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For: Lee J, Lee SY, Won DI, Cha SI, Park JY, Kim CH. Comparison of whole-blood interferon-γ assay and flow cytometry for the detection of tuberculosis infection. J Infect 2012;66:338-45. [PMID: 23010554 DOI: 10.1016/j.jinf.2012.08.020] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2012] [Revised: 08/01/2012] [Accepted: 08/16/2012] [Indexed: 12/01/2022]

For:	Lee J, Lee SY, Won DI, Cha SI, Park JY, Kim CH. Comparison of whole-blood interferon-γ assay and flow cytometry for the detection of tuberculosis infection. J Infect 2012;66:338-45. [PMID: 23010554 DOI: 10.1016/j.jinf.2012.08.020] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2012] [Revised: 08/01/2012] [Accepted: 08/16/2012] [Indexed: 12/01/2022]

Number

Cited by Other Article(s)

Peng L, Ma W, Zhong L, Yang J, Wu H, Zhu L, Huang X, Yang R, Li B, Ma W, Wu X, Song J, Luo S, Bao F, Liu A. Diagnostic Accuracy of Mycobacterium tuberculosis Antigen-Based Skin Tests (TBSTs) for Tuberculosis Infection Compared with TST and IGRA: A Network Meta-Analysis. Pathogens 2024;13:1050. [PMID: 39770310 PMCID: PMC11728611 DOI: 10.3390/pathogens13121050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2024] [Revised: 11/15/2024] [Accepted: 11/25/2024] [Indexed: 01/16/2025] Open

Abstract

The aim of this study was to evaluate the diagnostic accuracy of the IGRA, TST, and TBST by combining diagnostic test accuracy (DTA) analysis and network meta-analysis (NMA) to increase the reliability and accuracy of diagnostic methods and promote the eradication of TB. An electronic search of the PubMed, Embase, and Cochrane databases was conducted, from the date of establishment to September 30, 2024. Data were synthesized with frequentist random-effects network meta-analyses, a single-group rate meta-analysis algorithm, and a bivariate mixed-effects logistic regression model. Summarized receiver operating characteristic curves and Fagan nomograms were used to assess diagnostic accuracy and clinical utility. Deeks' funnel plots and the Quality Assessment of Diagnostic Accuracy Studies 2 tools were used to assess publication bias and risk of bias. Sources of heterogeneity were investigated using subgroup analyses. Forty-nine studies were identified. The diagnostic performance of the three diagnostic methods for TB infection is summarized as follows: the pooled sensitivity was 77.9% (95% confidence interval [CI], 0.69-0.856), and the pooled specificity was 80.3% (95% CI, 0.75-0.86). The sensitivity and specificity of the IGRA were 82.1% (95% CI, 0.78-0.86) and 81.1% (95% CI, 0.75-0.86), respectively, both higher than the TST. However, the TBST exhibited the highest specificity, at 98.5% (95% CI, 0.96-1.00), with a sensitivity of 78.7% (95% CI, 0.68-0.88), which was between that of the IGRA and TST. Subgroup analysis found that population categories and reference standards, among other factors, may be attributed to heterogeneity. In addition, the TST and IGRA add-on TBST can significantly improve diagnostic accuracy. In our study, the IGRA showed higher sensitivity, whereas the TBST showed higher specificity. Interestingly, under certain conditions, TST add-on TBST and IGRA add-on TBST showed better accuracy than TST and IGRA alone and could provide more effective guidance for clinical practice (PROSPERO CRD42023420136).

