Biochem Genet. 2025 Mar 16. doi: 10.1007/s10528-025-11085-4. Online ahead of print.
ABSTRACT
Chronic rhinosinusitis (CRS) and depression are both common conditions with significant socioeconomic impact. The high co-occurrence of depression in CRS patients suggests a common pathophysiology, but the mechanisms are unclear. This study aimed to identify potential molecular links between the two conditions. We retrieved gene expression datasets for CRS and depression from the GEO database. Using differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA), we identified co-expression genes associated with CRS and depression. Enrichment analyses including GO, KEGG, and GSEA were performed to explore biological pathways. Machine learning algorithms including random forest and LASSO regression were engaged to screen for shared hub genes predictive of CRS and depression. Single-cell RNA sequencing (scRNA-seq) data were analyzed to delineate the expression profiles of the shared hub genes across different cell types. Animal experiments were employed to validate the role of core genes in CRS-related depression. We identified five shared hub genes: CHRDL1, DIO2, HSD17B6, PDE3A, and PLA2G5, with the TGF-β signaling, cytokine-cytokine interaction receptors, and cell adhesion as key biological pathways. DIO2, as identified by machine learning, is a promising diagnostic biomarker for CRS and depression. The scRNA-seq analysis showed that DIO2 is primarily expressed in neurons and astrocytes. Animal experiments showed that overexpression of DIO2 improved the depressive-like behaviors in CRS mice. This study sheds new light on the molecular basis of the comorbidity between CRS and depression. DIO2 is a potential diagnostic and therapeutic target for CRS patients with comorbid depression.
PMID:40089956 | DOI:10.1007/s10528-025-11085-4
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