95% confidence intervals (CIs). We would like to highlight that this study has been registered with PROSPERO, and it can be identified by the registration number CRD42023484421. RESULTS: The study included twenty-four eligible studies. The results revealed that an increase of 10 µg/m3 in annual concentrations of PM1, PM2.5, PM10, NO2, SO2, and O3 was associated with a 29% increase in metabolic syndrome (MetS) risk for PM1 (OR = 1.29 [CI 1.07-1.54]), an 8% increase for PM2.5 (OR = 1.08 [CI 1.06-1.10]), a 17% increase for PM10 (OR = 1.17 [CI 1.08-1.27]), a 24% increase for NO2 (OR = 1.24 [CI 1.01-1.51]), a 19% increase for SO2 (OR = 1.19 [CI 1.04-1.36]), and a 10% increase for O3 (OR = 1.10 [CI 1.07-1.13]). CONCLUSION: The findings of this study demonstrate a significant association between exposure to fine particulate matter (PM1, PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and the incidence of metabolic syndrome (MetS). Moreover, the results suggest that air pollution exposure could potentially contribute to the development of MetS in humans.
Subject(s)
Air Pollutants , Environmental Exposure , Metabolic Syndrome , Particulate Matter , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Humans , Air Pollutants/adverse effects , Air Pollutants/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis , Environmental Exposure/adverse effects , Air Pollution/adverse effects , Air Pollution/analysis , Risk FactorsABSTRACT
Introduction: The pathogenesis of Post-Transplant Diabetes Mellitus (PTDM) is complex and multifactorial and it resembles that of Type-2 Diabetes Mellitus (T2DM). One risk factor specific to PTDM differentiates both entities: the use of immunosuppressive therapy. Specifically, Tacrolimus interacts with obesity and insulin resistance (IR) in accelerating the onset of PTDM. In a genotypic model of IR, the obese Zucker rats, Tacrolimus is highly diabetogenic by promoting the same changes in beta-cell already modified by IR. Nevertheless, genotypic animal models have their limitations and may not resemble the real pathophysiology of diabetes. In this study, we have evaluated the interaction between beta-cell damage and Tacrolimus in a non-genotypic animal model of obesity and metabolic syndrome. Methods: Sprague Dawley rats were fed a high-fat enriched diet during 45 days to induce obesity and metabolic dysregulation. On top of this established obesity, the administration of Tacrolimus (1mg/kg/day) during 15 days induced severe hyperglycaemia and changes in morphological and structural characteristics of the pancreas. Results: Obese animals administered with Tacrolimus showed increased size of islets of Langerhans and reduced beta-cell proliferation without changes in apoptosis. There were also changes in beta-cell nuclear factors such as a decrease in nuclear expression of MafA and a nuclear overexpression of FoxO1A, PDX-1 and NeuroD1. These animals also showed increased levels of pancreatic insulin and glucagon. Discussion: This model could be evidence of the relationship between the T2DM and PTDM physiopathology and, eventually, the model may be instrumental to study the pathogenesis of T2DM.
