Evidence map›Paper›PMID 40355674›Full record

ReviewNature human behaviour2025

Psychological and behavioural considerations for integrating polygenic risk scores for disease into clinical practice.

Saskia C Sanderson, Michael Inouye

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature human behaviour, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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.

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

9 citing papers in PubMed.

  1. Article
  2. Polygenic risk scores in clinical applications - opportunities and challenges.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
    Article
  3. Review
  4. Article
  5. Interaction of identity and beliefs with genetic literacy.American journal of human genetics · 2026
    Article
  6. Review
  7. Review
  8. Article
  9. 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

2 authors.

Saskia C SandersonDepartment of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. saskia.sanderson@kcl.ac.uk.ORCID http://orcid.org/0000-0001-8427-724X
Michael InouyeCambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-9413-6520

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A polygenic risk score (PRS) summarizes in one number an individual's estimated genetic association with a specific trait or disease based on the common DNA variants included in the score. Disease PRSs have the potential to positively affect population health by improving disease risk prediction, thereby also potentially improving disease prevention, early intervention and treatment. However, given the potential psychological, behavioural and other harms, there are also concerns about integrating PRSs into clinical tools and healthcare systems. Here we assess five arguments against implementing PRSs for physical disease in clinical practice that revolve around psychological and behavioural considerations. For each argument, we consider a counterargument, the evidence and underlying theory, any gaps in the evidence base and possible future directions and research priorities. We conclude that, although there may be other barriers to implementation, there is currently little evidence of psychological or behavioural harms from integrating PRSs into practice.

Indexed as

Genetic Predisposition to DiseaseMultifactorial InheritanceGenetic Risk ScoreHumansRisk AssessmentRisk Factors

Identifiers

PMID40355674

What OpenQuestion holds

Textmetadata
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.