Alam Aftab, Abubaker Bagabir Hala, Sultan Armiya, Siddiqui Mohd Faizan, Imam Nikhat, Alkhanani Mustfa F, Alsulimani Ahmad, Haque Shafiul, Ishrat Romana
Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.
Department of Physiology, Faculty of Medicine, King Abdulaziz University, Rabigh, Saudi Arabia.
Front Pharmacol. 2022 Jan 27;12:770762. doi: 10.3389/fphar.2021.770762. eCollection 2021.
Tuberculosis (TB) is the leading cause of death from a single infectious agent. The estimated total global TB deaths in 2019 were 1.4 million. The decline in TB incidence rate is very slow, while the burden of noncommunicable diseases (NCDs) is exponentially increasing in low- and middle-income countries, where the prevention and treatment of TB disease remains a great burden, and there is enough empirical evidence (scientific evidence) to justify a greater research emphasis on the syndemic interaction between TB and NCDs. The current study was proposed to build a disease-gene network based on overlapping TB with NCDs (overlapping means genes involved in TB and other/s NCDs), Parkinson's disease, cardiovascular disease, diabetes mellitus, rheumatoid arthritis, and lung cancer. We compared the TB-associated genes with genes of its overlapping NCDs to determine the gene-disease relationship. Next, we constructed the gene interaction network of disease-genes by integrating curated and experimentally validated interactions in humans and find the 13 highly clustered modules in the network, which contains a total of 86 hub genes that are commonly associated with TB and its overlapping NCDs, which are largely involved in the Inflammatory response, cellular response to cytokine stimulus, response to cytokine, cytokine-mediated signaling pathway, defense response, response to stress and immune system process. Moreover, the identified hub genes and their respective drugs were exploited to build a bipartite network that assists in deciphering the drug-target interaction, highlighting the influential roles of these drugs on apparently unrelated targets and pathways. Targeting these hub proteins by using drugs combination 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. Thus, understanding the (Mtb) infection and associated NCDs is a high priority to contain its short and long-term effects on human health. Our network-based analysis opens a new horizon for more personalized treatment, drug-repurposing opportunities, investigates new targets, multidrug treatment, and can uncover several side effects of unrelated drugs for TB and its overlapping NCDs.
结核病（TB）是单一感染源导致死亡的主要原因。2019年全球结核病估计死亡总数为140万。结核病发病率下降非常缓慢，而在低收入和中等收入国家，非传染性疾病（NCDs）的负担却在呈指数级增长，在这些国家，结核病的预防和治疗仍然是一项巨大负担，并且有足够的经验证据（科学证据）证明更应重视结核病与非传染性疾病之间的共病相互作用研究。本研究旨在构建一个基于结核病与非传染性疾病重叠（重叠是指涉及结核病和其他非传染性疾病的基因）、帕金森病、心血管疾病、糖尿病、类风湿关节炎和肺癌的疾病-基因网络。我们将结核病相关基因与其重叠的非传染性疾病基因进行比较，以确定基因-疾病关系。接下来，我们通过整合人类中经过整理和实验验证的相互作用构建疾病-基因的基因相互作用网络，并在网络中发现13个高度聚集的模块，其中共有86个枢纽基因，这些基因通常与结核病及其重叠的非传染性疾病相关，主要参与炎症反应、细胞对细胞因子刺激的反应、对细胞因子的反应、细胞因子介导的信号通路、防御反应、对压力的反应和免疫系统过程。此外，利用已鉴定的枢纽基因及其各自的药物构建一个二分网络，有助于解读药物-靶点相互作用，突出这些药物对明显不相关靶点和途径的影响作用。通过药物联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，增强少数药物的效力，并产生协同效应，取得更好的结果。因此，了解结核分枝杆菌（Mtb）感染及相关非传染性疾病对于控制其对人类健康的短期和长期影响至关重要。我们基于网络的分析为更个性化的治疗、药物再利用机会、研究新靶点、多药治疗开辟了新视野，并且可以揭示与结核病及其重叠的非传染性疾病无关的药物的几种副作用。