Subject(s)
Disease Models, Animal , Metabolic Syndrome , Obesity , Rats, Sprague-Dawley , Tacrolimus , Animals , Tacrolimus/pharmacology , Metabolic Syndrome/metabolism , Metabolic Syndrome/pathology , Metabolic Syndrome/chemically induced , Obesity/metabolism , Obesity/pathology , Rats , Male , Immunosuppressive Agents/adverse effects , Immunosuppressive Agents/pharmacology , Insulin-Secreting Cells/metabolism , Insulin-Secreting Cells/pathology , Insulin-Secreting Cells/drug effects , Phenotype , Diabetes Mellitus, Type 2/metabolism , Diabetes Mellitus, Type 2/pathology , Diabetes Mellitus, Experimental/pathology , Diabetes Mellitus, Experimental/metabolism , Insulin Resistance , Diet, High-Fat/adverse effectsABSTRACT
Importance: Prenatal exposure to ubiquitous endocrine-disrupting chemicals (EDCs) may increase the risk of metabolic syndrome (MetS) in children, but few studies have studied chemical mixtures or explored underlying protein and metabolic signatures. Objective: To investigate associations of prenatal exposure to EDC mixtures with MetS risk score in children and identify associated proteins and metabolites. Design, Setting, and Participants: This population-based, birth cohort study used data collected between April 1, 2003, and February 26, 2016, from the Human Early Life Exposome cohort based in France, Greece, Lithuania, Norway, Spain, and the UK. Eligible participants included mother-child pairs with measured prenatal EDC exposures and complete data on childhood MetS risk factors, proteins, and metabolites. Data were analyzed between October 2022 and July 2023. Exposures: Nine metals, 3 organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 5 perfluoroalkyl substances (PFAS), 10 phthalate metabolites, 3 phenols, 4 parabens, and 4 organophosphate pesticide metabolites measured in urine and blood samples collected during pregnancy. Main Outcomes and Measures: At 6 to 11 years of age, a composite MetS risk score was constructed using z scores of waist circumference, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and insulin levels. Childhood levels of 44 urinary metabolites, 177 serum metabolites, and 35 plasma proteins were quantified using targeted methods. Associations were assessed using bayesian weighted quantile sum regressions applied to mixtures for each chemical group. Results: The study included 1134 mothers (mean [SD] age at birth, 30.7 [4.9] years) and their children (mean [SD] age, 7.8 [1.5] years; 617 male children [54.4%] and 517 female children [45.6%]; mean [SD] MetS risk score, -0.1 [2.3]). MetS score increased per 1-quartile increase of the mixture for metals (ß = 0.44; 95% credible interval [CrI], 0.30 to 0.59), organochlorine pesticides (ß = 0.22; 95% CrI, 0.15 to 0.29), PBDEs (ß = 0.17; 95% CrI, 0.06 to 0.27), and PFAS (ß = 0.19; 95% CrI, 0.14 to 0.24). High-molecular weight phthalate mixtures (ß = -0.07; 95% CrI, -0.10 to -0.04) and low-molecular weight phthalate mixtures (ß = -0.13; 95% CrI, -0.18 to -0.08) were associated with a decreased MetS score. Most EDC mixtures were associated with elevated proinflammatory proteins, amino acids, and altered glycerophospholipids, which in turn were associated with increased MetS score. Conclusions and Relevance: This cohort study suggests that prenatal exposure to EDC mixtures may be associated with adverse metabolic health in children. Given the pervasive nature of EDCs and the increase in MetS, these findings hold substantial public health implications.
Subject(s)
Endocrine Disruptors , Metabolic Syndrome , Prenatal Exposure Delayed Effects , Humans , Female , Pregnancy , Prenatal Exposure Delayed Effects/chemically induced , Prenatal Exposure Delayed Effects/epidemiology , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Child , Male , Endocrine Disruptors/adverse effects , Endocrine Disruptors/urine , Risk Factors , Environmental Pollutants/urine , Environmental Pollutants/blood , Environmental Pollutants/adverse effects , Adult , Maternal Exposure/adverse effects , Maternal Exposure/statistics & numerical data , Cohort Studies , Birth CohortABSTRACT
INTRODUCTION: The RISKMet project aims to: (1) identify risk factors for metabolic syndrome (MetS) by comparing patients with and without MetS; (2) characterise patients treated with second-generation antipsychotics (SGAs) about MetS diagnosis; (3) study behavioural patterns, including physical activity (PA) and dietary habits, in patients and healthy individuals using a prospective cohort design. METHOD: The RISKMet project investigates MetS in individuals treated with SGAs, focusing on both adult and paediatric populations. The study utilizes a case-control design to examine potential risk factors for MetS, categorizing participants as MetS+ considered as "Cases" and MetS- considered as "Controls" matched by sex and age. The evaluation of factors such as MetS, lifestyle habits, and environmental influences is conducted at two time points, T0 and T3, after 3 months. Subsequently, the project aims to assess body parameters, including physical examinations, and blood, and stool sample collection, to evaluate metabolic markers and the impact of SGAs. The analysis includes pharmacological treatment data and genetic variability. Behavioural markers related to lifestyle, eating behaviour, PA, and mood are assessed at both T0 and T3 using interviews, accelerometers, and a mobile app. The study aims to improve mental and physical well-being in SGA-treated individuals, establish a biobank for MetS research, build an evidence base for physical health programs, and develop preventive strategies for SGA-related comorbidities. CONCLUSIONS: This project innovates MetS monitoring in psychiatry by using intensive digital phenotyping, identifying biochemical markers, assessing familial risks, and including genetically similar healthy controls. STUDY REGISTRATION NUMBER: ISRCTN18419418 at www.isrctn.com.
