{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T12:06:41Z","timestamp":1794571601731,"version":"4.9.1"},"reference-count":95,"publisher":"Oxford University Press (OUP)","issue":"R2","license":[{"start":{"date-parts":[[2019,7,31]],"date-time":"2019-07-31T00:00:00Z","timestamp":1564531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,11,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Prediction of disease risk is an essential part of preventative medicine, often guiding clinical management. Risk prediction typically includes risk factors such as age, sex, family history of disease and lifestyle (e.g. smoking status); however, in recent years, there has been increasing interest to include genomic information into risk models. Polygenic risk scores (PRS) aggregate the effects of many genetic variants across the human genome into a single score and have recently been shown to have predictive value for multiple common diseases. In this review, we summarize the potential use cases for seven common diseases (breast cancer, prostate cancer, coronary artery disease, obesity, type 1 diabetes, type 2 diabetes and Alzheimer\u2019s disease) where PRS has or could have clinical utility. PRS analysis for these diseases frequently revolved around (i) risk prediction performance of a PRS alone and in combination with other non-genetic risk factors, (ii) estimation of lifetime risk trajectories, (iii) the independent information of PRS and family history of disease or monogenic mutations and (iv) estimation of the value of adding a PRS to specific clinical risk prediction scenarios. We summarize open questions regarding PRS usability, ancestry bias and transferability, emphasizing the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing. In conclusion, it is becoming clear that PRS have value in disease risk prediction and there are multiple areas where this may have clinical utility.<\/jats:p>","DOI":"10.1093\/hmg\/ddz187","type":"journal-article","created":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T07:28:05Z","timestamp":1564039685000},"page":"R133-R142","source":"Crossref","is-referenced-by-count":568,"title":["Towards clinical utility of polygenic risk scores"],"prefix":"10.1093","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8222-008X","authenticated-orcid":false,"given":"Samuel A","family":"Lambert","sequence":"first","affiliation":[{"name":"Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK"},{"name":"Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia"},{"name":"MRC\/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK"},{"name":"Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gad","family":"Abraham","sequence":"additional","affiliation":[{"name":"Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK"},{"name":"Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia"},{"name":"Department of Clinical Pathology, University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Inouye","sequence":"additional","affiliation":[{"name":"Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK"},{"name":"Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia"},{"name":"MRC\/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK"},{"name":"Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK"},{"name":"Department of Clinical Pathology, University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2019,7,31]]},"reference":[{"key":"2019112117503133500_ref1","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1038\/nature09298","article-title":"Integrating common and rare genetic variation in diverse human populations","volume":"467","author":"Altshuler","year":"2010","journal-title":"Nature"},{"key":"2019112117503133500_ref2","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/nature15393","article-title":"A global reference for human genetic variation","volume":"526","author":"1000 Genomes Project Consortium","year":"2015","journal-title":"Nature"},{"key":"2019112117503133500_ref3","doi-asserted-by":"crossref","first-page":"D1005","DOI":"10.1093\/nar\/gky1120","article-title":"The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019","volume":"47","author":"Buniello","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"2019112117503133500_ref4","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.gde.2015.06.005","article-title":"Genomic risk prediction of complex human disease and its clinical application","volume":"33","author":"Abraham","year":"2015","journal-title":"Curr. Opin. Genet. Dev."