Sex-biased transcriptomic landscapes in bipolar disorder: integrating neurobiology and clinical heterogeneity through cross-study meta-analysis.

Overview

1. Clinical Research Development Center, Imam Khomeini and Mohammad Kermanshahi and Farabi Hospitals, Kermanshah University of Medical Sciences,Kermanshah, Iran
2. Sleep Disorders Research Center, Health Policy and Promotion Institute, Kermanshah University of Medical Sciences,Kermanshah, Iran
3. Department of Medical Genetics, Shahid Beheshti University of Medical Sciences,Tehran, Iran
4. Medical Biotechnology, School of Medicine, Lorestan University of Medical Sciences,Khorramabad, Iran

Abstract

Background: Bipolar disorder (BD) exhibits significant sex differences in its frequency, symptom presentation, and treatment response, suggesting distinct underlying neurobiological mechanisms. However, transcriptomic studies investigating these sex-specific pathways have been fragmented and underpowered.

Method: We conducted the first meta-analysis of post-mortem brain RNA-seq data to delineate sex-related transcriptomic landscapes in BD. We integrated data from four public datasets (GSE80336, GSE80655, GSE202537, GSE42546) from GEO and Array Express, comprising an aggregate of 173 individuals (66 BD cases and 117 controls). After preprocessing and correcting for batch effects, sex-stratified expression analysis was performed using DESeq2. A meta-analysis was conducted with the metafor package to identify differentially expressed genes (DEGs) at an FDR < 0.05. We also performed functional enrichment, protein-protein interaction (PPI) network analysis, hub gene identification, regulatory network reconstruction, and supplementary quantitative analyses of sex-specific interaction effects.

Results: Our results reveal striking differences in transcriptomic signatures between men and women with bipolar disorder, with the most pronounced changes occurring in the brain. A meta-analysis across brain regions identified 34 significantly dysregulated genes. In females, upregulated genes were enriched for hormonal signaling (FSHR pathway, G-protein signaling) and transcriptional/epigenetic regulation (GLIS1, neural plasticity). In males, upregulated genes were involved in synaptic calcium signaling (PDLIM5, dendritic spine regulation) and DNA mismatch repair pathways (PMS1). Analysis of the striatum identified 289 differentially expressed genes. The most significantly upregulated genes in females were implicated in immunity and synaptic plasticity, while the male-specific pattern pointed to alterations in basic cellular functions like structure, internal communication, and genetic regulation. A quantitative interaction analysis revealed a negligible correlation (r = -0.122) between disease effect sizes in females and males and identified one gene with opposing, sex-dependent dysregulation (MEF2C).

Conclusion: This study provides robust evidence that bipolar disorder engages fundamentally distinct molecular pathways in males and females, underscoring the necessity of integrating sex as a biological variable in psychiatric research and advancing toward personalized therapeutic strategies.

Supplementary Information: The online version contains supplementary material available at 10.1186/s13293-026-00870-4.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

Code availability

The code developed for the analyses described in this work has been made. publicly available at GitHub( https://github.com/kazemisafa94-boop/Bipolar-meta-analysis/blob/3740010a5de1f6739f4f7f3499859002a19b69ca/scripts%20codes (https://github.com/kazemisafa94-boop/Bipolar-meta-analysis/blob/3740010a5de1f6739f4f7f3499859002a19b69ca/scripts codes)). All software and versions used are detailed in Additional file 2: Table S2.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• figshare:32842804, at figshare; found in DataCite
• figshare:32842807, at figshare; found in DataCite
• figshare:32842810, at figshare; found in DataCite
• figshare:32842813, at figshare; found in DataCite
• figshare:32842816, at figshare; found in DataCite
• figshare:32842819, at figshare; found in DataCite
• figshare:32842822, at figshare; found in DataCite
• figshare:32842825, at figshare; found in DataCite
• figshare:32842828, at figshare; found in DataCite
• figshare:32842831, at figshare; found in DataCite
• figshare:32842834, at figshare; found in DataCite

Data availability

The data used for the analyses described in this work are publicly available atGEO (24)The accession numbers of the GEO datasets downloaded are GSE80336, GSE80655, GSE202537, GSE42546.

Reproduced under the paper's license (CC BY), from the paper cited above.

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This paper

Davarinejad, O., Moradi, M.-T., Safarzadeh, A., Jalalvand, M., & Kazemisafa, F. (2026). Sex-biased transcriptomic landscapes in bipolar disorder: integrating neurobiology and clinical heterogeneity through cross-study meta-analysis. Biology of sex differences, 17(1), 125. https://doi.org/10.1186/s13293-026-00870-4

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