Researchers discover variants in DNA that significantly influence how the body distributes fat
February 18, 2019
A new breakthrough from the Genetic Investigation of Anthropometric Traits (GIANT) consortium identifies multiple genetic variants associated with how the body regulates and distributes body-fat tissue. The new findings broaden the understanding of how genes can predispose certain individuals to obesity.
The GIANT Consortium is a major international collaboration that seeks to identify genetic loci that modulate human body size and shape, including height and measures of obesity.
Kari E. North, PhD, professor of epidemiology at the University of North Carolina at Chapel Hill Gillings School of Global Public Health, is joint lead author of the new study, “Protein-Coding Variants Implicate Novel Genes Related to Lipid Homeostasis 1 Contributing to Body Fat Distribution,” published February 18 in Nature Genetics.
Co-authors from the Gillings School include Kristin Young, PhD, assistant professor; Misa Graff, PhD, assistant professor; and Heather Highland, PhD, postdoctoral fellow, all in the UNC Gillings School’s Department of Epidemiology.
Identifying the genetic variants associated with obesity is central to developing targeted interventions that can reduce the risks of chronic illnesses such as hypertension, Type 2 diabetes and heart disease, to which obesity contributes in significant ways. Genome-wide association studies previously identified 49 loci, or positions along a chromosome where the related genetic variants are located, that predispose individuals to a higher waist-to-hip ratio (WHR), which is a way to assess body-fat distribution. Lower values of WHR are associated with lower incidence of these diseases.
In this study, with a specific focus on coding variation, the team found 24 coding loci – 15 common and nine rare – along the chromosomes of individuals that predispose to higher WHR. Further analysis revealed pathways and gene sets that influenced not only metabolism but also the regulation of body fat tissue, bone growth and adiponectin, a hormone that controls glucose levels and breaks down fat.
The team also performed functional studies across other organisms and identified two genes that were associated with a significant increase in triglyceride levels and body fat across species.
North said the study is one of the largest ever to explore the influence of low frequency and rare coding variation in body-fat distribution. The information the team collected on the impacts of the rarer variants they discovered is particularly valuable, she said.
“For the first time, we were able to examine, on a large scale, how low-frequency and rare variants influence body fat distribution,” North said. “These variants are rarer in the population, but the effects they have on individuals are much larger, possibly making them more clinically relevant.”
Another major finding from the study is the importance of lipid metabolism to body fat distribution, which could lead to a better understanding of the ways obesity causes downstream diseases such as Type 2 diabetes and cardiovascular disease.
“A better understanding of the genetic underpinnings of body fat distribution may lead to better treatments for this highly prevalent disease and the cascade of downstream diseases on which obesity has an impact,” North said.
The study includes the efforts of more than 275 scientists from around the world.
Other lead authors are Anne E. Justice, PhD, former Gillings School postdoctoral fellow, now assistant professor of biomedical and translational informatics in the Geisinger Health System, in Danville, Pa.; Cecilia M. Lindgren, PhD, professor of genomic endocrinology and metabolism in the University of Oxford (U.K.) Nuffield Department of Medicine and group lead at the University of Oxford’s Big Data Institute; and Ruth J.F. Loos, PhD, professor at The Charles Bronfman Institute for Personalized Medicine at Mount Sinai’s Icahn School of Medicine and director of Mount Sinai’s Genetics of Obesity and Related Metabolic Traits Program.
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