首页> 外文期刊>Veterinary Immunology and Immunopathology >Development of a multiplex assay for the detection of antibodies to Borrelia burgdorferi in horses and its validation using Bayesian and conventional statistical methods.
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Development of a multiplex assay for the detection of antibodies to Borrelia burgdorferi in horses and its validation using Bayesian and conventional statistical methods.

机译:开发用于检测马中伯氏疏螺旋体抗体的多重检测方法,并使用贝叶斯和常规统计方法进行验证。

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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.Digital Object Identifier http://dx.doi.org/10.1016/j.vetimm.2011.08.005
机译:莱姆病是一种人畜共患的媒介传播疾病,发生在包括马在内的哺乳动物中。该疾病是由伯氏疏螺旋体的螺旋体感染引起的。哺乳动物宿主的感染需要在tick叮咬期间通过被感染的s传播螺旋体。莱姆病的诊断基于临床体征,可能暴露于受感染的虱子以及传统上通过ELISA和Western blotting(WB)进行的抗体检测。该报告描述了用于检测针对B的抗体的新型基于荧光珠的多重测定法的开发和验证。马血清中的burgburgeri外表面蛋白A(OspA),OspC和OspF抗原。通过使用WB和新的多重测定法,盲目且平行地进行了562马血清的测试。由于莱姆抗体测试缺少真正的金标准,因此我们执行并比较了不同的统计方法,以验证新的莱姆多重测定。一种方法是在新测试的ROC曲线和似然比分析中将WB结果用作“相对黄金标准”。通过分析确定了多重测定的临界值和解释范围。第二种统计方法是使用贝叶斯模型来计算多重测定的诊断敏感性和特异性。贝叶斯分析考虑了不存在检测B抗体的真正金标准。 burgdorferi ,并比较了两种测试的估计敏感性和特异性。因此,贝叶斯分析还可以评估WB的诊断敏感性和特异性。总的来说,该新测定法的特征在于低背景值和宽动态定量范围,用于检测针对B的OspA,OspC和OspF抗原的抗体。 burgdorferi 。 OspA珠基检测的诊断灵敏度和特异性分别计算为49%和85%,并通过标准ROC曲线分析仅是因为无法在该参数上运行贝叶斯模型。 OspC和OspF分析的贝叶斯派生诊断敏感性分别为80%和86%。为了进行比较,贝叶斯派生的WB估计值对OspC的敏感性为72%,对OspF的敏感性为80%。多重测定的贝叶斯诊断特异性对于OspC和OspF分别为79%和69%。 WB分析对OspC的特异性为92%,对OspF的特异性为77%。尽管在没有真正金标准的情况下进行新测定的分析仍然具有挑战性,但是当新技术和传统使用的测试标准的分析灵敏度明显不同时,此处使用的方法可以帮助解决此问题,从而在计算中引起问题新测定的诊断灵敏度和灵敏度值。总之,用于检测针对B的抗体的新的多重测定法。与WB分析相比,马血清中的burgdorferi OspA,OspC和OspF抗原具有更高的分析和诊断敏感性。多重分析是一种有价值的定量工具,可同时检测表示莱姆病原体自然感染和/或已接种疫苗的抗体。数字对象标识符http://dx.doi.org/10.1016/j.vetimm.2011.08.005

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