Identification and Validation of Slit3 as a Depression Biomarker Modulating Dynorphinergic Neurons in the Hypothalamic Paraventricular Nucleus.

Depression is a psychiatric disorder primarily characterized by anhedonia, yet its underlying mechanisms remain incompletely understood. In this study, using a chronic social defeat stress (CSDS) models of male C57BL/6J mice, we observed increased co-localization of NeuN and c-Fos in the paraventricular nucleus of the hypothalamus (PVN). Subsequently, PVN tissues were subjected to RNA sequencing, and differentially expressed genes (DEGs) were screened. Enrichment analyses were performed using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathways. We further analyzed relevant gene modules via weighted gene co-expression network analysis (WGCNA) to identify candidate hub modules, and ultimately identified two hub genes, Nek5 and Slit3, using the least absolute shrinkage and selection operator (LASSO) algorithm and random forest algorithm. Then gene set enrichment analysis (GSEA) was exerted to explore the signaling pathways related to the hub genes. qRT-PCR and western blot revealed that only Slit3 exhibited consistent changes at both the gene and protein expression levels in the PVN following CSDS or CRS exposure. Co-localization of dynorphinergic neurons with c-Fos, as well as with Slit3, increased in the PVN of CSDS and CRS groups. Notably, Slit3 knockdown in PVN improved CSDS- and CRS-induced depression like behaviors. These findings suggest that Slit3 could serve as a potential biomarker for depression and holds important application value for depression risk prediction.

• Publication year

  2025

• Venue

  Neuropharmacology

• Publication date

  2025-11-01

• Fields of study

  Biology, Medicine

• Identifiers
  DOI 10.1016/j.neuropharm.2025.110765PMID 41232827
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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