Evidence map›Paper›PMID 34598685›Full record

ReviewBMC medical genomics2021

Design and user experience testing of a polygenic score report: a qualitative study of prospective users.

Deanna G Brockman, Lia Petronio, Jacqueline S Dron, Bum Chul Kwon, Trish Vosburg, Lisa Nip, Andrew Tang, Mary O'Reilly, Niall Lennon, Bang Wong and 4 more

Registry-linked trialAbstract readReview
In one paragraph

Review in BMC medical genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07039123 (Polygenic Risk Score to Optimize Primary Prevention in Intermediate Risk Population), which is not on this map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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.

NCT07039123 naactive not recruitingnot on this mapstarted 2025, after this paper: background citation

Polygenic Risk Score to Optimize Primary Prevention in Intermediate Risk Population (PERSONAL)

TypeinterventionalSponsorUniversity of BernRan2025 to 2027Enrolled205ConditionsPrimary Prevention of Cardiovascular DiseaseArmsPolygenic Risk Score for Coronary Artery Disease (PRS-CAD), Standardized Risk Communication Tool (SCORE2)
3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. Trial
  2. Educational considerations based on medical student use of polygenic risk information and apparent race in a simulated consultation.Genetics in medicine : official journal of the American College of Medical Genetics · 2022
    Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Polygenic Risk Scores in Human Disease.Clinical chemistry · 2025
    Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

14 authors.

Deanna G Brockman *Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Simches Research Building | CPZN 6.256, Boston, MA, 02114, USA.
Lia Petronio *Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Jacqueline S DronProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Bum Chul KwonCenter for Computational Health, IBM Research, Cambridge, MA, USA.
Trish VosburgProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Lisa NipPattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Andrew TangPattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Mary O'ReillyPattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Niall LennonGenomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Bang WongPattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Kenney NgCenter for Computational Health, IBM Research, Cambridge, MA, USA.
Katherine H HuangPattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Akl C FahedCenter for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Simches Research Building | CPZN 6.256, Boston, MA, 02114, USA.
Amit V KheraCenter for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Simches Research Building | CPZN 6.256, Boston, MA, 02114, USA. avkhera@broadinstitute.org.ORCID 0000-0001-6535-5839

Funding

Enabling improved applicability and transferability of polygenic scores across populationsU01HG011719 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI Alicia Martin · 2021 to 2026
$5.5M
Polygenic prediction of common, complex diseasesK08HG010155 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI KHERA, AMIT VIKRAM · 2018 to 2021
$1.1M
NHGRI NIH HHS 1K08HG010155NHGRI NIH HHS 1U01HG011719NHGRI NIH HHS K08 HG010155
6 · The paper itself

Abstract

backgroundPolygenic scores-which quantify inherited risk by integrating information from many common sites of DNA variation-may enable a tailored approach to clinical medicine. However, alongside considerable enthusiasm, we and others have highlighted a lack of standardized approaches for score disclosure. Here, we review the landscape of polygenic score reporting and describe a generalizable approach for development of a polygenic score disclosure tool for coronary artery disease.

methodsWe assembled a working group of clinicians, geneticists, data visualization specialists, and software developers. The group reviewed existing polygenic score reports and then designed a two-page mock report for coronary artery disease. We then conducted a qualitative user-experience study with this report using an interview guide focused on comprehension, experience, and attitudes. Interviews were transcribed and analyzed for themes identification to inform report revision.

resultsReview of nine existing polygenic score reports from commercial and academic groups demonstrated significant heterogeneity, reinforcing the need for additional efforts to study and standardize score disclosure. Using a newly developed mock score report, we conducted interviews with ten adult individuals (50% females, 70% without prior genetic testing experience, age range 20-70 years) recruited via an online platform. We identified three themes from interviews: (1) visual elements, such as color and simple graphics, enable participants to interpret, relate to, and contextualize their polygenic score, (2) word-based descriptions of risk and polygenic scores presented as percentiles were the best recognized and understood, (3) participants had varying levels of interest in understanding complex genomic information and therefore would benefit from additional resources that can adapt to their individual needs in real time. In response to user feedback, colors used for communicating risk were modified to minimize unintended color associations and odds ratios were removed. All 10 participants expressed interest in receiving a polygenic score report based on their personal genomic information.

conclusionsOur findings describe a generalizable approach to develop a polygenic score report understandable by potential patients. Although additional studies are needed across a wider spectrum of patient populations, these results are likely to inform ongoing efforts related to polygenic score disclosure within clinical practice.

Indexed as

Multifactorial InheritanceAdultAgedCoronary Artery DiseaseDNAFemaleHumansMaleMiddle AgedProspective StudiesQualitative ResearchYoung AdultDNAData visualizationGenomic medicineHealth communicationLaboratory reportsPatient communicationPolygenic scoresPopulation health

Identifiers

PMID34598685
PMCPMC8485114

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.