4.8 Article

Kernel-based genetic association analysis for microbiome phenotypes identifies host genetic drivers of beta-diversity

Journal

MICROBIOME
Volume 11, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s40168-023-01530-0

Keywords

Microbiome; Beta-diversity; GWAS; Kernel machines; Covariate adjustment

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This study proposes a novel approach called the covariate-adjusted KRV framework to map genetic variants associated with microbiome beta-diversity. The framework evaluates the association between genetics and microbes by comparing similarity in genetic profiles to similarity in microbiome profiles across individuals. The study identifies an immunity-related gene IL23R and three other novel genes involved in immune functions or autoimmune disorders. Simulation studies show that the covariate-adjusted KRV has a greater power than other microbiome GWAS methods.
Background Understanding human genetic influences on the gut microbiota helps elucidate the mechanisms by which genetics may influence health outcomes. Typical microbiome genome-wide association studies (GWAS) marginally assess the association between individual genetic variants and individual microbial taxa. We propose a novel approach, the covariate-adjusted kernel RV (KRV) framework, to map genetic variants associated with microbiome beta-diversity, which focuses on overall shifts in the microbiota. The KRV framework evaluates the association between genetics and microbes by comparing similarity in genetic profiles, based on groups of variants at the gene level, to similarity in microbiome profiles, based on the overall microbiome composition, across all pairs of individuals. By reducing the multiple-testing burden and capturing intrinsic structure within the genetic and microbiome data, the KRV framework has the potential of improving statistical power in microbiome GWAS.Results We apply the covariate-adjusted KRV to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) in a two-stage (first gene-level, then variant-level) genome-wide association analysis for gut microbiome beta-diversity. We have identified an immunity-related gene, IL23R, reported in a previous microbiome genetic association study and discovered 3 other novel genes, 2 of which are involved in immune functions or autoimmune disorders. In addition, simulation studies show that the covariate-adjusted KRV has a greater power than other microbiome GWAS methods that rely on univariate microbiome phenotypes across a range of scenarios.Conclusions Our findings highlight the value of the covariate-adjusted KRV as a powerful microbiome GWAS approach and support an important role of immunity-related genes in shaping the gut microbiome composition.

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