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Meta-analysis of host response networks identifies a common core in tuberculosis
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 r...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445610/ https://www.ncbi.nlm.nih.gov/pubmed/28649431 http://dx.doi.org/10.1038/s41540-017-0005-4 |
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author | Sambarey, Awanti Devaprasad, Abhinandan Baloni, Priyanka Mishra, Madhulika Mohan, Abhilash Tyagi, Priyanka Singh, Amit Akshata, JS Sultana, Razia Buggi, Shashidhar Chandra, Nagasuma |
author_facet | Sambarey, Awanti Devaprasad, Abhinandan Baloni, Priyanka Mishra, Madhulika Mohan, Abhilash Tyagi, Priyanka Singh, Amit Akshata, JS Sultana, Razia Buggi, Shashidhar Chandra, Nagasuma |
author_sort | Sambarey, Awanti |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5445610 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54456102017-06-23 Meta-analysis of host response networks identifies a common core in tuberculosis Sambarey, Awanti Devaprasad, Abhinandan Baloni, Priyanka Mishra, Madhulika Mohan, Abhilash Tyagi, Priyanka Singh, Amit Akshata, JS Sultana, Razia Buggi, Shashidhar Chandra, Nagasuma NPJ Syst Biol Appl Article 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. Nature Publishing Group UK 2017-02-10 /pmc/articles/PMC5445610/ /pubmed/28649431 http://dx.doi.org/10.1038/s41540-017-0005-4 Text en © The Author(s) 2017 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Sambarey, Awanti Devaprasad, Abhinandan Baloni, Priyanka Mishra, Madhulika Mohan, Abhilash Tyagi, Priyanka Singh, Amit Akshata, JS Sultana, Razia Buggi, Shashidhar Chandra, Nagasuma Meta-analysis of host response networks identifies a common core in tuberculosis |
title | Meta-analysis of host response networks identifies a common core in tuberculosis |
title_full | Meta-analysis of host response networks identifies a common core in tuberculosis |
title_fullStr | Meta-analysis of host response networks identifies a common core in tuberculosis |
title_full_unstemmed | Meta-analysis of host response networks identifies a common core in tuberculosis |
title_short | Meta-analysis of host response networks identifies a common core in tuberculosis |
title_sort | meta-analysis of host response networks identifies a common core in tuberculosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445610/ https://www.ncbi.nlm.nih.gov/pubmed/28649431 http://dx.doi.org/10.1038/s41540-017-0005-4 |
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