Biomarkers Of Metabolic Syndrome Research Articles

Chemerin, IL-18 and IL-1 Beta as Biomarkers of Metabolic Syndrome in Egyptian Obese Children

Chemerin, IL-18 and IL-1 Beta as Biomarkers of Metabolic Syndrome in Egyptian Obese Children

Searching for better biomarkers for metabolic syndrome

Searching for better biomarkers for metabolic syndrome

Delving the Role of Caralluma fimbriata: An Edible Wild Plant to Mitigate the Biomarkers of Metabolic Syndrome

Metabolic syndrome (MS), commonly known as syndrome X or insulin resistance syndrome, is a collection of risk factors for cardiovascular diseases and type II diabetes. MS is believed to impact over a billion individuals worldwide. It is a medical condition defined by visceral obesity, insulin resistance, high blood pressure, and abnormal cholesterol levels, according to the World Health Organization. The current dietary trends are more focused on the use of functional foods and nutraceuticals that are well known for their preventive and curative role against such pathological disorders. Caralluma fimbriata is one such medicinal plant that is gaining popularity. It is a wild, edible, succulent roadside shrub with cactus-like leaves. Besides its main nutrient contents, various bioactive constituents have been identified and linked with positive health outcomes of appetite-suppressing, hypolipidemic, antioxidant, hepatoprotective, and anticancer potentials. Hence, such properties make C. fimbriata an invaluable plant against MS. The current review compiles recent available literature on C. fimbriata's nutritional composition, safety parameters, and therapeutic potential for MS. Summarized data in this review reveals that C. fimbriata remains a neglected plant with limited food and therapeutic applications. Yet various studies explored here do prove its positive health-ameliorating outcomes.

A comparison of the ratios of C-reactive protein and triglycerides to high-density lipoprotein-cholesterol as biomarkers of metabolic syndrome in African Americans and non-Hispanic Whites

AimsThe ratio of triglycerides (TG) to high density lipoprotein–cholesterol (HDL-C) is a validated biomarker of insulin resistance and metabolic syndrome (MetS). In African–Americans (AA) there is concern about this ratio because their mean TG level is lower than the general population. As an alternative approach, we examined the CRP:HDL-C ratio in both AA and non-Hispanic whites (NHW) in the NHANES study for its association with MetS. MethodsA total of n = 3541 individuals were studied from the NHANES data. Fasting blood samples were obtained for lipids, insulin, and CRP. TG and CRP ratios to HDL-C were calculated. ResultsThe TG:HDL-C ratio was significantly increased in NHW compared to AA, but the CRP:HDL-C ratio did not differ between NHW and AA groups. Both ratios were significantly increased in MetS patients versus controls (both races) and increased with greater severity of MetS. Receiver Operating Characteristic (ROC) curve analysis showed that the TG:HDL-C area under the curve was superior to CRP:HDL-C in predicting MetS in both AA and NHW patients. ConclusionIn this large NHANES study, the TG:HDL-C ratio is a superior predictor of MetS in both AA and NHW persons despite the lower TG levels in AA persons.

Searching for better biomarkers for metabolic syndrome

Searching for better biomarkers for metabolic syndrome

Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS.

Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (n = 26), normoglycemic MetS patients (n = 30), and healthy (normoglycemic lean) subjects (n = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highly sensitive ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). One-way ANOVA analysis revealed that 59 metabolites differed significantly among the three groups (p < 0.05). Glutamine, 5-hydroxy-L-tryptophan, L-sorbose, and hippurate were highly associated with MetS. However, 9-methyluric acid, sphinganine, and threonic acid were highly associated with prediabetes/MetS. Metabolic pathway analysis showed that arginine biosynthesis and glutathione metabolism were associated with MetS/prediabetes, while phenylalanine, D-glutamine and D-glutamate, and lysine degradation were highly impacted in MetS. The current study sheds light on the potential diagnostic value of some metabolites in metabolic syndrome and the role of their alteration on some of the metabolic pathways. More studies are needed in larger cohorts in order to verify the implication of the above metabolites on MetS and their diagnostic value.

