Evidence map›Paper›PMID 37759039›Full record

ArticleMolecular psychiatry2023

Psychiatric disorders and brain white matter exhibit genetic overlap implicating developmental and neural cell biology.

Nadine Parker, Weiqiu Cheng, Guy F L Hindley, Pravesh Parekh, Alexey A Shadrin, Ivan I Maximov, Olav B Smeland, Srdjan Djurovic, Anders M Dale, Lars T Westlye and 2 more

Open access · greenAbstract read
In one paragraph

Article in Molecular psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
6.3field-weighted citation impact, top 3% 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

15 citing papers in PubMed, 20 citations in OpenAlex.

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  10. Cortical myelin mapping in antipsychotic medication-naïve, first-episode psychosis patients.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025
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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

12 authors at 3 institutions in 3 countries.

Nadine ParkerNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway. nadine.parker@medisin.uio.no.ORCID 0000-0002-8369-0152
Weiqiu ChengNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Guy F L HindleyNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0003-1666-4701
Pravesh ParekhNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0002-1930-1167
Alexey A ShadrinNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Ivan I MaximovDepartment of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.ORCID 0000-0001-6319-6774
Olav B SmelandNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0002-3761-5215
Srdjan DjurovicDepartment of Medical Genetics, Oslo University Hospital, Oslo, Norway.ORCID 0000-0002-8140-8061
Anders M DaleMultimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-6126-2966
Lars T WestlyeNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0001-8644-956X
Oleksandr FreiNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID 0000-0002-6427-2625
Ole A AndreassenNORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway. ole.andreassen@medisin.uio.no.ORCID 0000-0002-4461-3568
Oslo University Hospital · NOUniversity of California San Diego · USWestern Norway University of Applied Sciences · NO

Funding

ABCD-USA Consortium: Data Analysis, Informatics and Resource CenterU24DA041123 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE · 2015 to 2026
$51.5M
Healthy Brain and Child Development National Consortium Data Coordinating CenterU24DA055330 · NIDA · WASHINGTON UNIVERSITY · PI ANDERS M DALE, Damien A Fair · 2021 to 2026
$34.6M
The VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)R01AG076838 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE, Jeremy A Elman · 2022 to 2026
$8.7M
EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions) 801133EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 847776EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 964874NIA NIH HHS R01 AG076838NIDA NIH HHS U24 DA041123NIDA NIH HHS U24 DA055330Norges Forskningsråd (Research Council of Norway) 300309
6 · The paper itself

Abstract

Improved understanding of the shared genetic architecture between psychiatric disorders and brain white matter may provide mechanistic insights for observed phenotypic associations. Our objective is to characterize the shared genetic architecture of bipolar disorder (BD), major depression (MD), and schizophrenia (SZ) with white matter fractional anisotropy (FA) and identify shared genetic loci to uncover biological underpinnings. We used genome-wide association study (GWAS) summary statistics for BD (n = 413,466), MD (n = 420,359), SZ (n = 320,404), and white matter FA (n = 33,292) to uncover the genetic architecture (i.e., polygenicity and discoverability) of each phenotype and their genetic overlap (i.e., genetic correlations, overlapping trait-influencing variants, and shared loci). This revealed that BD, MD, and SZ are at least 7-times more polygenic and less genetically discoverable than average FA. Even in the presence of weak genetic correlations (range = -0.05 to -0.09), average FA shared an estimated 42.5%, 43.0%, and 90.7% of trait-influencing variants as well as 12, 4, and 28 shared loci with BD, MD, and SZ, respectively. Shared variants were mapped to genes and tested for enrichment among gene-sets which implicated neurodevelopmental expression, neural cell types, myelin, and cell adhesion molecules. For BD and SZ, case vs control tract-level differences in FA associated with genetic correlations between those same tracts and the respective disorder (r

Indexed as

Bipolar DisorderMajor Depressive DisorderWhite MatterDiffusion Tensor ImagingGenome-Wide Association StudyHumans

Identifiers

PMID37759039
PMCPMC11771104
OpenAlexW4387106001

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.