Biomarker Discovery including proteomic analysis of Biological Material
Project Description: The purpose of this study is to examine what new insights we can get into ALS by analysing samples collected over time in conjunction with their detailed clinical data.
Project Objective: The common objective of the Project is to provide and validate a prediction model for disease progression (using ALSFRS-R Slope, staging scales, ECAS and other measures of progression), and to refine this model using novel markers from serum, plasma and CSF and other markers such as neuroelectric signal analysis, that will support new pharmaceutical developments for the clinical treatment of ALS patients. (A prediction model is a statistical or machine learning model that uses historical and current data to forecast future outcomes.) This requires collaborative inputs from the partners expertise in data science, clinical domain, and pharmaceutical outcomes to effect the full ambition of the project. The samples will undergo proteomics analysis as part of this study. (Proteomic analysis, or proteomics, involves the systematic identification and quantification of the complete set of proteins (the proteome) in a cell, tissue, organ, or organism at a specific time.) This work is includes samples and data from the following four Precision ALS Sites; Dublin, Utrecht, Karolinska (Stockholm) and Bellvitge (Barcelona).
Project Status: Follow-up data sampling is continuing. Approx. 650 participants have been sampled at time one for blood serum and plasma (and cerebrospinal fluid (CSF) at a subset of sites) in line with the original project plan and are currently being followed up at 4-6 monthly intervals for up to three follow-up samplings of blood serum and plasma. Sampling will finish in summer 2026 and these samples will then be analysed in conjunction with the prospective data collected and the work will be published in peer reviewed journals.