Authors

Xiaofeng Zhu, CASE School of Medicine
J. H. Young, Johns Hopkins University School of Medicine
Ervin Fox, University of Mississippi School of Medicine
Brendan J. Keating, University of Pennsylvania Perelman School of Medicine
Nora Franceschini, UNC Gillings School of Global Public Health
Sunjung Kang, CASE School of Medicine
Bamidele Tayo, Stritch School of Medicine
Adebowale Adeyemo, National Human Genome Research Institute (NHGRI)
Yun V. Sun, University of Michigan School of Public Health
Yali Li, CASE School of Medicine
Alanna Morrison, University of Texas Health Science Center at Houston
Christopher Newton-Cheh, Broad Institute
Kiang Liu, Northwestern University Feinberg School of Medicine
Santhi K. Ganesh, Michigan Medicine
Abdullah Kutlar, Medical College of Georgia
Ramachandran S. Vasan, Boston University Chobanian & Avedisian School of Medicine
Albert Dreisbach, University of Mississippi School of Medicine
Sharon Wyatt, University of Mississippi Medical Center
Joseph Polak, Tufts Medical Center
Walter Palmas, Columbia University
Solomon Musani, University of Mississippi School of Medicine
Herman Taylor, University of Mississippi School of Medicine
Richard Fabsitz, National Heart, Lung, and Blood Institute (NHLBI)
Raymond R. Townsend, University of Pennsylvania Perelman School of Medicine
Daniel Dries, University of Pennsylvania Perelman School of Medicine
Joseph Glessner, The Children's Hospital of Philadelphia
Charleston W.K. Chiang, Harvard Medical School
Thomas Mosley, University of Mississippi School of Medicine
Sharon Kardia, University of Michigan School of Public Health
David Curb, Pacific Health Research Institute Hawaii
Joel N. Hirschhorn, Harvard Medical School
Charles Rotimi, National Human Genome Research Institute (NHGRI)
Alexander Reiner, Division of Biology and Medicine

Document Type

Article

Publication Date

6-1-2011

Abstract

Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P < 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P < 10-5). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P < 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10-7 for SBP and 7.52 × 10-7 for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genomewide association studies because of drastically reduced number of tests in the whole genome. © The Author 2011. Published by Oxford University Press.

Publication Source (Journal or Book title)

Human Molecular Genetics

First Page

2285

Last Page

2295

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