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Dataset Information

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts.


ABSTRACT:

Background

Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways.

Methods

We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0

SUBMITTER: Shi M 

PROVIDER: S-EPMC10276453 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature