Evidence map›Paper›PMID 32709988›Full record

ReviewNature protocols2020

Tutorial: a guide to performing polygenic risk score analyses.

Shing Wan Choi, Timothy Shin-Heng Mak, Paul F O'Reilly

Open access · greenAbstract readReview
In one paragraph

Review in Nature protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,165 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,165citing papers in PubMed, 5 pooled it
187.5field-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

1,165 citing papers in PubMed, 5 syntheses or guidelines pooled it, 1,959 citations in OpenAlex.

  1. Pooled it
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  5. Pooled it
  6. Platelet count polygenic scores may modify the effect of aspirin in primary prevention of dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Trial
  7. Trial
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  13. Using Polygenic Risk Scores to Refine Risk and Outcomes in High-grade Serous Ovarian Cancer in Australia.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
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  16. Review
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  18. Genetic architectures of brain-related traits are shaped by strong selective constraints.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  19. Article
  20. Article

1,105 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

3 authors at 3 institutions in 3 countries.

Shing Wan ChoiMRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Timothy Shin-Heng MakCentre of Genomic Sciences, University of Hong Kong, Hong Kong, China.ORCID http://orcid.org/0000-0002-2151-2406
Paul F O'ReillyMRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. paul.oreilly@mssm.edu.
Chinese University of Hong Kong · HKIcahn School of Medicine at Mount Sinai · USKing's College London · GB

Funding

Department of HealthMedical Research Council MR/N015746/1
6 · The paper itself

Abstract

A polygenic score (PGS) or polygenic risk score (PRS) is an estimate of an individual's genetic liability to a trait or disease, calculated according to their genotype profile and relevant genome-wide association study (GWAS) data. While present PRSs typically explain only a small fraction of trait variance, their correlation with the single largest contributor to phenotypic variation-genetic liability-has led to the routine application of PRSs across biomedical research. Among a range of applications, PRSs are exploited to assess shared etiology between phenotypes, to evaluate the clinical utility of genetic data for complex disease and as part of experimental studies in which, for example, experiments are performed that compare outcomes (e.g., gene expression and cellular response to treatment) between individuals with low and high PRS values. As GWAS sample sizes increase and PRSs become more powerful, PRSs are set to play a key role in research and stratified medicine. However, despite the importance and growing application of PRSs, there are limited guidelines for performing PRS analyses, which can lead to inconsistency between studies and misinterpretation of results. Here, we provide detailed guidelines for performing and interpreting PRS analyses. We outline standard quality control steps, discuss different methods for the calculation of PRSs, provide an introductory online tutorial, highlight common misconceptions relating to PRS results, offer recommendations for best practice and discuss future challenges.

Indexed as

Practice Guidelines as TopicGenetic Predisposition to DiseaseHumansQuality ControlRisk Assessment

Identifiers

PMID32709988
PMCPMC7612115
OpenAlexW3045441625

What OpenQuestion holds

Textmetadata
LicenceTDM
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.