Title

Rare coding variants in RCN3 are associated with blood pressure

Authors

Karen Y. He, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA.
Tanika N. Kelly, Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
Heming Wang, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
Jingjing Liang, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA.
Luke Zhu, Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY, USA.
Brian E. Cade, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
Themistocles L. Assimes, Department of Medicine (Division of Cardiovascular Medicine), Stanford University, Palo Alto, CA, USA.
Lewis C. Becker, GeneSTAR Research Program, Department of Medicine, Divisions of Cardiology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Amber L. Beitelshees, Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Lawrence F. Bielak, Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Adam P. Bress, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, USA.
Jennifer A. Brody, Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
Yen-Pei Christy Chang, Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Yi-Cheng Chang, Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, Taipei City, Taiwan.
Paul S. de Vries, Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Ravindranath Duggirala, Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA.
Ervin R. Fox, Division of Cardiovascular Diseases, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
Nora Franceschini, Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA.
Anna L. Furniss, Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA.
Yan Gao, Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA.
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, CA, USA.
Jeffrey Haessler, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Yi-Jen Hung, Institute of Preventive Medicine, National Defense Medical Center, New Taipei City, Taiwan.
Shih-Jen Hwang, Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA.
Marguerite Ryan Irvin, Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AB, USA.
Rita R. Kalyani, GeneSTAR Research Program, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Ching-Ti Liu, Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA.
Chunyu Liu, Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA.
Lisa Warsinger Martin, Division of Cardiology, Department of Medicine, George Washington University, Washington, DC, USA.
May E. Montasser, Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Paul M. Muntner, Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AB, USA.
Stanford Mwasongwe, Jackson Heart Study, Jackson State University, Jackson, MS, USA.

Document Type

Journal Article

Publication Date

2-19-2022

Journal

BMC genomics

Volume

23

Issue

1

DOI

10.1186/s12864-022-08356-4

Keywords

Blood pressure; Rare variant analysis; Whole genome sequencing

Abstract

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). 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.

Department

Medicine

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