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논문 기본 정보

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학술저널
저자정보
Kyle M. Hatton-Jones (School of Pharmacy and Medical Science, Griffith University, Southport, Australia) Nicholas P. West (School of Pharmacy and Medical Science, Griffith University, Southport, Australia) Mike W.C. Thang (QCIF Facility for Advanced Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Australia) Pin-Yen Chen (School of Pharmacy and Medical Science, Griffith University, Southport, Australia) Peter Davoren (Diabetes and Endocrinology, Gold Coast University Hospital, Southport, Australia) Allan W. Cripps (Menzies Health Institute Queensland, Griffith University, Southport, Australia) Amanda J. Cox (School of Pharmacy and Medical Science, Griffith University, Southport, Australia)
저널정보
대한비만학회 Journal of Obesity & Metabolic Syndrome Journal of Obesity & Metabolic Syndrome Vol.33 No.1
발행연도
2024.3
수록면
64 - 75 (12page)
DOI
10.7570/jomes23022

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Background: The contributions of the gut microbiota to obesity and metabolic disease represent a potentially modifiable factor that may explain variation in risk between individuals. This study aimed to explore relationships among microbial composition and imputed functional attributes, a range of soluble metabolic and immune indices, and gene expression markers in males with or without evidence of metabolic dysregulation (MetDys). Methods: This case-control study included healthy males (n=15; 41.9±11.7 years; body mass index [BMI], 22.9±1.2 kg/m2) and males with evidence of MetDys (n=14; 46.6±10.0 years; BMI, 35.1±3.3 kg/m2) who provided blood and faecal samples for assessment of a range of metabolic and immune markers and microbial composition using 16S rRNA gene sequencing. Metagenomic functions were imputed from microbial sequence data for analysis. Results: In addition to elevated values in a range of traditional metabolic, adipokine and inflammatory indices in the MetDys group, 23 immunomodulatory genes were significantly altered in the MetDys group. Overall microbial diversity did not differ between groups; however, a trend for a higher relative abundance of the Bacteroidetes (P=0.06) and a lower relative abundance of the Verrucomicrobia (P=0.09) phyla was noted in the MetDys group. Using both family- and genera-level classifications, a partial least square discriminant analysis revealed unique microbial signatures between the groups. Conclusion: These findings confirm the need for ongoing investigations in human clinical cohorts to further resolve the relationships between the gut microbiota and metabolic and immune markers and risk for metabolic disease.

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