Dataset Information

Blood Metabolite Signatures of Metabolic Syndrome in Two Cross-Cultural Older Adult Cohorts.

ABSTRACT: Metabolic syndrome (MetS) affects an increasing number of older adults worldwide. Cross-cultural comparisons can provide insight into how factors, including genetic, environmental, and lifestyle, may influence MetS prevalence. Metabolomics, which measures the biochemical products of cell processes, can be used to enhance a mechanistic understanding of how biological factors influence metabolic outcomes. In this study we examined associations between serum metabolite concentrations, representing a range of biochemical pathways and metabolic syndrome in two older adult cohorts: The Tsuruoka Metabolomics Cohort Study (TMCS) from Japan (n = 104) and the Baltimore Longitudinal Study of Aging (BLSA) from the United States (n = 146). We used logistic regression to model associations between MetS and metabolite concentrations. We found that metabolites from the phosphatidylcholines-acyl-alkyl, sphingomyelin, and hexose classes were significantly associated with MetS and risk factor outcomes in both cohorts. In BLSA, metabolites across all classes were uniquely associated with all outcomes. In TMCS, metabolites from the amino acid, biogenic amines, and free fatty acid classes were uniquely associated with MetS, and metabolites from the sphingomyelin class were uniquely associated with elevated triglycerides. The metabolites and metabolite classes we identified may be relevant for future studies exploring disease mechanisms and identifying novel precision therapy targets for individualized medicine.

SUBMITTER: Mahajan UV

PROVIDER: S-EPMC7072935 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Blood Metabolite Signatures of Metabolic Syndrome in Two Cross-Cultural Older Adult Cohorts.

Mahajan Uma V UV Varma Vijay R VR Huang Chiung-Wei CW An Yang Y Tanaka Toshiko T Ferrucci Luigi L Takebayashi Toru T Harada Sei S Iida Miho M Legido-Quigley Cristina C Thambisetty Madhav M

International journal of molecular sciences 20200216 4

Metabolic syndrome (MetS) affects an increasing number of older adults worldwide. Cross-cultural comparisons can provide insight into how factors, including genetic, environmental, and lifestyle, may influence MetS prevalence. Metabolomics, which measures the biochemical products of cell processes, can be used to enhance a mechanistic understanding of how biological factors influence metabolic outcomes. In this study we examined associations between serum metabolite concentrations, representing ...[more]

PMID: 32079087

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Project description:Metabolic dysregulation underlies key metabolic risk factors—obesity, dyslipidemia, and dysglycemia.To uncover mechanistic links between metabolomic dysregulation and metabolic risk by testing metabolite associations with risk factors cross-sectionally and with risk factor changes over time.Cross-sectional—discovery samples (n = 650; age, 36–69 years) from the Framingham Heart Study (FHS) and replication samples (n = 670; age, 61–76 years) from the BioImage Study, both following a factorial design sampled from high vs low strata of body mass index, lipids, and glucose. Longitudinal—FHS participants (n = 554) with 5–7 years of follow-up for risk factor changes.Observational studies.Cross-sectional samples with or without obesity, dysglycemia, and dyslipidemia, excluding prevalent cardiovascular disease and diabetes or dyslipidemia treatment. Age- and sex-matched by group.None.Gas chromatography-mass spectrometry detected 119 plasma metabolites. Cross-sectional associations with obesity, dyslipidemia, and dysglycemia were tested in discovery, with external replication of 37 metabolites. Single- and multi-metabolite markers were tested for association with longitudinal changes in risk factors.Cross-sectional metabolite associations were identified with obesity (n = 26), dyslipidemia (n = 21), and dysglycemia (n = 11) in discovery. Glutamic acid, lactic acid, and sitosterol associated with all three risk factors in meta-analysis (P < 4.5 × 10?4). Metabolites associated with longitudinal risk factor changes were enriched for bioactive lipids. Multi-metabolite panels explained 2.5–15.3% of longitudinal changes in metabolic traits.Cross-sectional results implicated dysregulated glutamate cycling and amino acid metabolism in metabolic risk. Certain bioactive lipids were associated with risk factors cross-sectionally and over time, suggesting their upstream role in risk factor progression. Functional studies are needed to validate findings and facilitate translation into treatments or preventive measures.

Dataset Information

Blood Metabolite Signatures of Metabolic Syndrome in Two Cross-Cultural Older Adult Cohorts.

Publications

Blood Metabolite Signatures of Metabolic Syndrome in Two Cross-Cultural Older Adult Cohorts.

Similar Datasets

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