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Genome-wide associations of human gut microbiome variation and implications for causal inference analyses

微生物群 生物 全基因组关联研究 孟德尔随机化 人体微生物群 遗传关联 人口 单核苷酸多态性 遗传建筑学 遗传变异 遗传学 数量性状位点 基因 人类微生物组计划 基因型 医学 环境卫生 遗传变异
作者
David A. Hughes,Rodrigo Bacigalupe,Jun Wang,Malte C. Rühlemann,Raúl Y. Tito,Gwen Falony,Marie Joossens,Sara Vieira-Silva,Liesbet Henckaerts,Leen Rymenans,Chloë Verspecht,Susan M. Ring,André Franke,Kaitlin H Wade,Nicholas J. Timpson,Jeroen Raes
出处
期刊:Nature microbiology 卷期号:5 (9): 1079-1087 被引量:148
标识
DOI:10.1038/s41564-020-0743-8
摘要

Recent population-based1-4 and clinical studies5 have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci6, human twin studies7 and microbiome genome-wide association studies1,3,8-12 have provided evidence for genetic contributions to microbiome composition. Despite this, there is still poor overlap in genetic association across human studies. Using appropriate taxon-specific models, along with support from independent cohorts, we show an association between human host genotype and gut microbiome variation. We also suggest that interpretation of applied analyses using genetic associations is complicated by the probable overlap between genetic contributions and heritable components of host environment. Using faecal 16S ribosomal RNA gene sequences and host genotype data from the Flemish Gut Flora Project (n = 2,223) and two German cohorts (FoCus, n = 950; PopGen, n = 717), we identify genetic associations involving multiple microbial traits. Two of these associations achieved a study-level threshold of P = 1.57 × 10-10; an association between Ruminococcus and rs150018970 near RAPGEF1 on chromosome 9, and between Coprococcus and rs561177583 within LINC01787 on chromosome 1. Exploratory analyses were undertaken using 11 other genome-wide associations with strong evidence for association (P < 2.5 × 10-8) and a previously reported signal of association between rs4988235 (MCM6/LCT) and Bifidobacterium. Across these 14 single-nucleotide polymorphisms there was evidence of signal overlap with other genome-wide association studies, including those for age at menarche and cardiometabolic traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease (including Bifidobacterium and body composition); however, in the absence of clear microbiome-driven effects, caution is needed in interpretation. Overall, this work marks a growing catalogue of genetic associations that will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.
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