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Background: <p>Individuals 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.</p> Methods: <p>We 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.</p> Results: <p>Here 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.</p> Conclusions: <p>These 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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月27日

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  • 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,
  • Anders M. Dale,
  • Ole A. Andreassen

摘要

Background:

Individuals 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.

Methods:

We 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.

Results:

Here 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.

Conclusions:

These 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.