Evidence map›Paper›PMID 30586733›Full record

Trial reportCirculation2019

Whole-Genome Sequencing to Characterize Monogenic and Polygenic Contributions in Patients Hospitalized With Early-Onset Myocardial Infarction.

Amit V Khera, Mark Chaffin, Seyedeh M Zekavat, Ryan L Collins, Carolina Roselli, Pradeep Natarajan, Judith H Lichtman, Gail D'Onofrio, Jennifer Mattera, Rachel Dreyer and 13 more

2 registry-linked trialsAbstract readClinical TrialComparative StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Circulation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 185 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
185citing papers in PubMed, 4 pooled it
–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.

NCT00597922 completednot on this map

Variation in Recovery: Role of Gender on Outcomes of Young Acute Myocardial Infarction (AMI) Patients (VIRGO)

TypeobservationalSponsorYale UniversityRan2007 to 2013Enrolled2,985ConditionsAcute Myocardial Infarction
NCT05277116 naactive not recruitingnot on this mapstarted 2022, after this paper: background citation

The Electronic Medical Records and GEnomics (eMERGE) Network Genomic Risk Assessment

TypeinterventionalSponsorVanderbilt University Medical CenterRan2022 to 2030Enrolled26,877ConditionsGenetic DiseaseArmsGenome Informed Risk Assessment (GIRA) report
3 · Its place in the literature

Who cites it

185 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Pooled it
  5. Trial
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  8. Article
  9. Article
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  11. Review
  12. Cross-ancestry polygenic risk scores enhance Alzheimer's disease risk prediction in multiethnic cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  13. Article
  14. Review
  15. Clinical utility of polygenic risk scores in cardiovascular disorders.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
    Article
  16. Review
  17. Article
  18. Polygenic risk scores for cardiovascular disease: clinical utility and limitations.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2026
    Review
  19. Article
  20. Article

125 more citing papers are in PubMed but not listed here.

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

23 authors.

Amit V KheraCenter for Genomic Medicine (A.V.K., R.L.C., M.E.T., S.K.), Massachusetts General Hospital, Boston.
Mark ChaffinCardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.).
Seyedeh M ZekavatCardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.).
Ryan L CollinsCenter for Genomic Medicine (A.V.K., R.L.C., M.E.T., S.K.), Massachusetts General Hospital, Boston.
Carolina RoselliCardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.).
Pradeep NatarajanDivision of Cardiology (A.V.K., P.N., S.K.), Massachusetts General Hospital, Boston.
Judith H LichtmanDepartment of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT (J.H.L.).
Gail D'OnofrioDepartment of Emergency Medicine, Yale University, New Haven, CT (G.D., R.D.).
Jennifer MatteraCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, CT (J.M., H.M.K.).
Rachel DreyerDepartment of Emergency Medicine, Yale University, New Haven, CT (G.D., R.D.).
John A SpertusDepartment of Biomedical and Health Informatics, Saint Luke's Mid America Heart Institute, University of Missouri, Kansas City (J.A.S.).
Kent D TaylorInstitute for Translational Genomics and Population Sciences, LABioMed, Torrance, CA (K.D.T., Y.-D.I.C., J.I.R.).
Bruce M PsatyUniversity of Washington and Kaiser Permanente, Seattle (B.M.P.).
Stephen S RichCenter for Public Health Genomics, University of Virginia School of Medicine, Richmond (S.S.R.).
Wendy PostJohns Hopkins University School of Medicine, Baltimore, MD (W.P.).
Namrata GuptaCardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.).
Stacey GabrielCardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.).
Eric LanderCardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.).
Yii-Der Ida ChenInstitute for Translational Genomics and Population Sciences, LABioMed, Torrance, CA (K.D.T., Y.-D.I.C., J.I.R.).
Michael E TalkowskiCenter for Genomic Medicine (A.V.K., R.L.C., M.E.T., S.K.), Massachusetts General Hospital, Boston.
Jerome I RotterInstitute for Translational Genomics and Population Sciences, LABioMed, Torrance, CA (K.D.T., Y.-D.I.C., J.I.R.).
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, CT (J.M., H.M.K.).
Sekar KathiresanCenter for Genomic Medicine (A.V.K., R.L.C., M.E.T., S.K.), Massachusetts General Hospital, Boston.

