4.7 Article

An Integrative Network Approach to Identify Common Genes for the Therapeutics in Tuberculosis and Its Overlapping Non-Communicable Diseases

Journal

FRONTIERS IN PHARMACOLOGY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fphar.2021.770762

Keywords

Network Biology; Network Medicines; Disease-disease relationship; Disease-target interaction; MTB and NCDs

Funding

  1. Department of Health Research (DHR), Ministry of Health and Family Welfare, Government of India [R.12014/06/2019-HR]

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Tuberculosis (TB) is the leading cause of death from a single infectious agent, and its burden remains significant, especially in low- and middle-income countries. This study investigates the interaction between TB and noncommunicable diseases (NCDs), such as Parkinson's disease, cardiovascular disease, diabetes mellitus, rheumatoid arthritis, and lung cancer. By analyzing overlapping genes and constructing gene networks, the study identifies hub genes commonly associated with TB and its overlapping NCDs. Furthermore, a bipartite network of drugs and their targets is utilized to explore potential drug repurposing opportunities and identify side effects related to TB and its overlapping NCDs.
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), such as 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 Mycobacterium tuberculosis (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.

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