Grant Number:	1R01CA188214-01 Interpret this number
Primary Investigator:	Zheng, Wei
Organization:	Vanderbilt University
Project Title:	Colorectal Cancer Risk Loci: Gwas, Fine-Mapping, and Functional Analysis
Fiscal Year:	2014

DESCRIPTION (provided by applicant): Since 2007, approximately 30 low-penetrance genetic susceptibility loci have been identified for colorectal cancer (CRC) in genome-wide association studies (GWAS). These genetic factors, along with rare, high-penetrance germline mutations in known CRC susceptibility genes, explain only a small fraction of CRC heritability. We propose to expand, in a very cost-efficient way, our ongoing GWAS of CRC conducted in East Asians to identify new genetic susceptibility loci for CRC. We propose further to fine-map and functionally characterize GWAS-identified risk loci for CRC to discover functional variants and genes that drive the associations. Specifically, we propose to accomplish the following aims: 1) Expand the GWAS to include approximately 10,100 cases and 22,700 controls in the discovery stage and 8,000 cases and 8,000 controls in replication stages. Genome-wide scan data will be imputed using the 1000 Genomes Project data as the reference. Promising SNPs will be selected, functionally annotated, and de novo genotyped for replication to identify new risk loci for CRC. 2) Use densely genotyped data from 5,000 cases and 5,000 controls, along with genome-wide scanned and imputed data from 30,400 cases and 44,700 controls of East Asian, African, and European-ancestry to fine-map 30 to 50 newly identified CRC loci to identify independent and potentially functional variants. 3) Perform in vitro experiments to identify functional variants inup to 15 newly identified CRC loci. 4) Utilize a novel stem-cell-driven mouse model of colonic neoplasia to further determine specific CRC genes and susceptibility alleles in selected loci identified in GWAS. This proposed GWAS expansion will be the first large study in East Asians to comprehensively search for genetic risk factors for CRC. This study, by capitalizing on GWAS data generated from existing studies and functional genomic data, will be extremely cost-efficient. Through functional characterization using experimental approaches, we anticipate identifying functional variants and novel genes/pathways for CRC to improve the understanding of biological mechanisms through which GWAS-identified loci contribute to CRC risk. This information will help accelerate the translation of GWAS findings into disease prevention and treatment.




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