Grant Number:	3R00CA246063-04S1 Interpret this number
Primary Investigator:	Darst, Burcu
Organization:	Fred Hutchinson Cancer Center
Project Title:	Integrating Genomics and Metabolomics to Develop Predictive Models of Prostate Cancer in Multiethnic Men
Fiscal Year:	2023

PROJECT SUMMARY/ABSTRACT OF THE FUNDED PARENT AWARD Prostate cancer (PCa) is the second leading cause of cancer death among American men, with men of African ancestry have the highest PCa incidence and mortality rates. While the causes of this notable health disparity are not fully understood, growing evidence suggests that genetics is a contributing factor. However, most PCa research has focused on men of European descent, particularly genome-wide association studies (GWAS), which has resulted in polygenic models having poorer predictive value in non-Europeans. The overarching goal of this research is to identify genomic and metabolomic factors that contribute to PCa risk in men across multi- ancestry populations. In the R00 phase of this award, Dr. Darst will initiate a new line of research that applies integrative techniques to investigate combined genomic and metabolomic factors influencing PCa risk. This will build directly upon the research and training received in the K99 period. She will identify genetically regulated metabolites that could be causally associated with PCa risk in multi-ancestry populations and/or indicate potentially novel genetic risk loci (Aim 1). This will require developing a large multi-ancestry metabolomic imputation panel and performing two-sample Mendelian randomization for each metabolite and GWAS summary statistics from the large and diverse PRACTICAL Consortium. Using a subset of 872 African American men from the Multiethnic Cohort (MEC) and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, Dr. Darst will investigate the biological mechanisms implicated by genetic risk of PCa, as measured by a multi- ancestry polygenic risk score, metabolites that could mediate the effects of genetic factors on overall and aggressive PCa, and whether integrative techniques could be used to identify genomic and metabolomic factors that distinguish subgroups of individuals with high PCa risk (Aim 2). Results are expected to substantially improve our ability to detect high risk individuals who would benefit from earlier or more intensive PCa screening across multi-ancestry populations and provide novel biological mechanisms to target for preventative measures, likely reducing PCa mortality and the number of indolent PCa cases treated unnecessarily.





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