Literature DB >> 32201389

Identification of eight-protein biosignature for diagnosis of tuberculosis.

Qianting Yang1, Qi Chen1, Mingxia Zhang1, Yi Cai2, Fan Yang2, Jieyun Zhang1, Guofang Deng1, Taosheng Ye1, Qunyi Deng1, Guobao Li1, Huihua Zhang3,4, Yuhua Yi3,4, Ruo-Pan Huang5,4, Xinchun Chen6.   

Abstract

BACKGROUND: Biomarker-based tests for diagnosing TB currently rely on detecting Mycobacterium tuberculosis (Mtb) antigen-specific cellular responses. While this approach can detect Mtb infection, it is not efficient in diagnosing TB, especially for patients who lack aetiological evidence of the disease.
METHODS: We prospectively enrolled three cohorts for our study for a total of 630 subjects, including 160 individuals to screen protein biomarkers of TB, 368 individuals to establish and test the predictive model and 102 individuals for biomarker validation. Whole blood cultures were stimulated with pooled Mtb-peptides or mitogen, and 640 proteins within the culture supernatant were analysed simultaneously using an antibody-based array. Sixteen candidate biomarkers of TB identified during screening were then developed into a custom multiplexed antibody array for biomarker validation.
RESULTS: A two-round screening strategy identified eight-protein biomarkers of TB: I-TAC, I-309, MIG, Granulysin, FAP, MEP1B, Furin and LYVE-1. The sensitivity and specificity of the eight-protein biosignature in diagnosing TB were determined for the training (n=276), test (n=92) and prediction (n=102) cohorts. The training cohort had a 100% specificity (95% CI 98% to 100%) and 100% sensitivity (95% CI 96% to 100%) using a random forest algorithm approach by cross-validation. In the test cohort, the specificity and sensitivity were 83% (95% CI 71% to 91%) and 76% (95% CI 56% to 90%), respectively. In the prediction cohort, the specificity was 84% (95% CI 74% to 92%) and the sensitivity was 75% (95% CI 57% to 89%).
CONCLUSIONS: An eight-protein biosignature to diagnose TB in a high-burden TB clinical setting was identified. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  zzm321990Mycobacterium tuberculosiszzm321990; antibody array; biomarker; diagnosis; protein array

Year:  2020        PMID: 32201389     DOI: 10.1136/thoraxjnl-2018-213021

Source DB:  PubMed          Journal:  Thorax        ISSN: 0040-6376            Impact factor:   9.139


  14 in total

1.  Deciphering a TB-related DNA methylation biomarker and constructing a TB diagnostic classifier.

Authors:  Mengyuan Lyu; Jian Zhou; Lin Jiao; Yili Wang; Yanbing Zhou; Hongli Lai; Wei Xu; Binwu Ying
Journal:  Mol Ther Nucleic Acids       Date:  2021-11-19       Impact factor: 8.886

2.  Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection.

Authors:  Ying Luo; Ying Xue; Liyan Mao; Qun Lin; Guoxing Tang; Huijuan Song; Wei Liu; Shutao Tong; Hongyan Hou; Min Huang; Renren Ouyang; Feng Wang; Ziyong Sun
Journal:  Front Immunol       Date:  2021-08-26       Impact factor: 7.561

3.  Dried blood sample analysis by antibody array across the total testing process.

Authors:  Kelly Whittaker; Ying-Qing Mao; Yongping Lin; Huihua Zhang; Siwei Zhu; Hannah Peck; Ruo-Pan Huang
Journal:  Sci Rep       Date:  2021-10-15       Impact factor: 4.379

Review 4.  A systematic review of potential screening biomarkers for active TB disease.

Authors:  James H Wykowski; Chris Phillips; Thao Ngo; Paul K Drain
Journal:  J Clin Tuberc Other Mycobact Dis       Date:  2021-11-05

5.  Novel Long Non-coding RNA and LASSO Prediction Model to Better Identify Pulmonary Tuberculosis: A Case-Control Study in China.

Authors:  Zirui Meng; Minjin Wang; Shuo Guo; Yanbing Zhou; Mengyuan Lyu; Xuejiao Hu; Hao Bai; Qian Wu; Chuanmin Tao; Binwu Ying
Journal:  Front Mol Biosci       Date:  2021-05-25

Review 6.  Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development.

Authors:  Shailja Jakhar; Alexis A Bitzer; Loreen R Stromberg; Harshini Mukundan
Journal:  Int J Mol Sci       Date:  2020-09-23       Impact factor: 5.923

7.  Biosignatures: The answer to Tuberculosis diagnosis in children?

Authors:  Pierre Goussard; Gerhard Walzl
Journal:  EBioMedicine       Date:  2020-09-22       Impact factor: 8.143

8.  Host Blood RNA Transcript and Protein Signatures for Sputum-Independent Diagnostics of Tuberculosis in Adults.

Authors:  Dhanasekaran Sivakumaran; Christian Ritz; John Espen Gjøen; Mario Vaz; Sumithra Selvam; Tom H M Ottenhoff; Timothy Mark Doherty; Synne Jenum; Harleen M S Grewal
Journal:  Front Immunol       Date:  2021-02-04       Impact factor: 7.561

9.  Combination of prealbumin and tuberculosis-specific antigen/phytohemagglutinin ratio for discriminating active tuberculosis from latent tuberculosis infection.

Authors:  Ying Luo; Ying Xue; Xu Yuan; Qun Lin; Guoxing Tang; Liyan Mao; Huijuan Song; Feng Wang; Ziyong Sun
Journal:  Int J Clin Pract       Date:  2020-11-27       Impact factor: 2.503

10.  Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection.

Authors:  Ying Luo; Ying Xue; Guoxing Tang; Yimin Cai; Xu Yuan; Qun Lin; Huijuan Song; Wei Liu; Liyan Mao; Yu Zhou; Zhongju Chen; Yaowu Zhu; Weiyong Liu; Shiji Wu; Feng Wang; Ziyong Sun
Journal:  Front Immunol       Date:  2021-06-30       Impact factor: 7.561

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.