| Title: | Rare coding variants in RCN3 are associated with blood pressure |
| Journal: | BMC Genomics |
| Published: | 19 Feb 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35183128/ |
| DOI: | https://doi.org/10.1186/s12864-022-08356-4 |
| URL: | https://bmcgenomics.biomedcentral.com/track/pdf/10.1186/s12864-022-08356-4 |
| Citations: | 2 (1 in last 2 years) as of 8 Aug 2024 |
Publication 12522
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Abstract
BackgroundWhile 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.ResultsAssociations 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).ConclusionsLow 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.</p>
8 Keywords
- Blood Pressure
- Genetic Linkage
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Polymorphism, Single Nucleotide
- Precision Medicine
- Whole Genome Sequencing
77 Authors
- Karen Y. He
- Tanika N. Kelly
- Heming Wang
- Jingjing Liang
- Luke Zhu
- Brian E. Cade
- Themistocles L. Assimes
- Lewis C. Becker
- Amber L. Beitelshees
- Lawrence F. Bielak
- Adam P. Bress
- Jennifer A. Brody
- Yen-Pei Christy Chang
- Yi-Cheng Chang
- Paul S. de Vries
- Ravindranath Duggirala
- Ervin R. Fox
- Nora Franceschini
- Anna L. Furniss
- Yan Gao
- Xiuqing Guo
- Jeffrey Haessler
- Yi-Jen Hung
- Shih-Jen Hwang
- Marguerite Ryan Irvin
- Rita R. Kalyani
- Ching-Ti Liu
- Chunyu Liu
- Lisa Warsinger Martin
- May E. Montasser
- Paul M. Muntner
- Stanford Mwasongwe
- Take Naseri
- Walter Palmas
- Muagututi'a Sefuiva Reupena
- Kenneth M. Rice
- Wayne H.-H. Sheu
- Daichi Shimbo
- Jennifer A. Smith
- Beverly M. Snively
- Lisa R. Yanek
- Wei Zhao
- John Blangero
- Eric Boerwinkle
- Yii-Der Ida Chen
- Adolfo Correa
- L. Adrienne Cupples
- Joanne E. Curran
- Myriam Fornage
- Jiang He
- Lifang Hou
- Robert C. Kaplan
- Sharon L. R. Kardia
- Eimear E. Kenny
- Charles Kooperberg
- Donald Lloyd-Jones
- Ruth J. F. Loos
- Rasika A. Mathias
- Stephen T. McGarvey
- Braxton D. Mitchell
- Kari E. North
- Patricia A. Peyser
- Bruce M. Psaty
- Laura M. Raffield
- D. C. Rao
- Susan Redline
- Alex P. Reiner
- Stephen S. Rich
- Jerome I. Rotter
- Kent D. Taylor
- Russell Tracy
- Ramachandran S. Vasan
- Alanna C. Morrison
- Daniel Levy
- Aravinda Chakravarti
- Donna K. Arnett
- Xiaofeng Zhu
1 Application
| Application ID | Title |
|---|---|
| 34201 | Epigenomics-mediated blood pressure and QT GWAS |
Enabling scientific discoveries that improve human health