Multiomic Predictors of Short‐Term Weight Loss and Clinical Outcomes During a Behavioral‐Based Weight Loss Intervention

Abstract

Objective Identifying predictors of weight loss and clinical outcomes may increase understanding of individual variability in weight loss response. We hypothesized that baseline multiomic features, including DNA methylation (DNAme), metabolomics, and gut microbiome, would be predictive of short‐term changes in body weight and other clinical outcomes within a comprehensive weight loss intervention. Methods Healthy adults with overweight or obesity (n = 62, age 18‐55 years, BMI 27‐45 kg/m2, 75.8% female) participated in a 1‐year behavioral weight loss intervention. To identify baseline omic predictors of changes in clinical outcomes at 3 and 6 months, whole‐blood DNAme, plasma metabolites, and gut microbial genera were analyzed. Results A network of multiomic relationships informed predictive models for 10 clinical outcomes (body weight, waist circumference, fat mass, hemoglobin A1c, homeostatic model assessment of insulin resistance, total cholesterol, triglycerides, C‐reactive protein, leptin, and ghrelin) that changed significantly (P < 0.05). For eight of these, adjusted R2 ranged from 0.34 to 0.78. Our models identified specific DNAme sites, gut microbes, and metabolites that were predictive of variability in weight loss, waist circumference, and circulating triglycerides and that are biologically relevant to obesity and metabolic pathways. Conclusions These data support the feasibility of using baseline multiomic features to provide insight for precision nutrition–based weight loss interventions.

The Gut Microbiota during a Behavioral Weight Loss Intervention

“…However, other studies have shown inconsistent relationships between Phascolarctobacterium and markers of insulin sensitivity (as discussed in Naderpoor et al, 2019). In this study, as well as in a prior multi-omic study using this same cohort, higher Lachnospiraceae other abundance at baseline was associated with less reduction in waist circumference [ 23 ], yet we also observed that an increase from baseline to three months in this taxon was actually associated with greater weight loss among DCR participants. This is a heterogeneous group with potentially diverse functional effects, and these associations should be further explored, ideally using shotgun metagenomic sequencing data to resolve species/strain-level taxonomy.…”

“…The data for this ancillary study includes information collected at baseline and three months into the intervention for the participants who provided a fecal sample at one of these study visits. As described previously [ 23 ], all participants in the parent trial receive a 12 month comprehensive behavioral weight loss intervention involving an energy-restricted diet, increased physical activity, and group-based behavioral support. Participants are randomized to focus on either IMF or DCR as the dietary strategy during the 12 month intervention.…”

Proteomics, dietary intake, and changes in cardiometabolic health within a behavioral weight‐loss intervention: A pilot study

“…All study procedures were approved by the Colorado Multiple Institutional Review Board, and participants provided written informed consent. Details regarding inclusion and exclusion criteria and complete study procedures have been published previously [16, 17].…”

“…Details regarding inclusion and exclusion criteria and complete study procedures have been published previously [16,17]. Daily intake of energy, macronutrients, fiber, micronutrients, and food-group serving counts were exported from NDSR, and mean intakes over the 7 days were calculated.…”

The microbiota composition drives personalized nutrition: Gut microbes as predictive biomarkers for the success of weight loss diets

“…For instance, the abundance of Subdoligranulum species was associated with more significant weight loss only after IF intervention (64). A short-term weight loss intervention based on a CRD reducing caloric intake by 34% showed improved weight reduction linked to Coprococcus species baseline abundance, while Bacteroides and Lachnospiraceae species were negatively related to waist circumference reduction (65).…”