M063 Evaluation of plasma copeptin as a novel biomarker of obesity-induced insulin resistance and metabolic syndrome

M063 Evaluation of plasma copeptin as a novel biomarker of obesity-induced insulin resistance and metabolic syndrome

Design of a clinical trial to isolate the experience of food insecurity and elucidate the biological mechanisms of risk for childhood health outcomes

BackgroundFood insecurity affects one in seven households with children in the United States, disproportionately impacts households headed by women and minorities, and is associated with childhood comorbidities, including obesity. While food insecurity likely contributes to poor health through its effect on diet, such a simplistic understanding likely obscures the effects of poverty-related stress and other Adverse Childhood Experiences, on metabolic health. MethodsOver two summers, 100 children, ages 8–12 years, will be recruited from low-income households in an urban, Rhode Island community, to participate in an 8-week trial designed to isolate the experience of food insecurity. Summer represents a natural risk period of food insecurity in children, such that children will be randomized to receive weekly shipments of five breakfast and lunch meals that mimic school meals or to experience the likely onset of summertime food insecurity and receive a weekly newsletter on community resources that is not expected to affect food insecurity. Through assessment visits at baseline, mid-summer and end of summer, we will examine group differences in change in diet quality, biomarkers of Metabolic Syndrome, inflammation, and stress, BMI z-scores, and child measures of behavior and anxiety and depression symptoms. We will also explore the impact of caregiver mood and stress on the health effects of food insecurity. ConclusionsFindings stand to clarify the mechanisms by which food insecurity affects child health outcomes and to inform how to best address food insecurity in the context of poverty-related stress. Trial registrationThis trial has been registered at ClinicalTrials.gov (NCT04968496).

Asprosin, visfatin and subfatin as new biomarkers of obesity and metabolic syndrome.

Metabolic syndrome (MetS) and obesity are important public health problems associated with adipose tissue mass. Asprosin, visfatin, and subfatin are new members of which fate in MetS and obesity has not been fully revealed yet. Thus, this study was to investigate the association between asprosin, visfatin, subfatin, and biochemical values, demographic data, and body composition measurement values in MetS patients with and without obesity. Blood samples were taken from a total of 90 people, including 31 MetS patients with obesity, 29 MetS patients without obesity, and 30 healthy (control). Asprosin, visfatin, and subfatin were studied by the ELISA method. There was a negative correlation between asprosin and Body Mass Index (BMI) in the MetS + Obese group. The correlations between asprosin and urea and fasting insulin (FI) levels in the MetS group were positive and statistically significant (p < 0.05). While there was a statistically significant negative correlation (p < 0.05) between visfatin and BMI in the MetS + Obese group, the correlation with waist circumference in the MetS + Obese and MetS groups was statistically significant and negative (p < 0.05). There was a statistically significant negative relationship (p < 0.05) between aspartate aminotransferase value and visfatin. The results between visfatin values and asprosin and subfatin in all groups were significant (p < 0.05). There is a direct relationship between circulating amounts of asprosin, visfatin, and subfatin hormones and age, weight, height, diastolic blood pressure, high-density lipoprotein-cholesterol, aspartate aminotransferase, alanine transaminase, and creatinine. Therefore, asprosin, visfatin, and subfatin hormones are the new biomarkers of metabolic turbulence.

