Dataset Information

Proteomic fingerprinting in HIV/HCV co-infection reveals serum biomarkers for the diagnosis of fibrosis staging.

ABSTRACT:

Background

Hepatic complications of hepatitis C virus (HCV), including fibrosis and cirrhosis are accelerated in human immunodeficiency virus (HIV)-infected individuals. Although, liver biopsy remains the gold standard for staging HCV-associated liver disease, this test can result in serious complications and is subject to sampling errors. These challenges have prompted a search for non-invasive methods for liver fibrosis staging. To this end, we compared serum proteome profiles at different stages of fibrosis in HIV/HCV co- and HCV mono-infected patients using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS).

Methods

Sera from 83 HIV/HCV co- and 68 HCV mono-infected subjects in 4 stages of fibrosis were tested. Sera were fractionated, randomly applied to protein chip arrays (IMAC, CM10 and H50) and spectra were generated at low and high laser intensities.

Results

Sixteen biomarkers achieved a p value < 0.01 (ROC values > 0.75 or < 0.25) predictive of fibrosis status in co-infected individuals and 14 in mono infected subjects. Five of these candidate biomarkers contributed to both mono- and co-infected subjects. Candidate diagnostic algorithms were created to distinguish between non-fibrotic and fibrotic individuals using a panel of 4 biomarker peaks.

Conclusion

These data suggest that SELDI MS profiling can identify diagnostic serum biomarkers for fibrosis that are both common and distinct in HIV/HCV co-infected and HCV mono-infected individuals.

SUBMITTER: Golizeh M

PROVIDER: S-EPMC5880398 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Proteomic fingerprinting in HIV/HCV co-infection reveals serum biomarkers for the diagnosis of fibrosis staging.

Golizeh Makan M Melendez-Pena Carlos E CE Ward Brian J BJ Saeed Sahar S Santamaria Cynthia C Conway Brian B Cooper Curtis C Klein Marina B MB Ndao Momar M

PloS one 20180402 4

<h4>Background</h4>Hepatic complications of hepatitis C virus (HCV), including fibrosis and cirrhosis are accelerated in human immunodeficiency virus (HIV)-infected individuals. Although, liver biopsy remains the gold standard for staging HCV-associated liver disease, this test can result in serious complications and is subject to sampling errors. These challenges have prompted a search for non-invasive methods for liver fibrosis staging. To this end, we compared serum proteome profiles at diffe ...[more]

PMID: 29608613

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Project description:HIV and HCV coinfection leads to accelerated liver fibrosis, in which microbial translocation and systemic inflammation might play important roles. This study aimed to provide an extensive profile of the plasma microbial translocation and inflammation biomarkers associated with advanced liver fibrosis among HIV-HCV-coinfected patients. This cross-sectional study recruited 343 HIV-HCV-coinfected patients on combination antiretroviral therapy (cART) from a rural prefecture of Yunnan province in Southwest China. The plasma concentrations of sCD14 and 27 cytokines and chemokines were assayed and compared against advanced or mild levels of liver fibrosis. Of the 343 HIV-HCV-coinfected patients, 188 (54.8%) had severe or advanced liver fibrosis (FIB-4 > 3.25). The patients with advanced liver fibrosis (FIB-4 > 3.25 vs. FIB-4 ≤ 3.25) had higher plasma levels of interleukin (IL)-1β, IL-6, IL-7, IL-9, IL-12, IL-15, IL-17, granulocyte macrophage colony stimulating factor (GM-CSF), Interferon-γ (IFN-γ), tumor necrosis factor (TNF-α), IL-4, IL-10, IL-13, fibroblast growth factor 2 (FGF-basic), and Monocyte chemoattractant protein-1 (MCP-1). Multivariable logistic regression models showed that advanced liver fibrosis was associated with an increased plasma level of IL-1β, IL-6, IL-7, IL-12, IL-17, GM-CSF, IFN-γ, IL-4, IL-10, MCP-1, Eotaxin, and FGF-basic, with FGF-basic continuing to be positively and significantly associated with advanced liver fibrosis, after Bonferroni correction for multiple comparisons (adjusted odds ratio (aOR) = 1.92; 95%CI: 1.32-2.81; p = 0.001). Plasma sCD14 was also significantly associated with advanced liver fibrosis (aOR = 1.13; 95%CI: 1.01-1.30; p = 0.049). HIV-HCV-coinfected patients are living with a high prevalence of advanced liver fibrosis which coexists with a mixture of elevated plasma inflammation and microbial translocation biomarkers. The significant associations of advanced liver fibrosis with FGF-basic and sCD14 may reveal pathogenic mechanisms and potential clinical intervention targets for liver fibrosis in HCV-HIV coinfection.

Project description:BackgroundWe investigated the potential of proteomic fingerprinting with mass spectrometric serum profiling, coupled with pattern recognition methods, to identify biomarkers that could improve diagnosis of tuberculosis.MethodsWe obtained serum proteomic profiles from patients with active tuberculosis and controls by surface-enhanced laser desorption ionisation time of flight mass spectrometry. A supervised machine-learning approach based on the support vector machine (SVM) was used to obtain a classifier that distinguished between the groups in two independent test sets. We used k-fold cross validation and random sampling of the SVM classifier to assess the classifier further. Relevant mass peaks were selected by correlational analysis and assessed with SVM. We tested the diagnostic potential of candidate biomarkers, identified by peptide mass fingerprinting, by conventional immunoassays and SVM classifiers trained on these data.FindingsOur SVM classifier discriminated the proteomic profile of patients with active tuberculosis from that of controls with overlapping clinical features. Diagnostic accuracy was 94% (sensitivity 93.5%, specificity 94.9%) for patients with tuberculosis and was unaffected by HIV status. A classifier trained on the 20 most informative peaks achieved diagnostic accuracy of 90%. From these peaks, two peptides (serum amyloid A protein and transthyretin) were identified and quantitated by immunoassay. Because these peptides reflect inflammatory states, we also quantitated neopterin and C reactive protein. Application of an SVM classifier using combinations of these values gave diagnostic accuracies of up to 84% for tuberculosis. Validation on a second, prospectively collected testing set gave similar accuracies using the whole proteomic signature and the 20 selected peaks. Using combinations of the four biomarkers, we achieved diagnostic accuracies of up to 78%.InterpretationThe potential biomarkers for tuberculosis that we identified through proteomic fingerprinting and pattern recognition have a plausible biological connection with the disease and could be used to develop new diagnostic tests.

Dataset Information

Proteomic fingerprinting in HIV/HCV co-infection reveals serum biomarkers for the diagnosis of fibrosis staging.

Background

Methods

Results

Conclusion

Publications

Proteomic fingerprinting in HIV/HCV co-infection reveals serum biomarkers for the diagnosis of fibrosis staging.

Similar Datasets

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