Microbiome-associated human genetic variants impact phenome-wide disease risk.


Journal

Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876

Informations de publication

Date de publication:
28 06 2022
Historique:
entrez: 24 6 2022
pubmed: 25 6 2022
medline: 29 6 2022
Statut: ppublish

Résumé

Human genetic variation associates with the composition of the gut microbiome, yet its influence on clinical traits remains largely unknown. We analyzed the consequences of nearly a thousand gut microbiome-associated variants (MAVs) on phenotypes reported in electronic health records from tens of thousands of individuals. We discovered and replicated associations of MAVs with neurological, metabolic, digestive, and circulatory diseases. Five significant MAVs in these categories correlate with the relative abundance of microbes down to the strain level. We also demonstrate that these relationships are independently observed and concordant with microbe by disease associations reported in case-control studies. Moreover, a selective sweep and population differentiation impacted some disease-linked MAVs. Combined, these findings establish triad relationships among the human genome, microbiome, and disease. Consequently, human genetic influences may offer opportunities for precision diagnostics of microbiome-associated diseases but also highlight the relevance of genetic background for microbiome modulation and therapeutics.

Identifiants

pubmed: 35749358
doi: 10.1073/pnas.2200551119
pmc: PMC9245617
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2200551119

Subventions

Organisme : NCI NIH HHS
ID : P30 CA068485
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL142856
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM127087
Pays : United States
Organisme : NLM NIH HHS
ID : T32 LM012412
Pays : United States

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Auteurs

Robert H George Markowitz (RHG)

Vanderbilt Microbiome Innovation Center, Vanderbilt University, Nashville, TN 37232.
Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232.

Abigail Leavitt LaBella (AL)

Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232.

Mingjian Shi (M)

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232.

Antonis Rokas (A)

Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232.

John A Capra (JA)

Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94143.
Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94143.

Jane F Ferguson (JF)

Vanderbilt Microbiome Innovation Center, Vanderbilt University, Nashville, TN 37232.
Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232.

Jonathan D Mosley (JD)

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232.
Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232.

Seth R Bordenstein (SR)

Vanderbilt Microbiome Innovation Center, Vanderbilt University, Nashville, TN 37232.
Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232.
Vanderbilt Institute for Infection, Immunology and Inflammation, Vanderbilt University Medical Center, Nashville, TN 37232.
Department of Pathology, Microbiology, and Immunology, School of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232.

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