Caitrin W McDonough1, Oyunbileg Magvanjav2, Ana C C Sá2, Nihal M El Rouby2, Chintan Dave2, Amelia N Deitchman2, Marina Kawaguchi-Suzuki2, Wenbin Mei2, Yong Shen2, Ravi Shankar Prasad Singh2, Mohamed Solayman2, Kent R Bailey2, Eric Boerwinkle2, Arlene B Chapman2, John G Gums2, Amy Webb2, Steven E Scherer2, Wolfgang Sadee2, Stephen T Turner2, Rhonda M Cooper-DeHoff2, Yan Gong2, Julie A Johnson2. 1. Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics (C.W.M., O.M., A.C.C.S., N.M.E.R., M.K.-S., M.S., J.G.G., R.M.C.-D., Y.G., J.A.J.), Department of Pharmaceutical Outcomes and Policy (C.D.), Department of Pharmaceutics, College of Pharmacy (A.N.D., R.S.P.S.), Genetics & Genomics Graduate Program, Genetics Institute (A.C.C.S., Y.S.), Department of Biology, College of Liberal Arts and Sciences (W.M.), Department of Community Health and Family Medicine, College of Medicine (J.G.G.), and Division of Cardiovascular Medicine, Department of Medicine (R.M.C.-D., J.A.J.), University of Florida, Gainesville; School of Pharmacy, College of Health Professions, Pacific University, Hillsboro, OR (M.K.-S.); Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt (M.S.); Division of Biomedical Statistics and Informatics, Department of Health Sciences Research (K.R.B.) and Division of Nephrology and Hypertension, Department of Medicine (S.T.T.), Mayo Clinic, Rochester, MN; Human Genetics Center, Institute of Molecular Medicine, University of Texas Health Science Center, Houston (E.B.); Section of Nephrology, Department of Medicine, University of Chicago, IL (A.B.C.); Department of Biomedical Informatics, Center for Pharmacogenomics (A.W.) and Department of Cancer Biology and Genetics, College of Medicine (W.S.), Ohio State University, Columbus; and Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (S.E.S.). cmcdonough@cop.ufl.edu. 2. Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics (C.W.M., O.M., A.C.C.S., N.M.E.R., M.K.-S., M.S., J.G.G., R.M.C.-D., Y.G., J.A.J.), Department of Pharmaceutical Outcomes and Policy (C.D.), Department of Pharmaceutics, College of Pharmacy (A.N.D., R.S.P.S.), Genetics & Genomics Graduate Program, Genetics Institute (A.C.C.S., Y.S.), Department of Biology, College of Liberal Arts and Sciences (W.M.), Department of Community Health and Family Medicine, College of Medicine (J.G.G.), and Division of Cardiovascular Medicine, Department of Medicine (R.M.C.-D., J.A.J.), University of Florida, Gainesville; School of Pharmacy, College of Health Professions, Pacific University, Hillsboro, OR (M.K.-S.); Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt (M.S.); Division of Biomedical Statistics and Informatics, Department of Health Sciences Research (K.R.B.) and Division of Nephrology and Hypertension, Department of Medicine (S.T.T.), Mayo Clinic, Rochester, MN; Human Genetics Center, Institute of Molecular Medicine, University of Texas Health Science Center, Houston (E.B.); Section of Nephrology, Department of Medicine, University of Chicago, IL (A.B.C.); Department of Biomedical Informatics, Center for Pharmacogenomics (A.W.) and Department of Cancer Biology and Genetics, College of Medicine (W.S.), Ohio State University, Columbus; and Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (S.E.S.).
Abstract
BACKGROUND: Plasma renin is an important regulator of blood pressure (BP). Plasma renin activity (PRA) has been shown to correlate with variability in BP response to antihypertensive agents. We conducted a genome-wide association study to identify single-nucleotide polymorphisms (SNPs) associated with baseline PRA using data from the PEAR study (Pharmacogenomic Evaluation of Antihypertensive Responses). METHODS: Multiple linear regression analysis was performed in 461 whites and 297 blacks using an additive model, adjusting for age, sex, and ancestry-specific principal components. Top SNPs were prioritized by testing the expected direction of association for BP response to atenolol and hydrochlorothiazide. Top regions from the BP response prioritization were tested for functional evidence through differences in gene expression by genotype using RNA sequencing data. Regions with functional evidence were assessed for replication with baseline PRA in an independent study (PEAR-2). RESULTS: Our top SNP rs3784921 was in the SNN-TXNDC11 gene region. The G allele of rs3784921 was associated with higher baseline PRA (β=0.47; P=2.09×10-6) and smaller systolic BP reduction in response to hydrochlorothiazide (β=2.97; 1-sided P=0.006). In addition, TXNDC11 expression differed by rs3784921 genotype (P=0.007), and rs1802409, a proxy SNP for rs3784921 (r2=0.98-1.00), replicated in PEAR-2 (β=0.15; 1-sided P=0.038). Additional SNPs associated with baseline PRA that passed BP response prioritization were in/near the genes CHD9, XIRP2, and GHR. CONCLUSIONS: We identified multiple regions associated with baseline PRA that were prioritized through BP response signals to 2 mechanistically different antihypertensive drugs. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00246519.
RCT Entities:
BACKGROUND: Plasma renin is an important regulator of blood pressure (BP). Plasma renin activity (PRA) has been shown to correlate with variability in BP response to antihypertensive agents. We conducted a genome-wide association study to identify single-nucleotide polymorphisms (SNPs) associated with baseline PRA using data from the PEAR study (Pharmacogenomic Evaluation of Antihypertensive Responses). METHODS: Multiple linear regression analysis was performed in 461 whites and 297 blacks using an additive model, adjusting for age, sex, and ancestry-specific principal components. Top SNPs were prioritized by testing the expected direction of association for BP response to atenolol and hydrochlorothiazide. Top regions from the BP response prioritization were tested for functional evidence through differences in gene expression by genotype using RNA sequencing data. Regions with functional evidence were assessed for replication with baseline PRA in an independent study (PEAR-2). RESULTS: Our top SNP rs3784921 was in the SNN-TXNDC11 gene region. The G allele of rs3784921 was associated with higher baseline PRA (β=0.47; P=2.09×10-6) and smaller systolic BP reduction in response to hydrochlorothiazide (β=2.97; 1-sided P=0.006). In addition, TXNDC11 expression differed by rs3784921 genotype (P=0.007), and rs1802409, a proxy SNP for rs3784921 (r2=0.98-1.00), replicated in PEAR-2 (β=0.15; 1-sided P=0.038). Additional SNPs associated with baseline PRA that passed BP response prioritization were in/near the genes CHD9, XIRP2, and GHR. CONCLUSIONS: We identified multiple regions associated with baseline PRA that were prioritized through BP response signals to 2 mechanistically different antihypertensive drugs. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00246519.
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