Grant: Catalyst Grant: Analysis of CLSA Data

Premature aging is a process associated with a progressive accumulation of deleterious changes over time across multiple organs, an impairment of physiologic functions, and an increase in the risk of disease and death. Among all organs, the kidneys are particularly affected by aging by their intrinsic exposure to exogenous compounds during the filtration process. The consequences of kidney aging and chronic kidney disease (CKD) are large for the society, including numerous co-morbidities, with currently no cure for chronic kidney disease and limited treatment options. Although the hallmarks of kidney aging have been well described, their effects are heterogenous across individuals, in part due to environmental and genetic influences unique to each individual, making it challenging to identify biomarkers and environments contributing to healthy aging of the kidney and identify individuals the most at risk for CKD and who would benefit the most from preventive strategies. Here, we propose to use CLSA cohort to test the overarching hypothesis that kidney fonction decline in the aging population follows different trajectories of either early and late onset kidney decline that are dependant upon personal genetic variation and environmental exposures response. We will harness this hypothesis to build integrative, multi-omics predictive models of kidney function decline trajectories that can be used to improve preventive strategies.