Brain differential gene expression and blood cross-validation of a molecular signature of patients with major depressive disorder

Abstract

IntroductionThe agreement between clinicians diagnosing major depressive disorder (MDD) is poor. The objective of this study was to identify a reproducible and robust gene expression marker capable of differentiating MDD from healthy control (HC) subjects. Materials and methodsBrain and blood gene expression datasets were searched, which included subjects with MDD and HC. The largest database including different areas of brain samples (GSE80655) was used to identify an initial gene expression marker. Tests of robustness and reproducibility were then implemented in 13 brain and 7 blood independent datasets. Correlations between expression in brain and blood samples were also examined. Finally, an enrichment analysis to explore the marker biological meaning was completed. ResultsTwenty-eight genes were differentially expressed in GSE80655, of which 23 were critical to differentiate MDD from HC. The accuracy obtained using the 23 genes was 0.77 and 0.8, before and after the forward selection model, respectively. The gene marker's robustness and reproducibility were between the range of 0.46 and 0.63 in the other brain datasets and between 0.45 and 0.78 for the blood datasets. Brain and blood expression tended to correlate in some samples. Thirteen of the 23 genes were related to stress and immune response. ConclusionA 23 gene expression marker was able to distinguish subjects with MDD from HC, with adequate reproducibility and low robustness in the independent databases investigated. This gene set was similarly expressed in the brain and blood and involved genes related to stress and immune response.

Integrative bioinformatics and artificial intelligence analyses of transcriptomics data identified genes associated with major depressive disorders including NRG1

“…Notably, we ascertained that out of the ten identified MDD-related biomarkers, six biomarkers ( CLEC12B, HP, LCN2, OLFM4, SERPING1, and THBS1 ) were related to a specific subset of brain regions, however, CEACAM8, DEFA4, NRG1, TCN1 do not show a distinct differential expression on the brain areas of healthy cases. These findings appear to be substantiated by previous studies revealing that identified hub-genes in peripheral blood samples are capable to classify MDD from HCs with high accuracy, although some of these reliable markers were not correlated with the brain differential gene expression ( Gomez Rueda and Bustillo, 2022 ). These results point to the probability that due to brain plasticity, not necessarily all mental-related biomarkers follow the usual computational analysis hypothesis.…”

Differential Gene Expression and DNA Methylation in the Risk of Depression in LOAD Patients

“…Similarly, the role of differential gene expression and DNA-methylation was also studied in depression. Several studies showed transcriptomic changes in MDD, implicating glutaminergic, dopaminergic, immune system, and inflammatory pathways [ 16 , 17 , 18 , 19 ]. However, Cole et al found no significant differential gene expression when looking at peripheral blood mononuclear cells (PBMC) samples [ 20 ].…”