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Veterinary immunology and immunopathology2011; 144(3-4); 374-381; doi: 10.1016/j.vetimm.2011.08.005

Development of a multiplex assay for the detection of antibodies to Borrelia burgdorferi in horses and its validation using Bayesian and conventional statistical methods.

Abstract: Lyme disease is a zoonotic, vector-borne disease and occurs in mammals including horses. The disease is induced by infection with spirochetes of the Borrelia burgdorferi sensu lato group. Infection of mammalian hosts requires transmission of spirochetes by infected ticks during tick bites. Lyme disease diagnosis is based on clinical signs, possible exposure to infected ticks, and antibody testing which is traditionally performed by ELISA and Western blotting (WB). This report describes the development and validation of a new fluorescent bead-based multiplex assay for the detection of antibodies to B. burgdorferi outer surface protein A (OspA), OspC and OspF antigens in horse serum. Testing of 562 equine sera was performed blindly and in parallel by using WB and the new multiplex assay. Because a true gold standard is missing for Lyme antibody testing, we performed and compared different statistical approaches to validate the new Lyme multiplex assay. One approach was to use WB results as a 'relative gold standard' in ROC-curve and likelihood-ratio analyses of the new test. Cut-off values and interpretation ranges of the multiplex assay were established by the analysis. The second statistical approach used a Bayesian model for the calculation of diagnostic sensitivities and specificities of the multiplex assay. The Bayesian analysis takes into consideration that no true gold standard exists for detecting antibodies to B. burgdorferi and estimated sensitivities and specificities of both tests that were compared. Therefore, the Bayesian analysis also resulted in an evaluation of diagnostic sensitivity and specificity of WB. Overall, the new assay was characterized by low background values and a wide dynamic quantification range for the detection of antibodies to OspA, OspC and OspF antigens of B. burgdorferi. The diagnostic sensitivity and specificity for the OspA bead-based assay were calculated as 49% and 85%, respectively, and by a standard ROC curve analysis only because the Bayesian model could not be run on this parameter. The Bayesian-derived diagnostic sensitivities of the OspC and OspF assays were 80% and 86%, respectively. For comparison, the Bayesian-derived estimates for WB resulted in sensitivities of 72% for OspC and 80% for OspF. The Bayesian diagnostic specificities of the multiplex assay were 79% and 69% for OspC and OspF, respectively. WB analysis had specificities of 92% for OspC and 77% for OspF. Although the analysis of a new assay in the absence of a true gold standard remains challenging, the approach used here can help to address this problem when new technologies and traditionally used test standards differ significantly in their analytical sensitivities, which consequently causes problems in the calculation of diagnostic sensitivity and sensitivity values for the new assay. In summary, the new multiplex assay for the detection of antibodies to B. burgdorferi OspA, OspC and OspF antigens in horse serum has improved analytical and diagnostic sensitivities compared to WB analysis. Multiplex analysis is a valuable quantitative tool that simultaneously detects antibodies indicative for natural infection with and/or vaccination against the Lyme pathogen.
Publication Date: 2011-08-17 PubMed ID: 21890217DOI: 10.1016/j.vetimm.2011.08.005Google Scholar: Lookup
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  • Journal Article
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  • Non-U.S. Gov't

Summary

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This study presents the development and validation of a diagnostic tool for detection of Lyme Disease antibodies in horses. Researchers developed a fluorescent bead-based multiplex assay that detects the presence of antibodies to B. burgdorferi outer surface protein A (OspA), OspC and OspF antigens. The study showed that the new assay has improved analytical and diagnostic sensitivities compared to conventional testing.

Building the Multiplex Assay

The study focused on the creation of a new diagnostic tool for the detection of antibodies to B. burgdorferi, the bacteria causing Lyme disease, in horses. This fluorescent bead-based multiplex assay detects the presence of antibodies to three specific B. burgdorferi antigens, OspA, OspC, and OspF.

  • The multiplex assay works by detecting the interaction between fluorescent beads and antibodies within a horse’s serum.
  • The assay employed a diagnostic target, known as B. burgdorferi outer surface protein A (OspA), and two antigens (OspC and OspF), which are markers of B. burgdorferi in the body.
  • The study used serum of 562 horses, with testing carried out blindly to ensure objective results.

Validation of the Multiplex Assay

After creation, the researchers performed a thorough validation of this new diagnostic tool using both traditional statistical methods and a Bayesian approach.

  • Because there is no definite ‘gold standard’ for Lyme disease testing, the established Western Blotting (WB) method was used as the ‘relative gold standard’ for comparison purposes.
  • The researchers performed ROC-curve and likelihood-ratio analyses, which are statistical methods used to evaluate the performance of a diagnostic test.
  • Furthermore, Bayesian statistical analysis, which considers the absence of a true gold standard, was also applied. This yielded estimates for diagnostic sensitivities and specificities for both the multiplex assay and the WB method.

Findings and Implications

The results from the testing revealed that the new multiplex assay had improved analytical and diagnostic sensitivity compared to the traditional WB testing.

  • The multiplex assay demonstrated low background values and a broad dynamic range for quantification of antibodies to OspA, OspC, and OspF antigens.
  • The Bayesian-derived diagnostic sensitivities of the multiplex assay for OspC and OspF antigens were 80% and 86% respectively, which show considerable improvements from WB estimates of 72% and 80%.
  • Furthermore, the multiplex assay allows simultaneous detection of antibodies that indicate natural infection and/or vaccination against the Lyme pathogen, providing a quantitative evaluation of a horse’s immunization status.
  • The development and validation of this novel diagnostic tool is significant, as it provides a new, potentially more accurate way to detect Lyme Disease antibodies in horses, possibly leading to better management and control of the disease.

Cite This Article

APA
Wagner B, Freer H, Rollins A, Erb HN, Lu Z, Gröhn Y. (2011). Development of a multiplex assay for the detection of antibodies to Borrelia burgdorferi in horses and its validation using Bayesian and conventional statistical methods. Vet Immunol Immunopathol, 144(3-4), 374-381. https://doi.org/10.1016/j.vetimm.2011.08.005

Publication

ISSN: 1873-2534
NlmUniqueID: 8002006
Country: Netherlands
Language: English
Volume: 144
Issue: 3-4
Pages: 374-381

Researcher Affiliations

Wagner, Bettina
  • Department of Population Medicine and Diagnostic Sciences, Cornell University, Ithaca, NY, USA. bw73@cornell.edu
Freer, Heather
    Rollins, Alicia
      Erb, Hollis N
        Lu, Zhao
          Gröhn, Yrjo

            MeSH Terms

            • Animals
            • Antibodies, Bacterial / immunology
            • Antigens, Bacterial / immunology
            • Antigens, Surface / immunology
            • Bacterial Outer Membrane Proteins / immunology
            • Bacterial Vaccines / immunology
            • Bayes Theorem
            • Borrelia burgdorferi / immunology
            • Data Interpretation, Statistical
            • Fluorescence
            • Horse Diseases / diagnosis
            • Horse Diseases / immunology
            • Horses / immunology
            • Immunoassay / methods
            • Immunoassay / veterinary
            • Likelihood Functions
            • Lipoproteins / immunology
            • Lyme Disease / diagnosis
            • Lyme Disease / immunology
            • Lyme Disease / veterinary
            • Microspheres
            • ROC Curve
            • Reproducibility of Results
            • Sensitivity and Specificity

            Citations

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