Host variables confound gut microbiota studies of human disease
Open accessAbstract
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false positives is exacerbated by wide interindividual heterogeneity in microbiota composition 1, probably due to population-wide differences in human lifestyle and physiological variables 2 that exert differential effects on the microbiota. Here we infer the greatest, generalized sources of heterogeneity in human gut microbiota profiles and also 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. We identify alcohol consumption frequency and bowel movement quality as unexpectedly strong sources of gut microbiota variance that differ in distribution between healthy participants and participants with a disease and that can confound study designs. We demonstrate that for numerous prevalent, high-burden human diseases, matching cases and controls for confounding variables reduces observed differences in the microbiota and the incidence of spurious associations. On this basis, we present a list of host variables that we recommend should be captured in human microbiota studies for the purpose of matching comparison groups, which we anticipate will increase robustness and reproducibility in resolving the members of the gut microbiota that are truly associated with human disease.
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Matching cases and controls for confounding variables can reduce differences in the microbiota and increase robustness and reproducibility in identifying bacterial taxa that are truly associated with human disease.
“Matching cases and controls for confounding variables can reduce differences in the microbiota, and increase robustness and reproducibility in identifying bacterial taxa that are truly associated with human disease [104].”
From Gut microbiota-mediated immunomodulation in tumor (2021) · cites this paper as [104]
Host variables such as alcohol intake frequency and bowel movement quality could exert great influence on microbial composition.
“host variables, such as alcohol intake frequency and bowel movement quality, could exert great influence on microbial composition [104].”
From Gut microbiota-mediated immunomodulation in tumor (2021) · cites this paper as [104]
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- Authors
- Vujkovic-Cvijin, I., Sklar, J., Jiang, L., Natarajan, L., Knight, R., & Belkaid, Y.
- Affiliations
- National Institutes of Health (US)
- University of California San Diego (US)
- Corresponding author
- Vujkovic-Cvijin, Ivan
- Belkaid, Yasmine
- Venue
- Nature
- Published
- 2020-11-04
- Volume
- 587
- Issue
- 7834
- Pages
- 448-454
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7677204
- OpenAlex
- W3097338697
- Cited by
- 614
- References
- 40
- Citations by year
- 2026: 114 · 2025: 90 · 2024: 96 · 2023: 93 · 2022: 129 · 2021: 85 · 2020: 3 · 2017: 2
- FWCI
- 25.23
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute of Allergy and Infectious Diseases (ZIAAI001115, ZIAAI001132)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK110541)
- National Center for Complementary and Integrative Health (DP1AT010885)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- gut microbiota, individual heterogeneity, alcohol consumption, case-control matching, reproducibility
- MeSH terms
- Gastrointestinal Microbiome, Machine Learning, Data Analysis, Adult, Aged, Aged, 80 and over, Alcohol Drinking, Diabetes Mellitus, Type 2, Diet, Disease, Feces, Female, Gastrointestinal Motility, Humans, Life Style, Male, Middle Aged, Residence Characteristics, RNA, Ribosomal, 16S, ROC Curve, Confounding Factors, Epidemiologic, Body Mass Index, Case-Control Studies, Area Under Curve, Young Adult
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