Subject(s)
Antipsychotic Agents , Metabolic Syndrome , Humans , Metabolic Syndrome/chemically induced , Metabolic Syndrome/genetics , Antipsychotic Agents/adverse effects , Antipsychotic Agents/therapeutic use , Risk Factors , Male , Female , Adult , Case-Control Studies , Prospective Studies , Life Style , Exercise , Middle Aged , ChildABSTRACT
BACKGROUND: Metabolic syndrome (MetS) is commonly associated with increased risk of cardiac disease that affects a large number of world populations. OBJECTIVE: This research attempted to investigate the efficacy of fennel seeds extract (FSE) in preventing development of cardiac dysfunction in rats on fructose enriched diet for 3 months, as a model of MetS. MATERIALS & METHODS: Thirty adult Wistar male rats (160-170â¯g) were assigned into 5 groups including control, vehicle, FSE (200â¯mg/kg BW) and fructose (60%) fed rats with and without FSE. Following the last treatment, blood pressure, ECG and heart rate were measured. Next, blood and cardiac tissues were taken for biochemical and histological investigations. RESULTS: Feeding fructose exhibited characteristic features of MetS involving, hypertension, abnormal ECG, elevated heart rate, serum glucose, insulin, lipids and insulin resistance, accompanied by abdominal obesity, cardiac hypertrophy and hyperuricemia. Fructose fed rats also showed significant reduction in cardiac antioxidants (GSH, SOD, CAT) with elevation in oxidative stress indices (NADPH oxidase, O2.-, H2O2, MDA, PCO), NF-κß, pro-inflammatory cytokines (TNF-α, IL-1ß, IL-6), adhesion molecules (ICAM-1, VCAM-1) and serum cardiac biomarkers (AST, LDH, CK-MB, cTn-I). Histopathological changes evidenced by destruction of cardiac myofibrils, cytoplasmic vacuolization, and aggregation of inflammatory cells were also detected. Consumption of FSE showed high ability to alleviate fructose-induced hypertension, ECG abnormalities, cardiac hypertrophy, metabolic alterations, oxidative stress, inflammation and histological injury. CONCLUSION: Findings could suggest FSE as a complementary supplement for preventing MetS and associated cardiac outcomes. However, well controlled clinical studies are still needed.
Subject(s)
Disease Models, Animal , Foeniculum , Fructose , Hyperuricemia , Inflammation , Metabolic Syndrome , NF-kappa B , Plant Extracts , Rats, Wistar , Seeds , Animals , Metabolic Syndrome/metabolism , Metabolic Syndrome/pathology , Metabolic Syndrome/chemically induced , Metabolic Syndrome/drug therapy , Fructose/adverse effects , Plant Extracts/pharmacology , Male , NF-kappa B/metabolism , Seeds/chemistry , Rats , Hyperuricemia/chemically induced , Hyperuricemia/drug therapy , Foeniculum/chemistry , Inflammation/pathology , Inflammation/metabolism , Oxidative Stress/drug effects , Signal Transduction/drug effectsABSTRACT
BACKGROUND AND PURPOSE: Cancer therapy-related cardiovascular adverse events (CAEs) in presence of comorbidities, are in the spotlight of the cardio-oncology guidelines. Carfilzomib (Cfz), indicated for relapsed/refractory multiple myeloma (MM), presents with serious CAEs. MM is often accompanied with co-existing comorbidities. However, Cfz use in MM patients with cardiometabolic syndrome (CMS) or in heart failure with reduced ejection fraction (HFrEF), is questionable. EXPERIMENTAL APPROACH: ApoE-/- and C57BL6/J male mice received 14 weeks Western Diet (WD) (CMS models). C57BL6/J male mice underwent permanent LAD ligation for 14 days (early-stage HFrEF model). CMS- and HFrEF-burdened mice received Cfz for two consecutive or six alternate days. Daily metformin and atorvastatin administrations were performed additionally to Cfz, as prophylactic interventions. Mice underwent echocardiography, while proteasome activity, biochemical and molecular analyses were conducted. KEY RESULTS: CMS did not exacerbate Cfz left ventricular (LV) dysfunction, whereas Cfz led to metabolic complications in both CMS models. Cfz induced autophagy and Ca2+ homeostasis dysregulation, whereas metformin and atorvastatin prevented Cfz-mediated LV dysfunction and molecular deficits in the CMS-burdened myocardium. Early-stage HFrEF led to depressed LV function and increased protein phosphatase 2A (PP2A) activity. Cfz further increased myocardial PP2A activity, inflammation and Ca2+-cycling dysregulation. Metformin co-administration exerted an anti-inflammatory potential on the myocardium without improving LV function. CONCLUSION AND IMPLICATIONS: CMS and HFrEF seem to exacerbate Cfz-induced CAEs, by presenting metabolism-related hidden toxicity and PP2A-related cardiac inflammation, respectively. Metformin retains its prophylactic potential in the presence of CMS, while mitigating inflammation and Ca2+ signalling dysregulation in the HFrEF myocardium.
