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Cell-based assays for the detection of MOG antibodies: a comparative study.
J Neurol. 2020 Jul 04 [Online ahead of print]JN

Abstract

BACKGROUND

The detection of antibodies to myelin oligodendrocyte glycoprotein (MOG) is fundamental for the identification of MOG antibody-associated disorders (MOGAD), and the differential diagnosis of acquired demyelinating syndromes of the CNS, among which multiple sclerosis (MS). We compared the diagnostic performance of four cell-based assays (CBAs) for their detection.

METHODS

Consecutive sera from 204 patients with 'possible MOGAD' (55), MS (112), and other neurological disorders (OND, 37) were tested for MOG-IgG with a live-CBA with anti-heavy-and-light chain secondary-antibody (LCBA-IgGH+L), and a live-CBA for IgG1 (LCBA-IgG1). A subgroup of 71 patients was additionally tested with a live-CBA with anti-Fcγ secondary-antibody (LCBA-IgGFcγ), and a commercial fixed-CBA with anti-Fcγ secondary-antibody (FCBA-IgGFcγ). RESULTS: Fifty-seven/204 patients (27.9%) were MOG-IgG-positive. Sensitivity was 89.1% (CI:77.8-95.9) and specificity 93.3% (CI:88.0-96.7) for LCBA-IgGH+L, and 74.6% (CI:61.0-85.3) and 100% (CI:97.6-100) for LCBA-IgG1. Eighteen of 57 (31%) samples showed discrepant results (all negative on LCBA-IgG1); of these, three with 'possible MOGAD' showed high-titer MOG-IgG (≥ 1:640), and positivity for MOG-IgG2, whereas 15/18 had low-titer MOG-IgG (1:160/1:320) and mixed diagnoses (5 'possible MOGAD', 6 MS, 4 OND). In the subgroup analysis, sensitivity was 92.3% (CI:79.1-98.4) and specificity 97.0% (CI:83.8-99.9) for LCBA-IgGFcγ, and 87.2% (CI:72.6-95.7) and 97.0% (CI:83.8-99.9) for FCBA-IgGFcγ.

CONCLUSIONS

LCBA-IgG1 showed the highest specificity but can miss MOG-IgG2 reactivities, whose meaning warrants further investigations. Titration of samples tested with LCBA-IgGH+L/ IgGFcγ is important for meaningful interpretation of the results. In the subgroup analysis, LCBA-IgGFcγ yielded the highest accuracy, and FCBA-IgGFcγ good specificity, but it was at risk of false-negative results.

Authors+Show Affiliations

Neuroimmunology Laboratory, IRCCS Mondino Foundation, Pavia, Italy. matteo.gastaldi@mondino.it. Neuro-Oncology and Neuroinflammation Unit, IRCCS Mondino Foundation, Pavia, Italy. matteo.gastaldi@mondino.it.Neuroimmunology Laboratory, IRCCS Mondino Foundation, Pavia, Italy.Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Otto Meyerhof Center, Heidelberg, Germany.Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Otto Meyerhof Center, Heidelberg, Germany.Neuroimmunology Laboratory, IRCCS Mondino Foundation, Pavia, Italy.Multiple Sclerosis Centre, IRCCS Mondino Foundation, Pavia, Italy.Multiple Sclerosis Centre, IRCCS Mondino Foundation, Pavia, Italy.Neuro-Oncology and Neuroinflammation Unit, IRCCS Mondino Foundation, Pavia, Italy.Pediatric Clinic, IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy.Pediatric Clinic, IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy.Neurology and Stroke Unit, Circolo Hospital/Macchi Foundation, University of Insubria, Varese, Italy.Neurology and Stroke Unit, Circolo Hospital/Macchi Foundation, University of Insubria, Varese, Italy.Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy.Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy. IRCCS Policlinico San Martino, Genoa, Italy.Unit of Child Neuropsychiatry, Clinical and Surgical Neurosciences Department, IRCCS Istituto Giannina Gaslini, Genova, Italy.Unit of Child Neuropsychiatry, Clinical and Surgical Neurosciences Department, IRCCS Istituto Giannina Gaslini, Genova, Italy.Multiple Sclerosis Centre, ASST Valle Olona - Gallarate Hospital, Gallarate, Italy.Multiple Sclerosis Centre, ASST Valle Olona - Gallarate Hospital, Gallarate, Italy.Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy.San Raffaele Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.Clinical Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK.Neuroimmunology Laboratory, IRCCS Mondino Foundation, Pavia, Italy.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32623596