},{"key":"2019112117503133500_ref5","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1038\/s41576-018-0018-x","article-title":"The personal and clinical utility of polygenic risk scores","volume":"19","author":"Torkamani","year":"2018","journal-title":"Nat. Rev. Genet."},{"key":"2019112117503133500_ref6","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.biopsych.2018.12.015","article-title":"Predicting polygenic risk of psychiatric disorders","volume":"86","author":"Martin","year":"2018","journal-title":"Biol. Psychiatry"},{"key":"2019112117503133500_ref7","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.ajhg.2017.06.005","article-title":"10 years of GWAS discovery: biology, function, and translation","volume":"101","author":"Visscher","year":"2017","journal-title":"Am. J. Hum. Genet."},{"key":"2019112117503133500_ref8","doi-asserted-by":"publisher","DOI":"10.1101\/416545","article-title":"A guide to performing polygenic risk score analyses","author":"Choi","year":"2018","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref9","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1038\/nrg.2016.27","article-title":"Developing and evaluating polygenic risk prediction models for stratified disease prevention","volume":"17","author":"Chatterjee","year":"2016","journal-title":"Nat. Rev. Genet."},{"key":"2019112117503133500_ref10","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1038\/nrg.2016.142","article-title":"Dissecting the genetics of complex traits using summary association statistics","volume":"18","author":"Pasaniuc","year":"2017","journal-title":"Nat. Rev. Genet."},{"key":"2019112117503133500_ref11","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1038\/nature08185","article-title":"Common polygenic variation contributes to risk of schizophrenia and bipolar disorder","volume":"460","author":"International Schizophrenia Consortium","year":"2009","journal-title":"Nature"},{"key":"2019112117503133500_ref12","doi-asserted-by":"crossref","first-page":"3525","DOI":"10.1093\/hmg\/ddp295","article-title":"Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk","volume":"18","author":"Evans","year":"2009","journal-title":"Hum. Mol. Genet."},{"key":"2019112117503133500_ref13","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1016\/j.ajhg.2015.09.001","article-title":"Modeling linkage disequilibrium increases accuracy of polygenic risk scores","volume":"97","author":"Vilhj\u00e1lmsson","year":"2015","journal-title":"Am. J. Hum. Genet."},{"key":"2019112117503133500_ref14","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1002\/gepi.22050","article-title":"Polygenic scores via penalized regression on summary statistics","volume":"41","author":"Mak","year":"2017","journal-title":"Genet. Epidemiol."},{"key":"2019112117503133500_ref15","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1097\/EDE.0b013e3181c30fb2","article-title":"Assessing the performance of prediction models","volume":"21","author":"Steyerberg","year":"2010","journal-title":"Epidemiology"},{"key":"2019112117503133500_ref16","doi-asserted-by":"crossref","first-page":"3267","DOI":"10.1093\/eurheartj\/ehw450","article-title":"Genomic prediction of coronary heart disease","volume":"37","author":"Abraham","year":"2016","journal-title":"Eur. Heart J."},{"key":"2019112117503133500_ref17","doi-asserted-by":"crossref","first-page":"2091","DOI":"10.1161\/CIRCULATIONAHA.116.024436","article-title":"Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting","volume":"135","author":"Natarajan","year":"2017","journal-title":"Circulation"},{"key":"2019112117503133500_ref18","doi-asserted-by":"crossref","first-page":"2264","DOI":"10.1016\/S0140-6736(14)61730-X","article-title":"Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials","volume":"385","author":"Mega","year":"2015","journal-title":"Lancet"},{"key":"2019112117503133500_ref19","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1161\/CIRCULATIONAHA.115.020109","article-title":"Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES clinical trial)","volume":"133","author":"Kullo","year":"2016","journal-title":"Circulation"},{"key":"2019112117503133500_ref20","doi-asserted-by":"crossref","first-page":"e0210010","DOI":"10.1371\/journal.pone.0210010","article-title":"Value of genetic testing in the prevention of cardiovascular events","volume":"14","author":"Hynninen","year":"2018","journal-title":"PLoS One"},{"key":"2019112117503133500_ref21","doi-asserted-by":"crossref","first-page":"1901","DOI":"10.1001\/jama.2018.3710","article-title":"Screening for prostate