系统药理学和网络分析促进2型糖尿病治疗的药物基因组学和精准医学决策

Aikaterini Saiti, Alexandros Giannopoulos-Dimitriou, Ioannis Kazakos, Eleftheria Galatou, I. Vizirianakis
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摘要

2型糖尿病(DMT2)是一种由多基因缺陷和环境因素引起的复杂的多因素代谢性疾病,其分子病理生理学研究仍然具有挑战性。此外,继发性器官并发症可能受到各种环境和生活方式因素的影响。DMT2代谢失衡表现为胰腺β-细胞分泌胰岛素功能障碍,其他组织细胞无法对胰岛素作出反应和利用血糖。然而,近年来,通过基因组学和分子分析的进展,一些基因和microrna已被证明是与DMT2预后、诊断和治疗相关的潜在生物标志物。此外,药物治疗和临床药理学也受益于药物基因组学,在某种程度上,分子知识可以转化为临床信息,旨在提高医疗保健中的准确性和个性化医学治疗方法。在这项工作中,使用系统药理学和网络分析方法,我们全面评估了与DMT2相关的分子和基因组学数据,以便:(a)更好地了解miRNA,基因和药物关联;(b)建立实际临床用途的连通性和相互作用图;(c)促进在群体和个体患者中应用精准医学治疗决策。此外,为了使临床药理学指南与生成的分子数据并行实施,我们还对影响DMT2药物治疗结果的特定药理学类别的药物相互作用进行了评估。总的来说,所提出的方法和得到的结果:(a)丰富了我们对DMT2分子病理生理学的理解;(b)揭示重要的生物标志物和药物基因药物基因组学关联;(c)帮助使用个性化治疗方案;(d)允许精准医学概念在新的治疗发展和临床环境中得到广泛利用。
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Systems Pharmacology and Network Analysis to Advance Pharmacogenomics and Precision Medicine Decisions in Type-2 Diabetes Therapy
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.
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