Evidence map›Paper›PMID 34399584›Full record

ReviewStroke2021

Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases.

Gad Abraham, Loes Rutten-Jacobs, Michael Inouye

Open access · bronzeAbstract readReview
In one paragraph

Review in Stroke, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
9.4field-weighted citation impact, top 2% 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

38 citing papers in PubMed, 71 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Stroke prevention in the Americas: from knowing to doing.Lancet regional health. Americas · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Genetic Determinants of Left Atrial Function Are Associated With Stroke.Journal of the American Heart Association · 2024
    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

3 authors at 2 institutions in 4 countries.

Gad AbrahamCambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (G.A., M.I.).
Loes Rutten-JacobsPersonalized Health Care Data Science, Real World Data, F. Hoffmann-La Roche Ltd, Basel, Switzerland (L.R.-J.).
Michael InouyeCambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (G.A., M.I.).
Baker Heart and Diabetes Institute · AURoche (Switzerland) · CH

Funding

British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946Chief Scientist OfficeMedical Research Council MR/L003120/1
6 · The paper itself

Abstract

Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of disease prevention. Clinical risk scores have been widely used for predicting CVD risk from known risk factors. Most CVDs have a substantial genetic component, which also has been confirmed for stroke in recent gene discovery efforts. However, the role of genetics in prediction of risk of CVD, including stroke, has been limited to testing for highly penetrant monogenic disorders. In contrast, the importance of polygenic variation, the aggregated effect of many common genetic variants across the genome with individually small effects, has become more apparent in the last 5 to 10 years, and powerful polygenic risk scores for CVD have been developed. Here we review the current state of the field of polygenic risk scores for CVD including stroke, and their potential to improve CVD risk prediction. We present findings and lessons from diseases such as coronary artery disease as these will likely be useful to inform future research in stroke polygenic risk prediction.

Indexed as

Cardiovascular DiseasesCoronary Artery DiseaseGenetic Predisposition to DiseaseHumansMultifactorial InheritanceRisk FactorsStrokecardiovascular diseasegeneticsmyocardial infarctionrisk assessmentstroke

Identifiers

PMID34399584
PMCPMC7611731
OpenAlexW3196033227

What OpenQuestion holds

Textmetadata
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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.