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Universal genome-wide association studies: Powerful joint ancestry and association testing
The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genot...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507155/ https://www.ncbi.nlm.nih.gov/pubmed/37653728 http://dx.doi.org/10.1016/j.xhgg.2023.100235 |
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author | Shriner, Daniel Bentley, Amy R. Gouveia, Mateus H. Heuston, Elisabeth F. Doumatey, Ayo P. Chen, Guanjie Zhou, Jie Adeyemo, Adebowale Rotimi, Charles N. |
author_facet | Shriner, Daniel Bentley, Amy R. Gouveia, Mateus H. Heuston, Elisabeth F. Doumatey, Ayo P. Chen, Guanjie Zhou, Jie Adeyemo, Adebowale Rotimi, Charles N. |
author_sort | Shriner, Daniel |
collection | PubMed |
description | The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genotype. We developed a joint test of ancestry and association that can be performed with summary statistics, is independent of study design, can take advantage of locus-specific ancestry effects to boost power in association testing, and can utilize association effects to fine map admixture peaks. We illustrate the test using the association between serum triglycerides and LPL. By combining data from African Americans, European Americans, and West Africans, we identify three conditionally independent variants with varying amounts of ancestrally differentiated allele frequencies. Using out-of-sample data, we demonstrate improved prediction achievable by accounting for multiple causal variants and locus-specific ancestry effects at a single locus. |
format | Online Article Text |
id | pubmed-10507155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105071552023-09-20 Universal genome-wide association studies: Powerful joint ancestry and association testing Shriner, Daniel Bentley, Amy R. Gouveia, Mateus H. Heuston, Elisabeth F. Doumatey, Ayo P. Chen, Guanjie Zhou, Jie Adeyemo, Adebowale Rotimi, Charles N. HGG Adv Article The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genotype. We developed a joint test of ancestry and association that can be performed with summary statistics, is independent of study design, can take advantage of locus-specific ancestry effects to boost power in association testing, and can utilize association effects to fine map admixture peaks. We illustrate the test using the association between serum triglycerides and LPL. By combining data from African Americans, European Americans, and West Africans, we identify three conditionally independent variants with varying amounts of ancestrally differentiated allele frequencies. Using out-of-sample data, we demonstrate improved prediction achievable by accounting for multiple causal variants and locus-specific ancestry effects at a single locus. Elsevier 2023-08-30 /pmc/articles/PMC10507155/ /pubmed/37653728 http://dx.doi.org/10.1016/j.xhgg.2023.100235 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shriner, Daniel Bentley, Amy R. Gouveia, Mateus H. Heuston, Elisabeth F. Doumatey, Ayo P. Chen, Guanjie Zhou, Jie Adeyemo, Adebowale Rotimi, Charles N. Universal genome-wide association studies: Powerful joint ancestry and association testing |
title | Universal genome-wide association studies: Powerful joint ancestry and association testing |
title_full | Universal genome-wide association studies: Powerful joint ancestry and association testing |
title_fullStr | Universal genome-wide association studies: Powerful joint ancestry and association testing |
title_full_unstemmed | Universal genome-wide association studies: Powerful joint ancestry and association testing |
title_short | Universal genome-wide association studies: Powerful joint ancestry and association testing |
title_sort | universal genome-wide association studies: powerful joint ancestry and association testing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507155/ https://www.ncbi.nlm.nih.gov/pubmed/37653728 http://dx.doi.org/10.1016/j.xhgg.2023.100235 |
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