Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
Causal relationship between gut microbiota and diabetes based on Mendelian randomization.
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Luo Manjun, Li Ziye, Sun Mengting, Tang Jiapeng, Wang Tingting, Qin Jiabi
Аннотация
OBJECTIVES: The gut microbiota plays a crucial role in the pathophysiology of various types of diabetes. However, the causal relationship between them has yet to be systematically elucidated. This study aims to explore the potential causal associations between gut microbiota and diabetes using a two-sample Mendelian randomization (MR) analysis, based on multiple taxonomic levels.
METHODS: Eligible instrumental variables were extracted from the selected genome-wide association study (GWAS) data on gut microbiota. These were combined with GWAS datasets on type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM) to conduct forward MR analysis, sensitivity analysis, reverse MR analysis, and validation of significant estimates. Microbial taxa with causal effects on T1D, T2D, and GDM were identified based on a comprehensive assessment of all analytical stages.
RESULTS: A total of 2 179, 2 176, and 2 166 single nucleotide polymorphisms (SNP) were included in the MR analyses for gut microbiota with T1D, T2D, and GDM, respectively. MR results indicated causal associations between: Six microbial taxa (Eggerthella, Lachnospira, Bacillales, Desulfovibrionales, Parasutterella, and Turicibacter) and T1D; 9 microbial taxa (Verrucomicrobia, Deltaproteobacteria, Actinomycetales, Desulfovibrionale, Actinomycetaceae, Desulfovibrionaceae, Actinomyces, Alcaligenaceae, and Lachnospiraceae NC2004 group) and T2D; 10 microbial taxa (Betaproteobacteria, Coprobacter, Ruminococcus2, Tenericutes, Clostridia, Methanobacteria, Mollicutes, Methanobacteriales, Methanobacteriaceae, and Methanobrevibacter) and GDM.
CONCLUSIONS: This study identified specific gut microbial taxa that may significantly increase or decrease the risk of developing diabetes. Some findings were fully replicated in independent validation datasets. However, the underlying biological mechanisms of these causal relationships warrant further investigation through mechanistic studies and population-based research.
METHODS: Eligible instrumental variables were extracted from the selected genome-wide association study (GWAS) data on gut microbiota. These were combined with GWAS datasets on type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM) to conduct forward MR analysis, sensitivity analysis, reverse MR analysis, and validation of significant estimates. Microbial taxa with causal effects on T1D, T2D, and GDM were identified based on a comprehensive assessment of all analytical stages.
RESULTS: A total of 2 179, 2 176, and 2 166 single nucleotide polymorphisms (SNP) were included in the MR analyses for gut microbiota with T1D, T2D, and GDM, respectively. MR results indicated causal associations between: Six microbial taxa (Eggerthella, Lachnospira, Bacillales, Desulfovibrionales, Parasutterella, and Turicibacter) and T1D; 9 microbial taxa (Verrucomicrobia, Deltaproteobacteria, Actinomycetales, Desulfovibrionale, Actinomycetaceae, Desulfovibrionaceae, Actinomyces, Alcaligenaceae, and Lachnospiraceae NC2004 group) and T2D; 10 microbial taxa (Betaproteobacteria, Coprobacter, Ruminococcus2, Tenericutes, Clostridia, Methanobacteria, Mollicutes, Methanobacteriales, Methanobacteriaceae, and Methanobrevibacter) and GDM.
CONCLUSIONS: This study identified specific gut microbial taxa that may significantly increase or decrease the risk of developing diabetes. Some findings were fully replicated in independent validation datasets. However, the underlying biological mechanisms of these causal relationships warrant further investigation through mechanistic studies and population-based research.