Pathogenesis and Biomarkers of Metabolic Syndrome

Metabolic syndrome (MetS) is a pathologic multifaceted condition characterized by elevated triacylglycerides, decreased high density lipoproteins, insulin resistance, increased blood pressure and fasting glucose. Together these abnormalities increase a risk of cardiovascular diseases and type 2 diabetes mellitus. Overnutrition and sedentary lifestyle followed by overweight and obesity are the main contributing factors to MetS development. The pathogenesis of MetS is very complex and not fully elucidated. The studies support the concept of oxidant/antioxidant imbalance and low-grade inflammation playing main roles in its manifestations. Diagnosis with MetS and the development of MetS complications can be detected and monitored via specific serum biomarkers. In this paper, we describe classical metabolic, hormonal and pro-/anti-inflammatory markers which are the most frequently used for MetS diagnostic and research. They include serum lipid profile (triacylglycerides, total cholesterol, low and high density lipoproteins), blood pressure, fasting glucose and HOMA-IR index, levels of anti-inflammatory adiponectin, pro-inflammatory C-reactive protein and cytokines (TNF-α, IL-1β, IL-6, etc.). We also analyze advantages of additional criteria such as levels of oxidative damages, appetite hormones (leptin, ghrelin), apolipoproteins and oxylipins, the composition of gut microbiota and levels of microbiome-derived metabolites, the ratios between different parameters as helpful biomarkers of MetS and concomitant cardiovascular diseases.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants.

BackgroundMetabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.MethodsPotential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.FindingsNine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.InterpretationWe identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.FundingThis work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Dysbiosis of the Salivary Microbiome is Associated with Hypertension and Correlated with Metabolic Syndrome Biomarkers.

BackgroundHypertension (HT) is an idiopathic disease with severe complications and a high incidence of global mortality. Although the disease shares characteristic features with diabetes and obesity, the complex interplay of endogenous and environmental factors is not well characterized. The oral microbiome has recently been studied to better understand the role of commensal microorganisms in metabolic disorders, including HT, although its role in disease etiology is unclear.MethodsTo bridge this gap, we compared the oral microbiome and clinical chemistry of adult subjects enrolled at Qatar Biobank. Clinical chemistry was performed using Roche Cobas-6000 analyzer. Saliva samples were subjected to 16S rRNA sequencing using Illumina MiSeq platform. Cross-gender comparisons were made between control (males/females) (C-M and C-F) and HT (HT-M and HT-F) groups.ResultsThe HT groups had higher (p ≤ 0.05) BMI, plasma glucose, insulin, C-peptide, and alkaline phosphatase (ALP) concentrations. Triglycerides, cholesterol, LDL-cholesterol, and sodium ions were similar among the groups. The microbiome was predominantly occupied by Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Firmicutes were higher (p ≤ 0.05) in the HT groups, whereas Proteobacteria was only higher in the C-F group. Prevotella and Veillonella were significantly higher in the HT groups and exhibited a positive correlation with blood pressure and hyperglycemia. In contrast to other studies, the mathematical summation of priori-select microbes reveals that nitrate-reducing microbes were higher in the HT groups compared with the controls.ConclusionIn conclusion, these observations suggest a strong association of HT with microbial dysbiosis, where microbial species other than nitrate-reducing microbes contribute to blood pressure regulation. The findings affirm plausible microbial signatures of hypertension and suggest manipulating these microbes as a novel treatment modality. Future experiments are warranted for the mechanistic investigation of hypertension metagenomics and microbial activity.

Potential evidence for epigenetic biomarkers of metabolic syndrome in human whole blood in Latinos.

