Neural antibodies have emerged as useful biomarkers in suspected autoimmune encephalitis. We reviewed results of neural antibody testing (anti-N-methyl D-aspartate receptor (NMDAR), leucine-rich glioma-inactivated protein (LGI1), contactin-associated protein-like 2 (CASPR2), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR), γ-aminobutyric acid type B receptor (GABA(B)R), dipeptidyl-peptidase-like protein-6 (DPPX), IgLON family member 5 (IgLON5) and glutamic acid decarboxylase-65 (GAD65)) using cell-based assays (CBAs) and tissue indirect immunofluorescence (TIIF) at our centre. Our findings suggest increased clinical sensitivity of CBA compared to TIIF. However, this may come at some expense to clinical specificity, as evidenced by possible false-positive results when weak serum positivity by CBA was observed for certain antibodies (i.e. anti-NMDAR, CASPR2). In such cases, correlation with serum TIIF, as well as CSF CBA and TIIF, aids in identifying true-positive results.
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http://dx.doi.org/10.1017/cjn.2021.23 | DOI Listing |
Mult Scler
January 2025
Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Testing for myelin oligodendrocyte glycoprotein immunoglobulin G antibodies (MOG-IgG) is essential to the diagnosis of MOG antibody-associated disease (MOGAD). Due to its central role in the evaluation of suspected inflammatory demyelinating disease, the last 5 years has been marked by an abundance of research into MOG-IgG testing ranging from appropriate patient selection, to assay performance, to utility of serum titers as well as cerebrospinal fluid (CSF) testing. In this review, we synthesize current knowledge pertaining to the "who, what, where, when, why, and how" of MOG-IgG testing, with the aim of facilitating accurate MOGAD diagnosis in clinical practice.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Pathology, Faculty of Health Care and Social Work, Trnava University and University Hospital, 917 02 Trnava, Slovakia.
The autoantibodies against the NR1 subunit are well known in the pathomechanism of NMDAR encephalitis. The dysfunction of the NR2 subunit could be a critical factor in this neurological disorder due to its important role in the postsynaptic pathways that direct synaptic plasticity. We report a case of paraneoplastic anti-NMDAR encephalitis presented alongside very severe illness.
View Article and Find Full Text PDFBMC Neurol
January 2025
Department of Hematology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
Background: Multiple myeloma (MM) with Guillain-Barré syndrome (GBS) is relatively rare, and the specific mechanism is still unclear. The previous infection, surgery, and medication use may have contributed to the occurrence of GBS. The use of bortezomib in patients with MM can easily lead to peripheral neuropathy, which is similar to the symptoms of GBS, making it challenging to diagnose GBS.
View Article and Find Full Text PDFBehav Brain Res
January 2025
Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Von-Siebold-Str. 5, 37075 Göttingen, Germany.
Background: Neural autoantibodies are being increasingly detected in conjunction with neurodegenerative dementias such as Alzheimer's disease dementia (AD), yet their significance is not well clarified. In this case report, we report the previously unreported long-lasting persistence of potassium voltage-gated channel subfamily A member 2 (KCNA2) antibodies in biomarker-supported AD.
Methods: We report on a 77-year-old, male patient evaluated in our outpatient memory clinic of the Department of Psychiatry and Psychotherapy, University Medical Center Göttingen.
Anal Chem
January 2025
The School of Information Sciences and Technology, Northwest University, Xi'an 710127, P.R.China.
Digital fluorescence immunoassay (DFI) based on random dispersion magnetic beads (MBs) is one of the powerful methods for ultrasensitive determination of protein biomarkers. However, in the DFI, improving the limit of detection (LOD) is challenging since the ratio of signal-to-background and the speed of manual counting beads are low. Herein, we developed a deep-learning network (ATTBeadNet) by utilizing a new hybrid attention mechanism within a UNet3+ framework for accurately and fast counting the MBs and proposed a DFI using CdS quantum dots (QDs) with narrow peak and optical stability as reported at first time.
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