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

项目摘要 行为减肥计划的成功被体重反弹所破坏。争议 存在着关于对体重减轻状态的生理适应对 体重恢复此外，关于增加的免疫抑制剂对复发的相对贡献知之甚少。 代谢效率和增加的食欲驱动。即使代谢效率随着 减肥，这并不一定意味着成功的节食者是低代谢的， 减肥状态为了解决这些科学问题，我们将招募100人参加一个 减肥计划的基础上修改版本的糖尿病预防计划。合格 参与者将在基线进行评估，如果他们达到最低7%的体重， 损失（称为第0个月），并在2个月和18个月后进行随访评估。 第2个月的重新评估将使我们能够研究向维护的过渡， 过程（即，从第0个月到第2个月的变化），而不仅仅是状态的离散变化（从基线到 第0个月）。对照组为33名体重稳定的超重个体， BMI和其他变量的体重减轻者，将在时间0招募，并与体重 失败者在所有的结果。新陈代谢和代谢的生理指标的变化 体重减轻期间的食欲将用于预测体重恢复的个体差异。通过 比较减肥和体重稳定的个体，我们将开发一个独特的参考点， 用于解释组内预测分析的结果。生理学结果 测量将包括：1）能量代谢（例如，静息和非静息能量消耗， 2)食欲驱动的神经指标（例如，纹状体对食物线索和食物味道的激活）， 3)对禁食和进食状态的神经内分泌反应（例如，瘦素、GLP-1）。全面 还将收集血液、粪便、肌肉和脂肪组织的生物库，以供未来发现 问题研究我们的措施和专业知识将为生理决定因素提供新的见解 减肥后体重反弹的可能性，这可能有助于改善未来的肥胖治疗。

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.