Membranous nephropathy (MN) and focal-segmental glomerulosclerosis (FSGS) are the most common causes of nephrotic syndrome in adults. Both familial and complex genetic forms are known, but the risk allele spectrum, genetic overlap and generalizability of risk genes to other CKD etiologies remain open questions. This project aims to address important knowledge gaps in a large, prospective study of 5217 patients with chronic kidney disease (CKD), the GCKD Study. We will first conduct genome-wide association studies at unprecedented coverage, using >10 million common genome-wide SNP markers per person, to map risk genes and refine risk variant associations for MN, FSGS and all-cause CKD. Additionally, we will carry out the first exome-wide examination of approximately 250,000 missense, splice and stop mutations discovered through whole exome sequencing to identify potentially causal mutations for MN, FSGS and all-cause CKD. After external validation, risk variants will be examined for their combined effect and for interactions with each other and environmental exposures, capitalizing on the detailed information about medication intake and the in-depth clinical and biochemical profiles available in GCKD. Genome-wide searches for effect modifiers will also be carried out. Specificity of identified risk variants for MN or FSGS versus their importance for all-cause CKD will be assessed by examination of effects across the many CKD etiologies represented in GCKD. Lastly, the risk variants will be evaluated for their association with CKD progression (kidney function decline, incident ESRD) and complications (cardiovascular events, mortality) using methods for prospective data analysis, complemented by genome-wide searches. The prospective nature of the GCKD Study allows for the evaluation of the identified risk variants as diagnostic and prognostic markers. In addition to a better understanding of the genetic architecture of MN, FSGS and all-cause CKD, this work can generate novel insights about the physiology of glomerular kidney diseases. The generation of genome-wide association statistics from thousands of CKD patients will provide a valuable resource for the targeted investigation of human genes studied in other KIDGEM projects.