Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program.
Ancestry
Ethnicity
Height
Million Veteran Program
Population stratification
Race
Journal
Human genomics
ISSN: 1479-7364
Titre abrégé: Hum Genomics
Pays: England
ID NLM: 101202210
Informations de publication
Date de publication:
02 06 2023
02 06 2023
Historique:
received:
06
09
2022
accepted:
05
05
2023
medline:
5
6
2023
pubmed:
3
6
2023
entrez:
2
6
2023
Statut:
epublish
Résumé
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]). 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 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.
Sections du résumé
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
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.
Identifiants
pubmed: 37268996
doi: 10.1186/s40246-023-00487-3
pii: 10.1186/s40246-023-00487-3
pmc: PMC10239111
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
46Subventions
Organisme : NIDA NIH HHS
ID : R21 DA047527
Pays : United States
Organisme : NIDCD NIH HHS
ID : R21 DC018098
Pays : United States
Organisme : NIDA NIH HHS
ID : R33 DA047527
Pays : United States
Organisme : NIMH NIH HHS
ID : F32 MH122058
Pays : United States
Informations de copyright
© 2023. The Author(s).
Références
Nat Genet. 2021 Dec;53(12):1634-1635
pubmed: 34824479
Science. 2008 Feb 22;319(5866):1100-4
pubmed: 18292342
J Epidemiol. 2017 Mar;27(3S):S2-S8
pubmed: 28189464
Gigascience. 2015 Feb 25;4:7
pubmed: 25722852
Nat Genet. 2021 Dec;53(12):1631-1633
pubmed: 34824480
PLoS Genet. 2017 May 1;13(5):e1006755
pubmed: 28459806
Int J Epidemiol. 2021 Jul 9;50(3):717-718e
pubmed: 34143882
Commun Biol. 2019 Jan 7;2:9
pubmed: 30623105
N Engl J Med. 2019 Aug 15;381(7):668-676
pubmed: 31412182
Cell. 2019 Oct 17;179(3):589-603
pubmed: 31607513
Nat Genet. 2015 Mar;47(3):291-5
pubmed: 25642630
Elife. 2019 Mar 21;8:
pubmed: 30895926
Curr Protoc Hum Genet. 2017 Oct 18;95:1.22.1-1.22.23
pubmed: 29044472
Nature. 2015 Oct 1;526(7571):68-74
pubmed: 26432245
Nat Genet. 2018 May;50(5):737-745
pubmed: 29700474
Am J Hum Genet. 2019 Oct 3;105(4):763-772
pubmed: 31564439
Nat Genet. 2021 Feb;53(2):195-204
pubmed: 33462486
Popul Dev Rev. 2009 Mar;35(1):1-51
pubmed: 20539823
Cell. 2019 Oct 17;179(3):736-749.e15
pubmed: 31626772
Cell. 2019 Mar 21;177(1):26-31
pubmed: 30901543
Genome Res. 2009 Sep;19(9):1655-64
pubmed: 19648217
Am J Hum Genet. 2020 Apr 2;106(4):535-548
pubmed: 32243820
J Clin Epidemiol. 2016 Feb;70:214-23
pubmed: 26441289
Hum Mol Genet. 2021 Jul 9;30(15):1457-1467
pubmed: 33890984