J Clin Microbiol. 2008 Mar 5 [Epub ahead of print]

IgG responses against a panel of Candida albicans antigens are accurate and early markers for systemic candidiasis.

Clancy CJ, Nguyen ML, Cheng S, Huang H, Fan G, Jaber RA, Wingard JR, Cline C, Nguyen MH. Department of Medicine, University of Florida College of Medicine, Gainesville, FL; North Florida/South Georgia Veterans Health System, Gainesville, FL; Emory University School of Medicine, Atlanta, GA.

Despite shortcomings, blood and sterile site cultures remain the gold-standard for diagnosing systemic candidiasis. Alternative diagnostic markers, including antibody detection, have been developed but none are widely accepted. In this study, we used ELISA to measure serum antibody responses against 15 recombinant Candida albicans antigens among 60 patients with systemic candidiasis due to various Candida spp. and 24 un-infected controls. Mean IgG responses against all 15 antigens were significantly higher among patients with systemic candidiasis than controls, whereas IgM responses were higher against only 7 antigens. Using discriminant analysis that included IgG responses against the 15 antigens, we derived a mathematical prediction model that identified patients with systemic candidiasis with an error rate of 3.7%, sensitivity of 96.6% and specificity of 95.6%. Furthermore, a prediction model using a subset of 4 antigens (SET1, ENO1, PGK1-2 and MUC1-2) identified through backwards elimination and canonical correlation analyses performed as accurately as the full panel. Using the simplified model, we predicted systemic candidiasis in a separate test sample of 32 patients and controls with 100% sensitivity and 87.5% specificity. We also demonstrated that IgG titers against each of the four antigens included in the prediction model were significantly higher in convalescent sera than in paired acute sera. Taken together, our findings suggest that IgG responses against a panel of candidal antigens might represent an accurate and early marker of systemic candidiasis, an hypothesis that should be tested in future trials.

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