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

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Hongjiao Liu , Wodan Ling , Xing Hua , Jee‐Young Moon , Jessica Williams‐Nguyen , Xiang Zhan , Anna Plantinga , Ni Zhao , Angela Zhang , Rob Knight , Qibin Qi , Robert D. Burk , Robert C. Kaplan , Michael C. Wu ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.1101/2021.10.15.464608

Understanding human genetic influences on the gut microbiota helps elucidate the mechanisms by which genetics affects health outcomes. 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 proposed KRV framework improves statistical power by capturing intrinsic structure within the genetic and microbiome data while reducing the multiple-testing burden. We apply the covariate-adjusted KRV test to the Hispanic Community Health Study/Study of Latinos in a genome-wide association analysis (first gene-level, then variant-level) for microbiome beta-diversity. We have identified an immunity-related gene, IL23R , reported in previous association studies and discovered 3 other novel genes, 2 of which are involved in immune functions or autoimmune disorders. Our findings highlight the value of the KRV as a powerful microbiome GWAS approach and support an important role of immunity-related genes in shaping the gut microbiome composition.

Related Topics

Microbiome

Biology

Genome-Wide Association Study

Phenotype

Genetic Diversity

Computational Biology

Concepts

Microbiome Biology Genome-wide association study Genetic association Gene Genetics Phenotype Genetic diversity Kernel (algebra) Computational biology Evolutionary biology Genotype Single-nucleotide polymorphism Medicine Population Environmental health Mathematics Combinatorics

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Type: preprint
Language: en
Landing Page: https://doi.org/10.1101/2021.10.15.464608
PDF: https://www.biorxiv.org/content/biorxiv/early/2021/10/16/2021.10.15.464608.full.pdf
OA Status: green
Cited By: 2
References: 65
Related Works: 10
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DOI: https://doi.org/10.1101/2021.10.15.464608

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

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Type: preprint

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Language: en

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Publication year: 2021

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Publication date: 2021-10-16

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Authors: Hongjiao Liu, Wodan Ling, Xing Hua, Jee‐Young Moon, Jessica Williams‐Nguyen, Xiang Zhan, Anna Plantinga, Ni Zhao, Angela Zhang, Rob Knight, Qibin Qi, Robert D. Burk, Robert C. Kaplan, Michael C. Wu

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Landing page: https://doi.org/10.1101/2021.10.15.464608

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Concepts: Microbiome, Biology, Genome-wide association study, Genetic association, Gene, Genetics, Phenotype, Genetic diversity, Kernel (algebra), Computational biology, Evolutionary biology, Genotype, Single-nucleotide polymorphism, Medicine, Population, Environmental health, Mathematics, Combinatorics

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Cited by: 2

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