A research team from the University of Pennsylvania has published groundbreaking results in Nature Genetics, developing an artificial intelligence-based tool for kidney disease analysis that advances the application of precision medicine in nephrology.

Led by nephrology expert Professor Katalin Susztak, the team created the SISKA 1.0 Atlas database, integrating over 1 million cells from 140 samples. Susztak stated: “We are shifting from empirical treatment to precision medicine, and AI has helped us identify 70 distinct kidney cell types.” The accompanying open-source tool CellSpectra enables analysis of individual patient samples and cross-species data interpretation.

The research overcomes limitations of traditional single-cell RNA sequencing by detecting gene programs rather than individual genes, improving the reliability of disease correlation analysis. Professor Nancy Zhang from the Wharton School noted: “These tools will be freely available to promote the development of personalized treatments.”

In a separate study published in Nature Medicine, the team established the first comprehensive kidney protein catalog, revealing differences between protein levels and gene activity. Susztak emphasized: “This discovery provides new directions for developing therapies targeting specific molecules.”