title: Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data.
abstract: Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.lastname: Shi
authors.affiliation: Department of Statistics, Dongguk University, Seoul, Korea.
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authors.identifier: http://orcid.org/0000-0001-9675-6475
authors.initials: JH
authors.lastname: Park
authors.affiliation: Center for Psychiatric Genetics, Department of Psychiatry and Behavioral Sciences, North Shore University Health System Research Institute, University of Chicago Pritzker School of Medicine, Evanston, Illinois, United States of America.
authors.forename: Jubao
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Dept. of Statistics, Northern Illinois University, DeKalb, Illinois, United States of America.
authors.forename: Winton
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
authors.forename: Kai
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Information Management Services, Inc., Rockville, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
authors.forename: Xing
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.forename: Chao Agnes
authors.initials: CA
authors.lastname: Hsiung
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.|Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Medical School, Edinburgh, United Kingdom.
authors.forename: Jonine D
authors.initials: JD
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authors.affiliation: Department of Preventive Medicine and Department of Obstetrics and Gynecology, USC Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America.|Norris Comprehensive Cancer Center, USC Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America.
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authors.affiliation: Human Genetics Foundation, Turin, Italy.|MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
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authors.affiliation: Department of Etiology & Carcinogenesis, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.|State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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authors.forename: Adeline
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authors.identifier: http://orcid.org/0000-0003-1761-6314
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authors.forename: Yun-Chul
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
authors.forename: Neil E
authors.initials: NE
authors.lastname: Caporaso
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
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authors.affiliation: Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Department of Epidemiology, the Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
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authors.initials: RE
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authors.affiliation: Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.|Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany.|German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.initials: MT
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authors.affiliation: Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
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authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
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mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D020412:Multifactorial Inheritance / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors