Exploring gene regulatory interaction networks and predicting therapeutic molecules among major depressive disorder and bipolar disorder: A bioinformatics approach

Background: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) are two common psychiatric disorders that have a substantial influence on people's mental health and quality of life. The identification of regulatory networks and potential drugs for both disorders enhances our understanding of these conditions and facilitates the development of targeted and effective therapies.

Methods: This study employed network-based methods to identify gene regulatory networks and potential therapeutics for Major Depressive Disorder (MDD) and Bipolar Disorder (BD). We identified intersecting genes, predicted miRNAs and transcription factors, and constructed the TF-miRNA-hub gene network. Modules, enrichment analysis, and motifs were identified, and potential drugs targeting disease-associated genes were discovered using the DSigDB from the Enricher database.

Results: We identified five common hub genes (AKT1, IL1B, IL6, MAPK3, and TNF) in MDD and BD protein-protein interaction networks. Our analysis revealed three microRNAs (hsa-let-7d-5p, hsa-let-7a-5p, and hsa-mir-34a-5p) and two transcription factors (NFKB1 and RELA) targeting these hub genes, which are also involved in various disorders and pathways, including cancer, hepatitis B, and the TNF signalling pathway. Notably, we identified 10 potential drug candidates targeting these hubs, providing valuable insights into MDD and BD's molecular mechanisms and potential therapeutic targets.

Limitation: Further experimental validation required to confirm the computational predictions.

Conclusion: The findings emphasize the importance of regulatory network motifs discovery in understanding the disorders-dynamics and therapeutics. These results provide the ground work for developing the common targeted interventions for MDD and BD.