Schizophrenia Fatty Acid Metabolism Gene Expression and Diagnostic Model

A dataset of cell type-specific fatty acid metabolism gene expression alterations in schizophrenia, derived from integrated single-cell and bulk RNA-seq data. The data was generated by Cui Zhao and published on figshare in 2026. It includes a five-gene diagnostic model validated in a mouse model.

Use Cases

• Validating diagnostic biomarkers for schizophrenia based on the five identified key genes (ACAA1, ACAT2, ACSS1, PSME1, S100A10).
• Analyzing cell type-specific dysregulation in fatty acid metabolism pathways, particularly in CUX2+ and OPRM1+ neuronal subtypes.
• Benchmarking LASSO regression models for constructing multi-gene diagnostic classifiers in psychiatric disorders.
• Correlating gene expression with inflammatory responses in neuronal cells based on the described negative correlations.

Strengths

• Includes a validated diagnostic model with an AUC of 0.856 in the training cohort and 0.779 in the validation cohort.
• Integrates data from multiple sources, including single-cell sequencing from 9 SCZ patients and 14 controls and bulk RNA-seq datasets.
• Key findings were validated in an MK-801-induced mouse model of schizophrenia via qPCR.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is very small at 10.9 KB, indicating limited raw data scope.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

figshare, author Cui Zhao.

Collection Method

Integrated analysis of single-cell and bulk RNA-seq data using Seurat, SCENIC, and Monocle 2, with validation via qPCR in a mouse model.

Freshness

Last updated 2026-04-21 05:30:02; freshness should be verified.