Cell type-specific alterations in fatty acid metabolism in neuronal subpopulations of schizophrenia and construction of a diagnostic model.

Objective: This study integrates single-cell and bulk RNA-seq to investigate cell type-specific alterations in fatty acid metabolism-related genes in the dorsolateral prefrontal cortex (DLPFC) of schizophrenia (SCZ) patients and to evaluate their potential as diagnostic biomarkers. Methods: Integrating single-cell sequencing data (9 SCZ patients and 14 controls) and Bulk RNA-seq data (GSE174407, GSE107638), cell subpopulation identification and annotation were performed using Seurat. Key genes were identified by integrating differential gene screening, transcriptional regulatory network construction (SCENIC), pseudotime analysis (Monocle 2), and functional enrichment. A multi-gene diagnostic model was established using LASSO regression. Model performance was validated using ROC curves, nomograms, and immune cell correlation analysis. Finally, an MK-801-induced mouse SCZ model was used to validate the expression of key genes via qPCR. Results: The study found that specific neuronal cell subtypes (e.g., CUX2+ NeuN and OPRM1+ NeuN) were significantly upregulated in SCZ, and the differentially expressed genes (DEGs) in these cells (e.g., Conclusion: This study reveals cell type-specific dysregulation of fatty acid metabolism in SCZ and provides a robust five-gene diagnostic model with translational potential.