Development of a multiplex bead-based assay for detection of hepatitis C virus

Autor: Leonardo Foti, Edimilson Domingos da Silva, Marcelle Bral de Mello, Lílian Dias Nascimento, Christiane de Fátima Silva Marques, Marco Aurélio Krieger, Bruna de Paula Fonseca e Fonseca, Nara Mazarakis Rubim, Antonio G. P. Ferreira, Leila Botelho Rodrigues da Silva
Rok vydání: 2011
Předmět:
Zdroj: Clinical and vaccine immunology : CVI. 18(5)
ISSN: 1556-679X
Popis: Hepatitis C virus (HCV) infection is a major burden to public health worldwide, affecting approximately 3% of the human population. Although HCV detection is currently based on reliable tests, the field of medical diagnostics has a growing need for inexpensive, accurate, and quick high-throughput assays. By using the recombinant HCV antigens NS3, NS4, NS5, and Combined, we describe a new bead-based multiplex test capable of detecting HCV infection in human serum samples. The first analysis, made in a singleplex format, showed that each antigen coupled to an individual bead set presented high-level responses for anti-HCV-positive reference serum pools and lower-level responses for the HCV-negative pools. Our next approach was to determine the sensitivity and specificity of each antigen by testing 93 HCV-positive and 93 HCV-negative sera. When assayed in the singleplex format, the NS3, NS4, and NS5 antigens presented lower sensitivity values (50.5%, 51.6%, and 55.9%, respectively) than did the Combined antigen, which presented a sensitivity of 93.5%. All antigens presented 100% specificity. These antigens were then multiplexed in a 4-plex assay, which resulted in increased sensitivity and specificity values, performing with 100% sensitivity and 100% specificity. The positive and negative predictive values for the 4-plex assay were 100%. Although preliminary, this 4-plex assay showed robust results that, aligned with its small-sample-volume requirements and also its cost- and time-effectiveness, make it a reasonable alternative to tests currently used for HCV screening of potentially infected individuals.
Databáze: OpenAIRE