Dataset Information

Discovery of Potential Plasma Biomarkers for Tuberculosis in HIV-Infected Patients by Data-Independent Acquisition-Based Quantitative Proteomics.

ABSTRACT: Purpose:Tuberculosis (TB) is the leading cause of mortality in individuals infected with human immunodeficiency virus (HIV), yet the methods for detecting Mycobacterium tuberculosis at an early stage remain insensitive or ineffective. This study aimed to discover plasma biomarkers for distinguishing HIV-TB coinfected individuals from HIV individuals without TB (HIV-nonTB). Patients and Methods:A total of 200 Chinese HIV-positive patients were recruited, 100 each for HIV-nonTB group and HIV-TB group. Plasma proteomic profiles were analyzed for 50 patients each in both groups, using data-independent acquisition (DIA)-mass spectrometry-based proteomics. Differently expressed proteins were revealed with ridge regression analysis. Enzyme-linked immunosorbent assay (ELISA) analyses were performed for further validation in other 100 patients. Results:DIA-mass spectrometry revealed 13 upregulated and 33 downregulated proteins in the HIV-TB group. AMACR (?-methylacyl-CoA racemase), LDHB (L-lactate dehydrogenase B chain), and RAP1B (Ras-related protein Rap-1b) were selected for building a diagnostic model, for which the receiver operation characteristic curve had under areas of 0.99 and 0.89 testing with proteomics data (sensitivity = 92%, specificity = 100%) and ELISA data (sensitivity = 76%, specificity = 92%), respectively. Conclusion:The combination of AMACR, LDHB, and RAP1B proteins may serve as a potential marker of TB in HIV-infected patients.

SUBMITTER: Shen Y

PROVIDER: S-EPMC7187936 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Discovery of Potential Plasma Biomarkers for Tuberculosis in HIV-Infected Patients by Data-Independent Acquisition-Based Quantitative Proteomics.

Shen Yinzhong Y Xun Jingna J Song Wei W Wang Zhenyan Z Wang Jiangrong J Liu Li L Zhang Renfang R Qi Tangkai T Tang Yang Y Chen Jun J Sun Jianjun J Lu Hongzhou H

Infection and drug resistance 20200424

<h4>Purpose</h4>Tuberculosis (TB) is the leading cause of mortality in individuals infected with human immunodeficiency virus (HIV), yet the methods for detecting <i>Mycobacterium tuberculosis</i> at an early stage remain insensitive or ineffective. This study aimed to discover plasma biomarkers for distinguishing HIV-TB coinfected individuals from HIV individuals without TB (HIV-nonTB).<h4>Patients and methods</h4>A total of 200 Chinese HIV-positive patients were recruited, 100 each for HIV-non ...[more]

PMID: 32425558

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Project description:The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients (n = 15), compared with LTBI individuals (n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set (n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set (n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic biomarkers for distinguishing PTB and LTBI.

Project description:There is an urgent need to identify immunological markers of tuberculosis (TB) risk in HIV co-infected individuals. Previously we have shown that TB recurrence in HIV co-infected individuals on ART was associated with markers of systemic inflammation (IL-6, IL1β and IL-1Rα). Here we examined the effect of additional acute inflammation and microbial translocation marker expression on risk of TB recurrence. Stored plasma samples were drawn from the TB Recurrence upon Treatment with HAART (TRuTH) study, in which individuals with previously treated pulmonary TB were screened for recurrence quarterly for up to 4 years. Recurrent TB cases (n = 37) were matched to controls (n = 102) by original trial study arm assignment and ART start date. Additional subsets of HIV infected (n = 41) and HIV uninfected (n = 37) individuals from Improving Recurrence Success (IMPRESS) study were sampled at active TB and post successful treatment completion. Plasma concentrations of soluble adhesion molecules (sMAdCAM, sICAM and sVCAM), lipopolysaccharide binding protein (LBP) and transforming growth factor-beta (TGF-β1, TGF-β2, TGF-β3) were measured by multiplex immunoassays and ELISA. Cytokine data was square root transformed in order to reduce variability. Multivariable analysis adjusted for a number of potential confounders measured at sample time-point: age, BMI, CD4 count, viral load (VL) and measured at baseline: presence or absence of lung cavities, previous history of TB, and WHO disease stage (4 vs 3). The following analytes were associated with increased risk of TB recurrence in the multivariable model: sICAM (aOR 1.06, 95% CI: 1.02-1.12, p = 0.009), LBP (aOR 8.78, 95% CI: 1.23-62.66, p = 0.030) and TGF-β3 (aOR 1.44, 95% CI 1.01-2.05, p = 0.044). Additionally, we observed a positive correlation between LBP and sICAM (r= 0.347, p<0.0001), and LBP and IL-6, identified to be one of the strongest predictors of TB risk in our previous study (r=0.623, p=0.03). These data show that increased risk of TB recurrence in HIV infected individuals on ART is likely associated with HIV mediated translocation of microbial products and the resulting chronic immune activation.

