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Identification of an eight-protein biosignature for the diagnosis of tuberculosis

ABSTRACT: Mycobacterium tuberculosis (Mtb) antigen-specific cellular response is promising for detectionof Mtb infection, but not efficient for diagnosis of TB. We firstly identified 16 TB disease-specific protein markers measured in the culture supernatant of Mtb-stimulated whole blood using a 640 human proteins array, the highest throughput antibody-based protein array available at the time when we did this study. Potential TB-related proteins were then analyzed across three different patient cohorts comprised of healthy controls, LTBI, non-TB pneumonia, and TB patients to evaluate how the biomarkers performed in diagnosing TB in the real clinical setting. The data finally reveal an eight-protein biosignature of TB. Overall design: We prospectively enrolled three cohorts into for our study, including 160 subjects to screen protein biomarkers of tuberculosis, 368 subjects to establish and test the predictive model, and 102 subjects for biomarker validation. Whole blood cultures were stimulated with pooled Mtb-peptides or mitogen, and then 640 proteins within the culture supernatant were analyzed simultaneously using an antibody-based array. 16 candidate biomarkers of tuberculosis were identified and developed into a custom multiplexed antibody array for biomarker validation.

INSTRUMENT(S): Raybio Human Cytokine Antibody Array Q-Series 640 (QAH-CAA-640)

ORGANISM(S): Homo sapiens

SUBMITTER: Huihua Zhang

PROVIDER: GSE133249 | GEO | 2019-06-25

REPOSITORIES: GEO

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Project description:Background Tuberculosis (TB) is one of the world’s most problematic infectious diseases. The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). No overt disease symptoms occur. The environmental and internal triggers leading to reactivation of TB are not well understood. Non-tuberculosis Mycobacteria (NTM) can also cause TB-like lung disease. Comparative analysis of blood plasma proteomes from subjects afflicted by these pathologies in an endemic setting may yield new differentiating biomarkers and insights into inflammatory and immunological responses to Mtb and NTM. Methods Blood samples from 40 human subjects in a pastoral region of Ethiopia were treated with the ESAT-6/CFP-10 antigen cocktail to stimulate anti-Mtb and anti-NTM immune responses. In addition to those of active TB, LTBI, and NTM cohorts, samples from matched healthy control (HC) subjects were available. Following the generation of sample pools, proteomes were analyzed via LC-MS/MS. These experiments were also performed without antigen stimulation steps. Statistically significant differences using the Z-score method were determined and interpreted in the context of the proteins’ functions and their contributions to biological pathways. Results More than 200 proteins were identified from unstimulated and stimulated plasma samples (UPSs and SPSs, respectively). Thirty-four and 64 proteins were differentially abundant with statistical significance (P <?0.05; Benjamini-Hochberg correction with an FDR <?0.05) comparing UPS and SPS proteomic data of four groups, respectively. Bioinformatics analysis of such proteins via the Gene Ontology Resource was indicative of changes in cellular and metabolic processes, responses to stimuli, and biological regulations. The m7GpppN-mRNA hydrolase was increased in abundance in the LTBI group compared to HC subjects. Charged multivesicular body protein 4a and platelet factor-4 were increased in abundance in NTM as compared to HC and decreased in abundance in NTM as compared to active TB. C-reactive protein, ?-1-acid glycoprotein 1, sialic acid-binding Ig-like lectin 16, and vitamin K-dependent protein S were also increased (P <?0.05; fold changes?2) in SPSs and UPSs comparing active TB with LTBI and NTM cases. These three proteins, connected in a STRING functional network, contribute to the acute phase response and influence blood coagulation. Conclusion Plasma proteomes are different comparing LTBI, TB, NTM and HC cohorts. The changes are augmented following prior blood immune cell stimulation with the ESAT-6/CFP-10 antigen cocktail. The results encourage larger-cohort studies to identify specific biomarkers to diagnose NTM infection, LTBI, and to predict the risk of TB reactivation.

Project description:Abstract Objectives The development of non?sputum?based assays for tuberculosis (TB) diagnosis and treatment monitoring is a key priority. Recent data indicate that whole blood?based assays to assess the phenotype of Mycobacterium tuberculosis (Mtb)?specific CD4 T cells hold promise for this purpose and require further investigation in well?characterised TB cohorts. In this study, we investigated the relationship between the phenotypic signature of Mtb?specific CD4 responses, TB disease extent and treatment response. Methods Using flow cytometry, we measured the expression of phenotypic and functional markers (HLA?DR, CD27, CD153, KLRG1, IL?2, MIP?1?, TNF?? and IFN??) on Mtb?specific CD4 T?cells in whole blood from 161 participants of varying TB and HIV status. TB disease extent was graded as a continuum using the Xpertct value, C?reactive protein, Timika radiographic score and monocyte/lymphocyte ratio. Results The phenotypic profile of Mtb?specific CD4 T cells pre?anti?tubercular treatment (ATT) strongly correlated with disease extent, irrespective of HIV status. ATT associated with major changes in the phenotype of Mtb?specific CD4 T cells, with decreased expression of HLA?DR and increased CD27 and CD153 expression. Principal component analysis showed an almost complete separation between latent TB infection (LTBI) and active TB (aTB) pre?ATT groups, whereas the profile of the aTB post?ATT group overlapped with the LTBI group. However, in patients experiencing treatment failure or relapse, no significant changes were observed in Mtb?specific CD4 T?cell phenotype pre? and post?ATT. Conclusion Whole blood?based assays of Mtb?specific CD4 T?cell activation and maturation markers can be used as non?sputum?based biomarkers of disease extent and treatment monitoring in TB, regardless of HIV?1 status. A better understanding of the relationship between host immune responses, tuberculosis (TB) disease severity and treatment outcome is key to the development of novel TB diagnostic and treatment monitoring tools. In this study, we defined the profile of Mycobacterium tuberculosis?specific IFN?+ CD4 T?cell response in TB patients, analysed its evolution after completion of a standard anti?tubercular treatment regimen and evaluated how the host CD4 response associates with clinical TB extent and treatment response.

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Identification of an eight-protein biosignature for the diagnosis of tuberculosis

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