Identifying Potential Novel Pathways and Therapeutic Targets of Major Depressive Disorder with Functional Genomics

Abstract

\n Background: Major depressive disorder (MDD) is a debilitating illness and a leading cause of disability, but its pathophysiology remains to be completely elucidated. Resistance to traditional antidepressant treatment is highly prevalent within patient populations. Ketamine, a rapid-acting antidepressant that has shown success in treating resistant patients, is hypothesized to function by modulating excitatory and inhibitory neurotransmitters. This has led to a paradigm shift from the monoaminergic hypothesis, towards a glutamate and neuroplasticity hypothesis, though this picture may still be incomplete. The purpose of this study is to identify novel systems potentially implicated in MDD and suggest potential therapeutic mechanisms.Methods: An integrative genomics and systems biology approach was used to identify genes and pathways that may be relevant to MDD. Starting with genes implicated in current, well-established paradigms, a correlation analysis was used to query publicly available microarray datasets to identify potential genes that may be relevant to MDD. Systems and pathways of interest were identified through functional enrichment. Through a manual review, genes of systems and pathways potentially relevant to MDD were used to generate a protein interaction network. Interesting genes identified from the network were functionally enriched and clustered to identify new high-level themes. Genes from the protein interaction network were then classified into sets based on different paradigms using functional annotations. Genes belonging to multiple sets – and thus being involved in multiple different paradigms relevant to MDD – were identified for future research.Results: The highest-ranked enrichment cluster contained GABAeric signaling, retrograde endocannabinoid signaling, and morphine addiction. Other interesting pathways identified were T cell receptor signaling, cocaine addiction, and nicotine addiction. Other broad themes identified in other clusters were calcium, serotonin, the immune system, TGF beta, glutamate, telomeres, the guanine nucleotide exchange factor, the extracellular matrix, and DNA regulation. Potential genes of interest are listed in Chart 3.Conclusions: Throughout the study, interesting genes, groups of genes, and systems were identified manually and systematically, some of which validate existing literature and some give possible directions for future research. Further experiments are required to confirm causal links.