Proteomic and molecular investigations into the diagnosis and progression of Motor Neuron Disease by the identification of biomarkers found in plasma

<p dir="ltr">Motor Neuron Disease (MND) encompasses a spectrum of neurodegenerative diseases that are progressive and fatal. Patients with a MND diagnosis on average will expect to live for approximately 2 years, however this can only be used as a guide given the heterogeneity of MND. Adding to the complexity of MND, it is often misdiagnosed as it can present as mimic degenerative diseases. This can prolong diagnosis and ultimately delay the intervention of treatments or care assistance. Currently there are no definitive biomarker/s for accurate diagnoses or the tracking of prognosis for majority of MND patients. It is the variability of disease combined with the extensive tests that only measure patient symptoms, which compound upon patient outcomes, treatments and care. The importance for prognostic and/or diagnostic biomarkers for MND are required to improve patient quality of life and outcomes. A potential robust biomarker derived from patient biofluid that is collected with minimum incisiveness is an avenue to scientifically explore for the betterment of patient outcomes with improved early treatment and manageable interventions due to the accurate and early detection of MND. The field of proteomics offers a solid base for the preliminary investigation of MND protein biomarkers. The Macquarie University, Neurodegenerative Diseases Biobank supplied a total 298 MND patient and control samples across 6 plasma biomarker studies. The first 3 studies (Chapter 4) were designed as Familial (genetic mutations; C9Orf72 and SOD1, Section 4.2), Sporadic (MND subtypes; ALS, PLS and FL, Section 4.3), and discordant Twins (Asymptomatic and Symptomatic, Section 4.4). Initially investigating from global proteomics studies SWATH Mass Spectrometry (SWATHMS) was chosen as the proteomic technique because it offers an unbiased and extensive exploration of potential proteins that are present in patient plasma samples. SWATHMS is capable of both qualitative and quantitative analysis of the proteins present in plasma. This allows for comparison of plasma samples across disease subsets of MND, genetic mutations (C9orf72 positive, Asymptomatic and Symptomatic) and longitudinally collected samples (Chapter 5), giving multi-directional avenues of data analysis that can pertain to either diagnostic or prognostic values of the data sets. Initially MND plasma SWATH-MS data from Familial and Sporadic Cohorts including those presenting with classical ALS, PLS and FL, identified approx. 400 proteins and of these, 20-40 proteins were listed as of interest based on statistical analysis. Interestingly, from gene ontology and pathways analysis, inflammatory/immune system markers were found to be deferentially expressed and will be explored using an orthogonal platform such as the BioPlex to validate. From the preliminary Global SWATH-MS data a further analysis applied machine learning (Chapter 7), with one application yielding a robust diagnostic identification pipeline for MND compared to healthy control samples. Machine learning has allowed for an applied pipeline with statistics applied and features to be tested by the training of data models to aid in the identification of proteins of interest that could be investigated further to be applied as a potential biomarker for MND. MND biomarkers will enable accurate diagnosis along with the potential to optimise clinical trials from how they are designed to applications of monitoring therapeutics for efficacy and improved patient treatment. This will be underpinned by an improved understanding of disease mechanisms, pathology and overall disease management to aid in both patient and clinical outcomes. Here recent insights related to potential MND biomarkers for both diagnostic and prognostic aspect of research and patient application will be discussed forming the preliminary ground work for a direct exploration of biofluid biomarker research.</p>