中国防痨杂志 ›› 2023, Vol. 45 ›› Issue (3): 253-259.doi: 10.19982/j.issn.1000-6621.20220391
收稿日期:
2022-10-09
出版日期:
2023-03-10
发布日期:
2023-03-07
通信作者:
王瑞白
E-mail:wangruibai@icdc.cn
Xia Hui1, Wang Ruibai2(), Zhao Yanlin1
Received:
2022-10-09
Online:
2023-03-10
Published:
2023-03-07
Contact:
Wang Ruibai
E-mail:wangruibai@icdc.cn
摘要:
中国是结核病及结核分枝杆菌潜伏感染高负担国家。结核分枝杆菌潜伏感染及活动性结核病的治疗管理和预后完全不同,现有潜伏感染诊断技术并不能有效预测和鉴别活动性结核病的进展和发生。因此,需要探索更加准确的生物标志物。本文主要就结核分枝杆菌潜伏感染和活动性结核病鉴别诊断生物标志物研究进展及问题进行总结和归纳,并展望其发展方向。
中图分类号:
夏辉, 王瑞白, 赵雁林. 结核分枝杆菌潜伏感染与活动性结核病的鉴别诊断[J]. 中国防痨杂志, 2023, 45(3): 253-259. doi: 10.19982/j.issn.1000-6621.20220391
Xia Hui, Wang Ruibai, Zhao Yanlin. Differential diagnosis between latent tuberculosis infection and active tuberculosis[J]. Chinese Journal of Antituberculosis, 2023, 45(3): 253-259. doi: 10.19982/j.issn.1000-6621.20220391
[1] | World Health Organization.Global tuberculosis report 2022. Geneva: World Health Organization, 2022. |
[2] |
高磊, 张慧, 胡茂桂, 等. 基于多中心调查数据和空间统计模型的全国结核分枝杆菌潜伏感染率估算. 中国防痨杂志, 2022, 44(1): 54-59. doi:10.19982/j.issn.1000-6621.20210661.
doi: 10.19982/j.issn.1000-6621.20210661 |
[3] |
Behr MA, Edelstein PH, Ramakrishnan L. Is Mycobacterium tuberculosis infection life long? BMJ, 2019, 367: I5770. doi:10.1136/bmj.15770.
doi: 10.1136/bmj.15770 |
[4] |
Rozot V, Vigano S, Mazza-Stalder J, et al. Mycobacterium tuberculosis-specific CD8+ T cells are functionally and phenotypically different between latent infection and active disease. Eur J Immunol, 2013, 43(6): 1568-1577. doi:10.1002/eji.201243262.
doi: 10.1002/eji.201243262 URL |
[5] |
Petruccioli E, Scriba TJ, Petrone L, et al. Correlates of tuberculosis risk: predictive biomarkers for progression to active tuberculosis. Eur Respir J, 2016, 48(6): 1751-1763. doi:10.1183/13993003.01012-2016.
doi: 10.1183/13993003.01012-2016 pmid: 27836953 |
[6] | World Health Organization. WHO consolidated guidelines on tuberculosis: module 3: diagnosis: tests for TB infection. Geneva: World Health Organization, 2022. |
[7] |
Chee CBE, Reves R, Zhang Y, et al. Latent tuberculosis infection: Opportunities and challenges. Respirology, 2018, 23(10): 893-900. doi:10.1111/resp.13346.
doi: 10.1111/resp.13346 pmid: 29901251 |
[8] |
Lillebaek T, Dirksen A, Baess I, et al. Molecular evidence of endogenous reactivation of Mycobacterium tuberculosis after 33 years of latent infection. J Infect Dis, 2002, 185(3): 401-404. doi:10.1086/338342.
doi: 10.1086/338342 pmid: 11807725 |
[9] |
Achkar JM, Jenny-Avital ER. Incipient and subclinical tuberculosis: defining early disease states in the context of host immune response. J Infect Dis, 2011, 204 Suppl 4 (Suppl 4): S1179-S1186. doi:10.1093/infdis/jir451.
doi: 10.1093/infdis/jir451 |
[10] |
Andersen P, Munk ME, Pollock JM, et al. Specific immune-based diagnosis of tuberculosis. Lancet, 2000, 356(9235): 1099-1104. doi:10.1016/s0140-6736(00)02742-2.
doi: 10.1016/s0140-6736(00)02742-2 pmid: 11009160 |
[11] |
Meier NR, Jacobsen M, Ottenhoff THM, et al. A Systematic Review on Novel Mycobacterium tuberculosis Antigens and Their Discriminatory Potential for the Diagnosis of Latent and Active Tuberculosis. Front Immunol, 2018, 9: 2476. doi:10.3389/fimmu.2018.02476.
