Obesity has become an epidemic in the United States and worldwide. During the past few years, genome-wide association studies (GWAS) have identified ~50 loci for obesity. However, those loci only account for small proportion (<5%) of the heritability of obesity, and the current GWAS have given us little insight into how these genetic variants are linked with obesity, and how they may response to environment (diet and lifestyle) modulation. The goal of this study is to address these GWAS limitations to provide further insights into a system-based understanding of the genetics of obesity. We propose to apply newly-developed pathway-based analysis by combining functional pathways, genetics of gene expression (GGE) analysis, and genome scans to identify novel obesity loci beyond conventional GWAS, in 11,577 men and women from the Nurses'Health Study (NHS) and Health Professionals'Follow-up Study (HPFS) with genome scans. The in silico validation will be performed in Framingham Heart Study (N=9,171) and GIANT consortium (N=121,600). We will determine the newly-identified and the established obesity variants in 811 individuals from a 2-year randomized diet intervention study, the POUNDS LOST trial. We will examine genetic effects on the 2-year weight changes in response to weight-loss diets varying in macronutrient compositions. The validation will be conducted in a separately-funded 2-year weight-loss trial, the Dietary Intervention Randomized Controlled Trial (DIRECT, n=322). We will also assess the genetic effects on the markers regulating energy intake and energy expenditure, including: 1) psychiatric measures for food craving, fullness, and hunger;2) energy expenditure (resting metabolic rate [RMR] and total energy expenditure [TEE]);3) biochemical markers of brain-gut- adipose axis, including leptin, insulin, glucose, ghrelin, GLP-1, adiponectin and RBP4;and 4) adipose gene expression profile. Because the genome-wide scans, diet intervention, and measures of energy intakes and expenditure, adipose gene expression, as well as body composition are funded through other grants, the proposed project will be extremely cost-effective. We have assembled a solid group of experienced collaborators with expertise in genetic epidemiology, statistics, pathway GGE analyses, clinical trial, obesity and nutrition. We believe that the unprecedented resources available in this project will provide a unique opportunity to identify novel genetic factors for obesity, and to get insights into the mechanisms of genetic and dietary factors in controlling long-term weight change in humans.

Public Health Relevance

The proposed study integrating novel pathway GGE analyses in large cohorts and comprehensive analyses on the genetic effects on long-term weight loss and mechanisms in response to weight-loss diets in randomized intervention trials would provide extraordinarily important and novel evidence to unravel theetiology of obesity, and have significant public health and clinical implications. Establishing relationship between genetic variants and diets in determining weight change will help identify individuals at high risk for obesity especially when adherent to specific diet. In addition, identifying genes related to energy intakes and expenditure relating to weight change should enable the discovery of new prevention and pharmaceutical treatment for obesity, and could significantly enhance the effectiveness of clinical patient care and assist personalized dietary approaches in prevention of obesity and related metabolic disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
1R01DK091718-01A1
Application #
8237351
Study Section
Kidney, Nutrition, Obesity and Diabetes (KNOD)
Program Officer
Karp, Robert W
Project Start
2012-05-01
Project End
2016-04-30
Budget Start
2012-05-01
Budget End
2013-04-30
Support Year
1
Fiscal Year
2012
Total Cost
$511,112
Indirect Cost
$194,634
Name
Harvard University
Department
Nutrition
Type
Schools of Public Health
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
Nisa, Hoirun; Qi, Kevin H T; Leng, Junhong et al. (2018) The Circadian Rhythm-Related MTNR1B Genotype, Gestational Weight Gain, and Postpartum Glycemic Changes. J Clin Endocrinol Metab 103:2284-2290
Sun, Dianjianyi; Li, Xiang; Heianza, Yoriko et al. (2018) History of Asthma From Childhood and Arterial Stiffness in Asymptomatic Young Adults: The Bogalusa Heart Study. Hypertension 71:928-936
Heianza, Yoriko; Sun, Dianjianyi; Ma, Wenjie et al. (2018) Gut-microbiome-related LCT genotype and 2-year changes in body composition and fat distribution: the POUNDS Lost Trial. Int J Obes (Lond) 42:1565-1573
Sun, Dianjianyi; Heianza, Yoriko; Li, Xiang et al. (2018) Genetic, epigenetic and transcriptional variations at NFATC2IP locus with weight loss in response to diet interventions: The POUNDS Lost Trial. Diabetes Obes Metab 20:2298-2303
Goni, Leticia; Sun, Dianjianyi; Heianza, Yoriko et al. (2018) A circadian rhythm-related MTNR1B genetic variant modulates the effect of weight-loss diets on changes in adiposity and body composition: the POUNDS Lost trial. Eur J Nutr :
Mendelian Randomization of Dairy Consumption Working Group (2018) Dairy Consumption and Body Mass Index Among Adults: Mendelian Randomization Analysis of 184802 Individuals from 25 Studies. Clin Chem 64:183-191
Heianza, Yoriko; Sun, Dianjianyi; Li, Xiang et al. (2018) Gut microbiota metabolites, amino acid metabolites and improvements in insulin sensitivity and glucose metabolism: the POUNDS Lost trial. Gut :
McKeown, Nicola M; Dashti, Hassan S; Ma, Jiantao et al. (2018) Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis. Diabetologia 61:317-330
Sun, D; Wang, T; Heianza, Y et al. (2018) Birthweight and cardiometabolic risk patterns in multiracial children. Int J Obes (Lond) 42:20-27
Han, Liyuan; Duan, Donghui; Zhang, Shuang et al. (2018) Effects of the interaction between glycated haemoglobin genetic risk score and postpartum weight reduction on glycaemic changes: A gene-weight interaction analysis. Diabetes Obes Metab 20:2733-2739

Showing the most recent 10 out of 87 publications