cancer","volume":"319","author":"Grossman","year":"2018","journal-title":"JAMA"},{"key":"2019112117503133500_ref22","doi-asserted-by":"crossref","first-page":"1086","DOI":"10.1038\/bjc.2015.289","article-title":"Reducing overdiagnosis by polygenic risk-stratified screening: findings from the Finnish section of the ERSPC","volume":"113","author":"Pashayan","year":"2015","journal-title":"Br. J. Cancer"},{"key":"2019112117503133500_ref23","doi-asserted-by":"crossref","first-page":"j5757","DOI":"10.1136\/bmj.j5757","article-title":"Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts","volume":"360","author":"Seibert","year":"2018","journal-title":"BMJ"},{"key":"2019112117503133500_ref24","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1038\/gim.2014.192","article-title":"Implications of polygenic risk-stratified screening for prostate cancer on overdiagnosis","volume":"17","author":"Pashayan","year":"2015","journal-title":"Genet. Med."},{"key":"2019112117503133500_ref25","doi-asserted-by":"crossref","first-page":"djw290","DOI":"10.1093\/jnci\/djw290","article-title":"Breast cancer screening in the precision medicine era: risk-based screening in a population-based trial","volume":"109","author":"Shieh","year":"2017","journal-title":"J. Natl. Cancer Inst."},{"key":"2019112117503133500_ref26","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.1001\/jamaoncol.2018.1901","article-title":"Cost-effectiveness and benefit-to-harm ratio of risk-stratified screening for breast cancer","volume":"4","author":"Pashayan","year":"2018","journal-title":"JAMA Oncol."},{"key":"2019112117503133500_ref27","doi-asserted-by":"crossref","first-page":"1883","DOI":"10.1016\/j.jacc.2018.07.079","article-title":"Genomic risk prediction of coronary artery disease in 480,000 adults: implications for primary prevention","volume":"72","author":"Inouye","year":"2018","journal-title":"J. Am. Coll. Cardiol."},{"key":"2019112117503133500_ref28","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.ajhg.2018.11.002","article-title":"Polygenic risk scores for prediction of breast cancer and breast cancer subtypes","volume":"104","author":"Mavaddat","year":"2019","journal-title":"Am. J. Hum. Genet."},{"key":"2019112117503133500_ref29","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1186\/s12885-019-5783-1","article-title":"Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification","volume":"19","author":"L\u00e4ll","year":"2019","journal-title":"BMC Cancer"},{"key":"2019112117503133500_ref30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pmed.1002258","article-title":"Genetic assessment of age-associated Alzheimer disease risk: development and validation of a polygenic hazard score","volume":"14","author":"Desikan","year":"2017","journal-title":"PLoS Med."},{"key":"2019112117503133500_ref31","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1002\/ana.25029","article-title":"Polygenic hazard scores in preclinical Alzheimer disease","volume":"82","author":"Tan","year":"2017","journal-title":"Ann. Neurol."},{"key":"2019112117503133500_ref32","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1016\/j.cell.2019.03.028","article-title":"Polygenic prediction of weight and obesity trajectories from birth to adulthood","volume":"177","author":"Khera","year":"2019","journal-title":"Cell"},{"key":"2019112117503133500_ref33","first-page":"1","article-title":"BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors","volume":"0","author":"Lee","year":"2019","journal-title":"Genet. Med."},{"key":"2019112117503133500_ref34","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1038\/ejhg.2009.177","article-title":"Sporadic cases are the norm for complex disease","volume":"18","author":"Yang","year":"2010","journal-title":"Eur. J. Hum. Genet."},{"key":"2019112117503133500_ref35","doi-asserted-by":"crossref","first-page":"e1002973","DOI":"10.1371\/journal.pgen.1002973","article-title":"Comparison of family history and SNPs for predicting risk of complex disease","volume":"8","author":"Do","year":"2012","journal-title":"PLoS Genet."},{"key":"2019112117503133500_ref36","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1093\/eurheartj\/ehv462","article-title":"Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history","volume":"37","author":"Tada","year":"2016","journal-title":"Eur. Heart J."},{"key":"2019112117503133500_ref37","doi-asserted-by":"publisher","DOI":"10.1101\/696799","article-title":"Very rare pathogenic genetic variants detected by SNP-chips are usually false positives: implications for direct-to-consumer genetic testing","author":"Weedon","year":"2019","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref38","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1038\/s41588-018-0183-z","article-title":"Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations","volume":"50","author":"Khera","year":"2018","journal-title":"Nat. Genet."