Abstract
PURPOSE: Renal ischemia-reperfusion injury (IRI) is a major posttransplant complication that promotes maladaptive repair and fibrosis, leading to allograft failure. However, the role of lactylation in these processes remains unclear. This study aimed to identify lactylation-associated biomarkers and their therapeutic potential in the IRI-induced maladaptive repair of kidney allografts and subsequent fibrosis. METHODS: A gene set encompassing genes involved in the enzymatic regulation of lactylation was summarized, which includes key substrate proteins, lactylation "writers" and "erasers". Single-cell RNA-seq data were used to identify overall and cell-specific lactylation activity after IRI and in fibrotic samples. hdWGCNA analysis was used to identify hub genes, followed by predictive model construction using machine-learning algorithms. The relationships between hub genes and renal function, immune cell infiltration, and fibrotic biomarkers were also analyzed. Pseudotime trajectory analysis was used to investigate hub genes expression changes along fibrosis progression. Finally, RT-qPCR of hub genes and immunohistochemical staining were performed in a mouse model of unilateral IRI-fibrosis fibrosis. RESULTS: Lactylation activity was elevated after IRI and in fibrotic samples, particularly in a subset of T cells, highlighting its importance in fibrogenesis. Four hub genes (HLA-E, IGHM, CORO1A, and TUBA1A) emerged as fibrosis biomarkers and showed robust predictive value for patient and graft survival (area under the curve of 0.83, 0.86, and 0.87 at 1, 2, and 3 years, respectively). Drug sensitivity and molecular docking analyses revealed the potential for repurposing existing drugs to target these genes. Lastly, experimental validation confirmed the increased mRNA expression of the hub genes. CONCLUSION: This multi-omics study identified a key lactylation-associated hub T cell potentially implicated in post-IRI induced maladaptive repair. Four lactylation-related T-cell biomarkers (CORO1A, HLA-E, IGHM, and TUBA1A) predicted allograft maladaptive repair and survival, providing a precise framework for early risk stratification and potential therapeutic intervention.