Large-scale association analyses identify host factors influencing human gut microbiome composition

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P <5 x 10(-8)) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 x 10(-20)), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 x 10(-10) <P <5 x 10(-8)) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis

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

Recent population-based(1-4)and clinical studies(5)have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci(6), human twin studies(7)and microbiome genome-wide association studies(1,3,8-12)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 ofP = 1.57 x 10(-10); an association betweenRuminococcusandnearRAPGEF1on chromosome 9, and betweenCoprococcusandwithinLINC01787on chromosome 1. Exploratory analyses were undertaken using 11 other genome-wide associations with strong evidence for association (P < 2.5 x 10(-8)) and a previously reported signal of association between(MCM6/LCT) andBifidobacterium. 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 (includingBifidobacteriumand 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

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

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.status: publishe

Genome-wide analysis of 944 133 individuals provides insights into the etiology of haemorrhoidal disease

Objective Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date. Design We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry. Results We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix. Conclusion HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction

Genome-wide analysis of 944 133 individuals provides insights into the etiology of haemorrhoidal disease

Objective Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date. Design We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry. Results We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix. Conclusion HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction