Nephrotic syndrome is the most common cause of kidney disease in children worldwide, with up to 3000 Canadian children newly diagnosed each year. Most children respond to first-line treatment with corticosteroids and are labelled as having steroid sensitive nephrotic syndrome (SSNS). There is enormous phenotypic variability in SSNS, ranging from an isolated episode to a severe relapsing course to dependence on ongoing immunosuppression to maintain remission; the cause of this variability is largely unknown and I hypothesize that genetic determinants play a role. In this project, I will correlate the specific clinical features of SSNS in 749 children with their genetic variants by (broadly) using linear regression analysis. This study will determine if there are genetic variants that can predict SSNS phenotype, which will then allow us to risk stratify patients with SSNS to optimize treatment regimens. 

For this project, the applicant will be required to collect the specific clinical information from my database of children with SSNS. This would include demographic information, number of disease relapses, medications and dosages, time to remission during initial episode, etc. I will later use this information to relate it to the genetic information collected on the same children.