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Predicting and monitoring outcomes in Autoimmune Encephalitis (POTA)

Autoimmune encephalitis (AE) is an important, potentially reversible cause of epilepsy. While relatively rare, AE is at least as common as infectious encephalitis [1] and its pathophysiology remains poorly understood. Despite effective treatments, long-term outcomes are variable and lack robust clinical and biochemical predictors.
There is a strong clinical need for biomarkers in AE that predict outcomes and direct treatments. With an Irish focus, there is a need for a centralised registry of patients with AE to optimise their involvement in research and ultimately their clinical management.
We will recruit patients with AE from Ireland and the UK create a biobank of serum and CSF samples for research into prognostic and mechanistic biomarkers of AE, such as microRNAs, cytokines and chemokines.
MicroRNAs are small, non-coding RNA molecules which target mRNAs to regulate gene expression, influencing cell development, homeostasis, degeneration, and inflammation. Differential expression of microRNAs in serum and cerebrospinal fluid (CSF) have been identified as potential biomarkers in epilepsy and other inflammatory neurological disorders like MS. They have demonstrated potential clinical applications as early diagnostic and prognostic markers, therapeutic targets, and markers of disease pathogenesis. However, there has been little study into the role of microRNAs in AE. We will use state-of-the-art Next Generation Sequencing (NGS) techniques to identify differences in microRNA expression between subgroups of patients with AE and between patients and controls.
Cytokines and chemokines, which promote and regulate inflammation, are showing increasing potential as biomarkers in AE, though there has been limited research into the prognostic values of such biomarkers. We propose to investigate the utility of CSF cytokines and chemokines in AE and predictors of disease outcomes.
The identification of robust biomarkers of treatment outcome and response will allow us to ‘risk-stratify’ patients with AE and direct their therapies early in the disease course.