Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review
Background. Immune parameters (IP) have been extensively studied to distinguish between latent tuberculosis (LTBI) and active tuberculosis (TB). Objective. To determine the IP associated with LTBI, compared to active TB and individuals not infected by M. tuberculosis published in literature. Methods...
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doaj-0d9cd7831f2f4f48945a32aa6cbe44c52020-11-25T02:00:30ZengHindawi LimitedJournal of Immunology Research2314-88612314-71562020-01-01202010.1155/2020/80741838074183Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic ReviewMariana Herrera0Cristian Vera1Yoav Keynan2Zulma Vanessa Rueda3Grupo de Epidemiología, Facultad Nacional de Salud Pública, Universidad de Antioquia, Medellín, ColombiaGrupo de Investigación en Salud Pública, Universidad Pontificia Bolivariana, Medellín, ColombiaDepartments of Internal Medicine, Medical Microbiology & Infectious Diseases and Community Health Sciences, University of Manitoba, Winnipeg, CanadaGrupo de Investigación en Salud Pública, Universidad Pontificia Bolivariana, Medellín, ColombiaBackground. Immune parameters (IP) have been extensively studied to distinguish between latent tuberculosis (LTBI) and active tuberculosis (TB). Objective. To determine the IP associated with LTBI, compared to active TB and individuals not infected by M. tuberculosis published in literature. Methods. We conducted a systematic search using Google Scholar and PubMed databases, combining the MeSH terms latent tuberculosis, Mycobacterium tuberculosis, cytokines, and biological markers, with the free terms, biomarkers and cytokines. Spanish, English, and Portuguese articles comparing the concentration of IP associated with LTBI, either in plasma/serum or in vitro, in adults and nonimmunocompromised versus individuals with TB or without M. tuberculosis infection between 2006 July and 2018 July were included. Two blinded reviewers carried out the searches, read the abstracts, and selected the articles for analysis. Participants’ information, diagnostic criteria, IP, detection methods, and biases were collected. Results. We analyzed 36 articles (of 637 abstracts) with 93 different biomarkers in different samples. We found 24 parameters that were increased only in active TB (TGF-α, CSF3, CSF2, CCL1 [I-309], IL-7, TGF-β1, CCL3 [MIP-1α], sIL-2R, TNF-β, CCL7 [MCP-3], IFN-α, fractalkine, I-TAG, CCL8 [MCP-2], CCL21 [6Ckine], PDGF, IL-22, VEGF-A, LXA4, PGE2, PGF2α, sCD163, sCD14, and 15-Epi-LXA4), five were elevated in LTBI (IL-5, IL-17F, IL-1, CCL20 [MIP-3α], and ICAM-1), and two substances were increased among uninfected individuals (IL-23 and basic FGF). We found high heterogeneity between studies including failure to account for the time/illness of the individuals studied; varied samples and protocols; different clinical classification of TB; different laboratory methods for IP detection, which in turn leads to variable units of measurement and assay sensitivities; and selection bias regarding TST and booster effect. None of the studies adjusted the analysis for the effect of ethnicity. Conclusions. It is mandatory to harmonize the study of immune parameters for LTBI diagnosis. This systematic review is registered with PROSPERO CRD42017073289.http://dx.doi.org/10.1155/2020/8074183 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mariana Herrera Cristian Vera Yoav Keynan Zulma Vanessa Rueda |
spellingShingle |
Mariana Herrera Cristian Vera Yoav Keynan Zulma Vanessa Rueda Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review Journal of Immunology Research |
author_facet |
Mariana Herrera Cristian Vera Yoav Keynan Zulma Vanessa Rueda |
author_sort |
Mariana Herrera |
title |
Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review |
title_short |
Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review |
title_full |
Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review |
title_fullStr |
Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review |
title_full_unstemmed |
Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review |
title_sort |
gaps in study design for immune parameter research for latent tuberculosis infection: a systematic review |
publisher |
Hindawi Limited |
series |
Journal of Immunology Research |
issn |
2314-8861 2314-7156 |
publishDate |
2020-01-01 |
description |
Background. Immune parameters (IP) have been extensively studied to distinguish between latent tuberculosis (LTBI) and active tuberculosis (TB). Objective. To determine the IP associated with LTBI, compared to active TB and individuals not infected by M. tuberculosis published in literature. Methods. We conducted a systematic search using Google Scholar and PubMed databases, combining the MeSH terms latent tuberculosis, Mycobacterium tuberculosis, cytokines, and biological markers, with the free terms, biomarkers and cytokines. Spanish, English, and Portuguese articles comparing the concentration of IP associated with LTBI, either in plasma/serum or in vitro, in adults and nonimmunocompromised versus individuals with TB or without M. tuberculosis infection between 2006 July and 2018 July were included. Two blinded reviewers carried out the searches, read the abstracts, and selected the articles for analysis. Participants’ information, diagnostic criteria, IP, detection methods, and biases were collected. Results. We analyzed 36 articles (of 637 abstracts) with 93 different biomarkers in different samples. We found 24 parameters that were increased only in active TB (TGF-α, CSF3, CSF2, CCL1 [I-309], IL-7, TGF-β1, CCL3 [MIP-1α], sIL-2R, TNF-β, CCL7 [MCP-3], IFN-α, fractalkine, I-TAG, CCL8 [MCP-2], CCL21 [6Ckine], PDGF, IL-22, VEGF-A, LXA4, PGE2, PGF2α, sCD163, sCD14, and 15-Epi-LXA4), five were elevated in LTBI (IL-5, IL-17F, IL-1, CCL20 [MIP-3α], and ICAM-1), and two substances were increased among uninfected individuals (IL-23 and basic FGF). We found high heterogeneity between studies including failure to account for the time/illness of the individuals studied; varied samples and protocols; different clinical classification of TB; different laboratory methods for IP detection, which in turn leads to variable units of measurement and assay sensitivities; and selection bias regarding TST and booster effect. None of the studies adjusted the analysis for the effect of ethnicity. Conclusions. It is mandatory to harmonize the study of immune parameters for LTBI diagnosis. This systematic review is registered with PROSPERO CRD42017073289. |
url |
http://dx.doi.org/10.1155/2020/8074183 |
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