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MicrobiomeGWAS: A Tool for Identifying Host Genetic Variants Associated with Microbiome Composition.

ABSTRACT: The microbiome is the collection of all microbial genes and can be investigated by sequencing highly variable regions of 16S ribosomal RNA (rRNA) genes. Evidence suggests that environmental factors and host genetics may interact to impact human microbiome composition. Identifying host genetic variants associated with human microbiome composition not only provides clues for characterizing microbiome variation but also helps to elucidate biological mechanisms of genetic associations, prioritize genetic variants, and improve genetic risk prediction. Since a microbiota functions as a community, it is best characterized by β diversity; that is, a pairwise distance matrix. We develop a statistical framework and a computationally efficient software package, microbiomeGWAS, for identifying host genetic variants associated with microbiome β diversity with or without interacting with an environmental factor. We show that the score statistics have positive skewness and kurtosis due to the dependent nature of the pairwise data, which makes p-value approximations based on asymptotic distributions unacceptably liberal. By correcting for skewness and kurtosis, we develop accurate p-value approximations, whose accuracy was verified by extensive simulations. We exemplify our methods by analyzing a set of 147 genotyped subjects with 16S rRNA microbiome profiles from non-malignant lung tissues. Correcting for skewness and kurtosis eliminated the dramatic deviation in the quantile-quantile plots. We provided preliminary evidence that six established lung cancer risk SNPs were collectively associated with microbiome composition for both unweighted (p = 0.0032) and weighted (p = 0.011) UniFrac distance matrices. In summary, our methods will facilitate analyzing large-scale genome-wide association studies of the human microbiome.

SUBMITTER: Hua X

PROVIDER: S-EPMC9317577 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Bacterial vaginosis (BV) affects 20% of women worldwide and is associated with adverse reproductive health outcomes and increased risk for HIV. Typically, BV represents a shift in the vaginal microbiome from one that is dominated by Lactobacillus to one that is diverse. Persistent racial differences in BV and diverse vaginal microbiome composition overlap with racial disparities in risks for HIV and sexually transmitted infection, especially among women of African descent. Risk factors for BV and nonoptimal vaginal microbiome include sexual practices, yet racial differences persist when adjusted for behavioral factors, suggesting a host genetic component. Here, we perform a genome-wide association study on vaginal microbiome traits in Kenyan women. Linear regression and logistic regression were performed, adjusting for age and principal components of genetic ancestry, to evaluate the association between Lactobacillus crispatus, Lactobacillus iners, Gardnerella vaginalis, Shannon diversity index, and community state type (CST) with host genetic single nucleotide polymorphisms (SNPs). We identified novel genomic loci associated with the vaginal microbiome traits, though no SNP reached genome-wide significance. During pathway enrichment analysis, Toll-like receptors (TLRs), cytokine production, and other components of innate immune response were associated with L. crispatus, L. iners, and CST. Multiple previously reported genomic loci were replicated, including IL-8 (Shannon, CST), TIRAP (L. iners, Shannon), TLR2 (Shannon, CST), MBL2 (L. iners, G. vaginalis, CST), and MYD88 (L. iners, Shannon). These genetic associations suggest a role for the innate immune system and cell signaling in vaginal microbiome composition and susceptibility to nonoptimal vaginal microbiome.IMPORTANCE Globally, bacterial vaginosis (BV) is a common condition in women. BV is associated with poorer reproductive health outcomes and HIV risk. Typically, BV represents a shift in the vaginal microbiome from one that is dominated by Lactobacillus to one that is diverse. Despite many women having similar exposures, the prevalence of BV and nonoptimal vaginal microbiome is increased for women of African descent, suggesting a possible role for host genetics. We conducted a genome-wide association study of important vaginal microbiome traits in Kenyan women. We identified novel genetic loci and biological pathways related to mucosal immunity, cell signaling, and infection that were associated with vaginal microbiome traits; we replicated previously reported loci associated with mucosal immune response. These results provide insight into potential host genetic influences on vaginal microbiome composition and can guide larger longitudinal studies, with genetic and functional comparison across microbiome sites within individuals and across populations.

Dataset Information

MicrobiomeGWAS: A Tool for Identifying Host Genetic Variants Associated with Microbiome Composition.

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