Dataset Information

Discovery and Validation of a Three-Cytokine Plasma Signature as a Biomarker for Diagnosis of Pediatric Tuberculosis.

ABSTRACT: Pediatric TB poses challenge in diagnosis due to the paucibacillary nature of the disease. We conducted a prospective diagnostic study to identify immune biomarkers of pediatric TB and controls (discovery cohort) and obtained a separate "validation" cohort of confirmed cases of pediatric TB and controls. Multiplex ELISA was performed to examine the plasma levels of cytokines. Discovery and validation cohorts revealed that baseline plasma levels of IFNγ, TNFα, IL-2, and IL-17A were significantly higher in active TB (confirmed TB and unconfirmed TB) in comparison to unlikely TB children. Receiver operating characteristics (ROC) curve analysis revealed that IFNγ, IL-2, TNFα, and IL-17A (in the discovery cohort) and TNFα and IL-17A (in the validation cohort) could act as biomarkers distinguishing confirmed or unconfirmed TB from unlikely TB with the sensitivity and specificity of more than 90%. In the discovery cohort, cytokines levels were significantly diminished following anti-tuberculosis treatment. In both the cohorts, combiROC models offered 100% sensitivity and 98% to 100% specificity for a three-cytokine signature of TNFα, IL-2, and IL-17A, which can distinguish confirmed or unconfirmed TB children from unlikely TB. Thus, a baseline cytokine signature of TNFα, IL-2, and IL-17A could serve as an accurate biomarker for the diagnosis of pediatric tuberculosis.

SUBMITTER: Kumar NP

PROVIDER: S-EPMC8085486 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Discovery and Validation of a Three-Cytokine Plasma Signature as a Biomarker for Diagnosis of Pediatric Tuberculosis.

Kumar Nathella Pavan NP Hissar Syed S Thiruvengadam Kannan K Banurekha Velayuthum V VV Suresh N N Shankar Janani J S Elilarasi E N S Gomathi G S Kalpana K J Ganesh G M A Aravind A Baskaran Dhanaraj D Tripathy Srikanth S Swaminathan Soumya S Babu Subash S

Frontiers in immunology 20210416

Pediatric TB poses challenge in diagnosis due to the paucibacillary nature of the disease. We conducted a prospective diagnostic study to identify immune biomarkers of pediatric TB and controls (discovery cohort) and obtained a separate "validation" cohort of confirmed cases of pediatric TB and controls. Multiplex ELISA was performed to examine the plasma levels of cytokines. Discovery and validation cohorts revealed that baseline plasma levels of IFNγ, TNFα, IL-2, and IL-17A were significantly ...[more]

PMID: 33936077

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Project description:Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.

Project description:BackgroundA nonsputum blood test capable of predicting progression of healthy individuals to active tuberculosis (TB) before clinical symptoms manifest would allow targeted treatment to curb transmission. We aimed to develop a proteomic biomarker of risk of TB progression for ultimate translation into a point-of-care diagnostic.Methods and findingsProteomic TB risk signatures were discovered in a longitudinal cohort of 6,363 Mycobacterium tuberculosis-infected, HIV-negative South African adolescents aged 12-18 years (68% female) who participated in the Adolescent Cohort Study (ACS) between July 6, 2005 and April 23, 2007, through either active (every 6 months) or passive follow-up over 2 years. Forty-six individuals developed microbiologically confirmed TB disease within 2 years of follow-up and were selected as progressors; 106 nonprogressors, who remained healthy, were matched to progressors. Over 3,000 human proteins were quantified in plasma with a highly multiplexed proteomic assay (SOMAscan). Three hundred sixty-one proteins of differential abundance between progressors and nonprogressors were identified. A 5-protein signature, TB Risk Model 5 (TRM5), was discovered in the ACS training set and verified by blind prediction in the ACS test set. Poor performance on samples 13-24 months before TB diagnosis motivated discovery of a second 3-protein signature, 3-protein pair-ratio (3PR) developed using an orthogonal strategy on the full ACS subcohort. Prognostic performance of both signatures was validated in an independent cohort of 1,948 HIV-negative household TB contacts from The Gambia (aged 15-60 years, 66% female), longitudinally followed up for 2 years between March 5, 2007 and October 21, 2010, sampled at baseline, month 6, and month 18. Amongst these contacts, 34 individuals progressed to microbiologically confirmed TB disease and were included as progressors, and 115 nonprogressors were included as controls. Prognostic performance of the TRM5 signature in the ACS training set was excellent within 6 months of TB diagnosis (area under the receiver operating characteristic curve [AUC] 0.96 [95% confidence interval, 0.93-0.99]) and 6-12 months (AUC 0.76 [0.65-0.87]) before TB diagnosis. TRM5 validated with an AUC of 0.66 (0.56-0.75) within 1 year of TB diagnosis in the Gambian validation cohort. The 3PR signature yielded an AUC of 0.89 (0.84-0.95) within 6 months of TB diagnosis and 0.72 (0.64-0.81) 7-12 months before TB diagnosis in the entire South African discovery cohort and validated with an AUC of 0.65 (0.55-0.75) within 1 year of TB diagnosis in the Gambian validation cohort. Signature validation may have been limited by a systematic shift in signal magnitudes generated by differences between the validation assay when compared to the discovery assay. Further validation, especially in cohorts from non-African countries, is necessary to determine how generalizable signature performance is.ConclusionsBoth proteomic TB risk signatures predicted progression to incident TB within a year of diagnosis. To our knowledge, these are the first validated prognostic proteomic signatures. Neither meet the minimum criteria as defined in the WHO Target Product Profile for a progression test. More work is required to develop such a test for practical identification of individuals for investigation of incipient, subclinical, or active TB disease for appropriate treatment and care.

Dataset Information

Discovery and Validation of a Three-Cytokine Plasma Signature as a Biomarker for Diagnosis of Pediatric Tuberculosis.

Publications

Discovery and Validation of a Three-Cytokine Plasma Signature as a Biomarker for Diagnosis of Pediatric Tuberculosis.

Similar Datasets

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