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糖基-iELISA:一种高度敏感且明确的血清学方法,用于诊断由血清型 O157 引起的 STEC-HUS。

Glyco-iELISA: a highly sensitive and unambiguous serological method to diagnose STEC-HUS caused by serotype O157.

机构信息

Radboud Institute for Molecular Life Sciences, Amalia Children's Hospital, Department of Pediatric Nephrology, Radboud University Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.

Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.

出版信息

Pediatr Nephrol. 2019 Apr;34(4):631-639. doi: 10.1007/s00467-018-4118-9. Epub 2018 Oct 26.

DOI:10.1007/s00467-018-4118-9
PMID:30367236
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6394669/
Abstract

BACKGROUND

Providing proof of presence of Shiga toxin-producing E. coli (STEC) infection forms the basis for differentiating STEC-hemolytic uremic syndrome (HUS) and atypical HUS. As the gold standard to diagnose STEC-HUS has limitations, using ELISA to detect serum antibodies against STEC lipopolysaccharides (LPS) has proven additional value. Yet, conventional LPS-ELISA has drawbacks, most importantly presence of cross-reactivity due to the conserved lipid A part of LPS. The newly described glyco-iELISA tackles this issue by using modified LPS that eliminates the lipid A part. Here, the incremental value of glyco-iELISA compared to LPS-ELISA is assessed.

METHODS

A retrospective study was performed including all pediatric patients (n = 51) presenting with a clinical pattern of STEC-HUS between 1990 and 2014 in our hospital. Subsequently, the diagnostic value of glyco-iELISA was evaluated in a retrospective nationwide study (n = 264) of patients with thrombotic microangiopathy (TMA). LPS- and glyco-iELISA were performed to detect IgM against STEC serotype O157. Both serological tests were compared with each other and with fecal diagnostics.

RESULTS

Glyco-iELISA is highly sensitive and has no cross-reactivity. In the single-center cohort, fecal diagnostics, LPS-ELISA, and glyco-iELISA identified STEC O157 infection in 43%, 65%, and 78% of patients, respectively. Combining glyco-iELISA with fecal diagnostics, STEC infection due to O157 was detected in 89% of patients. In the nationwide cohort, 19 additional patients (8%) were diagnosed with STEC-HUS by glyco-iELISA.

CONCLUSION

This study shows that using glyco-iELISA to detect IgM against STEC serotype O157 has clear benefit compared to conventional LPS-ELISA, contributing to optimal diagnostics in STEC-HUS.

摘要

背景

证明产志贺毒素大肠杆菌 (STEC) 感染的存在是区分 STEC-溶血尿毒综合征 (HUS) 和非典型 HUS 的基础。由于诊断 STEC-HUS 的金标准存在局限性,因此使用 ELISA 检测针对 STEC 脂多糖 (LPS) 的血清抗体已被证明具有额外的价值。然而,传统的 LPS-ELISA 存在缺陷,最重要的是由于 LPS 的保守脂质 A 部分存在交叉反应。新描述的糖基-iELISA 通过使用消除脂质 A 部分的修饰 LPS 来解决这个问题。在这里,评估了糖基-iELISA 与 LPS-ELISA 相比的增量价值。

方法

进行了一项回顾性研究,包括 1990 年至 2014 年间在我院就诊的具有 STEC-HUS 临床特征的所有儿科患者(n=51)。随后,在我们的全国性回顾性研究(n=264)中评估了糖基-iELISA 的诊断价值,该研究包括患有血栓性微血管病 (TMA) 的患者。进行 LPS-和 glyco-iELISA 以检测针对 STEC 血清型 O157 的 IgM。将这两种血清学检测方法相互比较,并与粪便诊断进行比较。

结果

糖基-iELISA 具有高度的敏感性且无交叉反应。在单中心队列中,粪便诊断、LPS-ELISA 和 glyco-iELISA 分别在 43%、65%和 78%的患者中确定了 STEC O157 感染。将 glyco-iELISA 与粪便诊断相结合,可在 89%的患者中检测到由 O157 引起的 STEC 感染。在全国性队列中,通过 glyco-iELISA 额外诊断出 19 例(8%)STEC-HUS 患者。

结论

本研究表明,与传统的 LPS-ELISA 相比,使用 glyco-iELISA 检测针对 STEC 血清型 O157 的 IgM 具有明显的优势,有助于 STEC-HUS 的最佳诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/423e1e2481f9/467_2018_4118_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/f599634c5181/467_2018_4118_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/cd0046a9414f/467_2018_4118_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/057fcefe774b/467_2018_4118_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/423e1e2481f9/467_2018_4118_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/f599634c5181/467_2018_4118_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/cd0046a9414f/467_2018_4118_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/057fcefe774b/467_2018_4118_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a24/6394669/423e1e2481f9/467_2018_4118_Fig4_HTML.jpg

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