},{"key":"2019112117503133500_ref39","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.118.035658","article-title":"Whole genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction","author":"Khera","year":"2018","journal-title":"Circulation"},{"key":"2019112117503133500_ref40","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1016\/j.jacl.2017.03.019","article-title":"Polygenic risk score predicts prevalence of cardiovascular disease in patients with familial hypercholesterolemia","volume":"11","author":"Paquette","year":"2017","journal-title":"J. Clin. Lipidol."},{"key":"2019112117503133500_ref41","doi-asserted-by":"crossref","first-page":"2240","DOI":"10.1200\/JCO.2016.69.4935","article-title":"Prediction of breast and prostate cancer risks in male BRCA1 and BRCA2 mutation carriers using polygenic risk scores","volume":"35","author":"Lecarpentier","year":"2017","journal-title":"J. Clin. Oncol."},{"key":"2019112117503133500_ref42","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1093\/jnci\/djw302","article-title":"Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers","volume":"109","author":"Kuchenbaecker","year":"2017","journal-title":"J. Natl. Cancer Inst."},{"key":"2019112117503133500_ref43","doi-asserted-by":"crossref","first-page":"3673","DOI":"10.1093\/brain\/awv268","article-title":"Common polygenic variation enhances risk prediction for Alzheimer\u2019s disease","volume":"138","author":"Escott-Price","year":"2015","journal-title":"Brain"},{"key":"2019112117503133500_ref44","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/S1474-4422(18)30053-X","article-title":"The effect of APOE and other common genetic variants on the onset of Alzheimer\u2019s disease and dementia: a community-based cohort study","volume":"17","author":"van der Lee","year":"2018","journal-title":"Lancet Neurol."},{"key":"2019112117503133500_ref45","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1038\/s41398-018-0221-8","article-title":"The genetic risk of Alzheimer\u2019s disease beyond APOE \u03b54: systematic review of Alzheimer\u2019s genetic risk scores","volume":"8","author":"Stocker","year":"2018","journal-title":"Transl. Psychiatry"},{"key":"2019112117503133500_ref46","doi-asserted-by":"crossref","first-page":"e001856","DOI":"10.1161\/CIRCGEN.117.001856","article-title":"Polygenic risk score for coronary heart disease modifies the elevated risk by cigarette smoking for disease incidence","volume":"11","author":"Hindy","year":"2018","journal-title":"Circ. Genom. Precis. Med."},{"key":"2019112117503133500_ref47","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1093\/ije\/dyx242","article-title":"Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the breast cancer association consortium","volume":"47","author":"Rudolph","year":"2018","journal-title":"Int. J. Epidemiol."},{"key":"2019112117503133500_ref48","doi-asserted-by":"crossref","first-page":"pii: E15","DOI":"10.3390\/jpm9010015","article-title":"Genetic testing to guide risk-stratified screens for breast cancer","volume":"9","author":"Willoughby","year":"2019","journal-title":"J. Pers. Med."},{"key":"2019112117503133500_ref49","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1158\/1055-9965.EPI-18-0810","article-title":"Performance of single-nucleotide polymorphisms in breast cancer risk prediction models: a systematic review and meta-analysis","volume":"28","author":"Fung","year":"2019","journal-title":"Cancer Epidemiol. Biomark. Prev."},{"key":"2019112117503133500_ref50","doi-asserted-by":"publisher","DOI":"10.1136\/jmedgenet-2019-106072","article-title":"Addition of a 161-SNP polygenic risk score to family history-based risk prediction: impact on clinical management in non-BRCA1\/2 breast cancer families","author":"Lakeman","year":"2019","journal-title":"J. Med. Genet."},{"key":"2019112117503133500_ref51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/jnci\/djv036","article-title":"Prediction of breast cancer risk based on profiling with common genetic variants","volume":"107","author":"Mavaddat","year":"2015","journal-title":"J. Natl. Cancer Inst."},{"key":"2019112117503133500_ref52","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1158\/1055-9965.EPI-15-0838","article-title":"Breast cancer risk prediction using clinical models and 77 independent risk-associated SNPs for women aged under 50 years: Australian breast cancer family registry","volume":"25","author":"Dite","year":"2016","journal-title":"Cancer Epidemiol. Biomark. Prev."