Evidence map›Paper›PMID 39763564›Full record

ArticlemedRxiv : the preprint server for health sciences2024

The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup.

Yu-Jyun Huang, Nuzulul Kurniansyah, Matthew O Goodman, Brian W Spitzer, Jiongming Wang, Adrienne Stilp, Cecelia Laurie, Paul S de Vries, Han Chen, Yuan-I Min and 23 more

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In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

33 authors.

Yu-Jyun HuangDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-7851-2722
Nuzulul KurniansyahDepartment of Medicine, Brigham and Women's Hospital, Boston, MA.
Matthew O GoodmanDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-3982-7940
Brian W SpitzerCardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA.
Jiongming WangDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Adrienne StilpDepartment of Biostatistics, University of Washington, Seattle, WA, USA.
Cecelia LaurieDepartment of Biostatistics, University of Washington, Seattle, WA, USA.
Paul S de VriesHuman Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Han ChenHuman Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.ORCID 0000-0002-9510-4923
Yuan-I MinDepartment of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
Mario SimsDepartment of Social Medicine, Population and Public Health, University of California at Riverside School of Medicine, Riverside, CA, USA.
Gina M PelosoDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Xiuqing GuoThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Joshua C BisCardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
Jennifer A BrodyCardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
Laura M RaffieldDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-7892-193X
Jennifer A SmithDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-3575-5468
Wei ZhaoDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Jerome I RotterThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Stephen S RichCenter for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA.
Susan RedlineDepartment of Medicine, Harvard Medical School, Boston, MA, USA.
Myriam FornageHuman Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.ORCID 0000-0003-0677-8158
Robert KaplanDivision of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Nora FranceschiniDepartment of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.
Daniel LevyThe Population Sciences Branch of the National Heart, Lung and Blood Institute, Bethesda, MD, USA.
Alanna C MorrisonHuman Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Eric BoerwinkleHuman Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Nicholas L SmithKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Charles KooperbergDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Bruce M PsatyCardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
Sebastian ZöllnerDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Trans-Omics in Precision Medicine Consortium
Tamar SoferDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-8520-8860

Funding

Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
Precision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5M
Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Adaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6M
University of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9M
California Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4M
All of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1M
New York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3M
SouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8M
Southern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5M
Illinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5M
The New England Precision Medicine Consortium of the All of Us Research ProgramOT2OD026553 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI CLARK, CHERYL RENEE, KARLSON, ELIZABETH W · 2018 to 2023
$58.8M
NHGRI NIH HHS R01 HG011031NHGRI NIH HHS R56 HG013163NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL139553NHLBI NIH HHS R01 HL142711NHLBI NIH HHS R01 HL154385NHLBI NIH HHS R01 HL161012NHLBI NIH HHS R01 HL163972NIA NIH HHS R01 AG080598NIDDK NIH HHS R01 DK117445NIH HHS OT2 OD023205NIH HHS OT2 OD023206NIH HHS OT2 OD025276NIH HHS OT2 OD025277NIH HHS OT2 OD025315NIH HHS OT2 OD025337NIH HHS OT2 OD026548NIH HHS OT2 OD026549NIH HHS OT2 OD026550NIH HHS OT2 OD026551NIH HHS OT2 OD026552NIH HHS OT2 OD026553NIH HHS OT2 OD026554NIH HHS OT2 OD026555NIH HHS OT2 OD026556NIH HHS OT2 OD026557NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196
6 · The paper itself

Abstract

Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup. We define a metric called "expected PRS" (ePRS), the expected value of a PRS based on one's global or local admixture patterns. We further define the "residual PRS" (rPRS), measuring the deviation of the PRS from the ePRS. Simulation studies confirm that it suffices to adjust for ePRS to obtain nearly unbiased estimates of the PRS-outcome association without further adjusting for PCs. Using the TOPMed dataset, the estimated effect size of the rPRS adjusting for the ePRS is similar to the estimated effect of the PRS adjusting for genetic PCs. Similarly, we applied the ePRS framework to six cardiovascular-related traits in the All of Us dataset, and the results are consistent with those from the TOPMed analysis. The ePRS framework can protect from population stratification in association analysis and provide an equitable strategy to quantify genetic risk across diverse populations.

Identifiers

PMID39763564
PMCPMC11702733

What Socratic holds

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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 Socratic graph.