From Single-Cell Clusters to Causality: ITCH Engagement for CKD Uncovered by Integrative Analysis of MR and MAGMA.

Chronic kidney disease (CKD) is a leading and rapidly rising contributor to global mortality, yet actionable molecular targets remain limited. Here, we integrated human kidney single-cell RNA sequencing (scRNA-seq) with genetic association and causal inference frameworks to prioritize putative CKD susceptibility genes. To mitigate cell-level pseudoreplication inherent to small-donor scRNA-seq datasets, we primarily implemented a donor-aware pseudobulk strategy to identify differentially expressed genes (DEGs) between CKD and control kidneys, and subsequently prioritized candidates by convergent evidence from Mendelian randomization (MR) and MAGMA gene-level association analyses using CKD-related GWAS summary statistics. Across these complementary layers, ITCH emerged as a high-confidence candidate, showing consistent support from transcriptomic dysregulation and genetic evidence. We further performed immunohistochemistry-based validation in an experimental kidney injury model, providing additional support for ITCH upregulation in diseased kidneys. Finally, to explore potential pharmacological modulation in a hypothesis-generating manner, we conducted DSigDB-based drug enrichment followed by molecular docking and 50-ns molecular dynamics simulations to evaluate structural compatibility and complex stability, nominating hesperetin as a higher-priority compound for subsequent experimental testing. Collectively, our multi-omics integration supports ITCH as a plausible gene involved in CKD pathobiology and provides a rationale for the hypothesis that targeting ITCH could alter disease progression, which warrants future experimental investigation.