Weighted gene co-expression network analysis identifies specific modules and hub genes related to subsyndromal symptomatic depression.

OBJECTIVES: The identification of the potential molecule targets for subsyndromal symptomatic depression (SSD) is critical for improving the effective clinical treatment on the mental illness. In the current study, we mined the genome-wide expression profiling and investigated the novel biological pathways associated with SSD.

METHODS: Expression of the DEG were analyzed with microarrays of blood tissue cohort of 8 SSD patients and 8 healthy subjects. The gene co - expression is calculated by WGCNA, a R package software. The function of the genes was annotated by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

RESULTS: We identified 11 modules from the 9427 DEGs. Three co-expression modules (Blue, cyan and red) showed striking correlated with the phenotypic trait between SSD and healthy controls. Gene ontology and KEGG pathway analysis demonstrated that the function of this three modules was enriched with the pathway of inflammatory response and type II diabetes mellitus. Finally, three hub genes, NT5DC1, SGSM2 and MYCBP, were identified from the blue module as significant genes.

CONCLUSIONS: This first blood gene expression study in SSD observed distinct patterns between cases and controls which may provide novel insight into understanding the molecular mechanisms of SSD.