Evidence map›Paper›PMID 38551411›Full record

ArticleEuropean heart journal2024

Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease.

Ling Li, Shichao Pang, Fabian Starnecker, Bertram Mueller-Myhsok, Heribert Schunkert

Open access · hybridAbstract read
In one paragraph

Article in European heart journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
27.0field-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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Pooled it
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  9. Clinical utility of polygenic risk scores in cardiovascular disorders.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
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  17. A practical guide to the management of dyslipidaemia.Clinical research in cardiology : official journal of the German Cardiac Society · 2026
    Review
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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

5 authors at 3 institutions in 2 countries.

Ling LiDepartment of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, Munich 80636, Germany.ORCID 0000-0002-3280-9475
Shichao PangDepartment of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, Munich 80636, Germany.ORCID 0000-0002-4111-2864
Fabian StarneckerDepartment of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, Munich 80636, Germany.ORCID 0000-0001-9850-4239
Bertram Mueller-MyhsokStatistical Genetics, Max Planck Institute of Psychiatry, Munich, Germany.ORCID 0000-0002-0719-101X
Heribert SchunkertDepartment of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Lazarettstr. 36, Munich 80636, Germany.ORCID 0000-0001-6428-3001
German Centre for Cardiovascular Research · DEDeutsches Herzzentrum München · DEUniversity of Liverpool · GB

Funding

and Care DMB-1805-0001and Energy ZF4590201BA8Bavarian State Ministry of HealthBHFDFGEuropean CommissionGerman Centre of Cardiovascular Research 81X2600522German Federal Ministry of EconomicsGerman Federal Ministry of Education and Research 01KL1802German Research FoundationLeducq Foundation for Cardiovascular Research 18CVD02MultiomIcs based Risk stratification of Atherosclerotic CardiovascuLar 101115381Sonderforschungsbereich 1123Sonderforschungsbereich 403584255
6 · The paper itself

Abstract

BACKGROUND AND

aimsIt is not clear how a polygenic risk score (PRS) can be best combined with guideline-recommended tools for cardiovascular disease (CVD) risk prediction, e.g. SCORE2.

methodsA PRS for coronary artery disease (CAD) was calculated in participants of UK Biobank (n = 432 981). Within each tenth of the PRS distribution, the odds ratios (ORs)-referred to as PRS-factor-for CVD (i.e. CAD or stroke) were compared between the entire population and subgroups representing the spectrum of clinical risk. Replication was performed in the combined Framingham/Atherosclerosis Risk in Communities (ARIC) populations (n = 10 757). The clinical suitability of a multiplicative model 'SCORE2 × PRS-factor' was tested by risk reclassification.

resultsIn subgroups with highly different clinical risks, CVD ORs were stable within each PRS tenth. SCORE2 and PRS showed no significant interactive effects on CVD risk, which qualified them as multiplicative factors: SCORE2 × PRS-factor = total risk. In UK Biobank, the multiplicative model moved 9.55% of the intermediate (n = 145 337) to high-risk group increasing the individuals in this category by 56.6%. Incident CVD occurred in 8.08% of individuals reclassified by the PRS-factor from intermediate to high risk, which was about two-fold of those remained at intermediate risk (4.08%). Likewise, the PRS-factor shifted 8.29% of individuals from moderate to high risk in Framingham/ARIC.

conclusionsThis study demonstrates that absolute CVD risk, determined by a clinical risk score, and relative genetic risk, determined by a PRS, provide independent information. The two components may form a simple multiplicative model improving precision of guideline-recommended tools in predicting incident CVD.

Indexed as

Cardiovascular DiseasesPractice Guidelines as TopicAdultAgedCoronary Artery DiseaseFemaleGenetic Predisposition to DiseaseHumansMaleMiddle AgedMultifactorial InheritanceRisk AssessmentRisk FactorsUnited KingdomCardiovascular diseasePolygenic risk scorePrevention guidelinesPrimary preventionRisk predictionSCORE2

Identifiers

PMID38551411
PMCPMC11129792
OpenAlexW4393318145

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.