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Original research
Identification of eight-protein biosignature for diagnosis of tuberculosis
  1. Qianting Yang1,
  2. Qi Chen1,
  3. Mingxia Zhang1,
  4. Yi Cai2,
  5. Fan Yang2,
  6. Jieyun Zhang1,
  7. Guofang Deng1,
  8. Taosheng Ye1,
  9. Qunyi Deng1,
  10. Guobao Li1,
  11. Huihua Zhang3,4,
  12. Yuhua Yi3,4,
  13. Ruo-Pan Huang3,4,
  14. Xinchun Chen2
  1. 1 National Clinical Research Center for Infectious Diseases, Guangdong Key Laboratory for Diagnosis & Treatment of Emerging Infectious Diseases, Shenzhen Third People’s Hospital, Shenzhen, China
  2. 2 Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
  3. 3 South China Biochip Research Center, RayBiotech, Guangzhou, China
  4. 4 Raybiotech Center, RayBiotech, Norcross, Georgia, USA
  1. Correspondence to Professor Xinchun Chen, Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen 518060, China; chenxinchun{at}; Dr Ruo-Pan Huang, RayBiotech, South China Biochip Research Center, Guangzhou 510663, China; rhuang{at}


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.

  • Mycobacterium tuberculosis
  • antibody array
  • protein array
  • diagnosis
  • biomarker

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  • Contributors R-PH, XC and QY designed the research and drafted the manuscript. QY, HZ and YY managed the database and statistical analyses. GD, TY, QD and GL collected the samples and clinical data. QC, MZ, YC, FY, JZ and QY performed the experiment. All authors were involved in critically revising and providing final manuscript approval.

  • Funding Financial supports for this work were provided by the National Science and Technology Major Project (2017ZX10201301-001-001, 2017ZX10201301-001-002) and by the Natural Science Foundation of China (81525016, 81671984), Guangdong Provincial Science and Technology Programme (2019B030301009). Science and Technology Project of Shenzhen (JCYJ20160427184123851, JCYJ20170412101048337) and Jin Qi team of Sanming Project of Medicine in Shenzhen (SZSM201412001).

  • Competing interests HZ, YY and R-PH are employees of RayBiotech Life, a company producing commercial antibody arrays, including the antibody array targeting 640 human proteins that was used in this study. The custom antibody array targeting 16 proteins was also produced by RayBiotech.

  • Patient consent for publication Not required.

  • Ethics approval The study was approved by the Institutional Review Board of Shenzhen Third People’s Hospital.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available in a public, open access repository. All protein data were uploaded to the GEO repository (No. GSE 133249, GSE141848).

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