Abstract
Objective: Autoimmune encephalitis (AE) is a severe but treatable autoimmune disorder that is diagnosed by antibody (Ab) testing. However, it is unrealistic to obtain an early diagnosis in some areas since the Ab status cannot be immediately determined due to time and technology restrictions. In our study, we aimed to validate the Antibody Prevalence in Epilepsy and Encephalopathy (APE2) score among patients diagnosed with possible AE as a predictive model to screen AE patients with antibodies to cell-surface proteins expressed in neurons.Methods: A total of 180 inpatients were recruited, and antibodies were detected through serological and/or cerebrospinal fluid (CSF) evaluations. The APE2 score was used to validate the predictive models of AE with autoantibodies.Results: The mean APE2 score in the Ab-positive cases was 7.25, whereas the mean APE2 score in the Ab-negative cases was 3.18 (P < 0.001). The APE2 score had a receiver operating characteristic (ROC) area under the curve of 0.924 [P < 0.0001, 95% confidence interval (CI) = 0.875–0.973]. With a cutoff score of 5, the APE2 score had the best psychometric properties, with a sensitivity of 0.875 and a specificity of 0.791.Conclusion: The APE2 score is a predictive model for AE with autoantibodies to cell-surface proteins expressed in neurons and was validated and shown to have high sensitivity and specificity in our study. We suggest that such a model should be used in patients with a suspected diagnosis of AE, which could increase the detection rate of Abs, reduce testing costs, and help patients to benefit from treatment quickly.
Highlights
Autoimmune encephalitis (AE) is an immune-mediated neurological disorder characterized by rapidly progressive central nervous system (CNS) symptoms that is associated with specific autoantibodies targeting cell-surface neuronal antigens [1]
As more related cases have been identified in the past 10 years, there has been increasing interest in the pathogenesis and clinical features of AE, especially in patients with Abs to cell-surface proteins expressed in neurons, including antibodies against synaptic receptors and antibodies targeting ion channels and cell-surface proteins, who have an effective response to immunosuppressive therapies and who respond well to immunosuppressive therapies [4]
All serum and cerebrospinal fluid (CSF) specimens were screened by standardized indirect immunofluorescence assays (IFAs) and cell-based assays (CBAs) using human embryonic kidney (HEK) 293 cells transfected with appropriate expression plasmids to confirm IgGs specific for N-methyl-D-aspartate receptor (NMDAR), AMPA1, AMPA2, leucine-rich gliomainactivated 1 (LGI1), CASPR2, gamma-aminobutyric acid B receptor (GABABR), and DPPX
Summary
Autoimmune encephalitis (AE) is an immune-mediated neurological disorder characterized by rapidly progressive central nervous system (CNS) symptoms that is associated with specific autoantibodies targeting cell-surface neuronal antigens [1]. The identified forms of AE might be associated with antibodies (Abs) against intracellular antigens, synaptic receptors, ion channels, or cell-surface proteins, according to the location of these specific autoantibodies [3]. An Ab prediction model that is not based on Ab detection is helpful for early diagnosis and can save medical resources and reduce the economic burden of patients These issues prompted researchers to explore methods for the early diagnosis of AE and to establish predictive models for the detection of autoantibodies based on the clinical presentation and initial neurologic evaluations prior to Ab testing
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