Project description:IntroductionThe pathophysiology of coronary chronic total occlusion (CTO) has not been fully elucidated.MethodsIn the present study, we aimed to investigate the potential plasma biomarkers associated with the pathophysiologic progression of CTO and identify protein dynamics in the plasma of CTO vessels immediately after successful revascularization. We quantitatively analyzed the plasma proteome profiles of controls (CON, n = 10) and patients with CTO pre- and post- percutaneous coronary intervention (PCI) (CTO, n = 10) by data-independent acquisition proteomics. We performed enzyme-linked immunosorbent assay (ELISA) to further confirm the common DEPs in the two-group comparisons (CON vs. CTO and CTO vs. CTO-PCI).ResultsA total of 1936 proteins with 69 differentially expressed proteins (DEPs) were detected in the plasma of patients with CTO through quantitative proteomics analysis. For all these DEPs, gene ontology (GO) analysis and protein-protein interaction (PPI) analysis were performed. The results showed that most of the proteins were related to the negative regulation of proteolysis, regulation of peptidase activity, negative regulation of hydrolase activity, humoral immune response, and lipid location. Furthermore, we identified 1927 proteins with 43 DEPs in the plasma of patients with CTO vessels after immediately successful revascularization compared to pre-PCI. GO analysis revealed that the above DEPs were enriched in the biological processes of extracellular structure organization, protein activation cascade, negative regulation of response to external stimulus, plasminogen activation, and fibrinolysis. More importantly, we generated a Venn diagram to identify the common DEPs in the two-group comparisons. Seven proteins, ADH4, CSF1, galectin, LPL, IGF2, IgH, and LGALS1, were found to be dynamically altered in plasma during the pathophysiological progression of CTO vessels and following successful revascularization, moreover, CSF1 and LGALS1 were validated via ELISA.ConclusionsThe results of this study reveal a dynamic pattern of the molecular response after CTO vessel immediate reperfusion, and identified seven proteins which would be the potential targets for novel therapeutic strategies to prevent coronary CTO.

Project description:BackgroundImaging of subclinical atherosclerosis improves cardiovascular risk prediction on top of traditional risk factors. However, cardiovascular imaging is not universally available. This work aims to identify circulating proteins that could predict subclinical atherosclerosis.MethodsHypothesis-free proteomics was used to analyze plasma from 444 subjects from PESA cohort study (222 with extensive atherosclerosis on imaging, and 222 matched controls) at two timepoints (three years apart) for discovery, and from 350 subjects from AWHS cohort study (175 subjects with extensive atherosclerosis on imaging and 175 matched controls) for external validation. A selected three-protein panel was further validated by immunoturbidimetry in the AWHS population and in 2999 subjects from ILERVAS cohort study.FindingsPIGR, IGHA2, APOA, HPT and HEP2 were associated with subclinical atherosclerosis independently from traditional risk factors at both timepoints in the discovery and validation cohorts. Multivariate analysis rendered a potential three-protein biomarker panel, including IGHA2, APOA and HPT. Immunoturbidimetry confirmed the independent associations of these three proteins with subclinical atherosclerosis in AWHS and ILERVAS. A machine-learning model with these three proteins was able to predict subclinical atherosclerosis in ILERVAS (AUC [95%CI]:0.73 [0.70-0.74], p < 1 × 10-99), and also in the subpopulation of individuals with low cardiovascular risk according to FHS 10-year score (0.71 [0.69-0.73], p < 1 × 10-69).InterpretationPlasma levels of IGHA2, APOA and HPT are associated with subclinical atherosclerosis independently of traditional risk factors and offers potential to predict this disease. The panel could improve primary prevention strategies in areas where imaging is not available.FundingThis study was supported by competitive grants from the Spanish Ministry of Science, Innovation and Universities (BIO2015-67580-P, PGC2018-097019-B-I00, PID2019-106814RB-I00 and SAF2016-80843-R), through the Carlos III Institute of Health-Fondo de Investigacion Sanitaria grant PRB3 (IPT17/0019 - ISCIII-SGEFI / ERDF, ProteoRed), CIBERCV and CIBERDEM, the Fundacio MaratoTV3 (grant 122/C/2015) and "la Caixa" Banking Foundation (project HR17-00247). The PESA study is co-funded equally by the Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain, and Banco Santander, Madrid, Spain. The ILERVAS study was funded by the Diputacio de Lleida. The study also receives funding from the Instituto de Salud Carlos III (PI15/02019; PI18/00610; RD16/0009) and the FEDER funds. The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia, Innovacion y Universidades (MCNU) and the Pro CNIC Foundation.

Dataset Information

Discovery of Potential Plasma Biomarkers for Tuberculosis in HIV-Infected Patients by Data-Independent Acquisition-Based Quantitative Proteomics.

Publications

Discovery of Potential Plasma Biomarkers for Tuberculosis in HIV-Infected Patients by Data-Independent Acquisition-Based Quantitative Proteomics.

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