Detection of intrathecal antibodies to diagnose enterovirus infections of the central nervous system

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Abstract

Background
Enterovirus-D68 (EV-D68) predominantly causes respiratory disease. However, EV-D68 infections also have been associated with central nervous system (CNS) complications, most specifically acute flaccid myelitis (AFM). Diagnosing EV-D68-associated CNS disease is challenging since viral RNA is rarely detected in cerebrospinal fluid (CSF).

Objective
In order to determine an EV antibody index (AI), we evaluated the value of a commercially available quantitative ELISA to detect EV-specific antibodies in paired CSF and blood.

Study design
Nine paired CSF and blood samples were obtained from patients with EV-D68-associated AFM or from patients with a confirmed EV-associated CNS disease. EV-specific antibodies were detected using a quantitative ELISA. A Reiber diagram analysis was performed, by which the AI was calculated. Subsequently, EV ELISA results were compared with an EV-D68 virus neutralization test.

Results
ELISA detected EV-specific antibodies in 1 out of the 3 patients with EV-D68-associated AFM and in 3 out of the 6 patients with confirmed EV-associated CNS disease. In these patients, the AI was indicative for intrathecal antibody production against enterovirus. Assay comparison showed that EV-D68 neutralizing antibody detection increased the sensitivity of EV-D68 antibody detection.

Conclusions
A quantitative EV IgG ELISA in combination with Reiber diagram analysis and AI-calculation can be used as a diagnostic tool for EV-associated CNS disease, including EV-D68. An EV-D68 specific ELISA will improve the sensitivity of the tool. With the growing awareness that the detection of non-polio enteroviruses needs to be improved, diagnostic laboratories should consider implementation of EV serology.
Original languageEnglish
Article number105190
JournalJournal of Clinical Virology
Volume152
DOIs
Publication statusPublished - Jul 2022

Bibliographical note

Funding Information:
DvR is supported by a fellowship from the Netherlands Organization for Scientific.Research (VIDI contract 91718308).

Publisher Copyright:
© 2022 The Author(s)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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