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Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape
Advances in discovery and validation of diagnostic, prognostic and treatment-monitoring transcriptomic signatures of tuberculosis (TB) disease could accelerate the goal to end TB. We conducted a review to evaluate whether mRNA transcriptomics technologies are sufficiently mature to develop accurate...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294474/ https://www.ncbi.nlm.nih.gov/pubmed/35850011 http://dx.doi.org/10.1016/j.ebiom.2022.104174 |
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author | Hamada, Yohhei Penn-Nicholson, Adam Krishnan, Sriram Cirillo, Daniela Maria Matteelli, Alberto Wyss, Romain Denkinger, Claudia M. Rangaka, Molebogeng X. Ruhwald, Morten Schumacher, Samuel G. |
author_facet | Hamada, Yohhei Penn-Nicholson, Adam Krishnan, Sriram Cirillo, Daniela Maria Matteelli, Alberto Wyss, Romain Denkinger, Claudia M. Rangaka, Molebogeng X. Ruhwald, Morten Schumacher, Samuel G. |
author_sort | Hamada, Yohhei |
collection | PubMed |
description | Advances in discovery and validation of diagnostic, prognostic and treatment-monitoring transcriptomic signatures of tuberculosis (TB) disease could accelerate the goal to end TB. We conducted a review to evaluate whether mRNA transcriptomics technologies are sufficiently mature to develop accurate next-generation TB diagnostic tests. Early studies tended to be limited in sample size, diversity of population groups, sample collection and processing methods, while recent prospective studies have addressed these limitations. Some of the existing signatures could be used for triage; however, high cost and complexity could limit their use. For a confirmatory test, setting an optimal cut-off to maintain specificity across populations and settings is a challenge. mRNA signatures have shown the potential to quantitatively monitor response to treatment. No prognostic signatures can accurately predict progression to active TB over 2 years while short term prediction is possible. The management strategy should be defined for individuals with positive prognostic tests. FUNDING: Development of this manuscript was supported by funding received from the Stop TB Partnership and USAID for the New Diagnostics Working Group. The funders had no role in paper design, article selection and review, interpretation, or writing of the paper. |
format | Online Article Text |
id | pubmed-9294474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-92944742022-07-20 Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape Hamada, Yohhei Penn-Nicholson, Adam Krishnan, Sriram Cirillo, Daniela Maria Matteelli, Alberto Wyss, Romain Denkinger, Claudia M. Rangaka, Molebogeng X. Ruhwald, Morten Schumacher, Samuel G. eBioMedicine Review Advances in discovery and validation of diagnostic, prognostic and treatment-monitoring transcriptomic signatures of tuberculosis (TB) disease could accelerate the goal to end TB. We conducted a review to evaluate whether mRNA transcriptomics technologies are sufficiently mature to develop accurate next-generation TB diagnostic tests. Early studies tended to be limited in sample size, diversity of population groups, sample collection and processing methods, while recent prospective studies have addressed these limitations. Some of the existing signatures could be used for triage; however, high cost and complexity could limit their use. For a confirmatory test, setting an optimal cut-off to maintain specificity across populations and settings is a challenge. mRNA signatures have shown the potential to quantitatively monitor response to treatment. No prognostic signatures can accurately predict progression to active TB over 2 years while short term prediction is possible. The management strategy should be defined for individuals with positive prognostic tests. FUNDING: Development of this manuscript was supported by funding received from the Stop TB Partnership and USAID for the New Diagnostics Working Group. The funders had no role in paper design, article selection and review, interpretation, or writing of the paper. Elsevier 2022-07-15 /pmc/articles/PMC9294474/ /pubmed/35850011 http://dx.doi.org/10.1016/j.ebiom.2022.104174 Text en © 2022 Published by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Hamada, Yohhei Penn-Nicholson, Adam Krishnan, Sriram Cirillo, Daniela Maria Matteelli, Alberto Wyss, Romain Denkinger, Claudia M. Rangaka, Molebogeng X. Ruhwald, Morten Schumacher, Samuel G. Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape |
title | Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape |
title_full | Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape |
title_fullStr | Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape |
title_full_unstemmed | Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape |
title_short | Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape |
title_sort | are mrna based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - a review of evidence and the technological landscape |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294474/ https://www.ncbi.nlm.nih.gov/pubmed/35850011 http://dx.doi.org/10.1016/j.ebiom.2022.104174 |
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