Publication: Admixture mapping in the Hispanic Community Health Study/Study of Latinos reveals regions of genetic associations with blood pressure traits
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Date
2017
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Public Library of Science
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Citation
Sofer, T., L. J. Baier, S. R. Browning, T. A. Thornton, G. A. Talavera, S. Wassertheil-Smoller, M. L. Daviglus, et al. 2017. “Admixture mapping in the Hispanic Community Health Study/Study of Latinos reveals regions of genetic associations with blood pressure traits.” PLoS ONE 12 (11): e0188400. doi:10.1371/journal.pone.0188400. http://dx.doi.org/10.1371/journal.pone.0188400.
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Abstract
Admixture mapping can be used to detect genetic association regions in admixed populations, such as Hispanics/Latinos, by estimating associations between local ancestry allele counts and the trait of interest. We performed admixture mapping of the blood pressure traits systolic and diastolic blood pressure (SBP, DBP), mean arterial pressure (MAP), and pulse pressure (PP), in a dataset of 12,116 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Hispanics/Latinos have three predominant ancestral populations (European, African, and Amerindian), for each of which we separately tested local ancestry intervals across the genome. We identified four regions that were significantly associated with a blood pressure trait at the genome-wide admixture mapping level. A 6p21.31 Amerindian ancestry association region has multiple known associations, but none explained the admixture mapping signal. We identified variants that completely explained this signal. One of these variants had p-values of 0.02 (MAP) and 0.04 (SBP) in replication testing in Pima Indians. A 11q13.4 Amerindian ancestry association region spans a variant that was previously reported (p-value = 0.001) in a targeted association study of Blood Pressure (BP) traits and variants in the vitamin D pathway. There was no replication evidence supporting an association in the identified 17q25.3 Amerindian ancestry association region. For a region on 6p12.3, associated with African ancestry, we did not identify any candidate variants driving the association. It may be driven by rare variants. Whole genome sequence data may be necessary to fine map these association signals, which may contribute to disparities in BP traits between diverse populations.
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Keywords
Biology and Life Sciences, Computational Biology, Genome Analysis, Genome-Wide Association Studies, Genetics, Genomics, Human Genetics, Molecular Biology, Molecular Biology Techniques, Gene Mapping, Chromosome Mapping, Gene Identification and Analysis, Medicine and Health Sciences, Vascular Medicine, Blood Pressure, People and places, Population groupings, Ethnicities, Latin American people, Mexican People, Heredity, Genetic Mapping, Variant Genotypes, Cell Biology, Signal Transduction, Cell Signaling, Genomic Signal Processing
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