},{"key":"2019112117503133500_ref53","doi-asserted-by":"crossref","first-page":"e1002644","DOI":"10.1371\/journal.pmed.1002644","article-title":"Addition of a polygenic risk score, mammographic density, and endogenous hormones to existing breast cancer risk prediction models: a nested case\u2013control study","volume":"15","author":"Zhang","year":"2018","journal-title":"PLoS Med."},{"key":"2019112117503133500_ref54","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13058-019-1138-8","article-title":"Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk","volume":"21","author":"Vachon","year":"2019","journal-title":"Breast Cancer Res."},{"key":"2019112117503133500_ref55","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.2337\/dc18-0087","article-title":"A type 1 diabetes genetic risk score predicts progression of islet autoimmunity and development of type 1 diabetes in individuals at risk","volume":"41","author":"Redondo","year":"2018","journal-title":"Diabetes Care"},{"key":"2019112117503133500_ref56","doi-asserted-by":"crossref","first-page":"1894","DOI":"10.1016\/j.jacc.2018.08.1041","article-title":"Polygenic risk scoring for coronary heart disease","volume":"72","author":"Natarajan","year":"2018","journal-title":"J. Am. Coll. Cardiol."},{"key":"2019112117503133500_ref57","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/s13059-018-1396-2","article-title":"A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog","volume":"19","author":"Morales","year":"2018","journal-title":"Genome Biol."},{"key":"2019112117503133500_ref58","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1038\/s41588-019-0379-x","article-title":"Clinical use of current polygenic risk scores may exacerbate health disparities","volume":"51","author":"Martin","year":"2019","journal-title":"Nat. Genet."},{"key":"2019112117503133500_ref59","doi-asserted-by":"publisher","DOI":"10.1101\/106062","article-title":"Heterogeneity in polygenic scores for common human traits","author":"Ware","year":"2017","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref60","doi-asserted-by":"crossref","first-page":"e0179238","DOI":"10.1371\/journal.pone.0179238","article-title":"Comparing distributions of polygenic risk scores of type 2 diabetes and coronary heart disease within different populations","volume":"12","author":"Reisberg","year":"2017","journal-title":"PLoS One"},{"key":"2019112117503133500_ref61","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1186\/s13059-018-1561-7","article-title":"Genetic disease risks can be misestimated across global populations","volume":"19","author":"Kim","year":"2018","journal-title":"Genome Biol."},{"key":"2019112117503133500_ref62","doi-asserted-by":"crossref","first-page":"406","DOI":"10.2337\/dc18-1727","article-title":"Type 1 diabetes risk in African-ancestry participants and utility of an ancestry-specific genetic risk score","volume":"42","author":"Onengut-Gumuscu","year":"2019","journal-title":"Diabetes Care"},{"key":"2019112117503133500_ref63","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1097\/YPG.0000000000000206","article-title":"Polygenic risk score for schizophrenia is more strongly associated with ancestry than with schizophrenia","volume":"28","author":"Curtis","year":"2018","journal-title":"Psychiatr. Genet."},{"key":"2019112117503133500_ref64","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1016\/j.ajhg.2017.03.004","article-title":"Human demographic history impacts genetic risk prediction across diverse populations","volume":"100","author":"Martin","year":"2017","journal-title":"Am. J. Hum. Genet."},{"key":"2019112117503133500_ref65","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1038\/nrg2813","article-title":"New approaches to population stratification in genome-wide association studies","volume":"11","author":"Price","year":"2010","journal-title":"Nat. Rev. Genet."},{"key":"2019112117503133500_ref66","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/s41467-018-08219-1","article-title":"Apparent latent structure within the UK biobank sample has implications for epidemiological analysis","volume":"10","author":"Haworth","year":"2019","journal-title":"Nat. Commun."},{"key":"2019112117503133500_ref67","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1016\/j.ajhg.2019.05.001","article-title":"Geographic variation and bias in the polygenic scores of complex diseases and traits in Finland","volume":"104","author":"Kerminen","year":"2019","journal-title":"Am. J. Hum. Genet."