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Affiliation(s)

Li Peng Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Weijie Ma Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Lei Zhong Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Jiaru Yang Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Hanxin Wu Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Liangyu Zhu Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Xun Huang Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Rui Yang Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Bingxue Li Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Weijiang Ma Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Xinya Wu Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Jieqin Song Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Suyi Luo Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.)
Fukai Bao Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.) Research Center, Baoshan People’s Hospital, Baoshan 678000, China Yunnan Provincial Key Laboratory of Public Health and Biosafety, School of Public Health, Kunming Medical University, Kunming 650500, China
Aihua Liu Yunnan Province Key Laboratory of Children’s Major Diseases Research, School of Basic Medical Sciences, Kunming Medical University, Kunming 650500, China; (L.P.); (W.M.); (L.Z.); (J.Y.); (H.W.); (L.Z.); (X.H.); (R.Y.); (B.L.); (W.M.); (X.W.); (J.S.); (S.L.) Yunnan Provincial Key Laboratory of Public Health and Biosafety, School of Public Health, Kunming Medical University, Kunming 650500, China

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Jonas DE, Riley SR, Lee LC, Coffey CP, Wang SH, Asher GN, Berry AM, Williams N, Balio C, Voisin CE, Kahwati LC. Screening for Latent Tuberculosis Infection in Adults: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA 2023;329:1495-1509. [PMID: 37129650 DOI: 10.1001/jama.2023.3954] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]

Abstract

Importance

Latent tuberculosis infection (LTBI) can progress to active tuberculosis disease, causing morbidity and mortality.

Objective

To review the evidence on benefits and harms of screening for and treatment of LTBI in adults to inform the US Preventive Services Task Force (USPSTF).

Data Sources

PubMed/MEDLINE, Cochrane Library, and trial registries through December 3, 2021; references; experts; literature surveillance through January 20, 2023.

Study Selection

English-language studies of LTBI screening, LTBI treatment, or accuracy of the tuberculin skin test (TST) or interferon-gamma release assays (IGRAs). Studies of LTBI screening and treatment for public health surveillance or disease management were excluded.

Data Extraction and Synthesis

Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings; meta-analyses conducted when a sufficient number of similar studies were available.

Main Outcomes and Measures

Screening test accuracy; development of active tuberculosis disease, transmission, quality of life, mortality, and harms.

Results

A total of 113 publications were included (112 studies; N = 69 009). No studies directly evaluated the benefits and harms of screening. Pooled estimates for sensitivity of the TST were 0.80 (95% CI, 0.74-0.87) at the 5-mm induration threshold, 0.81 (95% CI, 0.76-0.87) at the 10-mm threshold, and 0.60 (95% CI, 0.46-0.74) at the 15-mm threshold. Pooled estimates for sensitivity of IGRA tests ranged from 0.81 (95% CI, 0.79-0.84) to 0.90 (95% CI, 0.87-0.92). Pooled estimates for specificity of screening tests ranged from 0.95 to 0.99. For treatment of LTBI, a large (n = 27 830), good-quality randomized clinical trial found a relative risk (RR) for progression to active tuberculosis at 5 years of 0.35 (95% CI, 0.24-0.52) for 24 weeks of isoniazid compared with placebo (number needed to treat, 112) and an increase in hepatotoxicity (RR, 4.59 [95% CI, 2.03-10.39]; number needed to harm, 279). A previously published meta-analysis reported that multiple regimens were efficacious compared with placebo or no treatment. Meta-analysis found greater risk for hepatotoxicity with isoniazid than with rifampin (pooled RR, 4.22 [95% CI, 2.21-8.06]; n = 7339).

Conclusions and Relevance

No studies directly evaluated the benefits and harms of screening for LTBI compared with no screening. TST and IGRAs were moderately sensitive and highly specific. Treatment of LTBI with recommended regimens reduced the risk of progression to active tuberculosis. Isoniazid was associated with higher rates of hepatotoxicity than placebo or rifampin.