Subject(s)
Cardiotoxicity , Heart Failure , Mice, Inbred C57BL , Oligopeptides , Animals , Male , Cardiotoxicity/prevention & control , Oligopeptides/pharmacology , Oligopeptides/administration & dosage , Heart Failure/chemically induced , Heart Failure/metabolism , Heart Failure/drug therapy , Heart Failure/prevention & control , Mice , Metabolic Syndrome/chemically induced , Metabolic Syndrome/drug therapy , Metabolic Syndrome/metabolismABSTRACT
Endocrine-disrupting chemicals (EDCs) may play a role in non-alcoholic fatty liver disease (NAFLD); however, studies on the combined effects of EDC mixtures on NAFLD development are limited. Here, we explored the association between exposure to EDC mixtures and NAFLD and investigated the potential mediating role of metabolic syndrome (MetS). We included participants from the Korean National Environmental Health Survey Cycle 4 (2018-2020) and quantified the urinary concentrations of various EDCs-eight phthalate metabolites, three phenols, one antibacterial compound, four parabens, four polycyclic aromatic hydrocarbons, and one pyrethroid pesticide metabolite-as well as serum concentrations of five perfluorinated compounds (PFCs). NAFLD was defined as a hepatic steatosis index (HSI) ≥36 or a fatty liver index (FLI) ≥60. Weighted quantile sum (WQS) regression was employed to evaluate the associations between EDC mixtures and the risk of MetS or NAFLD. Causal mediation analysis was conducted to explore the potential mediating effect of MetS on the association between mixtures of EDCs and NAFLD risk. All estimates were adjusted for age, sex, educational level, physical activity, smoking status, involuntary smoking, and drinking habits. A total of 2942 adults were included in the analysis. Moderate-to-high positive correlations were identified between phthalate metabolites and PFCs. Higher WQS scores were associated with an elevated risk of MetS and NAFLD. The sex-stratified WQS regression model showed that the interactions between the WQS index and sex were significant for MetS and NAFLD. According to the causal mediation analysis, both the direct and indirect effects of EDC mixtures on NAFLD, with MetS as a mediator, were significant in females. Collectively, these findings highlight the need for interventions that could address both EDC mixture exposure and metabolic status to effectively reduce the risks associated with NAFLD and its related complications.
Subject(s)
Endocrine Disruptors , Environmental Pollutants , Metabolic Syndrome , Non-alcoholic Fatty Liver Disease , Humans , Republic of Korea/epidemiology , Non-alcoholic Fatty Liver Disease/epidemiology , Non-alcoholic Fatty Liver Disease/chemically induced , Male , Female , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Adult , Middle Aged , Environmental Pollutants/urine , Environmental Exposure/statistics & numerical data , Aged , Phthalic Acids/urineABSTRACT
Background: Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets using machine learning (ML) method. Methods: The data used in this study are from the national health and nutrition examination survey 2003-2018. According to the demographic information and heavy metal exposure level of participants, a total of 22 variables were included. Lasso was used to screen out the key variables, and 9 commonly used ML models were selected to establish the associations with the 5-fold cross validation method. Finally, we choose the SHapley Additive exPlanations (SHAP) method to explain the prediction results of Adaboost model. Results: 11,667 eligible individuals were randomly divided into two groups to train and verify the prediction model. Through lasso, characteristic variables were selected from 24 variables as predictors. The AUC (area under curve) of the models selected in this study were all greater than 0.7, and AdaBoost was the best model. The AUC value of AdaBoost was 0.807, the accuracy was 0.720, and the sensitivity was 0.792. It is noteworthy that higher levels of cadmium, body mass index, cesium, being female, and increasing age were associated with an increased probability of MetS. Conversely, lower levels of cobalt and molybdenum were linked to a decrease in the estimated probability of MetS. Conclusion: Our study highlights the AdaBoost model proved to be highly effective, precise, and resilient in detecting a correlation between exposure to heavy metals and MetS. Through the use of interpretable methods, we identified cadmium, molybdenum, cobalt, cesium, uranium, and barium as prominent contributors within the predictive model.
