Institute of Computer Science and Information Technology, Department of Mathematics, Magadh University, Bodh Gaya, Bihar India.
Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi India.
Brief Funct Genomics. 2023 May 18;22(3):250-262. doi: 10.1093/bfgp/elac054.
Primary hyperparathyroidism is caused by solitary parathyroid adenomas (PTAs) in most cases (⁓85%), and it has been previously reported that PTAs are associated with cardiovascular disease (CVD) and type-2 diabetes (T2D). To understand the molecular basis of PTAs, we have investigated the genetic association amongst PTAs, CVD and T2D through an integrative network-based approach and observed a remarkable resemblance. The current study proposed to compare the PTAs-associated proteins with the overlapping proteins of CVD and T2D to determine the disease relationship. We constructed the protein-protein interaction network by integrating curated and experimentally validated interactions in humans. We found the $11$ highly clustered modules in the network, which contain a total of $13$ hub proteins (TP53, ESR1, EGFR, POTEF, MEN1, FLNA, CDKN2B, ACTB, CTNNB1, CAV1, MAPK1, G6PD and CCND1) that commonly co-exist in PTAs, CDV and T2D and reached to network's hierarchically modular organization. Additionally, we implemented a gene-set over-representation analysis over biological processes and pathways that helped to identify disease-associated pathways and prioritize target disease proteins. Moreover, we identified the respective drugs of these hub proteins. We built a bipartite network that helps decipher the drug-target interaction, highlighting the influential roles of these drugs on apparently unrelated targets and pathways. Targeting these hub proteins by using drug combinations or drug-repurposing approaches will improve the clinical conditions in comorbidity, enhance the potency of a few drugs and give a synergistic effect with better outcomes. This network-based analysis opens a new horizon for more personalized treatment and drug-repurposing opportunities to investigate new targets and multi-drug treatment and may be helpful in further analysis of the mechanisms underlying PTA and associated diseases.
原发性甲状旁腺功能亢进症（PHPT）大多由甲状旁腺腺瘤（PTAs）引起（⁓85%），此前已有报道称，PTAs 与心血管疾病（CVD）和 2 型糖尿病（T2D）有关。为了了解 PTA 的分子基础，我们通过整合网络的方法研究了 PTA、CVD 和 T2D 之间的遗传关联，并观察到了显著的相似性。本研究旨在通过比较 PTA 相关蛋白与 CVD 和 T2D 的重叠蛋白来确定疾病的关系。我们通过整合人类已验证的和经实验验证的相互作用构建了蛋白质-蛋白质相互作用网络。我们发现网络中有$11$个高度聚类的模块，其中包含$13$个总枢纽蛋白（TP53、ESR1、EGFR、POTEF、MEN1、FLNA、CDKN2B、ACTB、CTNNB1、CAV1、MAPK1、G6PD 和 CCND1），这些蛋白共同存在于 PTA、CVD 和 T2D 中，达到了网络的层次模块化组织。此外，我们对生物过程和途径进行了基因集过度表达分析，有助于识别与疾病相关的途径并确定靶向疾病蛋白的优先级。此外，我们还确定了这些枢纽蛋白各自的药物。我们构建了一个二分网络，有助于解析药物-靶点相互作用，突出了这些药物对明显无关的靶点和途径的影响作用。通过使用药物组合或药物再利用方法靶向这些枢纽蛋白，将改善合并症的临床状况，提高少数药物的效力，并产生更好的协同效应。这种基于网络的分析为更个性化的治疗和药物再利用机会开辟了新的视野，以研究新的靶点和多药物治疗，并可能有助于进一步分析 PTA 及其相关疾病的潜在机制。
