ArticleBMC microbiology2025
Gut microbiome links obesity to type 2 diabetes: insights from Mendelian randomization.
Article in BMC microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Review
- Metabolic and gut microbiota effects of ketogenic diet and exogenous ketone salts in a rat model of metabolic syndrome.European journal of nutrition · 2026Article
- Gut Microbiota Signatures and Potential Mediators in the Trajectory of Age-related Macular Degeneration: A Phased Atlas by Genetic Inference.International journal of medical sciences · 2026Article
- Anti-Obesity Effects of Pea Peptides Modified by Steam Explosion on Obese Mice: Regulation of Gut Microbiota and Glucose Metabolism.Foods (Basel, Switzerland) · 2025Article
- Immunometabolic crossroads: infections as bidirectional modulators in diabetes and metabolic syndromes.Frontiers in endocrinology · 2025Review
- Gut and oral microbiome profiles in patients with obesity and ischemic heart disease.Frontiers in cellular and infection microbiology · 2025Article
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4 authors.
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Abstract
backgroundResearch has established links between the gut microbiome (GM) and both obesity and type 2 diabetes (T2D), which is much discussed, but underexplored. This study employed body mass index (BMI) as the measurement of obesity to delve deeper into the correlations from a genetic perspective.
methodsWe performed the Mendelian randomization (MR) analysis to examine the causal effects of GM on T2D and BMI, and vice versa. Genome-wide association study (GWAS) summary datasets were utilized for the analysis, including T2D (N = 933,970), BMI (N = 806,834), and two GM datasets from the international consortium MiBioGen (211 taxa, N = 18,340) and the Dutch Microbiome Project (DMP) (207 taxa, N = 7,738). These datasets mainly cover European populations, with additional cohorts from Asia and other regions. To further explore the potential mediating role of GM in the connections between BMI and T2D, their interaction patterns were summarized into a network.
resultsMR analysis identified 9 taxa that showed protective properties against T2D. Seven species were within the Firmicutes and Bacteroidales phyla in the DMP, and two were from the MiBioGen (Odds Ratio (OR): 0.94-0.95). Conversely, genetic components contributing to the abundance of 12 taxa were associated with increased risks of T2D (OR: 1.04-1.12). Furthermore, T2D may elevate the abundance of seven taxa (OR: 1.03-1.08) and reduce the abundance of six taxa (OR: 0.93-0.97). In the analysis of the influence of the genetic component of BMI on GM composition, BMI affected 52 bacterial taxa, with 28 decreasing (OR: 0.75-0.92) and 24 increasing (OR: 1.08-1.27). Besides, abundances of 25 taxa were negatively correlated with BMI (OR: 0.95-0.99), while positive correlations were detected for 14 taxa (OR: 1.01-1.05). Notably, we uncovered 11 taxa genetically associated with both BMI and T2D, which formed an interactive network.
conclusionsOur findings provide evidence for the GM-mediated links between obesity and T2D. The identification of relevant GM taxa offers valuable insights into the potential role of the microbiome in these diseases.
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