Validation of a Microsphere-Based Immunoassay for Detection of Anti-West Nile Virus and Anti-St. Louis Encephalitis Virus Immunoglobulin M Antibodies

Abstract

A microsphere-based immunoassay (MIA) was previously developed that is capable of determining the presence of anti-West Nile (WN) virus or anti-St. Louis encephalitis (SLE) virus immunoglobulin M (IgM) antibodies in human serum or cerebrospinal fluid. The original data set on which the classification rules were based comprised 491 serum specimens obtained from the serum bank at the Division of Vector-Borne Infectious Diseases of the Centers for Disease Control and Prevention (DVBID). The classification rules were used to provide a result and to determine whether confirmatory testing was necessary for a given sample. A validation study was coordinated between the DVBID and five state health laboratories to determine (i) the reproducibility of the test between different laboratories, (ii) the correlation between the IgM-enzyme-linked immunosorbent assay (MAC-ELISA) and the MIA, and (iii) whether the initial nonspecific parameters could be refined to reduce the volume of confirmatory testing. Laboratorians were trained in the method, and reagents and data analysis software developed at the DVBID were shipped to each validating laboratory. Validating laboratories performed tests on approximately 200 samples obtained from their individual states, the collections of which comprised approximately equal numbers of WN virus-positive and -negative samples, as determined by MAC-ELISA. In addition, 377 samples submitted to the DVBID for arbovirus testing were analyzed using the MIA and MAC-ELISA at the DVBID only. For the specimens tested at both the state and the DVBID laboratories, a correlation of results indicated that the technology is readily transferable between laboratories. The detection of IgM antibodies to WN virus was more consistent than detection of IgM antibodies to SLE virus. Some changes were made to the analysis software that resulted in an improved accuracy of diagnosis.