Hypothesis
1. CRTI leaves a mark on the plasma proteome.
2. Proteins act as mediators of the effect of CRTI on adverse cardiometabolic health. 3. Proteins can help classify ADVANCE participants as OA/non-OA.
Summary
The aims of the main project are:
- To find proteins associated with CRTI/amputation which will offer molecular insight into adverse cardiometabolic health in response to CRTI.
- To build machine-learning models to predict cardiometabolic trajectories using proteomics data and find predictive biomarkers for collaboration with Bio-Mil-OA: 1. We aim to build a machine-learning model to classify participants as OA/non-OA based on their proteomic profiles and in that way find predictive biomarkers. Only computational methods including linear modelling, structural equation modelling, tree-based modelling, and mediation analysis, will be used for these analyses.
Keywords
Proteomics, CRTI, Machine Learning, Osteoarthritis, Plasma Proteome