Introducing Pain-Related Molecular Pathways in Painful Diabetic Neuropathy Via Protein Interaction Networks.

Background: Painful diabetic neuropathy (PDN) is one of the most drastic complications of diabetes. Patients with PDN always reveal spontaneous and stimulus-evoked pain. However, the pathogenesis mechanisms of PDN are not entirely distinct. Objectives: In the present study protein-protein interaction (PPI) network for PDN was constructed and analyzed to identify key proteins as potential biomarker candidates. Methods: The transcriptomic (genes) and proteomic (proteins) data in articles that focused on PDN with differential expressions were collected. Protein networks were constructed and analyzed using STRING and Cytoscape software, respectively. Further PPI network analysis, gene ontology, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis were performed using MCODE and DAVID tools. Results: A total of 147 differentially regulated proteins/genes were identified in painful diabetic neuropathy, including 91 up-regulatedand56 down-regulated proteins/genes. Anetwork analysis of genes/proteins related toPDNidentified COX4I1, NDUFS8, UQCRC1, COX7C, and some other NADH dehydrogenases, including NDUFB7, NDUFS7, NDUFS3, NDUFB5, NDUFA2, and NDUFB4 as hub-bottleneck proteins. With functional enrichment analysis of network clustering, COX7C, HP, RPS12, KCNIP2, and CoL4A1 were established as distinct seed proteins in the obtained modules, which could lead to the discovery of biomarker candidates. Conclusions: These results could provide new insights into pathology and molecular mechanisms, as well as the identification of pathways and proteins/genes involved in causing PDN in diabetic patients. COX7C, HP, RPS12, KCNIP2, and CoL4A1 are the top 5 seed nodes (hub proteins) and can serve as potential biomarker candidates and targets for PDN management. However, further investigations are needed to evaluate these proteins in detail. [ABSTRACT FROM AUTHOR]