|
|
|
| Research progress on the detection techniques and diagnosis of latent tuberculosis infection |
| CHEN Guozhi1, ZHAO Lina2
|
1. Yueqing Center for Disease Control and Prevention (Yueqing Institute of Public Health Supervision), Yueqing, Zhejiang 325600, China;
2. Wenzhou Center for Disease Control and Prevention (Wenzhou Institute of Public Health Supervision), Wenzhou, Zhejiang 325000, China |
|
|
|
|
Abstract Latent tuberculosis infection (LTBI) refers to a specific immune state after Mycobacterium tuberculosis infection, affecting approximately one quarter of the global population and contributing to 85%-90% of active pulmonary tuberculosis cases. At present, the tuberculin skin test and interferon-gamma release assay are the main detection methods for LTBI, yet both have certain limitations, and there is no unified standard for LTBI diagnosis. With the rapid advancement of molecular biotechnology and artificial intelligence, technologies such as RNA sequencing, proteomics and machine learning have opened up new perspectives for LTBI diagnosis. RNA sequencing and proteomics can reveal the complexity and diversity of gene and protein expression profiles under LTBI status, and improve diagnostic accuracy by identifying specific biomarkers. Machine learning can establish diagnostic models through algorithm training, so as to provide rapid diagnosis and personalized decision support for LTBI screening. This paper reviews the current diagnostic situation, novel detection techniques of LTBI and the application of machine learning in auxiliary diagnosis of LTBI, aiming to provide theoretical references for the diagnosis of LTBI.
|
|
Received: 20 January 2026
Revised: 25 April 2026
Published: 27 May 2026
|
|
|
|
|
|
[1] World Health Organization.Global tuberculosis reports,1997 to 2025[EB/OL].[2026-04-25].https://www.who.int/teams/global-programme-on-tuberculosis-and-lung-health/tb-reports.
[2] 王歆尧,姜美丽,庞元捷,等.中国结核病疾病负担现状[J].中华流行病学杂志,2024,45(6):857-864.
[3] ZHANG H Y,GUAN W W,ZHOU J K.Advances in the diagnosis of latent tuberculosis infection[J].Infect Drug Resist,2025,18:483-493.
[4] 邱曼玲,江毅,李梦映,等.在校学生结核潜伏感染及预防性治疗研究进展[J].预防医学,2024,36(1):30-33.
[5] 张铭锦,刘绘影,高嘉,等.结核潜伏感染的诊断现状与展望[J].中华传染病杂志,2024,42(8):500-505.
[6] 姜雯雯,徐勇胜.结核分枝杆菌潜伏感染筛查方法研究进展[J].中国实用儿科杂志,2023,38(12):948-952.
[7] TAYLOR Z,NOLAN C M,BLUMBERG H M,et al.Controlling tuberculosis in the United States.Recommendations from the American thoracic society,CDC,and the infectious diseases society of America[J].MMWR Recomm Rep,2005,54(12):1-81.
[8] CARRANZA C,PEDRAZA-SANCHEZ S,DE OYARZABAL-MENDEZ E,et al.Diagnosis for latent tuberculosis infection:new alternatives[J/OL].Front Immunol,2020,11[2026-04-25].https://doi.org/10.3389/fimmu.2020.02006.
[9] 张爽,赵弘,杨美霞.结核潜伏感染检测方法的研究进展[J].上海预防医学,2025,37(1):94-99.
[10] DING Y E,WONG M T J,NORAZMI M N,et al.Advancement in diagnostic approaches for latent tuberculosis:distinguishing recent from remote infections[J/OL].One Health Outlook,2025,7(1)[2026-04-25].https://doi.org/10.1186/s42522-025-00144-w.
[11] HAAS M K,BELKNAP R W.Diagnostic tests for latent tuberculosis infection[J].Clin Chest Med,2019,40(4):829-837.
[12] CODECASA L,MANTEGANI P,GALLI L,et al.An in-house RD1-based enzyme-linked immunospot-gamma interferon assay instead of the tuberculin skin test for diagnosis of latent Mycobacterium tuberculosis infection[J].J Clin Microbiol,2006,44(6):1944-1950.
[13] AHMED A,FENG P I,GAENSBAUER J T,et al.Interferon-γ release assays in children <15 years of age[J/OL].Pediatrics,2020,145(1)[2026-04-25].https://doi.org/10.1542/peds.2019-1930.
[14] PARK C H,PARK J H,JUNG Y S.Impact of immunosuppressive therapy on the performance of latent tuberculosis screening tests in patients with inflammatory bowel disease:a systematic review and meta-analysis[J/OL].J Pers Med,2022,12(3):[2026-04-25].https://doi.org/10.3390/jpm12030507.
[15] GONG W P,WU X Q.Differential diagnosis of latent tuberculosis infection and active tuberculosis:a key to a successful tuberculosis control strategy[J/OL].Front Microbiol,2021,12[2026-04-25].https://doi.org/10.3389/fmicb.2021.745592.
[16] STARSHINOVA A,DOVGALYK I,MALKOVA A,et al.Recombinant tuberculosis allergen (Diaskintest®) in tuberculosis diagnostic in Russia (meta-analysis)[J].Int J Mycobacteriol,2020,9(4):335-346.
[17] RUHWALD M,AGGERBECK H,GALLARDO R V,et al.Safety and efficacy of the C-Tb skin test to diagnose Mycobacterium tuberculosis infection,compared with an interferon γ release assay and the tuberculin skin test:a phase 3,double-blind,randomised,controlled trial[J].Lancet Respir Med,2017,5(4):259-268.
