Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain

Michael Rosenbaum, Tanya Agurs-Collins, Molly Bray, Kevin D. Hall, Mark Hopkins, Maren Laughlin, Paul S. MacLean, Padma Maruvada, Cary R. Savage, Dana M. Small, Luke Stoeckel

Research output: Contribution to journalArticle

  • 2 Citations

Abstract

Background: The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment. Objectives: The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research. Significance: The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments.

LanguageEnglish (US)
PagesS25-S34
JournalObesity
Volume26
DOIs
StatePublished - Apr 1 2018

Fingerprint

Obesity
Therapeutics
Biological Factors
Body Composition
Energy Intake
Weight Loss
Homeostasis
Biomarkers
Research Personnel
Pharmacology
Psychology
Sensitivity and Specificity
Brain
Research

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Nutrition and Dietetics

Cite this

Rosenbaum, M., Agurs-Collins, T., Bray, M., Hall, K. D., Hopkins, M., Laughlin, M., ... Stoeckel, L. (2018). Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain. Obesity, 26, S25-S34. https://doi.org/10.1002/oby.22156

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) : Recommendations from the Biological Domain. / Rosenbaum, Michael; Agurs-Collins, Tanya; Bray, Molly; Hall, Kevin D.; Hopkins, Mark; Laughlin, Maren; MacLean, Paul S.; Maruvada, Padma; Savage, Cary R.; Small, Dana M.; Stoeckel, Luke.

In: Obesity, Vol. 26, 01.04.2018, p. S25-S34.

Research output: Contribution to journalArticle

Rosenbaum, M, Agurs-Collins, T, Bray, M, Hall, KD, Hopkins, M, Laughlin, M, MacLean, PS, Maruvada, P, Savage, CR, Small, DM & Stoeckel, L 2018, 'Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain' Obesity, vol. 26, pp. S25-S34. https://doi.org/10.1002/oby.22156
Rosenbaum, Michael ; Agurs-Collins, Tanya ; Bray, Molly ; Hall, Kevin D. ; Hopkins, Mark ; Laughlin, Maren ; MacLean, Paul S. ; Maruvada, Padma ; Savage, Cary R. ; Small, Dana M. ; Stoeckel, Luke. / Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) : Recommendations from the Biological Domain. In: Obesity. 2018 ; Vol. 26. pp. S25-S34.
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