Dataset Information

A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases.

ABSTRACT: The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological, and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top two loci explaining 11% of the Prevotella-Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Our two-stage metagenome genome-wide association studies on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.

SUBMITTER: Liu X

PROVIDER: S-EPMC7873036 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases.

Liu Xiaomin X Tang Shanmei S Zhong Huanzi H Tong Xin X Jie Zhuye Z Ding Qiuxia Q Wang Dan D Guo Ruidong R Xiao Liang L Xu Xun X Yang Huanming H Wang Jian J Zong Yang Y Liu Weibin W Liu Xiao X Zhang Yong Y Brix Susanne S Kristiansen Karsten K Hou Yong Y Jia Huijue H Zhang Tao T

Cell discovery 20210209 1

The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated ...[more]

PMID: 33563976

Similar Datasets

Project description:BackgroundHuman genome sequencing has enabled the association of phenotypes with genetic loci, but our ability to effectively translate this data to the clinic has not kept pace. Over the past 60 years, pharmaceutical companies have successfully demonstrated the safety and efficacy of over 1,200 novel therapeutic drugs via costly clinical studies. While this process must continue, better use can be made of the existing valuable data. In silico tools such as candidate gene prediction systems allow rapid identification of disease genes by identifying the most probable candidate genes linked to genetic markers of the disease or phenotype under investigation. Integration of drug-target data with candidate gene prediction systems can identify novel phenotypes which may benefit from current therapeutics. Such a drug repositioning tool can save valuable time and money spent on preclinical studies and phase I clinical trials.MethodsWe previously used Gentrepid (http://www.gentrepid.org) as a platform to predict 1,497 candidate genes for the seven complex diseases considered in the Wellcome Trust Case-Control Consortium genome-wide association study; namely Type 2 Diabetes, Bipolar Disorder, Crohn's Disease, Hypertension, Type 1 Diabetes, Coronary Artery Disease and Rheumatoid Arthritis. Here, we adopted a simple approach to integrate drug data from three publicly available drug databases: the Therapeutic Target Database, the Pharmacogenomics Knowledgebase and DrugBank; with candidate gene predictions from Gentrepid at the systems level.ResultsUsing the publicly available drug databases as sources of drug-target association data, we identified a total of 428 candidate genes as novel therapeutic targets for the seven phenotypes of interest, and 2,130 drugs feasible for repositioning against the predicted novel targets.ConclusionsBy integrating genetic, bioinformatic and drug data, we have demonstrated that currently available drugs may be repositioned as novel therapeutics for the seven diseases studied here, quickly taking advantage of prior work in pharmaceutics to translate ground-breaking results in genetics to clinical treatments.

Dataset Information

A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases.

Publications

A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure