Affiliation:
1. Laboratory of Pharmacology, School of Pharmacy, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2. Department of Health Sciences, School of Life and Health Sciences, University of Nicosia, 2417 Nicosia, Cyprus
Abstract
Diabetes mellitus type-2 (DMT2) molecular pathophysiology is still challenging since the disease represents a complex, multifactorial metabolic disease caused by polygenic defects and environmental factors. In addition, the resulting secondary organ complications can be affected by various environmental and life-style factors over the years. The metabolic imbalance in DMT2 is manifested by the dysfunction of pancreatic β-cells in secreting insulin and the inability of other tissue cells to respond to insulin and utilize blood glucose. However, over recent years, through the advances in genomics and molecular analysis, several genes and microRNAs have been shown to be correlated as potential biomarkers with DMT2 prognosis, diagnosis, and therapy. Furthermore, drug therapy and clinical pharmacology have benefited from pharmacogenomics in a manner where the molecular knowledge can be translated into clinical information aiming to improve precision and personalized medicine therapeutic methodologies in healthcare. In this work, using systems pharmacology and network analysis approaches, we comprehensively assessed the molecular and genomics data associated with DMT2 to: (a) Better understand miRNA, gene, and drug associations; (b) Create connectivity and interaction maps of practical clinical utility; and (c) Facilitate the application of precision medicine therapeutic decisions in group and individual patients. Moreover, in order for the clinical pharmacology guidelines to be implemented in parallel with the generated molecular data, we also carried out an assessment of drug interactions in specific pharmacological classes that affect DMT2 pharmacotherapy outcomes. Overall, the proposed methodology and the results obtained: (a) Enrich our understanding of DMT2 molecular pathophysiology; (b) Unveil important biomarker and drug-gene pharmacogenomics associations; (c) Help the use of personalized therapy options; and (d) Allow precision medicine concepts to be broadly exploited in new therapeutic developments and within the clinical setting.