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Affiliation(s)

Daniel E Jonas RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
Sean R Riley RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
Lindsey C Lee Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
Cory P Coffey Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
Shu-Hua Wang Department of Internal Medicine, The Ohio State University College of Medicine, Columbus Global One Health Initiative, The Ohio State University, Columbus
Gary N Asher RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park Department of Family Medicine, University of North Carolina at Chapel Hill
Anne M Berry Department of Family Medicine, University of North Carolina at Chapel Hill Department of Family Medicine and Community Health, Duke University, Durham, North Carolina
Niketa Williams Department of Family Medicine, University of North Carolina at Chapel Hill North Carolina Department of Health and Human Services, Division of Public Health, Raleigh
Casey Balio RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park Center for Rural Health Research, East Tennessee State University, Johnson City
Christiane E Voisin RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park Department of Internal Medicine, The Ohio State University College of Medicine, Columbus
Leila C Kahwati RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park RTI International, Research Triangle Park, North Carolina

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Saha A, Escuduero J, Layouni T, Richardson B, Hou S, Mugo N, Mujugira A, Celum C, Baeten JM, Lingappa J, John-Stewart GC, LaCourse SM, Shah JA. Mycobacterium tuberculosis-Specific T-Cell Responses Are Impaired During Late Pregnancy With Elevated Biomarkers of Tuberculosis Risk Postpartum. J Infect Dis 2022;225:1663-1674. [PMID: 34929030 PMCID: PMC9071276 DOI: 10.1093/infdis/jiab614] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 12/16/2021] [Indexed: 11/12/2022] Open

Affiliation(s)

Aparajita Saha Department of Medicine, University of Washington, Seattle, Washington, USA Department of Global Health, University of Washington, Seattle, Washington, USA
Jaclyn Escuduero Department of Global Health, University of Washington, Seattle, Washington, USA
Troy Layouni VA Puget Sound Health Care System, Seattle, Washington, USA
Barbra Richardson Department of Global Health, University of Washington, Seattle, Washington, USA Department of Biostatistics, University of Washington, Seattle, Washington, USA
Sharon Hou Department of Global Health, University of Washington, Seattle, Washington, USA
Nelly Mugo Kenya Medical Research Institute, Nairobi, Kenya
Andrew Mujugira Department of Global Health, University of Washington, Seattle, Washington, USA Infectious Diseases Institute, Makerere University, Kampala, Uganda
Connie Celum Department of Medicine, University of Washington, Seattle, Washington, USA Department of Global Health, University of Washington, Seattle, Washington, USA Department of Pediatrics, University of Washington, Seattle, Washington, USA
Jared M Baeten Department of Global Health, University of Washington, Seattle, Washington, USA Gilead Sciences, Foster City, California, USA
Jairam Lingappa Department of Medicine, University of Washington, Seattle, Washington, USA Department of Global Health, University of Washington, Seattle, Washington, USA Department of Biostatistics, University of Washington, Seattle, Washington, USA
Grace C John-Stewart Department of Medicine, University of Washington, Seattle, Washington, USA Department of Global Health, University of Washington, Seattle, Washington, USA Department of Pediatrics, University of Washington, Seattle, Washington, USA Department of Epidemiology, University of Washington, Seattle, Washington, USA
Sylvia M LaCourse Department of Medicine, University of Washington, Seattle, Washington, USA Department of Global Health, University of Washington, Seattle, Washington, USA
Javeed A Shah Department of Medicine, University of Washington, Seattle, Washington, USA Department of Global Health, University of Washington, Seattle, Washington, USA VA Puget Sound Health Care System, Seattle, Washington, USA

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Bender Ignacio RA, Long J, Saha A, Nguyen FK, Joudeh L, Valinetz E, Mendelsohn SC, Scriba TJ, Hatherill M, Janes H, Churchyard G, Buchbinder S, Duerr A, Shah JA, Hawn TR. Mycobacterium tuberculosis infection, immune activation, and risk of HIV acquisition. PLoS One 2022;17:e0267729. [PMID: 35503767 PMCID: PMC9064099 DOI: 10.1371/journal.pone.0267729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 04/12/2022] [Indexed: 12/15/2022] Open

Abstract

BACKGROUND

Although immune activation is associated with HIV acquisition, the nature of inflammatory profiles that increase HIV risk, which may include responses to M. tuberculosis (Mtb) infection, are not well characterized.