Subject(s)
Machine Learning , Metabolic Syndrome , Metals, Heavy , Nutrition Surveys , Humans , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Female , Male , Middle Aged , Adult , Risk Factors , Environmental Exposure/adverse effects , Aged , Body Mass IndexABSTRACT
Mounting evidence shows that bisphenol A (BPA) is associated with metabolic risk factors. The aim of this study was to review related epidemiologic studies and conduct a meta-analysis to quantitatively estimate the association between BPA and metabolic syndrome. Four electronic databases were systematically searched to identify suitable articles. A total of 47 published studies were finally included. Two studies involved metabolic syndrome. Of the 17, 17, 14, and 13 studies on the relationship between BPA with abdominal obesity, blood pressure, fasting plasma glucose, and dyslipidemia, 10, 6, 3, and 4 studies were included in the meta-analysis, respectively. The results showed that the risk of abdominal obesity increased with the increase of BPA exposure, especially in the group with higher BPA exposure levels (Quartile 2 vs. Quartile 1, pooled OR = 1.16, 95%CI: 1.01, 1.33; Q3 vs. Q1, pooled OR = 1.31, 95%CI: 1.13, 1.51; Q4 vs. Q1, pooled OR = 1.40, 95%CI: 1.21, 1.61). However, there was no significant correlation between BPA exposure and metabolic syndrome components including hypertension, abnormal fasting plasma glucose, and dyslipidemia. The present study found that BPA exposure is significantly associated with a higher risk of abdominal obesity. However, the relationship between BPA with metabolic syndrome and its other components needs further longitudinal studies to verify.
Subject(s)
Benzhydryl Compounds , Metabolic Syndrome , Phenols , Benzhydryl Compounds/adverse effects , Metabolic Syndrome/chemically induced , Metabolic Syndrome/epidemiology , Humans , Phenols/adverse effects , Obesity, Abdominal/epidemiology , Environmental Exposure/adverse effects , Dyslipidemias/chemically induced , Dyslipidemias/epidemiology , Risk FactorsABSTRACT
The risk of metabolic syndrome (MetS) has been attributed to antipsychotic use in psychiatric patients. To date, there is limited data on the relationship between antipsychotic polypharmacy and MetS in patients with schizophrenia, schizoaffective disorder and bipolar disorder. Therefore, we aimed to investigate the rate of MetS in patients with these disorders receiving antipsychotic monotherapy and polypharmacy. We conducted a cross-sectional study on patients seen between January 2017 and December 2020, collecting data on the class, type, route of administration and number of antipsychotics received. We used the American Association of Clinical Endocrinology criteria to diagnose MetS. We included 833 subjects of whom 573 (68.8%) received antipsychotic monotherapy and 260 (31.2%) received polypharmacy. Overall, 28.6% ( N â =â 238) had MetS with no statistical difference between the two groups. Diastolic blood pressure and receiving olanzapine were significant predictors for developing MetS. In conclusion, our study found no significant difference in the rate of MetS between antipsychotic monotherapy and polypharmacy. A number of variables were significant predictors for MetS. Our findings were consistent with other studies and warrant the need for careful choice of antipsychotics and regular screening and management of abnormal metabolic parameters.
