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Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program

BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in...

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Autores principales: Wendt, Frank R., Pathak, Gita A., Vahey, Jacqueline, Qin, Xuejun, Koller, Dora, Cabrera-Mendoza, Brenda, Haeny, Angela, Harrington, Kelly M., Rajeevan, Nallakkandi, Duong, Linh M., Levey, Daniel F., De Angelis, Flavio, De Lillo, Antonella, Bigdeli, Tim B., Pyarajan, Saiju, Gaziano, John Michael, Gelernter, Joel, Aslan, Mihaela, Provenzale, Dawn, Helmer, Drew A., Hauser, Elizabeth R., Polimanti, Renato
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239111/
https://www.ncbi.nlm.nih.gov/pubmed/37268996
http://dx.doi.org/10.1186/s40246-023-00487-3
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author Wendt, Frank R.
Pathak, Gita A.
Vahey, Jacqueline
Qin, Xuejun
Koller, Dora
Cabrera-Mendoza, Brenda
Haeny, Angela
Harrington, Kelly M.
Rajeevan, Nallakkandi
Duong, Linh M.
Levey, Daniel F.
De Angelis, Flavio
De Lillo, Antonella
Bigdeli, Tim B.
Pyarajan, Saiju
Gaziano, John Michael
Gelernter, Joel
Aslan, Mihaela
Provenzale, Dawn
Helmer, Drew A.
Hauser, Elizabeth R.
Polimanti, Renato
author_facet Wendt, Frank R.
Pathak, Gita A.
Vahey, Jacqueline
Qin, Xuejun
Koller, Dora
Cabrera-Mendoza, Brenda
Haeny, Angela
Harrington, Kelly M.
Rajeevan, Nallakkandi
Duong, Linh M.
Levey, Daniel F.
De Angelis, Flavio
De Lillo, Antonella
Bigdeli, Tim B.
Pyarajan, Saiju
Gaziano, John Michael
Gelernter, Joel
Aslan, Mihaela
Provenzale, Dawn
Helmer, Drew A.
Hauser, Elizabeth R.
Polimanti, Renato
author_sort Wendt, Frank R.
collection PubMed
description BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen’s d < 0.259, p < 7.80 × 10(−4)). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00487-3.
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spelling pubmed-102391112023-06-04 Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program Wendt, Frank R. Pathak, Gita A. Vahey, Jacqueline Qin, Xuejun Koller, Dora Cabrera-Mendoza, Brenda Haeny, Angela Harrington, Kelly M. Rajeevan, Nallakkandi Duong, Linh M. Levey, Daniel F. De Angelis, Flavio De Lillo, Antonella Bigdeli, Tim B. Pyarajan, Saiju Gaziano, John Michael Gelernter, Joel Aslan, Mihaela Provenzale, Dawn Helmer, Drew A. Hauser, Elizabeth R. Polimanti, Renato Hum Genomics Research BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen’s d < 0.259, p < 7.80 × 10(−4)). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00487-3. BioMed Central 2023-06-02 /pmc/articles/PMC10239111/ /pubmed/37268996 http://dx.doi.org/10.1186/s40246-023-00487-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wendt, Frank R.
Pathak, Gita A.
Vahey, Jacqueline
Qin, Xuejun
Koller, Dora
Cabrera-Mendoza, Brenda
Haeny, Angela
Harrington, Kelly M.
Rajeevan, Nallakkandi
Duong, Linh M.
Levey, Daniel F.
De Angelis, Flavio
De Lillo, Antonella
Bigdeli, Tim B.
Pyarajan, Saiju
Gaziano, John Michael
Gelernter, Joel
Aslan, Mihaela
Provenzale, Dawn
Helmer, Drew A.
Hauser, Elizabeth R.
Polimanti, Renato
Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program
title Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program
title_full Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program
title_fullStr Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program
title_full_unstemmed Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program
title_short Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program
title_sort modeling the longitudinal changes of ancestry diversity in the million veteran program
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239111/
https://www.ncbi.nlm.nih.gov/pubmed/37268996
http://dx.doi.org/10.1186/s40246-023-00487-3
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