The 3rd Annual Queen Square Address Symposium

3 December 2024

This year’s symposium, held on 24th October 2024, focused on clinical and digital biomarkers for various neurological and neuromuscular diseases. The event featured talks on Alzheimer’s, Parkinson’s, Multiple Sclerosis, Epilepsy, and Peripheral Neuropathies.

The Symposium was organized by the IoN Deputy Director for Translation and Enterprise, Professor Dimitri Kullmann, the Deputy Director for Partnership and Communication, Professor Selina Wray, and the Senior Translational Research Manager, Dr. Eleonora Lugarà.

Dr. Ashvini Keshavan

Dr Keshavan presented the ADAPT (Alzheimer's disease Diagnosis and Plasma p-Tau217) study, which explores the use of blood tests for the early diagnosis of Alzheimer’s Disease (AD). Accurate diagnosis is crucial as it not only prepares patients and their families for the future but also provides access to experimental trials and research studies. Currently, misdiagnosis rates for AD can be as high as 30%. As new therapies emerge, an accurate diagnosis will become even more essential to maximise their impact.

Professor Thomas Foltynie

Professor Foltynie discussed the various biomarkers in Parkinson’s disease (PD). A major focus in PD research is measuring alpha-synuclein, which has been, and in some aspects still is a long-standing challenge. The most advanced alpha-synuclein measurements can distinguish healthy controls from patients, classify disease severity and progression, and differentiate PD from other forms of Parkinsonism. Recently, the seed amplification assay has emerged as one of the most successful and precise tests for distinguishing PD from dementia with Lewy bodies and other neurodegenerative diseases. Professor Foltynie concluded by listing other biomarkers for PD, such as imaging techniques and digital wearable devices.

Dr Vino Vivekanandam

Dr Vivekanadam talked about the evolution and outlook for biomarkers in muscle channelopathies and periodic paralysis. Historically, diagnosis relied heavily on symptom observation and electromyography (EMG), both of which have served as the gold standard for evaluating these rare conditions. However, these methods often exhibit significant variability in interpretation and frequently show limited correlation with one another. Since then, the field has progressed to include validated patient-reported outcome measures, though these remain subject to considerable subjective interpretation. To address this, newer digital wearables, such as wristbands and gait-monitoring insoles, are now being developed to objectively quantify aspects that hold subjective importance for patients. Also intramuscular fat accumulation muscle MRI and diffusion MRI are on the cusp of being developed for these and similar indications.

Professor Beate Diehl

Professor Diehl explained the clinical and imaging biomarkers used for a greatly underserved and misunderstood issue in the Epilepsy field, namely Sudden and Unexpected Death linked with Epilepsy (SUDEP). SUDEP is the second biggest cause of ‘years of potential life lost’ due to neurological disease in many geographies, overcome just by stroke. The difficulty lies in the lack of predictive biomarkers. Poor adherence to medication, family history, severity of seizures and cardiac arrhythmia are examples of clinical biomarkers used in everyday assessment. Newer imaging biomarkers in specific brain regions, coupled with cardiorespiratory measurements have been recently identified as promising prognostic markers, but a lot more work needs to be done to understand this disease fully.

Professor Ahmed Toosy

Professor Toosy talked about the complex clinical evolution of Multiple Sclerosis (MS) during a patient’s lifetime. Professor Toosy elucidated current (2017) MS diagnosis criteria, including the appearance of lesions in time and space, highlighting the importance of early diagnosis for improving clinical outcomes. In MS as in other therapeutic areas highlighted above, advanced imaging technologies are extremely important for delineating the mechanisms of neurodegeneration, especially coupled with newer artificial intelligence tools.