METHODS

We conducted a nested case-control study using cryopreserved samples from persons who did and did not acquire HIV during the multinational Step clinical trial of the MRKAd5 HIV-1 vaccine. PBMCs from the last HIV-negative sample from incident HIV cases and controls were stimulated with Mtb-specific antigens (ESAT-6/CFP-10) and analyzed by flow cytometry with intracellular cytokine staining and scored with COMPASS. We measured inflammatory profiles with five Correlates of TB Risk (CoR) transcriptomic signatures. Our primary analysis examined the association of latent Mtb infection (LTBI; IFNγ+CD4+ T cell frequency) or RISK6 CoR signature with HIV acquisition. Conditional logistic regression analyses, adjusted for known predictors of HIV acquisition, were employed to assess whether TB-associated immune markers were associated with HIV acquisition.

RESULTS

Among 465 participants, LTBI prevalence (21.5% controls vs 19.1% cases, p = 0.51) and the RISK6 signature were not higher in those who acquired HIV. In exploratory analyses, Mtb antigen-specific polyfunctional CD4+ T cell COMPASS scores (aOR 0.96, 95% CI 0.77, 1.20) were not higher in those who acquired HIV. Two CoR signatures, Sweeney3 (aOR 1.38 (1.07, 1.78) per SD change) and RESPONSE5 (0.78 (0.61, 0.98)), were associated with HIV acquisition. The transcriptomic pattern used to differentiate active vs latent TB (Sweeney3) was most strongly associated with acquiring HIV.

CONCLUSIONS

LTBI, Mtb polyfunctional antigen-specific CD4+ T cell activation, and RISK6 were not identified as risks for HIV acquisition. In exploratory transcriptomic analyses, two CoR signatures were associated with HIV risk after adjustment for known behavioral and clinical risk factors. We identified host gene expression signatures associated with HIV acquisition, but the observed effects are likely not mediated through Mtb infection.

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Affiliation(s)

Rachel A. Bender Ignacio Department of Medicine, University of Washington, Seattle, WA, United States of America Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America * E-mail:
Jessica Long Department of Medicine, University of Washington, Seattle, WA, United States of America
Aparajita Saha Department of Medicine, University of Washington, Seattle, WA, United States of America
Felicia K. Nguyen Department of Medicine, University of Washington, Seattle, WA, United States of America
Lara Joudeh Department of Medicine, University of Washington, Seattle, WA, United States of America
Ethan Valinetz Department of Medicine, University of Washington, Seattle, WA, United States of America
Simon C. Mendelsohn South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
Thomas J. Scriba South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
Mark Hatherill South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
Holly Janes Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
Gavin Churchyard Aurum Institute, Parktown, South Africa School of Public Health, University of Witwatersrand, Johannesburg, South Africa Department of Medicine, Vanderbilt University, Nashville, TN, United States of America
Susan Buchbinder San Francisco Department of Public Health and Departments of Medicine and Epidemiology, University of California San Francisco, San Francisco, CA, United States of America
Ann Duerr Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
Javeed A. Shah Department of Medicine, University of Washington, Seattle, WA, United States of America Veteran Affairs Puget Sound Healthcare System, Seattle, WA, United States of America
Thomas R. Hawn Department of Medicine, University of Washington, Seattle, WA, United States of America

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Development of an improved ESAT-6 and CFP-10 peptide-based cytokine flow cytometric assay for bovine tuberculosis. Comp Immunol Microbiol Infect Dis 2015;42:1-7. [DOI: 10.1016/j.cimid.2015.07.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Revised: 07/07/2015] [Accepted: 07/29/2015] [Indexed: 11/18/2022]

Papageorgiou CV, Anastasopoulos A, Ploussi M, Leventopoulos M, Karabela S, Fotiadis K, Papavasileiou A, Vogiatzakis E, Ioakeimidis D, Gritzapis AD, Poulakis N. Flow cytometry analysis of CD4+IFN-γ+ T-cells for the diagnosis of mycobacterium tuberculosis infection. CYTOMETRY PART B-CLINICAL CYTOMETRY 2015. [DOI: 10.1002/cyto.b.21275] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]

