Evidence map›Paper›PMID 32068817›Full record

ArticleJAMA2020

Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease.

Jonathan D Mosley, Deepak K Gupta, Jingyi Tan, Jie Yao, Quinn S Wells, Christian M Shaffer, Suman Kundu, Cassianne Robinson-Cohen, Bruce M Psaty, Stephen S Rich and 6 more

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in JAMA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
174citing papers in PubMed, 4 pooled it
47.3field-weighted citation impact, top 1% of its field
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

174 citing papers in PubMed, 4 syntheses or guidelines pooled it, 350 citations in OpenAlex.

  1. Pooled it
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  10. Age-Specific Associations of Polygenic Risk Scores With Advanced Fibrosis and Histological Activity in Biopsy-Proven MASLD.Liver international : official journal of the International Association for the Study of the Liver · 2026
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114 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 9 institutions in 1 country.

Jonathan D MosleyDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Deepak K GuptaDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Jingyi TanLos Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Department of Pediatrics, Torrance, California.
Jie YaoLos Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Department of Pediatrics, Torrance, California.
Quinn S WellsDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Christian M ShafferDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Suman KunduDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Cassianne Robinson-CohenDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Bruce M PsatyDepartments of Medicine, Epidemiology and Health Services, University of Washington School of Public Health; and Kaiser Permanente Washington Health Research Institute, Seattle, Washington.
Stephen S RichDepartment of Public Health Sciences, Center for Public Health Genomics, Charlottesville, Virginia.
Wendy S PostDepartment of Medicine, Johns Hopkins University, Baltimore, Maryland.
Xiuqing GuoLos Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Department of Pediatrics, Torrance, California.
Jerome I RotterLos Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Department of Pediatrics, Torrance, California.
Dan M RodenDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Robert E GersztenBeth Israel Deaconess Medical Center, Division of Cardiovascular Medicine, Boston, Massachusetts.
Thomas J WangDepartment of Internal Medicine, University of Texas Southwestern Medical Center.
Vanderbilt University Medical Center · USHarbor–UCLA Medical Center · USUCLA Medical Center · USBeth Israel Deaconess Medical Center · USJohns Hopkins Medicine · USKaiser Permanente Washington Health Research Institute · USOffice of Public Health Genomics · USThe University of Texas Southwestern Medical Center · USVanderbilt University · US

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MILES Frome WILKINSON · 2003 to 2026
$40.4M
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
Proteomic Pathway Discovery in Cardiovascular DiseaseR01HL132320 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GERSZTEN, ROBERT E, RAMACHANDRAN, VASAN S · 2016 to 2019
$3.4M
Virtual metabolomics as a discovery tool for novel cardiometabolic disease biologyR01HL142856 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI FERGUSON, JANE F, MOSLEY, JONATHAN DAVID · 2019 to 2023
$2.7M
GWA for Gene-Environment Interaction Effects Influencing CHDU01HG004402 · NHGRI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A. · 2007 to 2009
$1.6M
The natriuretic peptide system in African-AmericansK23HL128928 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GUPTA, DEEPAK · 2016 to 2019
$737k
American Heart Association-American Stroke Association 16FTF30130005NHGRI NIH HHS U01 HG004402NHLBI NIH HHS K23 HL128928NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL132320NHLBI NIH HHS R01 HL142856NIDDK NIH HHS P30 DK063491
6 · The paper itself

Abstract

Importance: Polygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening. Objective: To determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation. Design, Setting, and Participants: A retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations. Exposures: Genetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study. Main Outcomes and Measures: Prediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI). Results: The study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, -0.001; 95% CI, -0.009 to 0.006; MESA, 0.021; 95% CI, -0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, -0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, -0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort. Conclusions and Relevance: In this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population.

Indexed as

Genetic Predisposition to DiseaseMultifactorial InheritanceAgedCohort StudiesCoronary DiseaseFemaleGenome-Wide Association StudyGenotypeHumansIncidenceMaleMiddle AgedMyocardial InfarctionOdds RatioPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID32068817
PMCPMC7042849
OpenAlexW3008788084

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.