Evidence map›Paper›PMID 35576555›Full record

ReviewAnnual review of biomedical data science2022

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores.

Ying Wang, Kristin Tsuo, Masahiro Kanai, Benjamin M Neale, Alicia R Martin

Abstract readReview
In one paragraph

Review in Annual review of biomedical data science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 3 pooled it
–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

120 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Primary care physician use of patient race and polygenic risk scores in medical decision-making.Genetics in medicine : official journal of the American College of Medical Genetics · 2023
    Trial
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Cross-ancestry polygenic risk scores enhance Alzheimer's disease risk prediction in multiethnic cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  12. Article
  13. Genetic analysis of imaging-derived phenotypes.Nature reviews. Genetics · 2026
    Review
  14. Review
  15. Linking the exposome to the brain-behaviour phenotype.Nature reviews. Neuroscience · 2026
    Review
  16. Polygenic risk scores in clinical applications - opportunities and challenges.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
    Article
  17. Article
  18. Breast cancer polygenic risk score performance varies by socioeconomic status.medRxiv : the preprint server for health sciences · 2026
    Article
  19. Article
  20. Review

60 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

5 authors.

Ying WangAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; email: armartin@broadinstitute.org.
Kristin TsuoAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; email: armartin@broadinstitute.org.
Masahiro KanaiAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; email: armartin@broadinstitute.org.
Benjamin M NealeAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; email: armartin@broadinstitute.org.
Alicia R MartinAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; email: armartin@broadinstitute.org.

Funding

Generalizing polygenic risk prediction methods across populations for insights into psychiatric diseaseR00MH117229 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN, ALICIA · 2020 to 2022
$724k
Generalizing polygenic risk prediction methods across populations for insights into psychiatric diseaseK99MH117229 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN, ALICIA · 2018 to 2019
$262k
NIMH NIH HHS K99 MH117229NIMH NIH HHS R00 MH117229
6 · The paper itself

Abstract

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyBiomarkersHumansMultifactorial InheritanceRisk FactorsBiomarkersclinical translation of PRSdiverse ancestry populationsgenetic risk predictionpolygenic risk scores (PRS)PRS generalizability

Identifiers

PMID35576555
PMCPMC9828290

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.