doi: 10.3389/fimmu.2018.02476 URL |
[12] |
Gong W, Wu X. Differential Diagnosis of Latent Tuberculosis Infection and Active Tuberculosis: A Key to a Successful Tuberculosis Control Strategy. Front Microbiol, 2021, 12: 745592. doi:10.3389/fmicb.2021.745592.
doi: 10.3389/fmicb.2021.745592 URL |
[13] |
Estévez O, Anibarro L, Garet E, et al. Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection. PLoS One, 2020, 15(7): e0235859. doi:10.1371/journal.pone.0235859.
doi: 10.1371/journal.pone.0235859 |
[14] |
Fisher KL, Moodley D, Rajkumar-Bhugeloo K, et al. Elevated IP-10 at the Protein and Gene Level Associates With Pulmonary TB. Front Cell Infect Microbiol, 2022, 12: 908144. doi:10.3389/fcimb.2022.908144.
doi: 10.3389/fcimb.2022.908144 URL |
[15] |
Sun Q, Wei W, Sha W. Potential Role for Mycobacterium tuberculosis Specific IL-2 and IFN-γ Responses in Discriminating between Latent Infection and Active Disease after Long-Term Stimulation. PLoS One, 2016, 11(12): e0166501. doi:10.1371/journal.pone.0166501.
doi: 10.1371/journal.pone.0166501 |
[16] |
Qiu B, Liu Q, Li Z, et al. Evaluation of cytokines as a biomarker to distinguish active tuberculosis from latent tuberculosis infection: a diagnostic meta-analysis. BMJ Open, 2020, 10(10): e039501. doi:10.1136/bmjopen-2020-039501.
doi: 10.1136/bmjopen-2020-039501 URL |
[17] |
贾红彦, 董静, 张宗德, 等. 结核分枝杆菌感染的免疫学检测技术研究进展及临床应用现状. 中国防痨杂志, 2022, 44(7): 720-726. doi:10.19982/j.issn.1000-6621.20220103.
doi: 10.19982/j.issn.1000-6621.20220103 |
[18] |
Riou C, Berkowitz N, Goliath R, et al. Analysis of the Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells to Discriminate Latent from Active Tuberculosis in HIV-Uninfected and HIV-Infected Individuals. Front Immunol, 2017, 8: 968. doi:10.3389/fimmu.2017.00968.
doi: 10.3389/fimmu.2017.00968 URL |
[19] |
Garand M, Goodier M, Owolabi O, et al. Functional and Phenotypic Changes of Natural Killer Cells in Whole Blood during Mycobacterium tuberculosis Infection and Disease. Front Immunol, 2018, 9: 257. doi:10.3389/fimmu.2018.00257.
doi: 10.3389/fimmu.2018.00257 URL |
[20] |
Silveira-Mattos PS, Barreto-Duarte B, Vasconcelos B, et al. Differential Expression of Activation Markers by Mycobacterium tuberculosis-specific CD4+ T Cell Distinguishes Extrapulmonary From Pulmonary Tuberculosis and Latent Infection. Clin Infect Dis, 2020, 71(8): 1905-1911. doi:10.1093/cid/ciz1070.
doi: 10.1093/cid/ciz1070 pmid: 31665254 |
[21] |
Mantei A, Meyer T, Schürmann M, et al. Mycobacterium tuberculosis-specific CD 4 T-cell scoring discriminates tuberculosis infection from disease. Eur Respir J, 2022, 60(1): 2101780. doi:10.1183/13993003.01780-2021.
doi: 10.1183/13993003.01780-2021 |
[22] |
Latorre I, Fernández-Sanmartín MA, Muriel-Moreno B, et al. Study of CD27 and CCR4 Markers on Specific CD4+ T-Cells as Immune Tools for Active and Latent Tuberculosis Management. Front Immunol, 2018, 9: 3094. doi:10.3389/fimmu.2018.03094.
doi: 10.3389/fimmu.2018.03094 pmid: 30687314 |
[23] |
Luo Y, Xue Y, Mao L, et al. Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection. Front Immunol, 2021, 12: 721013. doi:10.3389/fimmu.2021.721013.
doi: 10.3389/fimmu.2021.721013 URL |
[24] |
Acharya MP, Pradeep SP, Murthy VS, et al. CD38+CD27-TNF-α+ on Mtb-specific CD4+ T Cells Is a Robust Biomarker for Tuberculosis Diagnosis. Clin Infect Dis, 2021, 73(5): 793-801. doi:10.1093/cid/ciab144.
doi: 10.1093/cid/ciab144 pmid: 34492697 |
[25] |
Corrêa RDS, Rodrigues LS, Pereira LHL, et al. Neutrophil CD64 expression levels in IGRA-positive individuals distinguish latent tuberculosis from active disease. Mem Inst Oswaldo Cruz, 2019, 114: e180579. doi:10.1590/0074-02760180579.
doi: 10.1590/0074-02760180579 URL |
[26] |
La Manna MP, Orlando V, Dieli F, et al. Quantitative and qualitative profiles of circulating monocytes may help identi-fying tuberculosis infection and disease stages. PLoS One, 2017, 12(2): e0171358. doi:10.1371/journal.pone.0171358.
doi: 10.1371/journal.pone.0171358 |
[27] |
Estévez O, Anibarro L, Garet E, et al. Multi-parameter flow cytometry immunophenotyping distinguishes different stages of tuberculosis infection. J Infect, 2020, 81(1): 57-71. doi:10.1016/j.jinf.2020.03.064.
doi: S0163-4453(20)30218-8 pmid: 32330526 |
[28] |
Arrigucci R, Lakehal K, Vir P, et al. Active Tuberculosis Is Characterized by Highly Differentiated Effector Memory Th1 Cells. Front Immunol, 2018, 9: 2127. doi:10.3389/fimmu.2018.02127.
doi: 10.3389/fimmu.2018.02127 pmid: 30283456 |
[29] |
Luo Y, Xue Y, Cai Y, et al. Lymphocyte Non-Specific Function Detection Facilitating the Stratification of Mycobacterium tuberculosis Infection. Front Immunol, 2021, 12: 641378. doi:10.3389/fimmu.2021.641378.
doi: 10.3389/fimmu.2021.641378 URL |
[30] |
Grassi G, Vanini V, De Santis F, et al. PMN-MDSC Frequency Discriminates Active Versus Latent Tuberculosis and Could Play a Role in Counteracting the Immune-Mediated Lung Damage in Active Disease. Front Immunol, 2021, 12: 594376. doi:10.3389/fimmu.2021.594376.
doi: 10.3389/fimmu.2021.594376 URL |
[31] |
Berry MP, Graham CM, McNab FW, et al. An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis. Nature, 2010, 466(7309): 973-977. doi:10.1038/nature09247.
doi: 10.1038/nature09247 URL |
[32] |
Leong S, Zhao Y, Joseph NM, et al. Existing blood transcriptional classifiers accurately discriminate active tuberculosis from latent infection in individuals from south India. Tuberculosis (Edinb), 2018, 109: 41-51. doi:10.1016/j.tube.2018.01.002.
doi: 10.1016/j.tube.2018.01.002 URL |
[33] |
Jacobsen M, Repsilber D, Gutschmidt A, et al. Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis. J Mol Med (Berl), 2007, 85(6): 613-621. doi:10.1007/s00109-007-0157-6.
doi: 10.1007/s00109-007-0157-6 URL |
[34] |
Kaforou M, Wright VJ, Oni T, et al. Detection of tuberculosis in HIV-infected and -uninfected African adults using whole blood RNA expression signatures: a case-control study. PLoS Med, 2013, 10(10): e1001538. doi:10.1371/journal.pmed.1001538.
doi: 10.1371/journal.pmed.1001538 |
[35] |
Zak DE, Penn-Nicholson A, Scriba TJ, et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet, 2016, 387(10035): 2312-2322. doi:10.1016/S0140-6736(15)01316-1.
doi: S0140-6736(15)01316-1 pmid: 27017310 |
[36] |
Sweeney TE, Braviak L, Tato CM, et al. Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis. Lancet Respir Med, 2016, 4(3): 213-224. doi:10.1016/S2213-2600(16)00048-5.
doi: 10.1016/S2213-2600(16)00048-5 pmid: 26907218 |
[37] |
Warsinske HC, Rao AM, Moreira FMF, et al. Assessment of Validity of a Blood-Based 3-Gene Signature Score for Progression and Diagnosis of Tuberculosis, Disease Severity, and Treatment Response. JAMA Netw Open, 2018, 1(6): e183779. doi:10.1001/jamanetworkopen.2018.3779.
