Evaluation of gut microbiota predictive potential associated with phenotypic characteristics to identify multifactorial diseases.

ABSTRACT: Gut microbiota has been implicated in various clinical conditions, yet the substantial heterogeneity in gut microbiota research results necessitates a more sophisticated approach than merely identifying statistically different microbial taxa between healthy and unhealthy individuals. Our study seeks to not only select microbial taxa but also explore their synergy with phenotypic host variables to develop novel predictive models for specific clinical conditions.

Design

We assessed 50 healthy and 152 unhealthy individuals for phenotypic variables (PV) and gut microbiota (GM) composition by 16S rRNA gene sequencing. The entire modeling process was conducted in the R environment using the Random Forest algorithm. Model performance was assessed through ROC curve construction.

Results<

SUBMITTER: Fonseca DC 

PROVIDER: S-EPMC10798365 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature