Meta-analysis of host response networks identifies a common core in tuberculosis

Sambarey, Awanti and Devaprasad, Abhinandan and Baloni, Priyanka and Mishra, Madhulika and Mohan, Abhilash and Tyagi, Priyanka and Singh, Amit and Akshata, JS and Sultana, Razia and Buggi, Shashidhar and Chandra, Nagasuma (2017) Meta-analysis of host response networks identifies a common core in tuberculosis. In: npj Systems Biology and Applications, 3 (1). ISSN 2056-7189

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Abstract

Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host’s whole blood transcriptomic profiles that were integrated into a genome-scale protein–protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data.

Item Type:	Journal Article
Publication:	npj Systems Biology and Applications
Publisher:	Nature Publishing Group
Additional Information:	The Copyright of this article belongs to the Authors
Department/Centre:	Division of Biological Sciences > Biochemistry Division of Biological Sciences > Molecular Biophysics Unit Division of Biological Sciences > Centre for Infectious Disease Research
Date Deposited:	05 Jun 2022 05:30
Last Modified:	05 Jun 2022 05:30
URI:	https://eprints.iisc.ac.in/id/eprint/72958

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