Citation

Gastaldi, Matteo, et al. "Cell-based Assays for the Detection of MOG Antibodies: a Comparative Study." Journal of Neurology, 2020.
Gastaldi M, Scaranzin S, Jarius S, et al. Cell-based assays for the detection of MOG antibodies: a comparative study. J Neurol. 2020.
Gastaldi, M., Scaranzin, S., Jarius, S., Wildeman, B., Zardini, E., Mallucci, G., Rigoni, E., Vegezzi, E., Foiadelli, T., Savasta, S., Banfi, P., Versino, M., Benedetti, L., Novi, G., Mancardi, M. M., Giacomini, T., Annovazzi, P., Baroncini, D., Ferraro, D., ... Franciotta, D. (2020). Cell-based assays for the detection of MOG antibodies: a comparative study. Journal of Neurology. https://doi.org/10.1007/s00415-020-10024-0
Gastaldi M, et al. Cell-based Assays for the Detection of MOG Antibodies: a Comparative Study. J Neurol. 2020 Jul 4; PubMed PMID: 32623596.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Cell-based assays for the detection of MOG antibodies: a comparative study. AU - Gastaldi,Matteo, AU - Scaranzin,Silvia, AU - Jarius,Sven, AU - Wildeman,Brigitte, AU - Zardini,Elisabetta, AU - Mallucci,Giulia, AU - Rigoni,Eleonora, AU - Vegezzi,Elisa, AU - Foiadelli,Thomas, AU - Savasta,Salvatore, AU - Banfi,Paola, AU - Versino,Maurizio, AU - Benedetti,Luana, AU - Novi,Giovanni, AU - Mancardi,Margherita Maria, AU - Giacomini,Thea, AU - Annovazzi,Pietro, AU - Baroncini,Damiano, AU - Ferraro,Diana, AU - Lampasona,Vito, AU - Reindl,Markus, AU - Waters,Patrick, AU - Franciotta,Diego, Y1 - 2020/07/04/ PY - 2020/05/02/received PY - 2020/06/25/accepted PY - 2020/06/23/revised PY - 2020/7/6/entrez PY - 2020/7/6/pubmed PY - 2020/7/6/medline KW - Autoantibodies KW - Cell-based assay KW - Demyelinating disorders KW - Multiple sclerosis KW - Myelin oligodendrocyte glycoprotein KW - Myelitis KW - Optic neuritis KW - Standardization JF - Journal of neurology JO - J. Neurol. N2 - BACKGROUND: The detection of antibodies to myelin oligodendrocyte glycoprotein (MOG) is fundamental for the identification of MOG antibody-associated disorders (MOGAD), and the differential diagnosis of acquired demyelinating syndromes of the CNS, among which multiple sclerosis (MS). We compared the diagnostic performance of four cell-based assays (CBAs) for their detection. METHODS: Consecutive sera from 204 patients with 'possible MOGAD' (55), MS (112), and other neurological disorders (OND, 37) were tested for MOG-IgG with a live-CBA with anti-heavy-and-light chain secondary-antibody (LCBA-IgGH+L), and a live-CBA for IgG1 (LCBA-IgG1). A subgroup of 71 patients was additionally tested with a live-CBA with anti-Fcγ secondary-antibody (LCBA-IgGFcγ), and a commercial fixed-CBA with anti-Fcγ secondary-antibody (FCBA-IgGFcγ). RESULTS: Fifty-seven/204 patients (27.9%) were MOG-IgG-positive. Sensitivity was 89.1% (CI:77.8-95.9) and specificity 93.3% (CI:88.0-96.7) for LCBA-IgGH+L, and 74.6% (CI:61.0-85.3) and 100% (CI:97.6-100) for LCBA-IgG1. Eighteen of 57 (31%) samples showed discrepant results (all negative on LCBA-IgG1); of these, three with 'possible MOGAD' showed high-titer MOG-IgG (≥ 1:640), and positivity for MOG-IgG2, whereas 15/18 had low-titer MOG-IgG (1:160/1:320) and mixed diagnoses (5 'possible MOGAD', 6 MS, 4 OND). In the subgroup analysis, sensitivity was 92.3% (CI:79.1-98.4) and specificity 97.0% (CI:83.8-99.9) for LCBA-IgGFcγ, and 87.2% (CI:72.6-95.7) and 97.0% (CI:83.8-99.9) for FCBA-IgGFcγ. CONCLUSIONS: LCBA-IgG1 showed the highest specificity but can miss MOG-IgG2 reactivities, whose meaning warrants further investigations. Titration of samples tested with LCBA-IgGH+L/ IgGFcγ is important for meaningful interpretation of the results. In the subgroup analysis, LCBA-IgGFcγ yielded the highest accuracy, and FCBA-IgGFcγ good specificity, but it was at risk of false-negative results. SN - 1432-1459 UR - https://www.unboundmedicine.com/medline/citation/32623596/Cell-based_assays_for_the_detection_of_MOG_antibodies:_a_comparative_study L2 - https://dx.doi.org/10.1007/s00415-020-10024-0 DB - PRIME DP - Unbound Medicine ER -
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