Identification of potential Mitogen-Activated Protein Kinase-related key genes and regulation networks in molecular subtypes of major depressive disorder

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Clarification of the molecular mechanisms underlying glyphosate-induced major depressive disorder: a network toxicology approach

Major depressive disorder (MDD) is predicted to become the second most common cause of disability in the near future. Exposure to glyphosate (Gly)-based herbicides has been linked to the onset of MDD. However, the underlying mechanisms remain unclear. The aim of this study was to investigate the potential molecular mechanisms of MDD induced by Gly using network toxicology approach. The MDD dataset GSE76826 from the Gene Expression Omnibus database was referenced to identify differentially expressed genes (DEGs) in peripheral blood leukocytes of MDD patients and controls. The potential intersection targets of Gly-induced MDD were screened by network toxicology. The intersection targets were used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and to construct protein-protein interaction networks. The binding potentials of hub targets with Gly were validated by molecular docking. In total, 1216 DEGs associated with Gly-induced MDD were identified. Subsequent network pharmacology further refined the search to 43 targets. GO and KEGG enrichment analyses revealed multiple signaling pathways involved in GLY-induced MDD. Six potential core targets (CD40, FOXO3, FOS, IL6, TP53, and VEGFA) were identified. Finally, molecular docking demonstrated that Gly exhibited strong binding affinity to the core targets. The results of this study identified potential molecular mechanisms underlying Gly induced MDD and provided new insights for prevention and treatment.