Extended Data Fig. 11: Image-level pseudotime analysis from cluster mapping using PILOT.

(a) Pseudotime analysis was performed based on our interpretable clusters, identifying a path from controls to diabetic kidney disease (DKD) that correlates with histopathological changes. This path can be separated into two trajectories. (b) Trajectory 1 defined a transition based on estimated glomerular filtration rate (eGFR), marking the range in renal function in our non-diabetic controls. Pseudotime was strongly associated with clusters representing loss of tubular integrity, extracellular matrix remodelling (ECM; fibrosis) and myofibroblast expansion (fibrosis). (c) Trajectory 2 was strongly associated with clusters representing podocyte injury, mitochondrial stress in proximal tubuli (PTs) and glucocorticoid receptor (GR) dysfunction. PILOT uses non-linear regression methods and leverages the Wald test to evaluate the difference in the fitted model for each cluster vs. the model fitted for background clusters.