Interactions between species introduce spurious associations in microbiome studies

Microbiota contribute to many dimensions of host phenotype, including disease. To link specific microbes to specific phenotypes, microbiome-wide association studies compare microbial abundances between two groups of samples. Abundance differences, however, reflect not only direct associations with t...

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Bibliographic Details
Published in:PLoS computational biology 2018-01, Vol.14 (1), p.e1005939-e1005939
Main Authors: Menon, Rajita, Ramanan, Vivek, Korolev, Kirill S
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Bioinformatics
Biology and Life Sciences
Brain
Causes of
Child
Computational Biology
Crohn Disease - microbiology
Entropy (Thermodynamics)
Gastrointestinal Microbiome
Genome-Wide Association Study
Health aspects
Humans
Identification and classification
Immunomodulation
Inflammatory bowel disease
Inflammatory bowel diseases
Inflammatory Bowel Diseases - microbiology
Intestine
Medicine and Health Sciences
Methods
Microbial Interactions
Microbiomes
Microbiota
Microbiota (Symbiotic organisms)
Microorganisms
Models, Statistical
Observational studies
Phenotype
Phenotypes
Physical Sciences
Physics
Regression Analysis
Reproducibility of Results
Software
Statistical analysis
Statistical methods
Statistical physics
Studies
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Summary:Microbiota contribute to many dimensions of host phenotype, including disease. To link specific microbes to specific phenotypes, microbiome-wide association studies compare microbial abundances between two groups of samples. Abundance differences, however, reflect not only direct associations with the phenotype, but also indirect effects due to microbial interactions. We found that microbial interactions could easily generate a large number of spurious associations that provide no mechanistic insight. Using techniques from statistical physics, we developed a method to remove indirect associations and applied it to the largest dataset on pediatric inflammatory bowel disease. Our method corrected the inflation of p-values in standard association tests and showed that only a small subset of associations is directly linked to the disease. Direct associations had a much higher accuracy in separating cases from controls and pointed to immunomodulation, butyrate production, and the brain-gut axis as important factors in the inflammatory bowel disease.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1005939