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Center for Common Disease GeneticsUM1HG008895 · NHGRI · BROAD INSTITUTE, INC. · PI DALY, MARK JOSEPH, GABRIEL, STACEY · 2016 to 2020
$111.2M
Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM007205 · NIGMS · YALE UNIVERSITY · PI KAZMIERCZAK, BARBARA I · 1985 to 2019
$42.9M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Andrea L Hevener · 2003 to 2026
$40.4M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
MULTIDISCIPLINARY RESEARCH TRAINING IN CARDIOLOGYT32HL007208 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Patrick Thomas Ellinor, David E Sosnovik · 1985 to 2026
$16.1M
Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
Young Women With Acute Myocardial InfarctionR01HL081153 · NHLBI · YALE UNIVERSITY · PI KRUMHOLZ, HARLAN MARC · 2007 to 2012
$10.6M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
Harvard Clinical and Translational Science CenterKL2TR001100 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$8.5M
NCATS NIH HHS KL2 TR001100NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NHGRI NIH HHS K08 HG010155NHGRI NIH HHS T32 HG002295NHGRI NIH HHS UM1 HG008895NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL081153NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL127564NHLBI NIH HHS R01 HL142711NHLBI NIH HHS T32 HL007208NIDDK NIH HHS P30 DK063491NIGMS NIH HHS T32 GM007205
6 · The paper itself

Abstract

backgroundThe relative prevalence and clinical importance of monogenic mutations related to familial hypercholesterolemia and of high polygenic score (cumulative impact of many common variants) pathways for early-onset myocardial infarction remain uncertain. Whole-genome sequencing enables simultaneous ascertainment of both monogenic mutations and polygenic score for each individual.

methodsWe performed deep-coverage whole-genome sequencing of 2081 patients from 4 racial subgroups hospitalized in the United States with early-onset myocardial infarction (age ≤55 years) recruited with a 2:1 female-to-male enrollment design. We compared these genomes with those of 3761 population-based control subjects. We first identified individuals with a rare, monogenic mutation related to familial hypercholesterolemia. Second, we calculated a recently developed polygenic score of 6.6 million common DNA variants to quantify the cumulative susceptibility conferred by common variants. We defined high polygenic score as the top 5% of the control distribution because this cutoff has previously been shown to confer similar risk to that of familial hypercholesterolemia mutations.

resultsThe mean age of the 2081 patients presenting with early-onset myocardial infarction was 48 years, and 66% were female. A familial hypercholesterolemia mutation was present in 36 of these patients (1.7%) and was associated with a 3.8-fold (95% CI, 2.1-6.8; P<0.001) increased odds of myocardial infarction. Of the patients with early-onset myocardial infarction, 359 (17.3%) carried a high polygenic score, associated with a 3.7-fold (95% CI, 3.1-4.6; P<0.001) increased odds. Mean estimated untreated low-density lipoprotein cholesterol was 206 mg/dL in those with a familial hypercholesterolemia mutation, 132 mg/dL in those with high polygenic score, and 122 mg/dL in those in the remainder of the population. Although associated with increased risk in all racial groups, high polygenic score demonstrated the strongest association in white participants ( P for heterogeneity=0.008).

conclusionsBoth familial hypercholesterolemia mutations and high polygenic score are associated with a >3-fold increased odds of early-onset myocardial infarction. However, high polygenic score has a 10-fold higher prevalence among patients presents with early-onset myocardial infarction. CLINICAL

trial registrationURL: https://www.clinicaltrials.gov . Unique identifier: NCT00597922.

Indexed as

Genetic Predisposition to DiseaseGenome, HumanMultifactorial InheritanceAgedCholesterol, LDLFemaleHumansHyperlipoproteinemia Type IIMaleMiddle AgedMyocardial InfarctionWhole Genome SequencingCholesterol, LDLgeneticshumanshypercholesterolemiamyocardial infarctionrisk

Identifiers

PMID30586733
PMCPMC6433484

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Registered trials

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.