AUTHOR=Liu Siyuan , Li Fan , Cai Yunjia , Ren Linan , Sun Lin , Gang Xiaokun , Wang Guixia 

TITLE=Unraveling the mystery: a Mendelian randomized exploration of gut microbiota and different types of obesity

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=14

YEAR=2024

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2024.1352109

DOI=10.3389/fcimb.2024.1352109

ISSN=2235-2988

ABSTRACT=<sec><title>Background</title><p>Numerous studies have demonstrated the influence of gut microbiota on the development of obesity. In this study, we utilized Mendelian randomization (MR) analysis to investigate the gut microbiota characteristics among different types of obese patients, aiming to elucidate the underlying mechanisms and provide novel insights for obesity treatment.</p></sec><sec><title>Methods</title><p>Two-sample multivariable Mendelian randomization (MR) analysis was employed to assess causal relationships between gut microbiota and various obesity subtypes. Gut microbiota data were obtained from the international consortium MiBioGen, and data on obese individuals were sourced from the Finnish National Biobank FinnGen. Eligible single-nucleotide polymorphisms (SNPs) were selected as instrumental variables. Various analytical methods, including inverse variance weighted (IVW), MR-Egger regression, weighted median, MR-RAPS, and Lasso regression, were applied. Sensitivity analyses for quality control included MR-Egger intercept tests, Cochran’s Q tests, and leave-one-out analyses and others.</p></sec><sec><title>Results</title><p>Mendelian randomization studies revealed distinct gut microbiota profiles among European populations with different obesity subtypes. Following multivariable MR analysis, we found that <italic>Ruminococcaceae UCG010</italic> [<italic>Odds Ratio (OR)</italic>: 0.842, <italic>95% confidence interval (CI)</italic>: 0.766-0.926, Adjusted <italic>P</italic> value: 0.028] independently reduced the risk of obesity induced by excessive calorie intake, while <italic>Butyricimonas</italic> [<italic>OR</italic>: 4.252, <italic>95% CI</italic>: 2.177-8.307, Adjusted <italic>P</italic> value: 0.002] independently increased the risk of medication-induced obesity. For localized adiposity, <italic>Pasteurellaceae</italic> [<italic>OR</italic>: 0.213, <italic>95% CI</italic>: 0.115-0.395, Adjusted <italic>P</italic> value: &lt;0.001] acted as a protective factor. In the case of extreme obesity with alveolar hypoventilation, <italic>lactobacillus</italic> [<italic>OR</italic>: 0.724, <italic>95% CI</italic>: 0.609-0.860, Adjusted <italic>P</italic> value: 0.035] reduced the risk of its occurrence. Additionally, six gut microbiota may have potential roles in the onset of different types of obesity. Specifically, the <italic>Ruminococcus</italic> torques group may increase the risk of its occurrence. <italic>Desulfovibrio</italic> and <italic>Catenabacterium</italic> may serve as protective factors in the onset of Drug-induced obesity. <italic>Oxalobacteraceae</italic>, <italic>Actinomycetaceae</italic>, and <italic>Ruminiclostridium 9</italic>, on the other hand, could potentially increase the risk of Drug-induced obesity. No evidence of heterogeneity or horizontal pleiotropy among SNPs was found in the above studies (all <italic>P</italic> values for Q test and MR-Egger intercept &gt; 0.05).</p></sec><sec><title>Conclusion</title><p>Gut microbiota abundance is causally related to obesity, with distinct gut microbiota profiles observed among different obesity subtypes. Four bacterial species, including <italic>Ruminococcaceae UCG010</italic>, <italic>Butyricimonas</italic>, <italic>Pasteurellaceae</italic> and <italic>lactobacillus</italic> independently influence the development of various types of obesity. Probiotic and prebiotic supplementation may represent a novel approach in future obesity management.</p></sec>