Metabolic syndrome (MetS) is highly prevalent worldwide. In the United States, estimates show that more than 30% of the adult population has MetS. MetS consists of multiple phenotypes, including obesity, dyslipidemia, and impaired glucose tolerance. Therefore, identifying the molecular mechanisms to explain this complex disease is critical for diagnosing and treating MetS. We previously showed 70 increased genes and 20 decreased genes in whole blood in MetS participants. The present study aimed to identify blood-based DNA methylation biomarkers in non-MetS versus MetS participants. The present study analyzed whole blood DNA samples from 184 adult participants of Latino descent from the Arizona Insulin Resistance (AIR) registry. We used the National Cholesterol Education Program Adult Treatment Panel III (NCEP: ATP III) criteria to identify non-MetS (n = 110) and MetS (n = 74) participants. We performed whole blood methylation analysis on select genes: ATP Synthase, H+ Transporting mitochondrial F1 Complex, Epsilon Subunit (ATP5E), Cytochrome C Oxidase Subunit VIc (COX6C), and Ribosomal Protein L9 (RPL9). The pyrosequencing analysis was a targeted approach focusing on the promoter region of each gene that specifically captured CpG methylation sites. In MetS participants, we showed decreased methylation in two CpG sites in COX6C and three CpG sites in RPL9, all p < 0.05 using the Mann-Whitney U test. There were no ATP5E CpG sites differently methylated in the MetS participants. Furthermore, while adjusting for age, gender, and smoking status, logistic regression analysis reaffirmed the associations between MetS and mean methylation within COX6C and RPL9 (both p < 0.05). In addition, Spearman’s correlation revealed a significant inverse relationship between the previously published gene expression data and methylation data for RPL9 (p < 0.05). In summary, these results highlight potential blood DNA methylation biomarkers for the MetS phenotype. However, future validation studies are warranted to strengthen our findings.

Prevalence and biomarkers in metabolic syndrome

The prevalence of metabolic syndrome (MS) has a worldwide tendency to increase and depends on many components, which explains the complexity of diagnostics and approaches to the prevention and treatment of this pathology. Age, lifestyle, socioeconomic status, insulin resistance (IR), dyslipidemia, obesity and genetic predisposition are factors influencing the risk of developing and progression of MS. Features of the distribution and dysfunction of adipose tissue are important factors in the development of IR, with obesity, as well as the risk of the formation of cardiometabolic diseases and MS. ­Understanding of mechanisms is linked to advances in metabolic phenotyping. Metabolic phenotyping of obese persons is important for the development of important diseases in relation to the study of the pathophysiology of metabolic disorders, the possible concomitant disease and the search for innovative strategies for the prevention and treatment of MS. The understanding of MS mechanisms is associated with advances in metabolic phenotyping. Therefore, the relevance of further study of the pathophysiological mechanisms underlying various metabolic phenotypes of MS is one of the promising areas of modern scientific research. This review summarizes the current literature data on the prevalence of MS depending on gender, age, population, area of residence, education, level of physical activity, and many other parameters. Metabolic risks of MS development are detailed. Biological markers of MS are considered. The necessity of metabolic phenotyping of MS has been shown, which may have potential therapeutic value.

Screening the Influence of Biomarkers for Metabolic Syndrome in Occupational Population Based on the Lasso Algorithm.

Aim: Metabolic syndrome (MS) screening is essential for the early detection of the occupational population. This study aimed to screen out biomarkers related to MS and establish a risk assessment and prediction model for the routine physical examination of an occupational population.Methods: The least absolute shrinkage and selection operator (Lasso) regression algorithm of machine learning was used to screen biomarkers related to MS. Then, the accuracy of the logistic regression model was further verified based on the Lasso regression algorithm. The areas under the receiving operating characteristic curves were used to evaluate the selection accuracy of biomarkers in identifying MS subjects with risk. The screened biomarkers were used to establish a logistic regression model and calculate the odds ratio (OR) of the corresponding biomarkers. A nomogram risk prediction model was established based on the selected biomarkers, and the consistency index (C-index) and calibration curve were derived.Results: A total of 2,844 occupational workers were included, and 10 biomarkers related to MS were screened. The number of non-MS cases was 2,189 and that of MS was 655. The area under the curve (AUC) value for non-Lasso and Lasso logistic regression was 0.652 and 0.907, respectively. The established risk assessment model revealed that the main risk biomarkers were absolute basophil count (OR: 3.38, CI:1.05–6.85), platelet packed volume (OR: 2.63, CI:2.31–3.79), leukocyte count (OR: 2.01, CI:1.79–2.19), red blood cell count (OR: 1.99, CI:1.80–2.71), and alanine aminotransferase level (OR: 1.53, CI:1.12–1.98). Furthermore, favorable results with C-indexes (0.840) and calibration curves closer to ideal curves indicated the accurate predictive ability of this nomogram.Conclusions: The risk assessment model based on the Lasso logistic regression algorithm helped identify MS with high accuracy in physically examining an occupational population.