},{"key":"2019112117503133500_ref68","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1038\/ng.2897","article-title":"Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility","volume":"46","author":"Mahajan","year":"2014","journal-title":"Nat. Genet."},{"key":"2019112117503133500_ref69","doi-asserted-by":"crossref","first-page":"e1001078","DOI":"10.1371\/journal.pgen.1001078","article-title":"Consistent association of type 2 diabetes risk variants found in Europeans in diverse racial and ethnic groups","volume":"6","author":"Waters","year":"2010","journal-title":"PLoS Genet."},{"key":"2019112117503133500_ref70","doi-asserted-by":"crossref","first-page":"e98608","DOI":"10.1371\/journal.pone.0098608","article-title":"Evaluation of common type 2 diabetes risk variants in a south Asian population of Sri Lankan descent","volume":"9","author":"Hassanali","year":"2014","journal-title":"PLoS One"},{"key":"2019112117503133500_ref71","doi-asserted-by":"crossref","first-page":"1446","DOI":"10.1007\/s00125-016-3920-9","article-title":"Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie biobank","volume":"59","author":"Gan","year":"2016","journal-title":"Diabetologia"},{"key":"2019112117503133500_ref72","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1038\/s41586-019-1310-4","article-title":"Genetic analyses of diverse populations improves discovery for complex traits","volume":"570","author":"Wojcik","year":"2019","journal-title":"Nature"},{"key":"2019112117503133500_ref73","doi-asserted-by":"publisher","DOI":"10.1038\/s41576-019-0144-0","article-title":"Genomics of disease risk in globally diverse populations","author":"Gurdasani","year":"2019","journal-title":"Nat. Rev. Genet."},{"key":"2019112117503133500_ref74","doi-asserted-by":"publisher","DOI":"10.1101\/445874","article-title":"Comparative genetic architectures of schizophrenia in east Asian and European populations","author":"Lam","year":"2018","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref75","doi-asserted-by":"crossref","first-page":"4529","DOI":"10.1038\/s41598-018-22574-5","article-title":"Application of a genetic risk score to racially diverse type 1 diabetes populations demonstrates the need for diversity in risk-modeling","volume":"8","author":"Perry","year":"2018","journal-title":"Sci. Rep."},{"key":"2019112117503133500_ref76","doi-asserted-by":"crossref","first-page":"e0204834","DOI":"10.1371\/journal.pone.0204834","article-title":"Validation of a genetic risk score for Arkansas women of color","volume":"13","author":"Starlard-Davenport","year":"2018","journal-title":"PLoS One"},{"key":"2019112117503133500_ref77","doi-asserted-by":"publisher","DOI":"10.1101\/598730","article-title":"A polygenic risk score for breast cancer in U.S. Latinas and Latin-American women","author":"Shieh","year":"2019","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref78","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1038\/s41576-018-0083-1","article-title":"The role of sex in the genomics of human complex traits","volume":"20","author":"Khramtsova","year":"2019","journal-title":"Nat. Rev. Genet."},{"key":"2019112117503133500_ref79","doi-asserted-by":"publisher","DOI":"10.1101\/523217","article-title":"Causal relevance of obesity on the leading causes of death in women and men: a Mendelian randomization study","author":"Censin","year":"2019","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref80","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s00401-017-1789-4","article-title":"Polygenic hazard score: an enrichment marker for Alzheimer\u2019s associated amyloid and tau deposition","volume":"135","author":"Tan","year":"2018","journal-title":"Acta Neuropathol."},{"key":"2019112117503133500_ref81","doi-asserted-by":"crossref","first-page":"e1008060","DOI":"10.1371\/journal.pgen.1008060","article-title":"On the utilization of polygenic risk scores for therapeutic targeting","volume":"15","author":"Gibson","year":"2019","journal-title":"PLoS Genet."},{"key":"2019112117503133500_ref82","doi-asserted-by":"crossref","first-page":"e1000864","DOI":"10.1371\/journal.pgen.1000864","article-title":"The genetic interpretation of area under the ROC curve in genomic profiling","volume":"6","author":"Wray","year":"2010","journal-title":"PLoS Genet."},{"key":"2019112117503133500_ref83","doi-asserted-by":"crossref","first-page":"e1001230","DOI":"10.1371\/journal.pgen.1001230","article-title":"A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explained","volume":"6","author":"So","year":"2010","journal-title":"PLoS Genet."