Distinct Neonatal Brain Anatomy Is Associated With Cross‐Disorder Genetic Risk for Psychiatric Disorders

Psychiatric disorders share a complex polygenic architecture, yet how this genetic liability relates to early brain development remains unclear. This study investigated the associations between cross-disorder polygenic risk and neonatal brain anatomy. We derived three latent psychiatric factors using GenomicSEM, reflecting shared genetic liability among related conditions: A neurodevelopmental factor, a compulsive factor, and a mood-psychosis factor. We then calculated respective polygenic risk scores (PRS) in 336 neonates from the Developing Human Connectome Project. We found that cross-disorder PRSs (neurodevelopmental and mood-psychosis factors) showed significantly broader associations with neonatal brain volumes than disorder-specific PRSs. These associations were highly robust, as confirmed through validation analyses using updated GWAS data and an alternative PRS method (PRS-CS). These cross-disorder PRSs were strongly correlated with smaller global brain size. After accounting for this global effect, associations with a subset of brain regions remained detectable. In exploratory analyses, the neurodevelopmental factor was reproducibly linked to heightened alertness at 18 months. Our results reveal that shared genetic risk for psychiatric disorders manifests as both global and regionally specific variations in brain anatomy at birth, highlighting the value of cross-disorder genetic models for elucidating early neurodevelopmental vulnerability.

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Publication Details

Journal
Human Brain Mapping
Published
2026-04-15
DOI
https://doi.org/10.1002/hbm.70532
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Distinct Neonatal Brain Anatomy Is Associated With Cross‐Disorder Genetic Risk for Psychiatric Disorders

M Li, Xixi Dang, D W Wu, Ruiqi Su
Human Brain Mapping
Genetic Associations and Epidemiology
article

Distinct Neonatal Brain Anatomy Is Associated With Cross‐Disorder Genetic Risk for Psychiatric Disorders

M Li, Xixi Dang, D W Wu, Ruiqi Su
article en

Abstract

Psychiatric disorders share a complex polygenic architecture, yet how this genetic liability relates to early brain development remains unclear. This study investigated the associations between cross-disorder polygenic risk and neonatal brain anatomy. We derived three latent psychiatric factors using GenomicSEM, reflecting shared genetic liability among related conditions: A neurodevelopmental factor, a compulsive factor, and a mood-psychosis factor. We then calculated respective polygenic risk scores (PRS) in 336 neonates from the Developing Human Connectome Project. We found that cross-disorder PRSs (neurodevelopmental and mood-psychosis factors) showed significantly broader associations with neonatal brain volumes than disorder-specific PRSs. These associations were highly robust, as confirmed through validation analyses using updated GWAS data and an alternative PRS method (PRS-CS). These cross-disorder PRSs were strongly correlated with smaller global brain size. After accounting for this global effect, associations with a subset of brain regions remained detectable. In exploratory analyses, the neurodevelopmental factor was reproducibly linked to heightened alertness at 18 months. Our results reveal that shared genetic risk for psychiatric disorders manifests as both global and regionally specific variations in brain anatomy at birth, highlighting the value of cross-disorder genetic models for elucidating early neurodevelopmental vulnerability.

Human Brain MappingVol. 47(6)
Hangzhou Normal University (CN), Children's Hospital of Zhejiang University (CN), Zhejiang University (CN)
National Institute for Health and Care Research, European Commission, National Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China, Jilin Office of Philosophy and Social Science, Engineering and Physical Sciences Research Council, Centre For Medical Engineering, King’s College London, Natural Science Foundation of Zhejiang Province
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Genetic Associations and Epidemiology
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