Rare Coding Variants in RCN3 Are Associated with Blood Pressure

Authors

Karen Y. He, Case Western Reserve University
Tanika N. Kelly, Tulane University
Heming Wang, Brigham and Women's Hospital
Jingjing Liang, Case Western Reserve University
Luke Zhu, New York University
Brian E. Cade, Brigham and Women's Hospital
Themistocles L. Assimes, Stanford University
Lewis C. Becker, Johns Hopkins University
Amber L. Beitelshees, University of Maryland
Lawrence F. Bielak, University of Michigan
Adam P. Bress, University of Utah
Jennifer A. Brody, University of Washington
Yen-Pei Christy Chang, University of Maryland
Yi-Cheng Chang, National Taiwan University, Taiwan
Paul S. de Vries, University of Texas
Ravindranath Duggirala, University of Texas Rio Grande Valley
Ervin R. Fox, University of Mississippi
Nora Franceschini, University of North Carolina at Chapel Hill
Anna L. Furniss, University of Mississippi
Yan Gao, University of Mississippi
Donna K. Arnett, University of KentuckyFollow

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^− 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.

Document Type

Article

Publication Date

2-19-2022

Notes/Citation Information

Published in BMC Genomics, v. 23, article no. 148.

© 2022 The Author(s)

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The first 20 authors and the author from the University of Kentucky are shown on the author list above. Please refer to the downloaded document for the complete author list.

Digital Object Identifier (DOI)

https://doi.org/10.1186/s12864-022-08356-4

Funding Information

KYH was partially supported by grant T32 HL007567 from the National Heart, Lung, and Blood Institute (NHLBI). This work was supported by HL086694 from NHLBI, HG003054 and HG011052 from the National Human Genome Research Institute.

Related Content

All the TOPMed datasets generated and/or analyzed during the current study are available in the dbGaP repository and instructions for data access can be found at https://www.nhlbiwgs.org/topmed-data-access-scientific-community. The current study includes datasets: phs000956, phs001211, phs001644, phs001624, phs001612, phs000954, phs001368, phs000951, phs001218, phs001345, phs000974, phs001217, phs001395, phs001293, phs000964, phs001416, phs001215, phs000972, phs001387, phs001237. The UK Biobank data is available in the UK Biobank repository: ukbiobank.ac.uk.

Repository Citation

He, Karen Y.; Kelly, Tanika N.; Wang, Heming; Liang, Jingjing; Zhu, Luke; Cade, Brian E.; Assimes, Themistocles L.; Becker, Lewis C.; Beitelshees, Amber L.; Bielak, Lawrence F.; Bress, Adam P.; Brody, Jennifer A.; Chang, Yen-Pei Christy; Chang, Yi-Cheng; de Vries, Paul S.; Duggirala, Ravindranath; Fox, Ervin R.; Franceschini, Nora; Furniss, Anna L.; Gao, Yan; and Arnett, Donna K., "Rare Coding Variants in RCN3 Are Associated with Blood Pressure" (2022). Epidemiology and Environmental Health Faculty Publications. 91.
https://uknowledge.uky.edu/epidemiology_facpub/91