Podocyte injury is an early and critical event in the onset of chronic kidney disease (CKD), yet the molecular mechanisms underlying distinct injury etiologies remain poorly defined. Here, we present a human induced pluripotent stem cell (iPSC)-derived podocyte platform to model early, sublethal injury across multiple disease-relevant conditions. By integrating transcriptomic profiling with comparative computational analysis, we systematically characterized both shared and injury-specific molecular responses.

Differentiated podocytes were exposed to distinct stressors representing diverse pathogenic mechanisms, followed by bulk RNA sequencing and downstream pathway analysis. Our results reveal a core transcriptional injury program conserved across conditions, enriched for pathways related to cytoskeletal remodeling, metabolic dysregulation, and stress response signaling. In parallel, each injury modality exhibited unique gene expression signatures, reflecting mechanistic heterogeneity at early stages of disease progression.

Importantly, cross-condition integration identified a subset of consistently dysregulated genes and pathways that may serve as candidate biomarkers for early podocyte injury. These shared molecular features provide a foundation for developing diagnostic strategies that are independent of disease etiology. Ongoing validation using advanced platforms, including organ-on-chip systems, aims to further assess the translational potential of these candidates.

Together, this study establishes a scalable stem cell-based framework for modeling podocyte injury and highlights the power of integrative transcriptomics to uncover convergent and divergent disease mechanisms. These findings have implications for early detection and therapeutic targeting in CKD.

Co-authors: Bowen Jiang, Morgan Burt, Nikolaos Dimitrakakis, Samira Musah