BACKGROUND

We aimed to assess the interactions between mixed heavy metals, genes, and miRNAs implicated in depression development and to design and create miRNA sponges.

METHODS

The key data-mining approaches in this study were the Comparative Toxicogenomics Database (CTD), MIENTURNET, GeneMania, Metascape, Webgestalt, miRNAsong, and Cytoscape software.

RESULTS

A mixture of cadmium, lead, mercury, and arsenic was related to the development of depression. Even though the genes acquired from the heavy metals of depression studied were different, the "selenium micronutrient network", "vitamin B12 and folate metabolism", and "positive regulation of peptidyl-serine phosphorylation" pathways were highlighted. The heavy metal mixture altered the genes SOD1, IL6, PTGS2, PON1, BDNF, and ALB, highlighting the role of oxidative stress, pro-inflammatory cytokines, paraoxonase activity, neurotrophic factors, and antioxidants related to depression, as well as the possibility of targeting these genes in prospective depressive treatment. Chr1q31.1, five transcription factors (NR4A3, NR1H4, ATF3, CREB3L3, and NR1I3), the "endoplasmic reticulum lumen," "blood microparticle," and "myelin sheath", were found to be important chromosomal locations, transcription factors, and cellular parts linked to depression and affected by mixed heavy metals. Furthermore, we developed a network-based approach to detect significant genes, miRNA, pathways, and illnesses related to depression development. We also observed eight important miRNAs related to depression induced by mixed heavy metals (hsa-miR-16-5p, hsa-miR-132-3p, hsa-miR-1-3p, hsa-miR-204-5p, hsa-miR-206, hsa-miR-124-3p, hsa-miR-146a-5p, and hsa-miR-26a-5p). In addition, we created and evaluated miRNA sponge sequences for these miRNAs in silico.

LIMITATIONS

A toxicogenomic design in silico was used.

CONCLUSIONS

Our findings highlight the importance of oxidative stress, notably SOD1 and the selenium micronutrient network, in depression caused by heavy metal mixtures and provide additional insights into common molecular pathways implicated in depression pathogenesis.