Determine independent gut microbiota-diseases association by eliminating the effects of human lifestyle factors.

ABSTRACT: Lifestyle and physiological variables on human disease risk have been revealed to be mediated by gut microbiota. Low concordance between case-control studies for detecting disease-associated microbe existed due to limited sample size and population-wide bias in lifestyle and physiological variables. To infer gut microbiota-disease associations accurately, we propose to build machine learning models by including both human variables and gut microbiota. When the model's performance with both gut microbiota and human variables is better than the model with just human variables, the independent gut microbiota -disease associations will be confirmed. By building models on the American Gut Project dataset, we found that gut microbiota showed distinct association strengths with different diseases

SUBMITTER: Zhu C 

PROVIDER: S-EPMC8722223 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature