Kidney disease develops when specialised kidney cells stop working correctly. In rare genetic conditions, this can be due to inherited changes in DNA; in others, it happens because cells fail to cope with stress or damage.

Studying kidney cells usually requires an invasive biopsy, which is hard to repeat and unsuitable for many patients with rare kidney diseases, such as children.

At Newcastle University, Professor John Sayer’s team has developed a non-invasive alternative. They collect kidney cells from urine and grow them in the laboratory. They use these cells to study disease mechanisms and to test possible new treatments.

So far, measures of changes in the overall function of genes in these cells have relied on assessing the overall activity of all cells at once. While useful, this approach is limited because urine contains a mixture of cell types, and it is difficult to know whether differences between patients reflect actual disease changes or just differences in cell composition.

Newer approaches can study gene activity in individual cells, but these are expensive and technically demanding. A more practical solution is to use computer models that can “unmix” the gene activity signals from different cell types. To work well, these models need a reference with the gene activity patterns of different individual tissue cell types. Such a map does not yet exist for urine cells.

This project will create the first reference atlas of gene activity in cell types present in urine, combining existing datasets with new data from patients with rare kidney diseases. By sharing this as a community resource, we will improve the use of urine cells as a non-invasive model. This will make it possible to understand better how kidney disease develops, identify new biomarkers, and accelerate the search for new therapies.