{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T16:06:00Z","timestamp":1772813160786,"version":"3.50.1"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2019,7,27]],"date-time":"2019-07-27T00:00:00Z","timestamp":1564185600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["AI116794"],"award-info":[{"award-number":["AI116794"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["DK112217"],"award-info":[{"award-number":["DK112217"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["ES013508"],"award-info":[{"award-number":["ES013508"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["HL134015"],"award-info":[{"award-number":["HL134015"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["LM010098"],"award-info":[{"award-number":["LM010098"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["LM011360"],"award-info":[{"award-number":["LM011360"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["LM012601"],"award-info":[{"award-number":["LM012601"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["TR001263"],"award-info":[{"award-number":["TR001263"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007929","name":"Institute for Translational Medicine and Therapeutics","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007929","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007929","name":"ITMAT","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007929","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UL1TR001878"],"award-info":[{"award-number":["UL1TR001878"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000738","name":"US Department of Veterans Affairs","doi-asserted-by":"crossref","award":["IK2-CX001780"],"award-info":[{"award-number":["IK2-CX001780"]}],"id":[{"id":"10.13039\/100000738","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Pleiotropy, where 1 genetic locus affects multiple phenotypes, can offer significant insights in understanding the complex genotype\u2013phenotype relationship. Although individual genotype\u2013phenotype associations have been thoroughly explored, seemingly unrelated phenotypes can be connected genetically through common pleiotropic loci or genes. However, current analyses of pleiotropy have been challenged by both methodologic limitations and a lack of available suitable data sources.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>In this study, we propose to utilize a new regression framework, reduced rank regression, to simultaneously analyze multiple phenotypes and genotypes to detect pleiotropic effects. We used a large-scale biobank linked electronic health record data from the Penn Medicine BioBank to select 5 cardiovascular diseases (hypertension, cardiac dysrhythmias, ischemic heart disease, congestive heart failure, and heart valve disorders) and 5 mental disorders (mood disorders; anxiety, phobic and dissociative disorders; alcohol-related disorders; neurological disorders; and delirium dementia) to validate our framework.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Compared with existing methods, reduced rank regression showed a higher power to distinguish known associated single-nucleotide polymorphisms from random single-nucleotide polymorphisms. In addition, genome-wide gene-based investigation of pleiotropy showed that reduced rank regression was able to identify candidate genetic variants with novel pleiotropic effects compared to existing methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>The proposed regression framework offers a new approach to account for the phenotype and genotype correlations when identifying pleiotropic effects. By jointly modeling multiple phenotypes and genotypes together, the method has the potential to distinguish confounding from causal genotype and phenotype associations.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocz084","type":"journal-article","created":{"date-parts":[[2019,5,17]],"date-time":"2019-05-17T03:17:37Z","timestamp":1558063057000},"page":"1083-1090","source":"Crossref","is-referenced-by-count":12,"title":["A regression framework to uncover pleiotropy in large-scale electronic health record data"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7910-4253","authenticated-orcid":false,"given":"Ruowang","family":"Li","sequence":"first","affiliation":[{"name":"Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"},{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9261-4864","authenticated-orcid":false,"given":"Rui","family":"Duan","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachel L","family":"Kember","sequence":"additional","affiliation":[{"name":"Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"},{"name":"Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA"},{"name":"Regeneron Genetics Center, Tarrytown, New York, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel J","family":"Rader","sequence":"additional","affiliation":[{"name":"Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"},{"name":"Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Scott M","family":"Damrauer","sequence":"additional","affiliation":[{"name":"Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA"},{"name":"Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason