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 (rBD = 0.83, p = 4.99e-7 and rSZ = 0.65, p = 5.79e-4). Genetic overlap at the tract-level was consistent with average FA results. Overall, these findings suggest a genetic basis for the involvement of brain white matter aberrations in the pathophysiology of psychiatric disorders.
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Code availability
All tools used in this study are publicly available including: MiXeR v1.3 (https://github.com/precimed/mixer), cond/conjFDR (https://github.com/precimed/pleiofdr), LD score regression (https://github.com/bulik/ldsc), bedtools (bedtools.readthedocs.io), FUMA GWAS (https://fuma.ctglab.nl/).
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Acknowledgements
Funding was provided by the Research Council of Norway [grants 223273, 300309, 324252, 326813, 324499], the South-East Regional Health Authority [grant 2022-073], EEA and Norway [grant EEA-RO-NO-2018-0573], European Union’s Horizon 2020 Research and Innovation Programme [Grant 847776, 964874, the Marie Skłodowska-Curie Actions Grant 801133], and part of the convergence environment (MultiModal Mental Models [4MENT]) at the University of Oslo (UiO) Life Science. The authors have also received internationalization support from UiO:Life Science.We would like to thank the research participants for each GWAS. We additionally thank the staff at 23andMe, Inc and the Psychiatric Genomics Consortium for making this work possible and providing summary statistics. This work was performed on resources provided by Sigma2 (the National Infrastructure for High-Performance Computing and Data Storage in Norway) and the TSD (Tjeneste for Sensitive Data) facilities.
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NP and OAA conceived the study. NP conducted analyses and wrote the initial draft of the manuscript. NP, WC, GFLH, PP, OF, and OAA were involved in study design and provided analytical input. All authors contributed to data interpretation and editing of the manuscript.
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OAA reported personal fees from Lundbeck, Janssen, Sunovion (speaker’s honorarium), Biogen (consultant) outside the submitted work and is a consultant to Cortechs.ai (stock options). AMD is a founder of and holds equity interest in Cortechs.ai and serves on its scientific advisory board. He also receives research funding from General Electric Healthcare (GEHC).
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Parker, N., Cheng, W., Hindley, G.F.L. et al. Psychiatric disorders and brain white matter exhibit genetic overlap implicating developmental and neural cell biology. Mol Psychiatry 28, 4924–4932 (2023). https://doi.org/10.1038/s41380-023-02264-z
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DOI: https://doi.org/10.1038/s41380-023-02264-z
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