Subject(s)
Antipsychotic Agents , Bipolar Disorder , Metabolic Syndrome , Polypharmacy , Psychotic Disorders , Schizophrenia , Humans , Antipsychotic Agents/therapeutic use , Antipsychotic Agents/adverse effects , Schizophrenia/drug therapy , Female , Male , Bipolar Disorder/drug therapy , Metabolic Syndrome/epidemiology , Metabolic Syndrome/chemically induced , Cross-Sectional Studies , Adult , Psychotic Disorders/drug therapy , Middle AgedABSTRACT
Olanzapine-induced metabolic syndrome (MS) is a primary risk factor for insulin resistance, hepatorenal damage, and polycystic ovarian syndrome. The objective of the current study was to assess the protective effects of aprepitant (AP) against MS caused by olanzapine and the associated ovarian, renal, and liver dysfunction via modulation of IGF1/p-AKT/FOXO1 and NFκB/IL-1ß/TNF-α signaling pathways. AP mitigated all biochemical and histopathological abnormalities induced by olanzapine and resulted in a significant reduction of serum HOMA-IR, lipid profile parameters, and a substantial decrease in hepatic, renal, and ovarian MDA, IL-6, IL-1ß, TNF-α, NFκB, and caspase 3. Serum AST, ALT, urea, creatinine, FSH, LH, and testosterone also decreased significantly by AP administration. The FOXO 1 signaling pathway was downregulated in the AP-treated group, while GSH, SOD, and HDL cholesterol levels were elevated.
Subject(s)
Metabolic Syndrome , Female , Rats , Animals , Metabolic Syndrome/chemically induced , Metabolic Syndrome/drug therapy , Metabolic Syndrome/prevention & control , Aprepitant , Olanzapine , Proto-Oncogene Proteins c-akt , Tumor Necrosis Factor-alpha , Interleukin-1betaABSTRACT
OBJECTIVE: To summarize the available evidence on metabolic parameters indicating metabolic adverse effects and risk of metabolic syndrome in children and adolescents treated with antipsychotics, following a pre-specified protocol (PROSPERO ID 252336). METHOD: We searched PubMed, Embase and PsycINFO until May 14, 2021, to identify systematic reviews (SR), meta-analyses (MA) and network meta-analyses (NMA) examining symptoms associated to metabolic syndrome in patients <18 years of age who required treatment with oral antipsychotic drugs. Evidence from quantitative analyses for all outcomes related to anthropometric, glyco-metabolic, and blood pressure parameters (measured from baseline to intervention-end and/or follow-up, in subjects exposed to antipsychotics and placebo) was reported on the basis of their metrics (median difference [medianD], mean difference [MD], standardized mean difference [SMD], odds ratio [OR], risk ratio ([RR]). A qualitative synthesis was also made. A formal quality assessment of the included studies was carried out by using the AMSTAR 2. We also provided a hierarchical stratification of the evidence from meta-analyses based on the class of evidence. RESULTS: A total of 23 articles (13 MA, 4 NMA and 6 SR) were included for review. As compared with placebo, an increase in triglyceride levels was associated with olanzapine (medianD [95% CI]: 37 [12.27, 61.74] mg/dL; MD [95% CI]: 38.57 [21.44, 55.77] mg/dL) and quetiapine (medianD [95% CI]: 21.58 [95% CI]: 4.27, 38.31 mg/dL; MD [95% CI]: 34.87 [20.08, 49.67] mg/dL; SMD [95% CI]: 0.37 [0.06, 0.068]), whereas decreased triglyceride levels were found for lurasidone. Increased total cholesterol level was associated with asenapine (medianD [95% CI]: 9.1 [1.73, 16.44] mg/dL), quetiapine (medianD [95% CI]: 15.60 [7.30, 24.05] mg/dL; olanzapine (MD [95% CI] from 3.67 [1.43, 5.92] mg/dL to 20.47 [13.97, 26.94] mg/dL]; and lurasidone (medianD [95% CI]: 8.94 [1.27, 16.90] mg/dL). Change in glucose levels did not differ among antipsychotics or placebo. Lurasidone, molindone, and ziprasidone were the best tolerated in terms of weight gain. According to the AMSTAR 2 scoring system, 13 (56.5%) reviews were rated as very low quality. According to classes of evidence, most MA were level 4, especially because of their limited total sample size. CONCLUSION: By collating meta-analyses assessing biochemical markers of metabolic syndrome in antipsychotic-treated children, we conclude that olanzapine should not be the antipsychotic of choice in patients at risk for hypertriglyceridemia or hypercholesterolemia. Aripiprazole and lurasidone appear to be better tolerated in terms of metabolic adverse events. Insufficient meta-analytic data are available to provide a precise risk estimate of metabolic syndrome, and, overall, the quality of evidence is low. STUDY REGISTRATION INFORMATION: Association between the use of antipsychotic drugs and alterations of the parameters defining the Metabolic Syndrome (MetS) in children and adolescents: an umbrella review; https://www.crd.york.ac.uk/prospero/; CRD42021252336.