H","family":"Moore","sequence":"additional","affiliation":[{"name":"Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"},{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"},{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,7,27]]},"reference":[{"key":"2020110613072060200_ocz084-B1","author":"Visscher"},{"issue":"7265","key":"2020110613072060200_ocz084-B2","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1038\/nature08494","article-title":"Finding the missing heritability of complex diseases","volume":"461","author":"Manolio","year":"2009","journal-title":"Nature"},{"issue":"7218","key":"2020110613072060200_ocz084-B3","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1038\/456018a","article-title":"Personal genomes: the case of the missing heritability","volume":"456","author":"Maher","year":"2008","journal-title":"Nature"},{"issue":"6","key":"2020110613072060200_ocz084-B4","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1038\/nrg2999","article-title":"Using electronic health records to drive discovery in disease genomics","volume":"12","author":"Kohane","year":"2011","journal-title":"Nat Rev Genet"},{"issue":"2","key":"2020110613072060200_ocz084-B5","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1007\/s40142-015-0067-9","article-title":"Phenome-wide association studies: leveraging comprehensive phenotypic and genotypic data for discovery","volume":"3","author":"Pendergrass","year":"2015","journal-title":"Curr Genet Med Rep"},{"key":"2020110613072060200_ocz084-B6","doi-asserted-by":"crossref","first-page":"250","DOI":"10.3389\/fgene.2014.00250","article-title":"Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index","volume":"5","author":"Cronin","year":"2014","journal-title":"Front Genet"},{"key":"2020110613072060200_ocz084-B7","doi-asserted-by":"crossref","first-page":"78.","DOI":"10.1186\/s13073-016-0332-x","article-title":"Genetic pleiotropy in complex traits and diseases: implications for genomic medicine","volume":"8","author":"Gratten","year":"2016","journal-title":"Genome Med"},{"issue":"7","key":"2020110613072060200_ocz084-B8","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1038\/ng.3604","article-title":"A plethora of pleiotropy across complex traits","volume":"48","author":"Visscher","year":"2016","journal-title":"Nat Genet"},{"issue":"7","key":"2020110613072060200_ocz084-B9","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1038\/nrg3461","article-title":"Pleiotropy in complex traits: challenges and strategies","volume":"14","author":"Solovieff","year":"2013","journal-title":"Nat Rev Genet"},{"issue":"9","key":"2020110613072060200_ocz084-B10","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1093\/bioinformatics\/btq126","article-title":"PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations","volume":"26","author":"Denny","year":"2010","journal-title":"Bioinformatics"},{"issue":"7","key":"2020110613072060200_ocz084-B11","doi-asserted-by":"crossref","first-page":"e65245.","DOI":"10.1371\/journal.pone.0065245","article-title":"A unified framework for association analysis with multiple related phenotypes","volume":"8","author":"Stephens","year":"2013","journal-title":"PLoS One"},{"key":"2020110613072060200_ocz084-B12","doi-asserted-by":"crossref","first-page":"176","DOI":"10.3389\/fgene.2012.00176","article-title":"Bayesian methods for multivariate modeling of pleiotropic SNP associations and genetic risk prediction","volume":"3","author":"Hartley","year":"2012","journal-title":"Front Genet"},{"issue":"3","key":"2020110613072060200_ocz084-B13","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1002\/gepi.20372","article-title":"Bivariate association analyses for the mixture of continuous and binary traits with the use of extended generalized estimating equations","volume":"33","author":"Liu","year":"2009","journal-title":"Genet Epidemiol"},{"issue":"2","key":"2020110613072060200_ocz084-B14","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1093\/biostatistics\/4.2.195","article-title":"A multivariate family-based association test using generalized estimating equations: FBAT-GEE","volume":"4","author":"Lange","year":"2003","journal-title":"Biostatistics"},{"key":"2020110613072060200_ocz084-B15","doi-asserted-by":"crossref","first-page":"e34861","DOI":"10.1371\/journal.pone.0034861","article-title":"MultiPhen: joint model of multiple phenotypes can increase discovery in GWAS","volume":"7","author":"O\u2019Reilly","year":"2012","journal-title":"PLoS One"},{"key":"2020110613072060200_ocz084-B16","author":"Pingault"},{"key":"2020110613072060200_ocz084-B17","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2853-8","volume-title":"Multivariate Reduced-Rank Regression: Theory and Applications","author":"Reinsel","year":"1998"},{"issue":"2","key":"2020110613072060200_ocz084-B18","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/0047-259X(75)90042-1","article-title":"Reduced-rank regression for the multivariate linear model","volume":"5","author":"Izenman","year":"1975","journal-title":"J. Multivar. Anal"},{"issue":"2","key":"2020110613072060200_ocz084-B19","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1111\/j.1467-9868.2011.01002.x","article-title":"Reduced rank stochastic regression with