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Exploring Various Polygenic Risk Scores for Skin Cancer in the Phenomes of the Michigan Genomics Initiative and the UK Biobank with a Visual Catalog: PRSWeb

By Lars G. Fritsche, Lauren J. Beesley, Peter VandeHaar, Robert B. Peng, Maxwell Salvatore, Matthew Zawistowski, Sarah A. Gagliano, Sayantan Das, Jonathon LeFaive, Erin O. Kaleba, Thomas T. Klumpner, Stephanie E. Moser, Victoria M. Blanc, Chad M. Brummett, Sachin Kheterpal, Gonçalo R Abecasis, Stephen B. Gruber, Bhramar Mukherjee

Posted 04 Aug 2018
bioRxiv DOI: 10.1101/384909 (published DOI: 10.1371/journal.pgen.1008202)

Polygenic risk scores (PRS) are designed to serve as a single summary measure condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The construction of a PRS often depends on the purpose of the study, the available data/summary estimates and the underlying genetic architecture of a disease. In this paper, we consider several choices of constructing a PRS using summary data obtained from various publicly-available sources including the UK Biobank and evaluate them in predicting outcomes derived from electronic health records (EHR) that define the medical phenome. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma, which may share elements of a common genetic risk profile across the subtypes. This study is conducted using data from 30,702 unrelated, genotyped patients of recent European descent who consented to be part of the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate their association with secondary traits. PheWAS results are then replicated using population-based UK Biobank data. We develop a web platform called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods. The results of this study can provide guidance regarding PRS construction in future PRS-PheWAS studies using EHR data involving disease subtypes.

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