},{"key":"2019112117503133500_ref84","doi-asserted-by":"crossref","first-page":"e1003348","DOI":"10.1371\/journal.pgen.1003348","article-title":"Power and predictive accuracy of polygenic risk scores","volume":"9","author":"Dudbridge","year":"2013","journal-title":"PLoS Genet."},{"key":"2019112117503133500_ref85","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1038\/ng.2579","article-title":"Projecting the performance of risk prediction based on polygenic analyses of genome-wide association studies","volume":"45","author":"Chatterjee","year":"2013","journal-title":"Nat. Genet."},{"key":"2019112117503133500_ref86","doi-asserted-by":"publisher","DOI":"10.1101\/588020","article-title":"Recovery of trait heritability from whole genome sequence data","author":"Wainschtein","year":"2019","journal-title":"bioRxiv"},{"key":"2019112117503133500_ref87","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1534\/genetics.119.301859","article-title":"Complex trait prediction from genome data: contrasting EBV in livestock to PRS in humans","volume":"211","author":"Wray","year":"2019","journal-title":"Genetics"},{"key":"2019112117503133500_ref88","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1038\/s41588-017-0009-4","article-title":"Multi-trait analysis of genome-wide association summary statistics using MTAG","volume":"50","author":"Turley","year":"2018","journal-title":"Nat. Genet."},{"key":"2019112117503133500_ref89","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1038\/s41467-017-02769-6","article-title":"Improving genetic prediction by leveraging genetic correlations among human diseases and traits","volume":"9","author":"Maier","year":"2018","journal-title":"Nat. Commun."},{"key":"2019112117503133500_ref90","doi-asserted-by":"crossref","first-page":"248","DOI":"10.2337\/db17-1156","article-title":"Longitudinal analysis of genetic susceptibility and BMI throughout adult life","volume":"67","author":"Song","year":"2018","journal-title":"Diabetes"},{"key":"2019112117503133500_ref91","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.l4067","article-title":"Quantifying the impact of genes on body mass index during the obesity epidemic: longitudinal findings from the HUNT study","author":"Brandkvist","year":"2019","journal-title":"BMJ"},{"key":"2019112117503133500_ref92","doi-asserted-by":"crossref","first-page":"e1002548","DOI":"10.1371\/journal.pmed.1002548","article-title":"Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: a prospective study in children","volume":"15","author":"Bonifacio","year":"2018","journal-title":"PLoS Med."},{"key":"2019112117503133500_ref93","doi-asserted-by":"crossref","first-page":"200","DOI":"10.2337\/dc18-1785","article-title":"Development and standardization of an improved type 1 diabetes genetic risk score for use in Newborn screening and incident diagnosis","volume":"42","author":"Sharp","year":"2019","journal-title":"Diabetes Care"},{"key":"2019112117503133500_ref94","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1038\/gim.2016.103","article-title":"Personalized risk prediction for type 2 diabetes: the potential of genetic risk scores","volume":"19","author":"L\u00e4ll","year":"2017","journal-title":"Genet. Med."},{"key":"2019112117503133500_ref95","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.neurobiolaging.2016.07.018","article-title":"Polygenic score prediction captures nearly all common genetic risk for Alzheimer\u2019s disease","volume":"49","author":"Escott-Price","year":"2017","journal-title":"Neurobiol. Aging"}],"container-title":["Human Molecular Genetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/hmg\/advance-article-pdf\/doi\/10.1093\/hmg\/ddz187\/30095141\/ddz187.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/hmg\/article-pdf\/28\/R2\/R133\/31081033\/ddz187.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/hmg\/article-pdf\/28\/R2\/R133\/31081033\/ddz187.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,21]],"date-time":"2019-11-21T17:51:35Z","timestamp":1574358695000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/hmg\/article\/28\/R2\/R133\/5540980"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,31]]},"references-count":95,"journal-issue":{"issue":"R2","published-online":{"date-parts":[[2019,7,31]]},"published-print":{"date-parts":[[2019,11,21]]}},"URL":"https:\/\/doi.org\/10.1093\/hmg\/ddz187","relation":{},"ISSN":["0964-6906","1460-2083"],"issn-type":[{"value":"0964-6906","type":"print"},{"value":"1460-2083","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,10,15]]},"published":{"date-parts":[[2019,7,31]]}}}