Evaluation of an enzyme immunoassay for hepatitis C virus antibody detection using a recombinant protein derived from the core region of hepatitis C virus genome

Lopes, Edmundo Pessoa; Granato, Celso Francisco Hernandes; Lanzoni, Valéria Pereira; Granero, Luzete Cristina Silva; Paranhos-Baccalà, Gláucia; Tomiyama, Helena; Silva, Aeb; Ferraz, Maria Lúcia Cardoso Gomes

doi:10.1590/s0074-02762000000500019

Cited by 6 publications

(4 citation statements)

References 17 publications

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“…Lopes et al reported the evaluation of an EIA for anti-HCV antibody detection using single antigen [79]. A recombinant c22 antigen was localized on the solid-phase and allowed to complex with anti-HCV antibodies in serum samples to detect anti-HCV IgG.…”

Section: Enzyme Immunoassay (Eia)mentioning

confidence: 99%

Developments in the HCV Screening Technologies Based on the Detection of Antigens and Antibodies

Warkad

Song

Pal

et al. 2019

Sensors

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Hepatitis C virus (HCV) accounts for 15%–20% of cases of acute infection, and chronic HCV infection is developed in about 50%–80% of HCV patients. Unfortunately, due to the lack of proper medical care, difficulty in screening for HCV infection, and lack of awareness resulted in chronic HCV infection in 71 million people on a global scale, and about 399,000 deaths in 2016. It is crucial to recognize that the effective use of antiviral medicines can cure more than 95% of HCV infected people. The Global Health Sector Strategy (GHSS) aim is to reduce the new HCV infections and the HCV associated mortality by 90% and 65%, respectively. Therefore, the methods that are simple, yet powerful enough to detect HCV infections with high sensitivity, specificity, and a shorter window period are crucial to restrain the global burden of HCV healthcare. This article focuses on the technologies used for the detection of HCV in clinical specimens.

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Section: Enzyme Immunoassay (Eia)mentioning

confidence: 99%

Developments in the HCV Screening Technologies Based on the Detection of Antigens and Antibodies

Warkad

Song

Pal

et al. 2019

Sensors

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“…The diagnosis of anti‐HCV with third‐generation EIA offers high sensitivity and specificity, achieving a correct diagnosis in approximately 97% of the cases 13 . The detection of HCV‐RNA quantitative, which reflects the infection in course, is routinely performed using reverse transcriptase polymerase chain reaction (RT‐PCR) 14–17 . In clinical practise, blood samples are used to diagnose anti‐HCV and HCV‐RNA, which necessitates the puncture of a peripheral blood vein 18 .…”

Section: Introductionmentioning

confidence: 99%

“…13 The detection of HCV-RNA quantitative, which reflects the infection in course, is routinely performed using reverse transcriptase polymerase chain reaction (RT-PCR). [14][15][16][17] In clinical practise, blood samples are used to diagnose anti-HCV and HCV-RNA, which necessitates the puncture of a peripheral blood vein. 18 Furthermore, the longer the time for RT-PCR, the greater the risk of contamination, and the high cost of the procedure limits its use in daily practise.…”

mentioning

confidence: 99%

The metabolic fingerprint of chronic hepatitis C progression: Metabolome shifts and cutting‐edge diagnostic options

Deep,

Swaroop,

Dubey

et al. 2023

J of Molecular Recognition

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Hepatitis C virus infection causes chronic diseases such as cirrhosis and hepatocellular carcinoma. Metabolomics research has been shown to be linked to pathophysiologic pathways in liver illnesses. The aim of this study was to investigate the serum metabolic profile of patients with chronic hepatitis C (CHC) infection and to identify underlying mechanisms as well as potential biomarkers associated with the disease. Nuclear magnetic resonance (NMR) was used to evaluate the sera of 83 patients with CHC virus and 52 healthy control volunteers (NMR). Then, multivariate statistical analysis was used to find distinguishing metabolites between the two groups. Sixteen out of 40 metabolites including include 3‐HB, betaine, carnitine, creatinine, fucose, glutamine, glycerol, isopropanol, lysine, mannose, methanol, methionine, ornithine, proline, serine, and valine—were shown to be significantly different between the CHC and normal control (NC) groups (variable importance in projection >1 and p < 0.05). All the metabolic perturbations in this disease are associated with pathways of Glycine, serine, and threonine metabolism, glycerolipid metabolism, arginine and proline metabolism, aminoacyl‐tRNA biosynthesis, cysteine and methionine metabolism, alanine, aspartate, and glutamate metabolism. Multivariate statistical analysis constructed using these expressed metabolites showed CHC patients can be discriminated from NCs with high sensitivity (90%) and specificity (99%). The metabolomics approach may expand the diagnostic armamentarium for patients with CHC while contributing to a comprehensive understanding of disease mechanisms.

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“…The study of anti‐HCV with third‐generation EIA offers high sensitivity and specificity, achieving a correct diagnosis in approximately 97% of cases. The detection of HCV‐RNA, which reflects the infection in course, is routinely performed using polymerase chain reaction (PCR) [9–12]. In practice, both the study of anti‐HCV and HCV‐RNA are carried out with blood samples, which requires the puncturing of a peripheral vein.…”

Section: Introductionmentioning

confidence: 99%

Hepatitis C virus infection diagnosis using metabonomics

Godoy

Lopes

Silva

et al. 2010

Journal of Viral Hepatitis

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Metabonomics based on nuclear magnetic resonance (NMR) can reveal the profile of endogenous metabolites of low molecular weight in biofluids related to disease. The profile is identified a 'metabolic fingerprint' like from the pathological process, why this metabonomics has been used as a diagnostic method. The aim of the present study was to apply metabonomics to identify patients infected with the hepatitis C virus (HCV) through an analysis of ¹H NMR spectra of urine samples associated with multivariate statistical methods. A pilot study was carried out for the diagnostic test evaluation, involving two groups: (i) 34 patients positive for anti-HCV and HCV-RNA and negative for anti-HBc (disease group); and (ii) 32 individuals positive for anti-HBc and negative for HBsAg and anti-HCV. The urine samples were analyzed through ¹H NMR, applying principal component analysis and discriminant analysis for classification. The metabonomics model was capable of identifying 32 of the 34 patients in the disease group as positive and 31 of the 32 individuals in the control group as negative, demonstrating 94% sensitivity and specificity of 97% as well as positive and negative predictive values of 97% and 94%, respectively, and 95% accuracy (P < 0.001). In conclusion, the metabonomics model based on ¹H NMR spectra of urine samples in this preliminary study discriminated patients with HCV infection with high sensitivity and specificity, thereby demonstrating this model to be a potential tool for use in medical practice in the near future.

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Evaluation of an enzyme immunoassay for hepatitis C virus antibody detection using a recombinant protein derived from the core region of hepatitis C virus genome

Abstract: This study was undertaken to evaluate an enzyme immunoassay (EIA) for hepatitis C virus antibody detection (anti-HCV

Cited by 6 publications

References 17 publications

Developments in the HCV Screening Technologies Based on the Detection of Antigens and Antibodies

Developments in the HCV Screening Technologies Based on the Detection of Antigens and Antibodies

The metabolic fingerprint of chronic hepatitis C progression: Metabolome shifts and cutting‐edge diagnostic options

Hepatitis C virus infection diagnosis using metabonomics

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