CitationGordon-Larsen, Penny; French, John E.; Moustaid-Moussa, Naima; Voruganti, Venkata S.; Mayer-Davis, Elizabeth J.; Bizon, Christopher A.; Cheng, Zhiyong; Stewart, Delisha A.; Easterbrook, John W.; & Shaikh, Saame Raza (Online ahead of print). Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity. Advances in Nutrition.
AbstractObesity is routinely considered as a single disease state, which drives a "one-size-fits-all" approach to treatment. We recently convened the first annual University of North Carolina Interdisciplinary Nutrition Sciences Symposium to discuss the heterogeneity of obesity and the need for translational science to advance understanding of this heterogeneity. The symposium aimed to advance scientific rigor in translational studies from animal to human models with the goal of identifying underlying mechanisms and treatments. In this review, we discuss fundamental gaps in knowledge of the heterogeneity of obesity ranging from cellular to population perspectives. We also advocate approaches to overcoming limitations in the field. Examples include the use of contemporary mouse genetic reference population models such as the Collaborative Cross and Diversity Outbred mice that effectively model human genetic diversity and the use of translational models that integrate -omics and computational approaches from pre-clinical to clinical models of obesity. Finally, we suggest best scientific practices to ensure strong rigor that will allow investigators to delineate the sources of heterogeneity in the population with obesity. Collectively, we propose that it is critical to think of obesity as a heterogeneous disease with complex mechanisms and etiologies, requiring unique prevention and treatment strategies tailored to the individual.
Reference TypeJournal Article
Year PublishedOnline ahead of print
Journal TitleAdvances in Nutrition
French, John E.
Voruganti, Venkata S.
Mayer-Davis, Elizabeth J.
Bizon, Christopher A.
Stewart, Delisha A.
Easterbrook, John W.
Shaikh, Saame Raza