CATSS Collaborative Group (RPA Pilot / Seed Project)

The objectives of this proposal include the analysis of additional plasma samples to increase sample size and use of machine learning (ML) to identify biomarkers of cognitive outcomes for stroke patients. These data will be used to strengthen the preliminary data of our current grant submissions and create new grant proposals. The first four months will be used to collect 10 additional plasma samples for our BACTRAC study. We have 50 currently banked samples so a total of 60 samples will be sent to Olink proteomics for analysis. The analysis and associated data conversion will require another 3 months. The proteomic data will then be analyzed by ML over the next 3 months. The final two months will be used to compare the data analyzed by statistics with that of ML. The biomarkers that overlap with ML and statistical analysis will be considered the strongest candidates as biomarkers that predict cognitive performance after stroke. The NRPA funding will be used to increase our proteomic sample size for our project on predictive biomarkers for cognitive performance after stroke. Secondly, ML will be incorporated into this study as an additional technique to identify proteomic biomarkers associated with cognitive outcomes after stroke.