a sparse singular value decomposition","volume":"74","author":"Chen","year":"2012","journal-title":"J. R. Stat. Soc. Ser. B (Statistical Methodol)"},{"issue":"2","key":"2020110613072060200_ocz084-B20","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.ajhg.2013.01.001","article-title":"Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors","volume":"92","author":"Andreassen","year":"2013","journal-title":"Am J Hum Genet"},{"issue":"1","key":"2020110613072060200_ocz084-B21","first-page":"1.19","article-title":"Quality control procedures for genome-wide association studies","volume":"68","author":"Turner","year":"2011","journal-title":"Curr Protoc Hum Genet"},{"issue":"4","key":"2020110613072060200_ocz084-B22","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1080\/10618600.2017.1340891","article-title":"Sequential co-sparse factor regression","volume":"26","author":"Mishra","year":"2017","journal-title":"J Comput Graph Stat"},{"key":"2020110613072060200_ocz084-B23","volume-title":"Theses and Dissertations","author":"Chen","year":"2011"},{"key":"2020110613072060200_ocz084-B24","author":"Mukherjee"},{"key":"2020110613072060200_ocz084-B25","author":"Valente"},{"key":"2020110613072060200_ocz084-B26","author":"Wright"},{"key":"2020110613072060200_ocz084-B27","author":"Zou"},{"issue":"4","key":"2020110613072060200_ocz084-B28","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1214\/08-AOS625","article-title":"On the adaptive elastic-net with a diverging number of parameters","volume":"37","author":"Zou","year":"2009","journal-title":"Ann Stat"},{"key":"2020110613072060200_ocz084-B29","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.jmva.2018.04.011","article-title":"Leveraging mixed and incomplete outcomes via reduced-rank modeling","volume":"167","author":"Luo","year":"2018","journal-title":"J Multivar Anal"},{"issue":"D1","key":"2020110613072060200_ocz084-B30","doi-asserted-by":"crossref","first-page":"D896","DOI":"10.1093\/nar\/gkw1133","article-title":"The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)","volume":"45","author":"MacArthur","year":"2017","journal-title":"Nucleic Acids Res"},{"issue":"6","key":"2020110613072060200_ocz084-B31","doi-asserted-by":"crossref","first-page":"996","DOI":"10.1101\/gr.229102","article-title":"The Human Genome Browser at UCSC","volume":"12","author":"Kent","year":"2002","journal-title":"Genome Res"},{"issue":"7616","key":"2020110613072060200_ocz084-B32","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1038\/nature19057","article-title":"Analysis of protein-coding genetic variation in 60, 706 humans","volume":"536","author":"Lek","year":"2016","journal-title":"Nature"},{"issue":"3","key":"2020110613072060200_ocz084-B33","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1038\/ng.2892","article-title":"A general framework for estimating the relative pathogenicity of human genetic variants","volume":"46","author":"Kircher","year":"2014","journal-title":"Nat Genet"},{"issue":"44","key":"2020110613072060200_ocz084-B34","doi-asserted-by":"crossref","first-page":"18026","DOI":"10.1073\/pnas.1114759108","article-title":"Distribution of allele frequencies and effect sizes and their interrelationships for common genetic susceptibility variants","volume":"108","author":"Park","year":"2011","journal-title":"Proc Natl Acad Sci"},{"issue":"4","key":"2020110613072060200_ocz084-B35","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1038\/nrg2322","article-title":"Heritability in the genomics era\u2014concepts and misconceptions","volume":"9","author":"Visscher","year":"2008","journal-title":"Nat Rev Genet"},{"key":"2020110613072060200_ocz084-B36","doi-asserted-by":"crossref","DOI":"10.5962\/bhl.title.27468","volume-title":"The Genetical Theory of Natural Selection","author":"Fisher","year":"1930"},{"issue":"5","key":"2020110613072060200_ocz084-B37","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1016\/j.ajhg.2013.10.012","article-title":"Beyond GWASs: illuminating the dark road from association to function","volume":"93","author":"Edwards","year":"2013","journal-title":"Am J Hum Genet"},{"issue":"15","key":"2020110613072060200_ocz084-B38","doi-asserted-by":"crossref","first-page":"3372","DOI":"10.1093\/hmg\/ddw165","article-title":"Intergenic GWAS SNPs are key components of the spatial and regulatory network for human growth","volume":"25","author":"Schierding","year":"2016","journal-title":"Hum Mol Genet"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/jamia\/article-pdf\/26\/10\/1083\/34151991\/ocz084.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/jamia\/article-pdf\/26\/10\/1083\/34151991\/ocz084.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,6]],"date-time":"2020-11-06T19:14:13Z","timestamp":1604690053000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/26\/10\/1083\/5540139"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,27]]},"references-count":38,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2019,7,27]]},"published-print":{"date-parts":[[2019,10,1]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocz084","relation":{},"ISSN":["1527-974X"],"issn-type":[{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,10]]},"published":{"date-parts":[[2019,7,27]]}}}