Abstract Introduction: Genetic risk variants are critical to risk prediction for invasive epithelial ovarian cancer (EOC), yet an estimated 50-55% of EOC heritability remains missing. Novel approaches to risk variant discovery are needed to detect variants that have not been uncovered by linkage analysis or genome-wide association studies (GWAS). We approach risk variant discovery using Shared Genomic Segment analysis (SGS), a novel statistical genetics method that enables risk variant discovery in extended high-risk pedigrees. Methods: The Utah Population Database (UPDB) is a population-based resource of over ten million individuals connected to the state of Utah, five million of whom are linked to a minimum of three generations of genealogy data. By linking this genealogy data with cancer data from the Utah Cancer Registry, we identified pedigrees with an excess risk of EOC. We generated germline genotyping data from cases (diagnosed 1983-2018) in a subset of these high-risk pedigrees, focusing on pedigrees well-suited for SGS (i.e., at least 3 cases separated by a total of at least 12 meioses). SGS identifies all runs of consecutive alleles that are shared identical-by-state by cases in a pedigree and determines which of these genomic segments are longer than would be expected by chance. These long segments are likely to be identical-by-descent, inherited from a common founder, and may harbor risk variants. Results: We successfully linked UPDB genealogy data to information from the Utah Cancer Registry to identify approximately 2,000 extended high-risk pedigrees with ≥5 ovarian cancer cases, an average of 7-10 meioses between pairs cases, and a statistically significant excess risk of ovarian cancer (α=0.05). We obtained biospecimens for 141 cases in 36 of the most promising pedigrees (i.e., high familial standardized incidence ratio, p-value<0.005, not attributable to known risk variants in BRCA1 or BRCA2 as observed in first-, second- or third-degree relatives of EOC cases). We genotyped 96 out of the 141 cases in these pedigrees (68%). SGS analyses to identify genomic regions that may harbor risk variants are currently underway. Conclusions: Using pedigrees identified in the UPBD, SGS has identified risk loci and novel risk variants for a number of diseases, including breast and hematologic cancers. We have identified a set of EOC high-risk pedigrees for SGS analysis and will leverage SGS to identify genomic regions that may harbor EOC risk variants. Citation Format: Mollie E. Barnard, Robert Sargent, G. Bryce Christensen, Bonita A. Mahaffey, James Albro, Elke A. Jarboe, Terence Rhodes, Nicola J. Camp, Jennifer A. Doherty. A pedigree-based approach to ovarian cancer risk variant discovery in the Utah Population Database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 30.
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