Harvard Catalyst Profiles

Contact, publication, and social network information about Harvard faculty and fellows.

Login and Edit functionaility are currrently unavailable.

Genome-wide interactions with diet patterns on long-term weight change


Biography

Overview
Obesity and weight gain are major modifiable risk factors for cardiovascular disease (CVD), and the prevalence of obesity has been increasing alarmingly in the past decades. Diet is among the most important environmental factors that may interact with genomic variations in affecting obesity epidemic. However, no genome-wide study on gene-diet interactions has been reported, and previous gene-diet interaction studies are severely flawed in design and analytic strategies. The goal of this application is to conduct novel, genome-wide analyses of gene-diet interactions on long-term changes in obesity traits (body mass index, BMI; and waist to hip ratio, WHR) in the period of time when obesity rapidly increased in the United States (~1980-2000), and apply state-of-the-art approaches to overcome the major challenges in the field. We will use the newly- developed 'variance prioritization' procedure to select genetic variants sensitive to interactions with environment (Ai 1); and examine interactions between the prioritized genetic variants and overall diet patterns/quality indices in five prospective cohorts including in total ~59,000 US men and women from the DietGen and CHARGE Consortia (Aim 2). Because information of dietary intakes, obesity traits, and genome- wide scans are available in all the cohorts, the proposed project will be conducted in an extremely cost-efficient manner. We have assembled a solid group of experienced collaborators with expertise in epidemiology, genetics, statistics, gene-environment interactions, and nutrition. We believe that findings of this unparalleled study will provide a unique opportunity to identify novel gene-diet interactions on obesity epidemic, and promote diet modifications on prevention and treatment of obesity and CVD.
R21HL126024
QI, LU

Time
2014-12-01
2018-11-30
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.