Project 1
Identification of non-coding RNA biomarkers for disease prognosis and progression in Amyotrophic Lateral Sclerosis
PI: Majid Hafezparast
Researcher: Greig Joilin
Diagnosis of ALS/MND relies on clinical judgement and investigations to exclude other conditions, a process that may delay diagnosis and therefore treatment for many months. It is also difficult in the individuals with MND to predict the speed at which the disease will progress. Therefore, finding an indicator (biomarker) of disease in blood will decrease delay in diagnosis, improve understanding of progression, and, because some biomarkers are also related to causation, facilitate development of new treatments. We have been working on identifying a group of molecules called non-coding RNA (ncRNA) in the blood of people with ALS as potential biomarkers. We have identified seven ncRNAs that allow us to predict if a sample is from people with ALS or not. However, these ncRNAs do not reflect the speed at which the disease will progress, so we need to search for ncRNA biomarkers that change over time so that we can both predict and track disease progression. This will be done with the use of ALS samples collected over the course of the disease that have been enrolled into a large clinical trial and crucially we will use machine learning techniques to identify complex patterns of changes in dysregulated ncRNAs. This will allow us to predict the behaviour of ALS more accurately, to understand key differences between people with ALS, to aid in treatment development, and hence to improve outcomes for people affected by ALS.
This work is supported by the Motor Neurone Disease Association and the My Name'5 Doddie Association.
Joilin, G., Gray, E., Thompson, A. G., Bobeva, Y., Talbot, K., Weishaupt, J., Ludolph, A., Malaspina, A., Leigh, P. N., Newbury, S., Turner, M. R., & Hafezparast, M. (2020). Identification of a potential non-coding RNA biomarker signature for amyotrophic lateral sclerosis. Brain Communications, 2(1). Read more here >