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Rare coding variants in RCN3 are associated with blood pressure

dc.contributor.authorHe, Karen Y.
dc.contributor.authorKelly, Tanika N.
dc.contributor.authorWang, Heming
dc.contributor.authorLiang, Jingjing
dc.contributor.authorZhu, Luke
dc.contributor.authorCade, Brian E.
dc.contributor.authorAssimes, Themistocles L.
dc.contributor.authorBecker, Lewis C.
dc.contributor.authorBeitelshees, Amber L.
dc.contributor.authorBielak, Lawrence F.
dc.contributor.authorBress, Adam P.
dc.contributor.authorBrody, Jennifer A.
dc.contributor.authorChang, Yen-Pei C.
dc.contributor.authorChang, Yi-Cheng
dc.contributor.authorde Vries, Paul S.
dc.contributor.authorDuggirala, Ravindranath
dc.contributor.authorFox, Ervin R.
dc.contributor.authorFranceschini, Nora
dc.contributor.authorFurniss, Anna L.
dc.contributor.authorGao, Yan
dc.contributor.authorGuo, Xiuqing
dc.contributor.authorHaessler, Jeffrey
dc.contributor.authorHung, Yi-Jen
dc.contributor.authorHwang, Shih-Jen
dc.contributor.authorIrvin, Marguerite R.
dc.contributor.authorKalyani, Rita R.
dc.contributor.authorLiu, Ching-Ti
dc.contributor.authorLiu, Chunyu
dc.contributor.authorMartin, Lisa W.
dc.contributor.authorMontasser, May E.
dc.contributor.authorMuntner, Paul M.
dc.contributor.authorMwasongwe, Stanford
dc.contributor.authorNaseri, Take
dc.contributor.authorPalmas, Walter
dc.contributor.authorReupena, Muagututi’a S.
dc.contributor.authorRice, Kenneth M.
dc.contributor.authorSheu, Wayne H.
dc.contributor.authorShimbo, Daichi
dc.contributor.authorSmith, Jennifer A.
dc.contributor.authorSnively, Beverly M.
dc.contributor.authorYanek, Lisa R.
dc.contributor.authorZhao, Wei
dc.contributor.authorBlangero, John
dc.contributor.authorBoerwinkle, Eric
dc.contributor.authorChen, Yii-Der I.
dc.contributor.authorCorrea, Adolfo
dc.contributor.authorCupples, L. A.
dc.contributor.authorCurran, Joanne E.
dc.contributor.authorFornage, Myriam
dc.contributor.authorHe, Jiang
dc.contributor.authorHou, Lifang
dc.contributor.authorKaplan, Robert C.
dc.contributor.authorKardia, Sharon L. R.
dc.contributor.authorKenny, Eimear E.
dc.contributor.authorKooperberg, Charles
dc.contributor.authorLloyd-Jones, Donald
dc.contributor.authorLoos, Ruth J. F.
dc.contributor.authorMathias, Rasika A.
dc.contributor.authorMcGarvey, Stephen T.
dc.contributor.authorMitchell, Braxton D.
dc.contributor.authorNorth, Kari E.
dc.contributor.authorPeyser, Patricia A.
dc.contributor.authorPsaty, Bruce M.
dc.contributor.authorRaffield, Laura M.
dc.contributor.authorRao, D. C.
dc.contributor.authorRedline, Susan
dc.contributor.authorReiner, Alex P.
dc.contributor.authorRich, Stephen S.
dc.contributor.authorRotter, Jerome I.
dc.contributor.authorTaylor, Kent D.
dc.contributor.authorTracy, Russell
dc.contributor.authorVasan, Ramachandran S.
dc.contributor.authorMorrison, Alanna C.
dc.contributor.authorLevy, Daniel
dc.contributor.authorChakravarti, Aravinda
dc.contributor.authorArnett, Donna K.
dc.contributor.authorZhu, Xiaofeng
dc.date.accessioned2022-08-10T18:02:33Z
dc.date.available2022-08-10T18:02:33Z
dc.date.issued2022-02-19
dc.identifier.citationBMC Genomics. 2022 Feb 19;23(1):148
dc.identifier.urihttps://doi.org/10.1186/s12864-022-08356-4
dc.identifier.urihttps://hdl.handle.net/2027.42/173468en
dc.description.abstractAbstract Background While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries. Results Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10− 7). Conclusions Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
dc.titleRare coding variants in RCN3 are associated with blood pressure
dc.typeJournal Article
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/173468/1/12864_2022_Article_8356.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/5199
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dc.date.updated2022-08-10T18:02:32Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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