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Updated: Jun 20, 2026

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
Published on: January 7, 2019
Integrated metabolomics and metagenomics analysis identifies a unique signature characterizing metabolic syndrome
Sivaporn Wannaiampikul1, Brian Lee2, Jiarui Chen3
1Thai Canada Research Centre, Faculty of Medicine, Srinakharinwirot University, Ongkharak, Nakhon Nayok 26120, Thailand; Department of Biochemistry, Faculty of Medicine, Srinakharinwirot University, Bangkok, 10110, Thailand.
Abstract:
Metabolic Syndrome (MetS) presents a global health challenge, characterized by obesity, hypertension, dyslipidemia, and insulin resistance. Despite recognition of the gut microbiome's role in metabolic health, there remains an opportunity for defining association of unique microbes with clinical status. Unique genetic, dietary, and lifestyle factors may influence gut microbial composition and circulating metabolites, and consequently susceptibility to MetS. By identifying specific microbial and metabolomic signatures associated with MetS, we aim to uncover potential targets for reducing the disease burden. We correlate comprehensive clinical parameters with fecal metagenomics and untargeted serum metabolomics to delineate population-specific characteristics from 142 individuals with MetS (N=97) or control (CTRL; N=45). Microbiome species-level alpha diversity was reduced in MetS compared to CTRL. After adjustment for sex, age, BMI, and intensity of statin usage, we identified 20 MetS-related species. A co-abundant network analysis revealed Eubacterium eligens, enriched in the CTRL population, with the highest node degree. Serum metabolomics identified 106 significantly differentially regulated metabolites. N-arachidonoyl dopamine (NADA), an endocannabinoid implicated in GABAergic signaling, was the most significantly altered, enriched in CTRL and correlated with E. eligens. sPLS-DA modeling revealed that E. eligens and D. formicigenerans species cluster together with metabolites NADA and tetrahydrocorticosterone (THB), representing defining characteristics distinguishing MetS in this population. Our data reveal a distinct multi-omic signature of MetS, characterized by a significant reduction in E. eligens and D. formicigenerans abundance, and in circulating NADA and THB levels.
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