Abstract

ABSTRACTRecent human feeding studies have shown how the baseline taxonomic composition of the gut microbiome can determine responses to weight loss interventions. However, the functional determinants underlying this phenomenon remain unclear. We report a weight loss response analysis on a cohort of 105 individuals selected from a larger population enrolled in a commercial wellness program, which included healthy lifestyle coaching. Each individual in the cohort had baseline blood metabolomics, blood proteomics, clinical labs, dietary questionnaires, stool 16S rRNA gene sequencing data, and follow-up data on weight change. We generated additional targeted proteomics data on obesity-associated proteins in blood before and after intervention, along with baseline stool metagenomic data, for a subset of 25 individuals who showed the most extreme weight change phenotypes. We built regression models to identify baseline blood, stool, and dietary features associated with weight loss, independent of age, sex, and baseline body mass index (BMI). Many features were independently associated with baseline BMI, but few were independently associated with weight loss. Baseline diet was not associated with weight loss, and only one blood analyte was associated with changes in weight. However, 31 baseline stool metagenomic functional features, including complex polysaccharide and protein degradation genes, stress-response genes, respiration-related genes, and cell wall synthesis genes, along with gut bacterial replication rates, were associated with weight loss responses after controlling for age, sex, and baseline BMI. Together, these results provide a set of compelling hypotheses for how commensal gut microbiota influence weight loss outcomes in humans.IMPORTANCE Recent human feeding studies have shown how the baseline taxonomic composition of the gut microbiome can determine responses to dietary interventions, but the exact functional determinants underlying this phenomenon remain unclear. In this study, we set out to better understand interactions between baseline BMI, metabolic health, diet, gut microbiome functional profiles, and subsequent weight changes in a human cohort that underwent a healthy lifestyle intervention. Overall, our results suggest that the microbiota may influence host weight loss responses through variable bacterial growth rates, dietary energy harvest efficiency, and immunomodulation.

Highlights

  • IMPORTANCE Recent human feeding studies have shown how the baseline taxonomic composition of the gut microbiome can determine responses to dietary interventions, but the exact functional determinants underlying this phenomenon remain unclear

  • We set out to understand the possible interactions between baseline body mass index (BMI), dietary patterns, metabolic health, and gut microbiome profiles and how these factors may be associated with changes in weight and metabolic health following personalized, healthy lifestyle interventions

  • Personalized, telephonic behavioral coaching was provided to each participant on a monthly basis, with email or text communications between coaching calls

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Summary

Introduction

IMPORTANCE Recent human feeding studies have shown how the baseline taxonomic composition of the gut microbiome can determine responses to dietary interventions, but the exact functional determinants underlying this phenomenon remain unclear. Baseline gut microbiome functional signature associated with weight loss response following a healthy lifestyle intervention, independent of initial BMI or metabolic health state. While the exact mechanisms are unknown, the baseline taxonomic composition of the human gut microbiota appears to influence host responses to interventions It is unclear whether or not associations between the gut microbiome and weight loss phenotypes are independent of associations between baseline BMI and the microbiome. We set out to understand the possible interactions between baseline BMI, dietary patterns, metabolic health, and gut microbiome profiles and how these factors may be associated with changes in weight and metabolic health following personalized, healthy lifestyle interventions

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