Histopathological-based analysis of human kidney spatial transcriptomics data: toward precision pathology

In this study, we conducted a histopathological-based analysis of 10x Genomics Visium spatial transcriptomics data on a human kidney sample corresponding as closely as possible to the reality of the interpretation of a kidney biopsy in a healthcare or research context. Overall design: A kidney specimen from a 33-year-old deidentified patient with chronic kidney disease (CKD) as a consequence of diabetic and hypertensive nephropathy was used for analysis. Utilizing the H&E- and PAS-stained bright-field mosaics as references, a kidney pathologist (PI) conducted morphological-based clustering for each spatially-resolved spot on the Visium slide. This involved manually outlining each kidney morphological structure and/or lesion for the purpose of cluster identification. A GitHub repository containing the R, Julia, and Python scripts we wrote for the main and supplemental figures can be found at: