Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Tanika N. Kelly, Department of Epidemiology, Tulane University, New Orleans, LA. (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.).
Xiao Sun, Department of Epidemiology, Tulane University, New Orleans, LA. (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.).
Karen Y. He, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.).
Michael R. Brown, Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.).
Sarah A. Taliun, The University of Texas Health Science Center at Houston. Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor.
Jacklyn N. Hellwege, Division of Genetic Medicine, Department of Medicine (J.N.H.), Vanderbilt University Medical Center, Nashville, TN.
Marguerite R. Irvin, Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham.
Xuenan Mi, Department of Epidemiology, Tulane University, New Orleans, LA. (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.).
Jennifer A. Brody, Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle.
Nora Franceschini, Department of Epidemiology, University of North Carolina, Chapel Hill (N.F.).
Xiuqing Guo, The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., D.L.).
Shih-Jen Hwang, National Heart, Lung and Blood Institute, Population Sciences Branch, National Institutes of Health, Framingham, MA (S.-J.H.).
Paul S. de Vries, Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.).
Yan Gao, Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson.
Arden Moscati, The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY.
Girish N. Nadkarni, Department of Medicine (G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY.
Lisa R. Yanek, Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD.
Tali Elfassy, Division of Epidemiology, Department of Public Health Sciences, University of Miami Miller School of Medicine, FL (T.E.).
Jennifer A. Smith, Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor.
Ren-Hua Chung, Institute of Population Sciences, National Health Research Institutes, Taiwan (R.-H.C.).
Amber L. Beitelshees, Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.).
Amit Patki, Department of Biostatistics (A.P., V.S.), University of Alabama at Birmingham.
Stella Aslibekyan, Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham.
Brandon M. Blobner, Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA.
Juan M. Peralta, Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville (J.M.P., J.E.C., J.B.).
Themistocles L. Assimes, Division of Cardiovascular Medicine, Department of Medicine, Stanford University, CA (T.L.A.).
Walter R. Palmas, Division of General Medicine, Department of Medicine, Columbia University, New York, NY (W.R.P.).
Chunyu Liu, Department of Biostatistics, Boston University, MA (C.L.).
Adam P. Bress, Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City (A.P.B.).
Zhijie Huang, Department of Epidemiology, Tulane University, New Orleans, LA. (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.).
Lewis C. Becker, Division of Cardiology, Department of Medicine (L.C.B.), Johns Hopkins University School of Medicine, Baltimore, MD.
Chii-Min Hwa, Taichung Veterans General Hospital, Taichung, Taiwan (C.-M.H.).

Document Type

Journal Article

Publication Date

6-2-2022

Journal

Hypertension (Dallas, Tex. : 1979)

DOI

10.1161/HYPERTENSIONAHA.122.19324

Keywords

allele; blood pressure; genome; hypertension; whole-exome sequencing

Abstract

BACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5×10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99×10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18×10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28×10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1×10 and <1×10, respectively). DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

Department

Medicine

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