Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2022
2022
Historique:
received:
10
10
2021
accepted:
18
04
2022
entrez:
25
5
2022
pubmed:
26
5
2022
medline:
28
5
2022
Statut:
epublish
Résumé
Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.
Sections du résumé
BACKGROUND
Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program.
METHODS
An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization.
RESULTS
The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality.
CONCLUSION
A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.
Identifiants
pubmed: 35613103
doi: 10.1371/journal.pone.0267900
pii: PONE-D-21-32548
pmc: PMC9132265
doi:
Types de publication
Journal Article
Meta-Analysis
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0267900Subventions
Organisme : BLRD VA
ID : I01 BX003340
Pays : United States
Organisme : BLRD VA
ID : I01 BX004821
Pays : United States
Organisme : CSRD VA
ID : IK2 CX001780
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL127564
Pays : United States
Déclaration de conflit d'intérêts
I have read the journal’s policy and the authors of this manuscript have the following competing interests: CJO: Employed by Novartis Institutes for Biomedical Research. SMD: Research support to my institution from RenalytixAI and paid consulting from Calico Labs, both outside the current work. PN: Research support from Amgen, Apple, and Boston Scientific, and personal consulting fees from Apple and Blackstone Life Sciences, all unrelated to the present work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Références
Bioinformatics. 2014 Aug 15;30(16):2375-6
pubmed: 24733291
Clin Cardiol. 2017 Dec;40(12):1339-1346
pubmed: 29278429
Nat Genet. 2018 May;50(5):693-698
pubmed: 29686387
J Am Heart Assoc. 2013 Apr 25;2(3):e000058
pubmed: 23619743
Nucleic Acids Res. 2019 Jan 8;47(D1):D1005-D1012
pubmed: 30445434
Nat Commun. 2020 Jan 9;11(1):163
pubmed: 31919418
JAMA. 1999 Dec 1;282(21):2012-8
pubmed: 10591383
Am Heart J. 2016 May;175:112-20
pubmed: 27179730
Nat Commun. 2019 Jan 22;10(1):376
pubmed: 30670697
Nat Genet. 2013 Jan;45(1):25-33
pubmed: 23202125
PLoS Genet. 2017 Apr 27;13(4):e1006528
pubmed: 28448500
Diabetes. 2017 Nov;66(11):2888-2902
pubmed: 28566273
Am Heart J. 2016 Jun;176:134-44
pubmed: 27264232
Gigascience. 2019 Jul 1;8(7):
pubmed: 31307061
N Engl J Med. 2019 Dec 19;381(25):2440-2450
pubmed: 31851800
Hum Mol Genet. 2018 Oct 15;27(20):3641-3649
pubmed: 30124842
Int J Cardiol. 2016 Jul 1;214:279-83
pubmed: 27085116
Elife. 2018 May 30;7:
pubmed: 29846171
Prev Med. 2015 May;74:111-6
pubmed: 25712326
Bioinformatics. 2010 May 1;26(9):1205-10
pubmed: 20335276
Gigascience. 2015 Feb 25;4:7
pubmed: 25722852
Hum Mol Genet. 2007 Jan 1;16(1):24-35
pubmed: 17158188
Circulation. 2010 Feb 2;121(4):586-613
pubmed: 20089546
Circ Res. 2018 Feb 2;122(3):433-443
pubmed: 29212778
BMC Bioinformatics. 2010 May 28;11:288
pubmed: 20509871
Am J Cardiol. 2018 Jul 15;122(2):347-352
pubmed: 29753396
Am J Hum Genet. 2019 Oct 3;105(4):763-772
pubmed: 31564439
Nat Genet. 2010 May;42(5):448-53
pubmed: 20418888
Nat Genet. 2018 Oct;50(10):1412-1425
pubmed: 30224653
JAMA. 1990 Apr 4;263(13):1795-801
pubmed: 2179590
Bioinformatics. 2014 Jun 15;30(12):i185-94
pubmed: 24931982
BMJ. 2020 Jan 8;368:l6669
pubmed: 31915124
PLoS Genet. 2017 Nov 17;13(11):e1007081
pubmed: 29149188
Bioinformatics. 2010 Sep 15;26(18):2336-7
pubmed: 20634204
Am J Hum Genet. 2020 Apr 2;106(4):535-548
pubmed: 32243820
J Clin Epidemiol. 2016 Feb;70:214-23
pubmed: 26441289
Cochrane Database Syst Rev. 2015 Aug 04;(8):CD011163
pubmed: 26272648
Nat Genet. 2018 Nov;50(11):1514-1523
pubmed: 30275531
Cochrane Database Syst Rev. 2011 Jan 19;(1):CD001561
pubmed: 21249647
Bioinformatics. 2015 Apr 15;31(8):1334-6
pubmed: 25431330
Nat Genet. 2018 Apr;50(4):524-537
pubmed: 29531354
Nat Genet. 2019 Feb;51(2):237-244
pubmed: 30643251
Nature. 2015 Feb 12;518(7538):197-206
pubmed: 25673413