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

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.

Authors

Institutions

Publication Details

Journal
Biology of Sex Differences
Published
2026-05-08
DOI
https://doi.org/10.1186/s13293-026-00870-4
Primary Topic
Bipolar Disorder and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Omran Davarinejad, Mohammad‐Taher Moradi, Arash Safarzadeh, Fatemeh Kazemisafa et al.
Biology of Sex Differences
Bipolar Disorder and Treatment
article

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

Omran Davarinejad, Mohammad‐Taher Moradi, Arash Safarzadeh, Fatemeh Kazemisafa, Masumeh Jalalvand
article en

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.

Biology of Sex Differences
Lorestan University of Medical Sciences (IR), Kermanshah University of Medical Sciences (IR), Shahid Beheshti University of Medical Sciences (IR)
Gender equality
Openalex Percentile: Top 6%
Bipolar Disorder and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.