Evidence map›Paper›PMID 39315597›Full record

ArticleGenetic epidemiology2025

Comparing Ancestry Standardization Approaches for a Transancestry Colorectal Cancer Polygenic Risk Score.

Elisabeth A Rosenthal, Li Hsu, Minta Thomas, Ulrike Peters, Christopher Kachulis, Karynne Patterson, Gail P Jarvik

Abstract readComparative Study
In one paragraph

Article in Genetic epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

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

4 citing papers in PubMed.

  1. Non-Parametric Ancestry Adjustment for Polygenic Scores.medRxiv : the preprint server for health sciences · 2026
    Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Elisabeth A RosenthalDivision Medical Genetics, School of Medicine, University of Washington, Seattle, Washington, USA.ORCID http://orcid.org/0000-0001-6042-4487
Li HsuPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.ORCID http://orcid.org/0000-0001-8168-4712
Minta ThomasPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Ulrike PetersPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Christopher KachulisBroad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
Karynne PattersonDepartment of Genome Sciences, University of Washington, Seattle, Washington, USA.
Gail P JarvikDivision Medical Genetics, School of Medicine, University of Washington, Seattle, Washington, USA.

Funding

Northwest Genomics Center for All of UsOT2OD002748 · OD · UNIVERSITY OF WASHINGTON · PI EICHLER, EVAN, JARVIK, GAIL PAIRITZ · 2018 to 2023
$65.4M
Variation, Function, and Disease Supplement ProgramU01HG008657 · NHGRI · UNIVERSITY OF WASHINGTON · PI David Russell Crosslin, Gail Pairitz Jarvik · 2015 to 2026
$13.4M
NHGRI NIH HHS U01 HG008657NIH HHS OT2 OD002748This work was funded by the Office of the Director at the National Institute of Health, under award notice 1OT2OD002748-01 and by the NHGRI through the grant U01HG008657.
6 · The paper itself

Abstract

Colorectal cancer (CRC) is a complex disease with monogenic, polygenic and environmental risk factors. Polygenic risk scores (PRSs) aim to identify high polygenic risk individuals. Due to differences in genetic background, PRS distributions vary by ancestry, necessitating standardization. We compared four post-hoc methods using the All of Us Research Program Whole Genome Sequence data for a transancestry CRC PRS. We contrasted results from linear models trained on A. the entire data or an ancestrally diverse subset AND B. covariates including principal components of ancestry or admixture. Standardization with the training subset also adjusted the variance. All methods performed similarly within ancestry, OR (95% C.I.) per s.d. change in PRS: African 1.5 (1.02, 2.08), Admixed American 2.2 (1.27, 3.85), European 1.6 (1.43, 1.89), and Middle Eastern 1.1 (0.71, 1.63). Using admixture and an ancestrally diverse training set provided distributions closest to standard Normal. Training a model on ancestrally diverse participants, adjusting both the mean and variance using admixture as covariates, created standard Normal z-scores, which can be used to identify patients at high polygenic risk. These scores can be incorporated into comprehensive risk calculation including other known risk factors, allowing for more precise risk estimates.

Indexed as

Colorectal NeoplasmsGenetic Risk ScoreEthnicityFemaleGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single NucleotideRacial Groupsadmixtureall of uscolorectal cancerpolygenic risk scoretransancestry

Identifiers

PMID39315597
PMCPMC12331137

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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.