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High diagnostic accuracy of antigen microarray for sensitive detection of hepatitis C virus infection

Authors
Kwon, Jung-ahLee, HyeseonLee, Kap NoChae, KwangchunLee, SeramLee, Dong-kiKim, Soyoun
Issue Date
Feb-2008
Publisher
AMER ASSOC CLINICAL CHEMISTRY
Citation
CLINICAL CHEMISTRY, v.54, no.2, pp.424 - 428
Indexed
SCIE
SCOPUS
Journal Title
CLINICAL CHEMISTRY
Volume
54
Number
2
Start Page
424
End Page
428
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/124186
DOI
10.1373/clinchem.2007.090464
ISSN
0009-9147
Abstract
BACKGROUND: Hepatitis C virus (HCV) can be transmitted through blood transfusion. Screening ELISA, the most widely used method for HCV diagnosis, sometimes yields false-positive and false-negative results, so a confirmatory test is used. This secondary testing is labor-intensive and expensive, and thus is impractical for massive blood bank screening. Therefore, a new massive screening method with high accuracy is needed for sensitive and specific detection of HCV. METHODS: With sol-gel material, we designed novel antigen microarray in 96-well plates for HCV detection. Each individual well was spotted with 4 different HCV antigens. We used this new system to test 154 patient serum samples previously tested for HCV by ELISA (87 HCV positive and 67 HCV negative) (HCV EIA3.0, ABBOTT). We assessed the detection limit of our microarray system with the use of serial 10-fold dilutions of an HCV-positive sample. RESULTS: Our microarray assay was reproducible and displayed higher diagnostic accuracy (specificity) (98.78%) than did the ELISA (81.71%). Our method yielded significantly fewer false-positive results than did the ELISA. The detection limit of our assay was 1000 times more sensitive than that of the ELISA. In addition, we found this novel assay technology to be compatible with the currently employed automated methods used for ELISA. CONCLUSION: We successfully applied the sol-gel-based protein microarray technology to a screening assay for HCV diagnosis with confirmatory test-level accuracy. This new, inexpensive method will improve the specificity and sensitivity of massive sample diagnosis.
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