Predicting Weight Regain Following Weight Loss Using Physiological Measures of Appetite and Energy Expenditure

NIH RePORTER · NIH · UG3 · $250,000 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY The success of behavioral weight loss programs is undermined by weight regain. Controversy exists about how much physiological adaptations to the weight reduced state contribute to weight regain. Further, little is known about the relative contributions to relapse of increased metabolic efficiency and increased appetitive drive. Even if metabolic efficiency increases with weight loss, this does not necessarily mean that successful dieters are hypo-metabolic in their weight-reduced state. To address these scientific questions, we will recruit 100 individuals into a weight loss program based on a modified version of the Diabetes Prevention Program. Qualified participants will be assessed at baseline and reassessed if they attain a minimum 7% weight loss (called month 0) and undergo follow-up assessments 2 and 18-months later. Reassessment at month 2 will allow us to study the transition to maintenance as a dynamic process (i.e., change from month 0 to 2), not just as a discrete change of state (from baseline to month 0). A control group of 33 weight-stable overweight individuals, matched to successful weight losers on BMI and other variables, will be recruited at time 0 and compared to weight losers on all outcome measures. Changes in physiological measures of metabolism and appetite during weight loss will be used to predict individual differences in weight regain. By comparing weight-losing to weight-stable individuals, we will develop a unique reference point for interpreting the results of the within-group predictive analyses. Physiological outcome measures will include: 1) energy metabolism (e.g., resting and non-resting energy expenditure, 2) neural indicators of appetitive drive (e.g., striatal activation to food cues and food tastes) and 3) neuroendocrine responses to fasting and fed states (e.g., leptin, GLP-1). A comprehensive biobank of blood, fecal, muscle and adipose tissue will also be collected for future discovery studies. Our measures and expertise will provide new insight into the physiological determinants of weight regain following weight loss that could help improve obesity treatments in the future.

Key facts

NIH application ID
10189945
Project number
1UG3DK128298-01
Recipient
DREXEL UNIVERSITY
Principal Investigator
MATTHEW R HAYES
Activity code
UG3
Funding institute
NIH
Fiscal year
2021
Award amount
$250,000
Award type
1
Project period
2021-04-24 → 2022-03-31