doi: 10.1001/jamanetworkopen.2018.3779 URL |
[38] |
Petrilli JD, Araújo LE, da Silva LS, et al. Whole blood mRNA expression-based targets to discriminate active tuberculosis from latent infection and other pulmonary diseases. Sci Rep, 2020, 10(1): 22072. doi:10.1038/s41598-020-78793-2.
doi: 10.1038/s41598-020-78793-2 pmid: 33328540 |
[39] |
Kim H, Wang X, Jin P. Developing DNA methylation-based diagnostic biomarkers. J Genet Genomics, 2018, 45(2): 87-97. doi:10.1016/j.jgg.2018.02.003.
doi: S1673-8527(18)30027-4 pmid: 29496486 |
[40] |
Gauba K, Gupta S, Shekhawat J, et al. Immunomodulation by epigenome alterations in Mycobacterium tuberculosis infection. Tuberculosis (Edinb), 2021, 128: 102077. doi:10.1016/j.tube.2021.102077.
doi: 10.1016/j.tube.2021.102077 URL |
[41] |
Du Y, Gao X, Yan J, et al. Relationship between DNA Methy-lation Profiles and Active Tuberculosis Development from Latent Infection: a Pilot Study in Nested Case-Control Design. Microbiol Spectr, 2022, 10(3): e0058622. doi:10.1128/spectrum.00586-22.
doi: 10.1128/spectrum.00586-22 |
[42] |
Wang C, Yang S, Sun G, et al. Comparative miRNA expression profiles in individuals with latent and active tuberculosis. PLoS One, 2011, 6(10): e25832. doi:10.1371/journal.pone.0025832.
doi: 10.1371/journal.pone.0025832 URL |
[43] |
Looney M, Lorenc R, Halushka MK, et al. Key Macrophage Responses to Infection With Mycobacterium tuberculosis Are Co-Regulated by microRNAs and DNA Methylation. Front Immunol, 2021, 12: 685237. doi:10.3389/fimmu.2021.685237.
doi: 10.3389/fimmu.2021.685237 URL |
[44] |
de Araujo LS, Ribeiro-Alves M, Leal-Calvo T, et al. Reprogramming of Small Noncoding RNA Populations in Peripheral Blood Reveals Host Biomarkers for Latent and Active Mycobacterium tuberculosis Infection. mBio, 2019, 10(6): e01037-19. doi:10.1128/mBio.01037-19.
doi: 10.1128/mBio.01037-19 |
[45] |
Lu LL, Chung AW, Rosebrock TR, et al. A Functional Role for Antibodies in Tuberculosis. Cell, 2016, 167(2): 433-443.e14. doi:10.1016/j.cell.2016.08.072.
doi: S0092-8674(16)31170-9 pmid: 27667685 |
[46] |
Grace PS, Dolatshahi S, Lu LL, et al. Antibody Subclass and Glycosylation Shift Following Effective TB Treatment. Front Immunol, 2021, 12: 679973. doi:10.3389/fimmu.2021.679973.
doi: 10.3389/fimmu.2021.679973 URL |
[47] |
Broger T, Basu Roy R, Filomena A, et al. Diagnostic Performance of Tuberculosis-Specific IgG Antibody Profiles in Patients with Presumptive Tuberculosis from Two Continents. Clin Infect Dis, 2017, 64(7): 947-955. doi:10.1093/cid/cix023.
doi: 10.1093/cid/cix023 pmid: 28362937 |
[48] |
Lubbers R, Sutherland JS, Goletti D, et al. Complement Component C1q as Serum Biomarker to Detect Active Tuberculosis. Front Immunol, 2018, 9: 2427. doi:10.3389/fimmu.2018.02427.
doi: 10.3389/fimmu.2018.02427 pmid: 30405622 |
[49] |
Fernández-Carballo BL, Broger T, Wyss R, et al. Toward the Development of a Circulating Free DNA-Based In Vitro Diagnostic Test for Infectious Diseases: a Review of Evidence for Tuberculosis. J Clin Microbiol, 2019, 57(4): e01234-18. doi:10.1128/JCM.01234-18.
doi: 10.1128/JCM.01234-18 |
[50] |
Pan SW, Su WJ, Chan YJ, et al. Mycobacterium tuberculosis-derived circulating cell-free DNA in patients with pulmonary tuberculosis and persons with latent tuberculosis infection. PLoS One, 2021, 16(6): e0253879. doi:10.1371/journal.pone.0253879.
doi: 10.1371/journal.pone.0253879 URL |
[51] |
Burnham P, Dadhania D, Heyang M, et al. Urinary cell-free DNA is a versatile analyte for monitoring infections of the urinary tract. Nat Commun, 2018, 9(1): 2412. doi:10.1038/s41467-018-04745-0.