Advanced Molecular Imaging (MRI/MRS/1H NMR) for Metabolic Information in Young Adults with Health Risk Obesity.

Background: Obesity or being overweight is a medical condition of abnormal body fat accumulation which is associated with a higher risk of developing metabolic syndrome. The distinct body fat depots on specific parts of the anatomy have unique metabolic properties and different types of regional excessive fat distribution can be a disease hazard. The aim of this study was to identify the metabolome and molecular imaging phenotypes among a young adult population. Methods: The amount and distribution of fat and lipid metabolites profile in the abdomen, liver, and calf muscles of 46 normal weight, 17 overweight, and 13 obese participants were acquired using MRI and MR spectroscopy (MRS), respectively. The serum metabolic profile was obtained using proton NMR spectroscopy. NMR spectra were integrated into seven integration regions, which reflect relative metabolites. Results: A significant metabolic disorder symptom appeared in the overweight and obese group, and increased lipid deposition occurred in the abdomen, hepatocytes, and muscles that were statistically significant. Overall, the visceral fat depots had a marked influence on dyslipidemia biomarkers, blood triglyceride (r = 0.592, p < 0.001), and high-density lipoprotein cholesterol (r = −0.484, p < 0.001). Intrahepatocellular lipid was associated with diabetes predictors for hemoglobin (HbA1c%; r = 0.379, p < 0.001) and for fasting blood sugar (r = 0.333, p < 0.05). The lipid signals in serum triglyceride and glucose signals gave similar correspondence to biochemical lipid profiles. Conclusions: This study proves the association between alteration in metabolome in young adults, which is the key population for early prevention of obesity and metabolic syndrome. This study suggests that dyslipidemia prevalence is influenced mainly by the visceral fat depot, and liver fat depot is a key determinant for glucose metabolism and hyperglycemia. Moreover, noninvasive advanced molecular imaging completely elucidated the impact of fat distribution on the anthropometric and laboratory parameters, especially indices of the metabolic syndrome biomarkers in young adults.

The Effects of Ambient Air Pollution and Residential Greenness on Metabolic Disease Biomarkers in China

BACKGROUND AND AIM: We aim to study the association between air pollution, greenness, and metabolic syndrome (MetS) biomarkers, as mechanisms for cardiovascular diseases (CVD) and the mortality among the elderly in China. METHODS: We used the 2012 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) Biomarker Cohort. The cohort sampled participants from urban and rural areas of eight longevity counties. We matched the annual average fine particulate matter (PM2.5) concentrations in a 1 km × 1 km grid and calculated Normalized Difference Vegetation Index (NDVI) with a 500-meter radius. The medical technicians measured blood cholesterol, fasting glucose, blood pressure, height, weight, and waist circumference. We defined metabolic syndrome using modified Adult Treatment Panel III criteria. RESULTS:We had 1801 participants. Three-year average NDVI was slightly higher in the rural area than urban area (mean: 0.495 vs. 0.443) while the rural area had a similar three-year average PM2.5 level with the urban area (mean: 49.0 vs. 49.1). We found higher PM2.5 was associated with higher odds of abdominal obesity (AO) [OR (95%CI): 1.254 (1.159, 1.361)] and MetS [OR (95%CI): 1.165 (1.067, 1.278)]. Higher NDVI was associated with lower risk of AO [0.811 (0.711, 0.925)] and elevated fasting glucose [OR (95%CI): 0.84 (0.721, 0.982)], but was not significantly associated with MetS [OR (95% CI): 0.95 (0.821, 1.104)]. PM2.5 and NDVI had significant interaction on the risk of AO but not on the risk of MetS [p value of interaction term: 0.005 and 0.630 respectively]. CONCLUSIONS:We saw convergence of air pollution and greenness levels between urban and rural area among the eight counties studied in our cohort, with higher harmful effect of air pollution in rural areas and higher beneficial effect of greenness in urban areas. KEYWORDS: metabolic disease, greenness, air pollution, PM2.5, aging, China

