Evidence map›Paper›PMID 42060716›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Quantifying direct genetic signal captured by principal component adjustment.

Ramina Sotoudeh, Sam Trejo, Arbel Harpak, Dalton Conley

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Ramina SotoudehDepartment of Sociology, Yale University, New Haven, CT 06511.ORCID 0000-0002-1716-017X
Sam TrejoDepartment of Sociology, Princeton University, Princeton, NJ 08544.ORCID 0000-0002-9880-5354
Arbel HarpakDepartment of Population Health, Dell Medical School, University of Texas at Austin, Austin, TX 78712.ORCID 0000-0002-3655-748X
Dalton ConleyDepartment of Sociology, Princeton University, Princeton, NJ 08544.ORCID 0000-0002-5174-7222

Funding

Making Genomic Prediction of Complex Disease EquitableR35GM151108 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Arbel Harpak · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM151108
6 · The paper itself

Abstract

Contemporary genomic studies of complex traits, such as genome-wide association studies and polygenic index (PGI) analyses, frequently include the principal components of the genotype matrix (PCs) among their adjustments for population stratification. In this paper, we explore the extent to which we may be discounting direct genetic effects by adjusting for PCs. Using family-based models that control for parental genotype in the UK Biobank, we find that PCs capture direct genetic effects on all nine phenotypes we tested. These effects are generally small, and extremely similar to the population effects of the same PCs. This suggests that PC adjustment indeed diminishes, albeit very slightly, signals of direct genetic effects. Furthermore, we find that adjusting for PCs does not meaningfully alter estimates of the effect of the current PGIs within families. Our findings suggest that, for the phenotypes and populations studied here, direct genetic effects captured by PCs are modest, and adjusting for PCs does not seem to lead to meaningful attenuation in PGI estimates.

Indexed as

Genome-Wide Association StudyModels, GeneticMultifactorial InheritancePrincipal Component AnalysisGenetic Risk ScoreGenotypeHumansPhenotypePolymorphism, Single Nucleotidepolygenic indicespolygenic scorespopulation stratificationpopulation structuresociogenomics

Identifiers

PMID42060716
PMCPMC13142912

What OpenQuestion holds

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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.