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Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis.

ABSTRACT: New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% were sputum smear negative. Serum protein biomarkers were identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirnov (KS) statistics. A naive Bayes classifier using six host response markers (HR6 model), including SYWC, kallistatin, complement C9, gelsolin, testican-2, and aldolase C, performed well in a training set (area under the sensitivity-specificity curve [AUC] of 0.94) and in a blinded verification set (AUC of 0.92) to distinguish TB and non-TB samples. Differential expression was also highly significant (P < 10-20) for previously described TB markers, such as IP-10, LBP, FCG3B, and TSP4, and for many novel proteins not previously associated with TB. Proteins with the largest median fold changes were SAA (serum amyloid protein A), NPS-PLA2 (secreted phospholipase A2), and CA6 (carbonic anhydrase 6). Target product profiles (TPPs) for a non-sputum biomarker test to diagnose active TB for treatment initiation (TPP#1) and for a community-based triage or referral test (TPP#2) have been published by the WHO. With 90% sensitivity and 80% specificity, the HR6 model fell short of TPP#1 but reached TPP#2 performance criteria. In conclusion, we identified and validated a six-marker signature for active TB that warrants diagnostic development on a patient-near platform.

SUBMITTER: De Groote MA

PROVIDER: S-EPMC5625392 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis.

De Groote Mary A MA Sterling David G DG Hraha Thomas T Russell Theresa M TM Green Louis S LS Wall Kirsten K Kraemer Stephan S Ostroff Rachel R Janjic Nebojsa N Ochsner Urs A UA

Journal of clinical microbiology 20170809 10

New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% w ...[more]

PMID: 28794177

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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:Despite more than a century fighting against tuberculosis, the World Health Organisation has estimated that around 1.7 million people died of tuberculosis in 2016 and over a quarter of the world’s population is infected. One of the critical hurdles for stopping tuberculosis transmission is early and effective diagnosis of patients with the active pulmonary disease. Although important innovations in molecular diagnosis have been recently developed (e.g. Xpert MTB/RIF, Cepheid Inc., USA), there are no suitable tests for population screening at point-of-care. The current tuberculosis diagnosis pipeline presents a highly variable performance and requires access to reference laboratory facilities. A non-sputum based rapid test with high specificity and sensitivity could save ~400,000 lives per year. Therefore, new biomarkers for diagnosis are urgently required for identifying patients with early symptoms and to expedite treatment. Variable sensitivity and specificity can be overcome using a combination of multiple biomarkers (5). Proteins, as ultimate biological effectors, are ideal candidates for diagnostic biomarkers; consequently, proteomic studies are a crucial platform for biomarker discovery in tuberculosis. This work aims to develop a multi-marker panel for tuberculosis diagnosis with high performance capable of differentiating tuberculosis patients from relevant controls. Quantitative Multidimensional Protein Identification Technology (qMudPIT) is applied for biomarker discovery identifying candidates for early diagnosis of tuberculosis. The multidimensional method optimised in this work led to the identification of 5022 plasma proteins and 3577 quantified proteins using iTRAQ labelling. Known and completely novel markers for active tuberculosis in plasma were identified including a peptide derived from Mycobacterium tuberculosis. Complementary statistical and bioinformatic analysis were applied to prioritise candidates for validation in one or two independent cohorts. The plasma proteomic profile here described represents a power strategy for biomarker discovery and the panel proposed has the potential to be translated to a rapid test and which might contribute to tuberculosis control.

Project description:This study aimed to identify secreted protein biomarkers in serum from the label-free LC/MS proteomics of neutrophils in pulmonary tuberculosis (TB) patients for the diagnosis biomarkers of TB label-free LC/MS. The proteomic profiles of neutrophils from 15 active TB patients and 15 healthy controls (HCs) were analyzed using label-free LC/MS. We identified 358 differentially expressed proteins preliminarily, including 279 up-regulated proteins and 79 down-regulated proteins. Thirty-eight differentially expressed secreted proteins involved in the progress of platelet degranulation between TB patients and HCs were focused. Of these, serotransferrin (TRF), alpha-2-macroglobulin (AMG), alpha-1-antitrypsin (AAT), alpha-1-acid glycoprotein 1 (AAG), alpha-1-acid glycoprotein 2 (AGP2), and alpha-1B-glycoprotein (A1BG) were selected for further verification in the serum of additional 134 TB patients and 138 HCs by nephelometry and ELISA in the training set. Statistically significant differences of TRF (P < 0.0001), AAT (P < 0.0001), AAG (P < 0.0001), AGP2 (P < 0.0001), and A1BG (P = 0.0003) were observed. The serum concentration of TRF was down-regulated in TB patients compared with healthy controls, which was coincident with the proteomics results. An additional validation of TRF was performed in an independent cohort of patients with active TB (n = 46), patients with lung cancer (n = 37), 20 HCs, and patients with pneumonia (n = 35) in the test set by nephelometry. The serum expression levels of TRF in the TB patients showed lower levels compared with those in patients with pneumonia (P = 0.0125), lung cancer (P = 0.0005), HCs (P < 0.0001), and the non-TB controls (P < 0.0001). Furthermore, the AUC value of TRF was 0.647 with 90.22% sensitivity and 42.86% specificity in discriminating the TB group from the pneumonia group, 0.702 with 93.48% sensitivity and 47.16% specificity in discriminating the TB group from the lung cancer group, 0.894 with 91.30% sensitivity and 71.62% specificity in discriminating the TB group from all HCs, and 0.792 with 91.30% sensitivity and 58.90% specificity in discriminating the TB group from the non-TB controls. This study obtained the proteomic profiles of neutrophils in the TB patients and HCs, which contribute to a better understanding of the pathogenesis molecules existing in the neutrophils of pulmonary tuberculosis and provide candidate biomarkers for the diagnosis of pulmonary tuberculosis.

Dataset Information

Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis.

Publications

Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis.

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