Evidence map›Paper›PMID 34347061›Full record

ArticleJAMA network open2021

Generalizability of Polygenic Risk Scores for Breast Cancer Among Women With European, African, and Latinx Ancestry.

Cong Liu, Nur Zeinomar, Wendy K Chung, Krzysztof Kiryluk, Ali G Gharavi, George Hripcsak, Katherine D Crew, Ning Shang, Atlas Khan, David Fasel and 14 more

Abstract readMulticenter Study
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 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

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Breast cancer polygenic risk score performance varies by socioeconomic status.medRxiv : the preprint server for health sciences · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Within-family analysis of PRSJournal, genetic engineering & biotechnology · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

Cong LiuDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York.
Nur ZeinomarDepartment of Epidemiology, Columbia University Irving Medical Center, New York, New York.
Wendy K ChungDepartment of Pediatrics, Columbia University Irving Medical Center, New York, New York.
Krzysztof KirylukDepartment of Medicine, Columbia University Irving Medical Center, New York, New York.
Ali G GharaviDepartment of Medicine, Columbia University Irving Medical Center, New York, New York.
George HripcsakDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York.
Katherine D CrewDepartment of Medicine, Columbia University Irving Medical Center, New York, New York.
Ning ShangDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York.
Atlas KhanDepartment of Medicine, Columbia University Irving Medical Center, New York, New York.
David FaselDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York.
Teri A ManolioNational Human Genome Research Institute, Bethesda, Maryland.
Gail P JarvikDepartment of Medicine, University of Washington, Seattle.
Robb RowleyNational Human Genome Research Institute, Bethesda, Maryland.
Ann E JusticeDepartment of Population Health Sciences, Geisinger, Danville, Pennsylvania.
Alanna K RahmGenomic Medicine Institute, Geisinger, Danville, Pennsylvania.
Stephanie M FullertonDepartment of Bioethics and Humanities, University of Washington, Seattle.
Jordan W SmollerPsychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
Eric B LarsonKaiser Permanente Washington Health Research Institute, Seattle, Washington.
Paul K CraneDepartment of Medicine, University of Washington, Seattle.
Ozan DikilitasDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
Georgia L WiesnerDepartment of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Alexander G BickDepartment of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Mary Beth TerryDepartment of Epidemiology, Columbia University Irving Medical Center, New York, New York.
Chunhua WengDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Importance: Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. Objective: To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. Design, Setting, and Participants: This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. Main Outcomes and Measures: Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. Results: This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. Conclusions and Relevance: This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.

Indexed as

AlgorithmsBlack PeopleBreast NeoplasmsElectronic Health RecordsFemaleGene FrequencyGenetic Predisposition to DiseaseGenomicsHispanic or LatinoHumansInformation Storage and RetrievalLinkage DisequilibriumLogistic ModelsMiddle AgedOdds RatioPhenotype

Identifiers

PMID34347061
PMCPMC8339934

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Registered trials

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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.