Evidence map›Paper›PMID 40061314›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Trans-ancestry Genome-Wide Analyses in UK Biobank Yield Novel Risk Loci for Major Depression.

Madhurbain Singh, Chris Chatzinakos, Peter B Barr, Amanda Elswick Gentry, Tim B Bigdeli, Bradley T Webb, Roseann E Peterson

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Madhurbain SinghVirginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.ORCID 0000-0002-9396-2860
Chris ChatzinakosInstitute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.ORCID 0000-0003-0557-9501
Peter B BarrInstitute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.ORCID 0000-0001-9321-657X
Amanda Elswick GentryVirginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.ORCID 0000-0002-6425-9340
Tim B BigdeliInstitute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.ORCID 0000-0003-2215-5946
Bradley T WebbGenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA.ORCID 0000-0002-0576-5366
Roseann E PetersonInstitute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.ORCID 0000-0001-6402-849X

Funding

Cross-Population Working Group on Genes and Environment in Major Depression (POP-GEM): Advancing the Understating of Etiology through DiversityR01MH125938 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI Roseann Elizabeth Peterson · 2022 to 2026
$4.2M
3/7-PsycheMERGE: Advancing Precision PsychiatryR01MH137208 · NIMH · SUNY DOWNSTATE MEDICAL CENTER · PI Roseann Elizabeth Peterson · 2024 to 2026
$2.9M
Characterizing the sex-specific genetic architecture of alcohol use disorders with comorbid major depressive disorderK01AA031748 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI GENTRY, AMANDA ELSWICK · 2024 to 2025
$164k
NIAAA NIH HHS K01 AA031748NIMH NIH HHS R01 MH125938NIMH NIH HHS R01 MH137208
6 · The paper itself

Abstract

Most genome-wide association studies (GWASs) of depression focus on broad, heterogeneous outcomes, limiting the discovery of genomic risk loci specific to major depressive disorder (MDD). Previous UK Biobank (UKB) studies had limited ability to pinpoint MDD-associated loci due to a smaller sample with strictly defined MDD outcomes and further exclusion of many participants based on ancestry or relatedness, significantly underutilizing this resource's potential for elucidating the genetic architecture of MDD. Here, we present novel genomic insights into MDD by fully utilizing existing UKB data through (1) a trans-ancestry GWAS pipeline using two complementary approaches controlling for population structure and relatedness and (2) an increased sample with MDD symptom-level data across two mental health assessments. We identified strict MDD outcomes among 211,535 participants, representing a 38% increase in eligible participants from prior studies with only one assessment. Ancestrally inclusive analyses yielded 61 genomic risk loci across depression phenotypes, compared to 47 in the analyses restricted to participants genetically similar to European ancestry. Fourteen of these loci, including five novel, were associated with strict MDD phenotypes, whereas only one locus has been previously reported in UKB. MDD-associated genomic loci and predicted gene expression levels showed little overlap with broad depression, indicating higher specificity. Notably, polygenic scores based on these results were significantly associated with depression diagnoses across ancestry groups in the

Identifiers

PMID40061314
PMCPMC11888526

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.