Evidence map›Paper›PMID 42509310›Full record

ArticleCommunications medicine2026

Mapping genetic convergence across brain structure, mental health, and cardiometabolic disease.

Jakub Kopal, Alexey A Shadrin, Dennis van der Meer, Olav B Smeland, Sara E Stinson, Linn Rødevand, Nadine Parker, Kevin S O'Connell, Oleksandr Frei, Srdjan Djurovic and 2 more

Abstract read
In one paragraph

Article in Communications medicine, 2026. 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

5 · Who and what money

Authors and funding

12 authors.

Jakub KopalCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID http://orcid.org/0000-0002-1201-2872
Alexey A ShadrinCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Dennis van der MeerCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Olav B SmelandCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID http://orcid.org/0000-0002-3761-5215
Sara E StinsonCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Linn RødevandCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Nadine ParkerCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Kevin S O'ConnellCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Oleksandr FreiCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.ORCID http://orcid.org/0000-0002-6427-2625
Srdjan DjurovicCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Anders M DaleDepartment of Radiology, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Ole A AndreassenCentre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway. ole.andreassen@medisin.uio.no.ORCID http://orcid.org/0000-0002-4461-3568

Funding

OTA-21-015A Post-Acute Sequelae of SARS-CoV-2 Infection Initiative: NYU Langone Health Clinical Science Core, Data Resource Core, and PASC Biorepository CoreOT2HL161847 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GROSS, RACHEL SHARON, HORWITZ, LEORA · 2021 to 2025
$651.0M
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
NHLBI NIH HHS OT2 HL161847NIA NIH HHS R01 AG076838NIDA NIH HHS U24 DA041123NIDA NIH HHS U24 DA055330
6 · The paper itself

Abstract

backgroundIndividuals with psychiatric disorders frequently experience comorbid cardiometabolic conditions, complicating treatment and worsening health outcomes. Both psychiatric and cardiometabolic disorders have been individually associated with alterations in brain structure. Yet, it remains unclear whether these associations stem from a shared genetic basis that underlies their frequent co-occurrence.

methodsWe analyzed genome-wide association summary statistics from large international consortia of individuals of European ancestry, including psychiatric disorder GWAS with case-control sample sizes ranging from ~18,000 to ~158,000 cases, cardiometabolic disease GWAS with up to ~242,000 cases, and cortical morphology GWAS from UK Biobank comprising ~39,000 individuals. We applied complementary multivariate, causal, and mediation genetic analyses to disentangle genetic factors underlying brain alterations and comorbidity.

resultsHere we show that patterns of genetic overlap differ across disorders. Schizophrenia exhibits substantial polygenic overlap with cortical thickness and type 2 diabetes, despite low genetic correlation. In contrast, attention-deficit/hyperactivity disorder (ADHD) is more strongly correlated with cardiometabolic disease but shows limited overlap with cortical morphology. Notably, cortical surface area partly mediates the genetic association between ADHD and type 2 diabetes. Pathway analyses highlight metabolic stress processes in ADHD as well as neurodevelopmental and immune processes in schizophrenia.

conclusionsThese findings indicate that psychiatric-cardiometabolic comorbidity arises through both shared and disorder-specific genetic pathways. This work clarifies the genetic architecture of multimorbidity and highlights opportunities for trait-targeted prevention strategies in psychiatry.

Identifiers

PMID42509310
PMCPMC13407876

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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 OpenQuestion graph.