Subject(s)
Antipsychotic Agents , Metabolic Syndrome , Schizophrenia , Child , Humans , Adolescent , Antipsychotic Agents/adverse effects , Olanzapine/therapeutic use , Quetiapine Fumarate , Lurasidone Hydrochloride/therapeutic use , Metabolic Syndrome/chemically induced , Metabolic Syndrome/epidemiology , Metabolic Syndrome/drug therapy , Schizophrenia/drug therapy , Triglycerides/therapeutic useABSTRACT
BACKGROUND: Weight gain following initiation of antiretroviral therapy (ART) is common. We assessed the impact of changes in weight in the year following ART initiation with subsequent cardiometabolic disease among AIDS Clinical Trials Group (ACTG) participants. METHODS: Linear regression models were fit to examine the association between change in weight/waist circumference (WC) in weeks 0-48 and change in metabolic parameters in weeks 0-48 and 48-96. Cox proportional hazard models were fit to examine the association between changes in weight/WC in weeks 0-48 and diabetes mellitus (DM), metabolic syndrome, or cardiometabolic and cardiovascular events after week 48. RESULTS: Participants (N = 2624) were primarily male (81%) and non-White (60%). Mean weight gain from 0-48 weeks was 3.6 kg (SD 7.3); 130 participants developed DM; 360 metabolic syndrome; 424 any cardiometabolic event; 28 any cardiovascular event, over 480 weeks of follow-up. In adjusted models, total cholesterol increased by 0.63 mg/dL (95% confidence interval [CI] [.38, .089]) and LDL by 0.39 mg/dL (0.19, 0.59) per 1 kg increase in weight from weeks 0 to48. Participants who experienced >10% weight gain (vs -5% to 5%) had an increased risk of DM (hazard ratio [HR] 2.01, 95% CI [1.30, 3.08]), metabolic syndrome (HR 2.24, 95% CI [1.55, 2.62]), and cardiometabolic outcomes (HR 1.54, 95% CI [1.22, 1.95]). Participants who lost more than 5% of their baseline weight had a lower risk of incident metabolic syndrome (HR 0.67, 95% CI [0.42, 1.07]). Trends for WC were similar. CONCLUSIONS: Weight and body composition changes in the first year following ART initiation are associated with contemporaneous changes in metabolic parameters and subsequent cardiometabolic disease.
Subject(s)
Cardiovascular Diseases , Diabetes Mellitus , HIV Infections , Metabolic Syndrome , Humans , Male , Metabolic Syndrome/chemically induced , Metabolic Syndrome/epidemiology , Cardiovascular Diseases/chemically induced , Cardiovascular Diseases/epidemiology , Weight Gain , HIV Infections/drug therapy , Risk FactorsABSTRACT
BACKGROUND: Tyrosine kinase inhibitor (TKI) treatment has been identified to be a risk factor for metabolic syndrome and cardiovascular diseases (CVDs) in patients diagnosed with chronic myeloid leukemia (CML). However, the specific contribution of post-TKI metabolic syndrome and the individual TKIs, including imatinib, nilotinib, and dasatinib, contribute to the development of CVDs remains unclear. METHODS: We conducted a nationwide database to investigate the incidence of post-TKI metabolic syndrome, including diabetes, hyperlipidemia, and hypertension, as well as their association with CVDs. To compare the risk of post-TKI comorbidities and CVDs among TKIs, we utilized the incidence rate ratio (IRR), and subdistribution hazard ratio (SHR) calculated from multiple Fine-Gray models. RESULTS: A total of 1211 patients without diabetes, 1235 patients without hyperlipidemia, and 1074 patients without hypertension were enrolled in the study. The incidence rate of post-TKI diabetes and hyperlipidemia was the highest in patients treated with nilotinib compared to imatinib and dasatinib (IRRsâ ≥â 3.15, Psâ ≤â .047). After adjusting for confounders, nilotinib remained a significant risk factor for post-TKI diabetes and hyperlipidemia at an SHR of 3.83 (Pâ <â .001) and 5.15 (Pâ <â .001), respectively. Regarding the occurrence of CVDs, patients treated with nilotinib were more likely to develop CVDs than those treated with imatinib in non-hyperlipidemic group (IRRâ =â 3.21, Pâ =â .020). Pre-existing and post-TKI hyperlipidemia were found to have a stronger association with CVDs, with SHR values of 5.81 (Pâ =â .034) and 13.21 (Pâ =â .001), respectively. CONCLUSION: The findings of this study indicate that nilotinib treatment is associated with increased risks of diabetes and hyperlipidemia, with hyperlipidemia being the most significant risk for CVDs. Therefore, we recommend that CML patients receiving nilotinib should undergo screening for diabetes and hyperlipidemia prior to initiating TKI treatment. Additionally, regular monitoring of lipid profiles during TKI therapy and implementing effective management strategies to control hyperlipidemia are crucial.