doi: 10.1038/s41467-018-04745-0 pmid: 29925834 |
[1] | 陈瑞麒, 张明五, 王伟, 陈松华, 柳正卫, 陈彬. 浙江省常山县农村老年人结核分枝杆菌潜伏感染情况及影响因素[J]. 中国防痨杂志, 2024, 46(4): 383-389. |
[2] | 尚雪恬, 董静, 黄麦玲, 孙琦, 贾红彦, 张蓝月, 刘秋月, 姚明旭, 王颖超, 姬秀秀, 杜博平, 邢爱英, 潘丽萍. 结核分枝杆菌潜伏感染者外周血单个核细胞转录组学研究[J]. 中国防痨杂志, 2024, 46(4): 449-460. |
[3] | 姚阳阳, 梁长华, 韩东明, 崔俊伟, 潘犇, 王慧慧, 魏正琦, 甄思雨, 危涵羽. 基于CT影像组学结合临床特征鉴别肺结核与非结核分枝杆菌肺病的研究[J]. 中国防痨杂志, 2024, 46(3): 302-310. |
[4] | 国家呼吸内科医疗质量控制中心, 中华医学会结核病学分会, 中国防痨协会结核病控制专业分会, 中日友好医院. 综合医疗机构肺结核早期发现临床实践指南[J]. 中国防痨杂志, 2024, 46(2): 127-140. |
[5] | 张静, 付若楠, 王森路, 冯建宇, 张玲, 古丽娜·巴德尔汗, 祖力卡提阿衣·阿布都拉, 王新旗. 高负担地区肺结核密切接触者中结核分枝杆菌潜伏感染者预防性治疗接受意愿及影响因素研究[J]. 中国防痨杂志, 2024, 46(2): 165-172. |
[6] | 姜晓颖, 刘静, 张治国, 张文, 高孟秋, 杨新婷, 弭凤玲. 196例初治病原学阳性肺结核患者结核感染控制知识知晓情况调查[J]. 中国防痨杂志, 2024, 46(2): 213-220. |
[7] | 尚雪恬, 潘丽萍. 组织激肽释放酶家族在病原微生物感染中的作用[J]. 中国防痨杂志, 2024, 46(2): 239-244. |
[8] | 何翼君, 成君, 高磊. 循序渐进:系统性开展结核分枝杆菌潜伏感染流行病学调查[J]. 中国防痨杂志, 2024, 46(1): 1-7. |
[9] | 张丽帆, 马亚楠, 邹小青, 张月秋, 张奉春, 曾小峰, 赵岩, 刘升云, 左晓霞, 吴华香, 武丽君, 李鸿斌, 张志毅, 陈盛, 朱平, 张缪佳, 齐文成, 刘毅, 刘花香, 侍效春, 刘晓清, 中国风湿免疫病人群活动性结核病的流行病学调查和治疗效果及预后研究课题组. 风湿免疫病患者结核分枝杆菌潜伏感染率及相关影响因素的多中心横断面研究[J]. 中国防痨杂志, 2024, 46(1): 29-39. |
[10] | 杜毓, 张海鹏, 王鹏. 分枝杆菌噬菌体的研究现状及应用进展[J]. 中国防痨杂志, 2023, 45(9): 897-903. |
[11] | 毕秀丽, 耿红, 金瑾. 髓系细胞和CD4+ T细胞在结核分枝杆菌感染和免疫病理中的作用[J]. 中国防痨杂志, 2023, 45(9): 904-912. |
[12] | 郭同磊, 辛赫男, 高磊. 《世界卫生组织结核病整合指南模块1:结核病预防性治疗》解读[J]. 中国防痨杂志, 2023, 45(8): 723-727. |
[13] | 汪敏, 袁园, 谭守勇, 杨子龙, 冯治宇, 张宏, 吴迪, 陈泽莹, 黄显林, 邝浩斌. 2型糖尿病合并初治菌阳肺结核患者肺部广泛病灶和空洞发生的危险因素分析[J]. 中国防痨杂志, 2023, 45(8): 761-767. |
[14] | 贝呈, 李蒙, 高谦. 基于血液样本的转录标识物在结核病诊断中的研究进展[J]. 中国防痨杂志, 2023, 45(8): 801-807. |
[15] | 王涵飞, 赵雁林, 徐彩红. 亚临床结核病研究进展[J]. 中国防痨杂志, 2023, 45(8): 808-813. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||