Abstract: Predicting a weight loss potential from gut microbiome data is described herein. In an example, a system accesses gut microbiome metagenomic sequence data for a subject and determines a measurement of one or more weight loss features from the gut microbiome metagenomic sequence data. The one or more weight loss features define a gut microbiome signature for weight loss response for the subject independent of a body mass index of the subject. The system determines a weight loss potential for the subject based on a comparison of the measurement of the subject to a plurality of reference measurements of the one or more weight loss features for a reference population showing variable weight loss responses. The system outputs the weight loss potential for the subject.

Abstract: Predicting therapy from gut compositional data is described herein. In an example, a system accesses gut compositional data including a taxonomic abundance, a taxonomic diversity, and/or an enterotype for a subject. The system generates a gut microbiome signature for a safety and an efficacy of a statin therapy for the subject by applying a classifier to the gut compositional data. The safety of the statin therapy is characterized by an insulin resistance of the subject and the efficacy of the statin therapy is characterized by a blood hydroxymethylglutarate level of the subject. The system determines a recommended therapy for the subject based on the gut microbiome signature and one or more taxa of the gut compositional data of the subject. The recommended therapy is selected from a statin therapy intensity, a probiotic therapy, a prebiotic therapy, or a combination thereof. The system outputs the recommended therapy.