Subject(s)
Cardiovascular Diseases , Diabetes Mellitus , Hyperlipidemias , Hypertension , Leukemia, Myelogenous, Chronic, BCR-ABL Positive , Metabolic Syndrome , Humans , Dasatinib , Imatinib Mesylate , Cohort Studies , Cardiovascular Diseases/chemically induced , Cardiovascular Diseases/epidemiology , Metabolic Syndrome/chemically induced , Pyrimidines/adverse effects , Protein Kinase Inhibitors/adverse effects , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/complications , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/epidemiology , Diabetes Mellitus/chemically induced , Diabetes Mellitus/drug therapy , Diabetes Mellitus/epidemiology , Hypertension/chemically induced , Hypertension/complications , Hypertension/drug therapy , Hyperlipidemias/chemically induced , Hyperlipidemias/epidemiologyABSTRACT
INTRODUCTION: There are conflicting findings on the link between liver fibrosis and cumulative methotrexate dosages. We aimed to determine the frequency of liver fibrosis in rheumatoid arthritis patients treated with methotrexate and to identify its associated factors. METHODS: We conducted a cross-sectional study over 9 months (April-December 2021), including rheumatoid arthritis patients treated with methotrexate. Demographic and clinical data were collected. Liver stiffness was assessed by FibroScan. Fibrosis and significant liver fibrosis were defined as liver stiffness higher than 6 and 7.2 kPa, respectively. Liver tests, albuminemia, lipid profile, and blood glycemia were measured. Metabolic syndrome was also evaluated. Statistical analyses were performed using SPSS. RESULTS: We included 21 men and 47 women. The mean age was 51.60 ± 1.82 years. The mean disease duration was 8.29 ± 6.48 years. The mean weekly intake of methotrexate was 13.76 ± 3.91 mg. The mean methotrexate duration was 4.67 ± 4.24 years. The mean cumulative dose was 3508.87 ± 3390.48 mg. Hypoalbuminemia and metabolic syndrome were found in 34% and 25% of cases. We noted increased alkaline phosphatase levels in four cases. The mean liver stiffness was 4.50 ± 1.53 kPa. Nine patients had liver fibrosis, and four had significant fibrosis. Associated factors with liver fibrosis were as follows: age ≥ 60 years (OR:22.703; 95%CI [1.238-416.487]; p = 0.035), cumulated dose of methotrexate ≥ 3 g (OR: 76.501; 95%CI [2.383-2456.070]; p = 0.014), metabolic syndrome (OR: 42.743; 95%CI [1.728-1057.273]; p = 0.022), elevated alkaline phosphatase levels (OR: 28.252; 95%CI [1.306-611.007]; p = 0.033), and hypoalbuminemia (OR: 59.302; 95%CI [2.361-1489.718]; p = 0.013). CONCLUSION: Cumulating more than 3 g of methotrexate was associated with liver fibrosis in rheumatoid arthritis patients. Having a metabolic syndrome, higher age, hypoalbuminemia, and elevated alkaline phosphatase levels were also likely to be independently associated with liver fibrosis. Key points ⢠Rheumatoid arthritis patients require monitoring hepatic fibrosis when the cumulated dose of methotrexate is above 3 g. ⢠Metabolic syndrome is a risk factor for liver fibrosis, suggesting that its management is necessary to prevent this complication. ⢠Hypoalbuminemia and elevated alkaline phosphatase levels (twice the upper limit) in rheumatoid arthritis patients treated with methotrexate were associated with liver fibrosis.