Abstract
Many psychiatric disorders are heritable, but the molecular consequences of genetic risk remain difficult to resolve, in part due to environmental confounds and the complexity of transcriptomic data. This challenge impedes therapeutic development, which relies on integrating genetic and genomic insights. Here, we integrate diagnosis, toxicological exposure, and gene expression to clarify disease-associated transcriptomic patterns in the subgenual anterior cingulate cortex (sgACC), a brain region implicated in affective regulation and psychiatric illness. We applied group regularized canonical correlation analysis (GRCCA)—a multivariate regression method that models interdependent features—to deeply sequenced bulk RNA-seq data from individuals with bipolar disorder (BD; N = 35), major depression (MDD; N = 51), schizophrenia (SCZ; N = 44), and controls (N = 55). Toxicology data from 17 known compounds were included to assess the relative contribution of known environmental exposures. Case-control expression changes were also analyzed using traditional differential gene expression (DGE) analysis to compare biological interpretability across methods. Gene set enrichment analyses evaluated enrichments for neuropsychiatric risk genes, gene ontology pathways, and cell type markers. GRCCA identified a latent variable significantly associated with schizophrenia (pperm = 0.001). This expression pattern was enriched for upregulated neuronal pathways, downregulated immune processes, and genes within loci associated with schizophrenia by GWAS. While DGE results were correlated (r = 0.43; pperm = 1.0 × 10−4) and enriched for similar functional pathways, GRCCA showed stronger alignment with schizophrenia risk genes implicated by genome-wide association studies. Together, these findings define a schizophrenia-associated expression gradient in the sgACC and illustrate how multivariate integration can refine transcriptomic signals in the context of complex psychiatric disease.
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Data availability
The raw count data can be downloaded from dbGAP at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000979.v2.p2. The case-control differential gene expression results reported by Akula et al. [14] can be found at https://www.nature.com/articles/s41386-020-00949-5 (Supplementary Table 4 for schizophrenia vs controls). PsychENCODE developmental expression data are made available by Li et al. [56] https://www.science.org/doi/10.1126/science.aat7615. Cell-type specific latent factor 4 loadings are published in https://www.nature.com/articles/s41586-024-07109-5.
Code availability
Code for all analyses is available at https://github.com/rlsmith1/sgACC_transcriptomics_analyses.git.
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Acknowledgements
At the time of this work, R.L.S was a PhD candidate in the NIH Oxford-Cambridge Scholars Program. All research from the Department of Psychiatry at the University of Cambridge is made possible by the NIHR Cambridge Biomedical Research Centre and the NIHR East of England Applied Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. This work received computational support from the NIP HPC Biowulf cluster (http://hpc.nih.gov) and from the mental health theme of the National Institute of Health Research (NIHR) Cambridge Biomedical Research Center. Library preparation and RNA sequencing was performed at the NIH Sequencing Center. This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services. Thank you to families of the deceased for tissue donations and to the Offices of the Medical Examiner of the District of Columbia, Central and Northern Virginia for referrals and brain extraction.
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R.L.S., N.A., P.K.A., S.M., A.R., and F.J.M. are supported by the Intramural Research Program of the National Institute of Mental Health as follows: R.L.S., N.A., F.J.M (1ZIAMH002810); A.R. (1ZIAMH002949); P.K.A, S.M. (ZICMH002903-15). P.E.V. was supported by MQ: Transforming Mental Health (MQF17_24).
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Conceptualization, R.L.S., A.M. A.R., P.E.V., F.J.M.; methodology, R.L.S., A.M., N.A.; software, R.L.S., A.M..; formal analysis, R.L.S., A.M.; data curation, N.A., P.K.A., S.M., F.J.M.; writing – original draft, R.L.S., A.R., P.E.V., F.J.M.; writing – review and editing, R.L.S., A.M., N.A., P.K.A., S.M., A.R., P.E.V., F.J.M.; visualization, R.L.S.; supervision, A.R., P.E.V., F.J.M.; project administration, N.A., P.K.A., S.M., F.J.M.
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A.M. is currently employed full-time at Turbine Ltd.
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All samples in this study were collected with the informed consent of the next-of-kin under CNS IRB protocols 90M0142 and 17M-N073 or approved by the NIMH Human Brain Collection Core Oversight Committee.
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Smith, R.L., Mihalik, A., Akula, N. et al. A transcriptomic dimension of neuronal and immune gene programs within the subgenual anterior cingulate cortex in schizophrenia. Transl Psychiatry (2026). https://doi.org/10.1038/s41398-026-03814-z
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DOI: https://doi.org/10.1038/s41398-026-03814-z
