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Host variables confound gut microbiota studies of human disease
Low concordance between studies that examine the microbiota in human diseases is a pervasive challenge that limits capacity to identify causal relationships between host-associated microbes and pathology. Risks of obtaining false positives in human microbiota research are exacerbated by wide inter-i...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677204/ https://www.ncbi.nlm.nih.gov/pubmed/33149306 http://dx.doi.org/10.1038/s41586-020-2881-9 |
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author | Vujkovic-Cvijin, Ivan Sklar, Jack Jiang, Lingjing Natarajan, Loki Knight, Rob Belkaid, Yasmine |
author_facet | Vujkovic-Cvijin, Ivan Sklar, Jack Jiang, Lingjing Natarajan, Loki Knight, Rob Belkaid, Yasmine |
author_sort | Vujkovic-Cvijin, Ivan |
collection | PubMed |
description | Low concordance between studies that examine the microbiota in human diseases is a pervasive challenge that limits capacity to identify causal relationships between host-associated microbes and pathology. Risks of obtaining false positives in human microbiota research are exacerbated by wide inter-individual heterogeneity in microbiota composition(1) likely due to population-wide differences in human lifestyle and physiological variables(2) that exert differential impacts on the microbiota. Herein, we infer the greatest, generalized sources of heterogeneity in human gut microbiota profiles and, further, identify human lifestyle and physiological characteristics that, if not evenly matched between cases and controls, confound microbiota analyses to produce spurious microbial associations with human diseases. Surprisingly, we identify alcohol consumption frequency and bowel movement quality as unexpectedly strong sources of gut microbiota variance that differ in distribution between healthy and diseased subjects and can confound study designs. We demonstrate that for numerous prevalent, high-burden human diseases, matching cases and controls for confounding variables reduces observed microbiota differences and incidence of spurious associations. Thus, we present a list of recommended host variables to capture in human microbiota studies for the purpose of matching comparison groups, which we anticipate will increase robustness and reproducibility in resolving true disease-associated gut microbiota members in human disease. |
format | Online Article Text |
id | pubmed-7677204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76772042021-05-04 Host variables confound gut microbiota studies of human disease Vujkovic-Cvijin, Ivan Sklar, Jack Jiang, Lingjing Natarajan, Loki Knight, Rob Belkaid, Yasmine Nature Article Low concordance between studies that examine the microbiota in human diseases is a pervasive challenge that limits capacity to identify causal relationships between host-associated microbes and pathology. Risks of obtaining false positives in human microbiota research are exacerbated by wide inter-individual heterogeneity in microbiota composition(1) likely due to population-wide differences in human lifestyle and physiological variables(2) that exert differential impacts on the microbiota. Herein, we infer the greatest, generalized sources of heterogeneity in human gut microbiota profiles and, further, identify human lifestyle and physiological characteristics that, if not evenly matched between cases and controls, confound microbiota analyses to produce spurious microbial associations with human diseases. Surprisingly, we identify alcohol consumption frequency and bowel movement quality as unexpectedly strong sources of gut microbiota variance that differ in distribution between healthy and diseased subjects and can confound study designs. We demonstrate that for numerous prevalent, high-burden human diseases, matching cases and controls for confounding variables reduces observed microbiota differences and incidence of spurious associations. Thus, we present a list of recommended host variables to capture in human microbiota studies for the purpose of matching comparison groups, which we anticipate will increase robustness and reproducibility in resolving true disease-associated gut microbiota members in human disease. 2020-11-04 2020-11 /pmc/articles/PMC7677204/ /pubmed/33149306 http://dx.doi.org/10.1038/s41586-020-2881-9 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Vujkovic-Cvijin, Ivan Sklar, Jack Jiang, Lingjing Natarajan, Loki Knight, Rob Belkaid, Yasmine Host variables confound gut microbiota studies of human disease |
title | Host variables confound gut microbiota studies of human disease |
title_full | Host variables confound gut microbiota studies of human disease |
title_fullStr | Host variables confound gut microbiota studies of human disease |
title_full_unstemmed | Host variables confound gut microbiota studies of human disease |
title_short | Host variables confound gut microbiota studies of human disease |
title_sort | host variables confound gut microbiota studies of human disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677204/ https://www.ncbi.nlm.nih.gov/pubmed/33149306 http://dx.doi.org/10.1038/s41586-020-2881-9 |
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