Keyword search (4,163 papers available)

"microbiome" Keyword-tagged Publications:

Title Authors PubMed ID
1 Integrated metabolomics and metagenomics analysis identifies a unique signature characterizing metabolic syndrome Wannaiampikul S; Lee B; Chen J; Prentice KJ; Ayansola R; Xu A; Santosa S; Pantopoulos K; Sweeney G; 41794383
HKAP
2 Contrasting microbial assembly patterns in the woody endosphere of hybrid and non-hybrid em Populus /em trees Grant KR; Kembel SW; Naik S; Dayanandan S; 41089252
BIOLOGY
3 Dynamics of soil biota and nutrients at varied depths in a Tamarix ramosissima-dominated natural desert ecosystem: Implications for nutrient cycling and desertification management Islam W; Zeng F; Ahmed Dar A; Sohail Yousaf M; 38340666
CONCORDIA
4 Comparative analysis of functional diversity of rumen microbiome in bison and beef heifers Nguyen TTM; Badhan AK; Reid ID; Ribeiro G; Gruninger R; Tsang A; Guan LL; McAllister T; 38054735
CSFG
5 A metagenomic-based study of two sites from the Barbadian reef system Simpson S; Bettauer V; Ramachandran A; Kraemer S; Mahon S; Medina M; Vallès Y; Dumeaux V; Vallès H; Walsh D; Hallett MT; 37009568
BIOLOGY
6 BioMiCo: a supervised Bayesian model for inference of microbial community structure. Shafiei M, Dunn KA, Boon E, MacDonald SM, Walsh DA, Gu H, Bielawski JP 25774293
BIOLOGY

 

Title:Integrated metabolomics and metagenomics analysis identifies a unique signature characterizing metabolic syndrome
Authors:Wannaiampikul SLee BChen JPrentice KJAyansola RXu ASantosa SPantopoulos KSweeney G
Link:https://pubmed.ncbi.nlm.nih.gov/41794383/
DOI:10.1016/j.jnutbio.2026.110327
Publication:The Journal of nutritional biochemistry
Keywords:Host-Microbiome InteractionMetabolic SyndromeMetagenomicsObesitySerum MetabolomicsThai Population
PMID:41794383 Category: Date Added:2026-03-08
Dept Affiliation: HKAP
1 Thai Canada Research Centre, Faculty of Medicine, Srinakharinwirot University, Ongkharak, Thailand.; Division of Internal Medicine, HRH Princess Maha Chakri Sirindhorn Medical Center, Srinakharinwirot University, Ongkharak, Thailand.
2 Division of Internal Medicine, HRH Princess Maha Chakri Sirindhorn Medical Center, Srinakharinwirot University, Ongkharak, Thailand.
3 State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China; Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong SAR, China; Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, P.R. China.
4 Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Banting and Best Diabetes Centre, Toronto, Canada.
5 Department of Biology, York University, Toronto, Canada.
6 State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China; Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong SAR, China; Guangdong-Hong Kong Joint Institute for Metabolic Medicine, The University of Hong Kong, Hong Kong SAR, China.
7 Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montreal, Quebec, Canada.
8 Lady Davis Institute for Medical Research, Jewish General Hospital and Department of Medicine, McGill University, Montreal, Quebec, Canada.
9 Thai Canada Research Centre, Faculty of Medicine, Srinakharinwirot University, Ongkharak, Thailand.; Department of Biology, York University, Toronto, Canada.. Electronic address: gsweeney@yorku.ca.

Description:

Background: 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 scope 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.

Methods: 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).

Results: 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.

Conclusions: 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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