[18] AGGERBECK H,RUHWALD M,HOFF S T,et al.C-Tb skin test to diagnose Mycobacterium tuberculosis infection in children and HIV-infected adults:a phase 3 trial[J/OL].PLoS One,2018,13(9)[2026-04-25].https://doi.org/10.1371/journal.pone.0204554.
[19] LI F,XU M,QIN C,et al.Recombinant fusion ESAT6-CFP10 immunogen as a skin test reagent for tuberculosis diagnosis:an open-label,randomized,two-centre phase 2a clinical trial[J/OL].Clin Microbiol Infect,2016,22(10)[2026-04-25].https://doi.org/10.1016/j.cmi.2016.07.015.
[20] LI F,XU M,ZHOU L J,et al.Safety of recombinant fusion protein ESAT6-CFP10 as a skin test reagent for tuberculosis diagnosis:an open-label,randomized,single-center phase Ⅰ clinical trial[J].Clin Vaccine Immunol,2016,23(9):767-773.
[21] DAWADI P,POKHAREL B,SHRESTHA A,et al.From bench to bytes:a practical guide to RNA sequencing data analysis[J/OL].Front Genet,2025,16[2026-04-25].https://doi.org/10.3389/fgene.2025.1697922.
[22] FANG Y L,ZHAO J J,WANG X Y,et al.Identification of differentially expressed lncRNAs as potential plasma biomarkers for active tuberculosis[J/OL].Tuberculosis (Edinb),2021,128[2026-04-25].https://doi.org/10.1016/j.tube.2021.102065.
[23] MIRZAEI R,BABAKHANI S,AJORLOO P,et al.The emerging role of exosomal miRNAs as a diagnostic and therapeutic biomarker in Mycobacterium tuberculosis infection[J/OL].Mol Med,2021,27(1)[2026-04-25].https://doi.org/10.1186/s10020-021-00296-1.
[24] DE ARAUJO L S,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[J/OL].mBio,2019,10(6)[2026-04-25].https://doi.org/10.1128/mbio.01037-19.
[25] GUO J B,ZHANG X M,CHEN X C,et al.Proteomics in biomarker discovery for tuberculosis:current status and future perspectives[J/OL].Front Microbiol,2022,13[2026-04-25].https://doi.org/10.3389/fmicb.2022.845229.
[26] 贺仁忠,王霄,陈玲,等.结核潜伏感染诊断新型候选标志物的筛选及临床验证[J].中国人兽共患病学报,2018,34(9):794-800.
[27] SUN H S,PAN L P,JIA H Y,et al.Label-free quantitative proteomics identifies novel plasma biomarkers for distinguishing pulmonary tuberculosis and latent infection[J/OL].Front Microbiol,2018,9[2026-04-25].https://doi.org/10.3389/fmicb.2018.01267.
[28] MATEOS J,ESTÉVEZ O,GONZÁLEZ-FERNÁNDEZ Á,et al.High-resolution quantitative proteomics applied to the study of the specific protein signature in the sputum and saliva of active tuberculosis patients and their infected and uninfected contacts[J].J Proteomics,2019,195:41-52.
[29] DOMINGO-GONZALEZ R,PRINCE O,COOPER A,et al.Cytokines and chemokines in Mycobacterium tuberculosis infection[J/OL].Microbiol Spectr,2016,4(5)[2026-04-25].https://doi.org/10.1128/microbiolspec.tbtb2-0018-2016.
[30] WON E J,CHOI J H,CHO Y N,et al.Biomarkers for discrimination between latent tuberculosis infection and active tuberculosis disease[J].J Infect,2017,74(3):281-293.
[31] WANG S,LI Y,SHEN Y J,et al.Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB[J/OL].J Transl Med,2018,16(1)[2026-04-25].https://doi.org/10.1186/s12967-018-1572-x.
[32] THEODOSIOU A A,READ R C.Artificial intelligence,machine learning and deep learning:potential resources for the infection clinician[J].J Infect,2023,87(4):287-294.
[33] LI L S,YANG L,ZHUANG L,et al.From immunology to artificial intelligence:revolutionizing latent tuberculosis infection diagnosis with machine learning[J/OL].Mil Med Res,2023,10(1)[2026-04-25].https://doi.org/10.1186/s40779-023-00490-8.
[34] LU C Y,WU J,WANG H H,et al.Novel biomarkers distinguishing active tuberculosis from latent infection identified by gene expression profile of peripheral blood mononuclear cells[J/OL].PLoS One,2011,6(8)[2026-04-25].https://doi.org/10.1371/journal.pone.0024290.
[35] WANG S,HE L,WU J,et al.Transcriptional profiling of human peripheral blood mononuclear cells identifies diagnostic biomarkers that distinguish active and latent tuberculosis[J/OL].Front Immunol,2019,10[2026-04-25].https://doi.org/10.3389/fimmu.2019.02948.
[36] LI J,WANG Y G,YAN L,et al.Novel serological biomarker panel using protein microarray can distinguish active TB from latent TB infection[J/OL].Microbes Infect,2022,24(8)[2026-04-25].https://doi.org/10.1016/j.micinf.2022.105002.
[37] AGRANOFF D,FERNANDEZ-REYES D,PAPADOPOULOS M C,et al.Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum[J].Lancet,2006,368(9540):1012-1021.
[38] LUO Y,XUE Y,LIU W,et al.Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection[J/OL].BMC Infect Dis,2022,22(1)[2026-04-25].https://doi.org/10.1186/s12879-022-07954-7. |
|
|
|
