Evidence map›Paper›PMID 35613103›Full record

SynthesisPloS one2022

Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program.

Rose D L Huang, Xuan-Mai T Nguyen, Gina M Peloso, Mark Trinder, Daniel C Posner, Krishna G Aragam, Yuk-Lam Ho, Julie A Lynch, Scott M Damrauer, Kyong-Mi Chang and 10 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Rose D L HuangCenter for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Xuan-Mai T NguyenMAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Gina M PelosoCenter for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Mark TrinderCentre for Heart Lung Innovation, University of British Columbia, Vancouver, Canada.ORCID 0000-0001-8447-2897
Daniel C PosnerMAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Krishna G AragamProgram in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Yuk-Lam HoMAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Julie A LynchVA Informatics & Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, United States of America.
Scott M DamrauerCorporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America.
Kyong-Mi ChangCorporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0001-6811-9364
Philip S TsaoVA Palo Alto Health Care System, Palo Alto, California, United States of America.
Pradeep NatarajanProgram in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.ORCID 0000-0001-8402-7435
Themistocles AssimesVA Palo Alto Health Care System, Palo Alto, California, United States of America.
J Michael GazianoMAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Luc DjousseMAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Kelly ChoMAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Peter W F WilsonAtlanta VA Medical Center, Decatur, Georgia, United States of America.
Jennifer E HuffmanCenter for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.ORCID 0000-0002-9672-2491
Christopher J O'DonnellCenter for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.ORCID 0000-0002-2667-8624
Veterans Affairs’ Million Veteran Program

Funding

Using genetic variation to study biology of blood lipids & coronary heart diseaseR01HL127564 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Pradeep Natarajan, Gina Marie Peloso · 2015 to 2026
$7.3M
Cardiovascular Disease Risk Factors, Prevalent Cardiovascular Disease, and Genetics in the Million Veteran ProgramI01BX003340 · VA · VETERANS HEALTH ADMINISTRATION · PI CHO, KELLY, WILSON, PETER WYMAN · 2017 to 2017
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Genetics of Cardiometabolic Diseases in the VA PopulationI01BX003362 · VA · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · PI Kyong-Mi Chang, Philip S Tsao · 2017 to 2026
–
Cardiovascular Disease Risk Factors, Cardiovascular Disease Risk Prediction, and Genetics in the Million Veteran ProgramI01BX004821 · VA · VETERANS HEALTH ADMINISTRATION · PI PETER WYMAN WILSON · 2020 to 2026
–
Precision Cardio-Metabolic Phenotyping for Genetic Discovery and Risk PredictionIK2CX001780 · VA · PHILADELPHIA VA MEDICAL CENTER · PI DAMRAUER, SCOTT MICHAEL · 2018 to 2023
–
BLRD VA I01 BX003340BLRD VA I01 BX003362BLRD VA I01 BX004821CSRD VA IK2 CX001780NHLBI NIH HHS R01 HL127564
6 · The paper itself

Abstract

backgroundGenetic 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.

methodsAn 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.

resultsThe 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.

conclusionA 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.

Indexed as

Cardiovascular DiseasesVeteransFemaleGenome-Wide Association StudyHealth StatusHumansMalePhenomicsRisk Factors

Identifiers

PMID35613103
PMCPMC9132265

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.