The imputation-powered findings derive support from clinical record-based kidney disease information, such as for a previously unreported splice allele in PKD2, and from functional studies of a previously unreported frameshift allele in CLDN10. This cost-efficient approach boosts statistical power to detect and characterize both known and novel disease susceptibility variants and genes, can be generalized to larger future studies, and generates a comprehensive resource (https://ckdgen-ukbb.gm.eurac.edu/) to direct experimental and clinical studies of kidney disease. Here, CLDN10 is linked to kidney disorder.