Exploration of Genetic Overlap of Brain Phenotypes With Schizophrenia: Different Methods Provide Complementary Insights

Xiao Wu; Pravesh Parekh; Bochao Danae Lin; Lotta-Katrin Pries; Sinan Guloksuz; Bart P F Rutten; Ole A Andreassen; David E J Linden; Dennis van der Meer

doi:10.1093/schbul/sbaf096

Exploration of Genetic Overlap of Brain Phenotypes With Schizophrenia: Different Methods Provide Complementary Insights

Schizophr Bull. 2025 Jun 20:sbaf096. doi: 10.1093/schbul/sbaf096. Online ahead of print.

Authors

Xiao Wu¹, Pravesh Parekh², Bochao Danae Lin¹, Lotta-Katrin Pries¹, Sinan Guloksuz^{1

3}, Bart P F Rutten¹, Ole A Andreassen², David E J Linden^{1

4}, Dennis van der Meer^{1

2}

Affiliations

¹ Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, 6200 MD, The Netherlands.
² Centre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, 0316, Norway.
³ Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, United States.
⁴ Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, CF24 4HQ, United Kingdom.

PMID: 40579369
DOI: 10.1093/schbul/sbaf096

Abstract

Background: Genetic studies have shown associations between genetic risk for schizophrenia and brain imaging phenotypes. However, prior studies focused on a single neuroimaging modality and/or employed methods that do not fully elucidate the shared genetic architecture between them, limiting our understanding of their complex genetic relationship.

Study design: We used genome-wide association study summary statistics for schizophrenia alongside 37 brain measurements, selected based on adequate SNP-based heritability and representing structural, microstructural, and functional brain features derived from T1, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI). These were integrated with a clinical cohort (1065 cases, 1037 controls) to examine the polygenic overlap between schizophrenia and brain measurements. Polygenic overlap was assessed at genome-wide and individual locus levels through linkage disequilibrium score regression, polygenic scoring (PGS), bivariate MiXeR, and conjunctional false discovery rate.

Study results: Schizophrenia showed weak genetic correlations with all brain measures (rg = -0.131 to 0.146; PFDR = .069 to .019), and no significant correlation with brain PGS. Nonetheless, a substantial proportion of causal variants with mixed effect direction were shared between schizophrenia and brain traits. Genetic correlations and polygenic scores showed significant positive associations with the proportion of shared variants with concordant effect direction. Additionally, we identified 218 loci shared with schizophrenia in T1, 138 in DTI, and 24 in rs-fMRI measures.

Conclusions: Our findings indicate shared genetic underpinnings between schizophrenia and brain structure and functional connectivity, emphasizing the necessity for complementary methodologies to investigate the genetic overlap between complex polygenic traits.

Keywords: brain MRI; genetic overlap; genetics; genome-wide association study; pleiotropy; schizophrenia.

Abstract

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