PROJECT SUMMARY/ABSTRACT Children with proteinuric glomerulopathies are at considerable risk for cardiovascular disease. In addition to the high prevalence of traditional cardiovascular disease risk factors in this population, more than half of children with proteinuric glomerulopathies experience nocturnal blood pressure dysregulation, defined by nocturnal hypertension or a reduced decline in nocturnal blood pressure (non-dipping pattern). Nocturnal blood pressure dysregulation is independently associated with poor cardiovascular disease outcomes in adults. In this context, the objective of this proposal is to understand the cardiovascular disease risks, clinical predictors and molecular markers associated with nocturnal blood pressure dysregulation in children with proteinuric glomerulopathies. The central hypothesis is that nocturnal blood pressure dysregulation is independently associated with progression of cardiovascular target organ damage over time in children with proteinuric glomerulopathies. It is further hypothesized that clinical and molecular markers will be associated with the nocturnal blood pressure dysregulation phenotype. The specific aims of this proposal are: (Aim 1) To determine how nocturnal blood pressure dysregulation associates with target organ damage over time in children with proteinuric glomerulopathies; (Aim 2) To identify sleep- and circadian-related predictors of nocturnal blood pressure dysregulation in children with proteinuric glomerulopathies; (Aim 3) To investigate molecular pathways, networks and metabolic alterations associated with nocturnal blood pressure dysregulation in children with proteinuric glomerulopathies using multi-omic data integration . The proposed study will investigate nocturnal blood pressure dysregulation in a multi-center, longitudinal observational study of 120 children with proteinuric glomerulopathies enrolled from the Nephrotic Syndrome Study Network (NEPTUNE) and Cure Glomerulonephropathy Network (CureGN). Cardiovascular measures will be followed for three years to determine how the nocturnal BP dysregulation phenotype associates with progression of cardiovascular target organ damage. Predictive models will then be developed using machine learning methods to identify the clinical predictors of nocturnal blood pressure dysregulation, with a particular emphasis on sleep- and circadian-related predictors. Further, a precision medicine approach will be employed to define molecular markers of nocturnal blood pressure dysregulation using multi-omic data (genomics, transcriptomics, proteomics, metabolomics) integration. To this end, identifying the health risks, clinical predictors and molecular markers associated with nocturnal blood pressure dysregulation among children with proteinuric glomerulopathies using innovative bioinformatics approaches to analyze existing and novel data will fill a significant knowledge gap for a population of children at great cardiovascular risk. This study ...