Evidence map›Paper›PMID 37749244›Full record

ArticleNature genetics2023

A new method for multiancestry polygenic prediction improves performance across diverse populations.

Haoyu Zhang, Jianan Zhan, Jin Jin, Jingning Zhang, Wenxuan Lu, Ruzhang Zhao, Thomas U Ahearn, Zhi Yu, Jared O'Connell, Yunxuan Jiang and 7 more

Open access · greenAbstract read
In one paragraph

Article in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 1 pooled it
27.6field-weighted citation impact, top 1% of its field
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

71 citing papers in PubMed, 1 synthesis or guideline pooled it, 88 citations in OpenAlex.

  1. Pooled it
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  20. Genetic regulation of fatty acid content in adipose tissue.American journal of human genetics · 2026
    Article

11 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

17 authors at 7 institutions in 2 countries.

Haoyu ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. haoyu.zhang2@nih.gov.ORCID http://orcid.org/0000-0001-6423-0444
Jianan Zhan23andMe, Inc., Sunnyvale, CA, USA.
Jin JinDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Jingning ZhangDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID http://orcid.org/0000-0003-4698-0676
Wenxuan LuDepartment of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA.
Ruzhang ZhaoDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Thomas U AhearnDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.ORCID http://orcid.org/0000-0003-0771-7752
Zhi YuProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-4810-3474
Jared O'Connell23andMe, Inc., Sunnyvale, CA, USA.
Yunxuan Jiang23andMe, Inc., Sunnyvale, CA, USA.
Tony ChenDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID http://orcid.org/0000-0002-3269-7629
Dayne OkuharaBooz Allen Hamilton Inc., McLean, VA, USA.
23andMe Research Team
Montserrat Garcia-ClosasDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.ORCID http://orcid.org/0000-0003-1033-2650
Xihong LinDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID http://orcid.org/0000-0001-7067-7752
Bertram L Koelsch23andMe, Inc., Sunnyvale, CA, USA.
Nilanjan ChatterjeeDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. nilanjan@jhu.edu.ORCID http://orcid.org/0000-0002-9060-008X
23andMe (United States) · USJohns Hopkins University · USBroad Institute · USHarvard University · USBooz Allen Hamilton (United States) · USInstitute of Cancer Research · GBNational Cancer Institute · US

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
NCI NIH HHS K99 CA256513NCI NIH HHS R35 CA197449NCI NIH HHS U01 CA249866NCI NIH HHS U19 CA203654NHGRI NIH HHS K99 HG012956NHGRI NIH HHS R00 HG012223NHGRI NIH HHS R01 HG010480NHGRI NIH HHS U01 HG009088NHGRI NIH HHS U01 HG012064NHLBI NIH HHS R01 HL163560NHLBI NIH HHS T32 HL007604NIGMS NIH HHS T32 GM135117NIH 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) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning. We evaluated CT-SLEB and nine alternative methods with large-scale simulated genome-wide association studies (~19 million common variants) and datasets from 23andMe, Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank, involving 5.1 million individuals of diverse ancestry, with 1.18 million individuals from four non-European populations across 13 complex traits. Results demonstrated that CT-SLEB significantly improves PRS performance in non-European populations compared with simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offered insights into sample size requirements and SNP density effects on multiancestry risk prediction.

Indexed as

Multifactorial InheritancePopulation HealthBayes TheoremGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideRisk Factors

Identifiers

PMID37749244
PMCPMC10923245
OpenAlexW4387012794

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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.