Altered Serum Chitotriosidase Activity and Irisin Level in Obese Children

Objective:In this study, we aimed to investigate serum chitotriosidase (ChT) activity and irisin levels in children with obesity and compare them to those of healthy counterparts. Material and Methods: A total of 91 obese and 83 normal-weight children were included in the study. Serum ChT activity and irisin levels of children with obesity were compared to those of normal-weight children. Results: The mean ChT value in the obese group was 1825.332 ± 4804.147 nmol/L/h and was significantly higher than that in the control group. In contrast, the mean irisin level, 2679.663 ± 5473.58 pg/ml, was lower than that in the control group. The cutoff point of the continuous variable selected in the model for ChT was 601, with 31.9% sensitivity, 90.6% specificity, and an area under the curve of 0.596. The cutoff point for irisin was 901.4, with 83.5% sensitivity, 42.4% specificity, and an area under the curve of 0.617. Conclusion: This study is the first to show decreased serum both serum ChT activity and irisin level and ChT’s association with irisin levels in children with obesity . We argue that ChT and irisin should be considered potential biomarkers of metabolic syndrome in children with obesity.

Biomarkers of Metabolic Syndrome: Role in Pathogenesis and Pathophysiology Of Atrial Fibrillation.

The relationship between Metabolic syndrome and Atrial Fibrillation is confirmed by many studies. The components of Metabolic syndrome cause remodeling of the atrial. Metabolic syndrome and metabolic derangements of the syndrome could be the cause of the pathogenesis of AF. This review article discusses the major biomarkers of Metabolic syndrome and their role in the pathogenesis of AF. The biomarkers are adiponectin, leptin, Leptin/ Adiponectin ratio, TNF-α, Interleukin-6, Interleukin-10, PTX3, ghrelin, uric acid, and OxLDL.The elevated plasma levels of adiponectin were linked to the presence of persistent AF. Leptin signaling contributes to angiotensin-II evoked AF and atrial fibrosis. Tumor necrosis factor-alpha involvement has been shown in the pathogenesis of chronic AF. Similarly, Valvular AF patients showed high levels of TNF-α. Increased left atrial size was associated with the interleukin-6 because it is a well-known risk factor for AF. Interleukin-10 as well as TNF-α were linked to AF recurrence after catheter ablation. PTX3 could be superior to other inflammatory markers that were reported to be elevated in AF. The serum ghrelin concentration in AF patients was reduced and significantly increased after treatment. Elevated levels of uric acid could be related to the burden of AF. Increased OxLDL was found in AF as compared to sinus rhythm control.

Urine organic acids may be useful biomarkers for metabolic syndrome and its components in Korean adults.

Although metabolic syndrome (MetS) and its components are defined clinically, those with MetS may have various derangements in metabolic pathways. Thus, this study aimed to evaluate the traits of urine organic acid metabolites indicating the metabolic intermediates of the pathways in the subjects with MetS. This cross-sectional study included 246 men and 283 women in a hospital health check-up setting. Urine organic acid metabolites were assayed via high-performance liquid chromatography-mass spectrometry analyses. A high level of each metabolite was defined as the fifth quintile of the distribution. The subjects with MetS had high levels of pyruvate, α-ketoglutarate, α-ketoisovalerate, α-ketoisocaproate, formiminoglutamate, and quinolinate (odds ratios from 1.915 to 2.809 in logistic models adjusted for age and sex). Among the metabolites, pyruvate, formiminoglutamate, and quinolinate were not independent of homeostatic model assessment of insulin resistance (HOMA2-IR). Several metabolites were associated with one or more components of MetS and HOMA2-IR. Urine organic acid metabolites in MetS are characterized in altered carbohydrate and amino acid metabolism. MetS shared some traits in insulin resistance. These findings may promote the understanding of the pathophysiology of MetS.