Multifunctional Analysis of CD4+ T-Cell Response as Immune-Based Model for Tuberculosis Detection. J Immunol Res 2015;2015:217287. [PMID: 26339657 PMCID: PMC4539126 DOI: 10.1155/2015/217287] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 12/30/2014] [Accepted: 12/30/2014] [Indexed: 11/17/2022] Open

Sauzullo I, Mengoni F, Mascia C, Rossi R, Lichtner M, Vullo V, Mastroianni CM. Treatment of latent tuberculosis infection induces changes in multifunctional Mycobacterium tuberculosis-specific CD4+ T cells. Med Microbiol Immunol 2015;205:37-45. [PMID: 26108901 DOI: 10.1007/s00430-015-0424-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 06/12/2015] [Indexed: 01/09/2023]

Kim CH, Lee J. Reply to Hong et al. Clin Infect Dis 2014;59:142-3. [DOI: 10.1093/cid/ciu249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open

Sauzullo I, Scrivo R, Mengoni F, Ermocida A, Coppola M, Valesini G, Vullo V, Mastroianni CM. Multi-functional flow cytometry analysis of CD4+ T cells as an immune biomarker for latent tuberculosis status in patients treated with tumour necrosis factor (TNF) antagonists. Clin Exp Immunol 2014;176:410-7. [PMID: 24528189 DOI: 10.1111/cei.12290] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/04/2014] [Indexed: 12/11/2022] Open

Abstract

Although monitoring tuberculosis (TB) infection during long-term treatment with tumour necrosis factor (TNF) antagonists is of great importance, no monitoring strategy has yet proved successful. Indeed, even the newly proposed interferon-gamma release assays (IGRAs) are known to produce dynamic changes in IFN-γ plasma levels, making them unreliable indicators of patients' pathological/clinical status. We used intracellular cytokine flow cytometry (ICCFC) to investigate the performance of multi-functional CD4(+) T cells producing IFN-γ, interleukin (IL)-2 and/or TNF in response to Mycobacterium tuberculosis-specific antigens in subjects treated with TNF antagonists. Patients were classified into three groups based on their TB status before commencement of treatment and on IFN-γ level fluctuations evaluated by IGRA during a 36-month follow-up period. The cytokine profile of M. tuberculosis-specific CD4(+) T cells showed that latent tuberculosis infection (LTBI) subjects had a higher frequency of double-positive IFN-γ(+) IL-2(+) CD4(+) T cells and triple-positive IFN-γ(+) IL-2(+) TNF(+) CD4(+) T cells compared to those without LTBI, who showed IFN-γ-level fluctuations over time. In contrast, this latter group of patients showed similar proportions of cells producing IFN-γ alone, IL-2 alone and IL-2 in combination with TNF in response to M. tuberculosis-specific antigens. It therefore appears that patients with and without LTBI infection are characterized by different intracellular cytokine profiles. This is the first study evaluating ICCFC in patients treated with TNF antagonists, and suggests that multi-functional analysis of CD4(+) T cells could be useful for ruling out TB infection in patients classified at screening as LTBI-negative but who show IGRA fluctuations under long-term TNF antagonist treatment.

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Kim CH, Choi KJ, Yoo SS, Lee SY, Won DI, Lim JO, Cha SI, Park JY, Lee J. Comparative analysis of whole-blood interferon-γ and flow cytometry assays for detecting post-treatment immune responses in patients with active tuberculosis. CYTOMETRY PART B-CLINICAL CYTOMETRY 2013;86:236-43. [PMID: 23959689 DOI: 10.1002/cyto.b.21110] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2013] [Revised: 06/21/2013] [Accepted: 06/24/2013] [Indexed: 11/08/2022]