The overall goal of this project is to identify genes affecting common forms of human obesity. We have accrued samples of obese cases, normal weight controls and families segregating extreme obesity and normal weight. In this application, we propose a fine-grained association scan for a limited segment of the genome that has been highly selected to maximize the prior probability of identifying genes. The samples are unique, the target region is well supported, and the methods of genotyping and analysis will be state of the art. Finally, the two- stage approach using cases and controls followed by families enhances the power to identify causative genes while minimizing the chance of false positives. We propose to conduct a ~2kb association scan of a ~12.9mb genomic region identified in our previous work on chromosome 10p12. This region was chosen for several reasons: It is strongly linked to obesity related phenotypes in our samples;the linkages have been replicated by others;we and others have identified associations to genomic sequence in these regions but these associations do not account for the linkage signal, suggesting multiple genes may account for the quantitative trait locus (QTL) in this region. Finally, our linkage results and bioinformatics analyses of mouse and human sequence suggest that one or more obesity related genes in this region may be imprinted. Specifically, we will: 1. conduct an association scan across ~12.9 mb of chromosome 10p12 in obese cases and normal weight controls;2. use family based methods to replicate positive results from case-control analyses;3. genotype and analyze for association all common SNPs in the regions, including coding and possible regulatory sequence;4. conduct exploratory association analyses of families incorporating parent of origin. Obesity is an increasingly prevalent condition having serious consequences for health and quality of life. The identification of genes for common forms of human obesity should lead to more individualized therapies and more effective prevention strategies. The overall goal of this project is to identify genes affecting common forms of human obesity through association analyses using cases, controls and families. Obesity is an increasingly prevalent condition having serious consequences for health and quality of life. The identification of genes for common forms of obesity should lead to more individualized therapies and more effective prevention strategies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK076023-04
Application #
8063014
Study Section
Clinical and Integrative Diabetes and Obesity Study Section (CIDO)
Program Officer
Karp, Robert W
Project Start
2008-06-10
Project End
2013-03-31
Budget Start
2011-04-01
Budget End
2013-03-31
Support Year
4
Fiscal Year
2011
Total Cost
$391,096
Indirect Cost
Name
University of Pennsylvania
Department
Psychiatry
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Li, Wei-Dong; Jiao, Hongxiao; Wang, Kai et al. (2015) Pathway-Based Genome-wide Association Studies Reveal That the Rac1 Pathway Is Associated with Plasma Adiponectin Levels. Sci Rep 5:13422
Jiao, Hongxiao; Wang, Kai; Yang, Fuhua et al. (2015) Pathway-Based Genome-Wide Association Studies for Plasma Triglycerides in Obese Females and Normal-Weight Controls. PLoS One 10:e0134923
Li, Wei-Dong; Jiao, Hongxiao; Wang, Kai et al. (2013) A genome wide association study of plasma uric acid levels in obese cases and never-overweight controls. Obesity (Silver Spring) 21:E490-4
Wang, Kai; Li, Wei-Dong; Zhang, Clarence K et al. (2011) A genome-wide association study on obesity and obesity-related traits. PLoS One 6:e18939
Wang, Kai; Li, Wei-Dong; Glessner, Joseph T et al. (2010) Large copy-number variations are enriched in cases with moderate to extreme obesity. Diabetes 59:2690-4