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Transcriptomic alterations across various cell types in the PFC

GSE291951 Mus musculus Expression profiling by high throughput sequencing 12 samples 2025/08/20 GPL24247
Summary
Major depressive disorder (MDD) is a prevalent mental illness that significantly impacts global health, with women showing twice the prevalence of men. This study employed the chronic social defeat stress (CSDS) model in female mice to investigate cellular and molecular changes in the prefrontal cortex (PFC) associated with depressive-like behaviors. Using single-nucleus RNA sequencing (snRNA-Seq), we examined transcriptomic alterations across various cell types in the PFC. Our results revealed that interneurons exhibited the most significant transcriptomic changes among all analyzed cell types. Notably, we identified a specific subtype of interneurons, the Sox6+ interneurons (Sox6+Int), which showed a markedly increased proportion in the CSDS group. This increase was associated with enhanced inflammatory and immune responses, as well as alterations in synaptic function and mitochondrial pathways. Furthermore, we observed significant changes in cell-cell communication patterns, particularly between Sox6+Int and oligodendrocyte precursor cells (OPCs). Weighted gene co-expression network analysis (WGCNA) identified several gene modules in Sox6+Int associated with specific depressive-like behaviors, implicating pathways related to inflammation, autophagy, and synaptic function. These findings provide novel insights into the cellular and molecular mechanisms underlying MDD in females, highlighting the potential role of Sox6+Int in stress-induced depression. Our study not only extends our understanding of the neurobiological basis of depression but also identifies potential therapeutic targets for sex-specific interventions in MDD treatment.
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NCBI GEO page ↗ Paper (PMID 40581656) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more mouse RNA-seq datasets →
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