Abstract: TH-PO0992
Early Biomarkers of AKI After Liver Transplantation Identified by Integrated Multi-Omic Analysis
Session Information
- Transplantation: Basic - Immune Biology, Tissue Injury, and Emerging Technologies
October 22, 2026 | Location: Exhibit Hall A, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Transplantation
- 2001 Transplantation: Basic
Authors
- Rani, Alka, University of South Florida Morsani College of Medicine, Tampa, Florida, United States
- Tran, Minh Hoang, University of South Florida Morsani College of Medicine, Tampa, Florida, United States
- Parris, Colby Lucien, University of South Florida Morsani College of Medicine, Tampa, Florida, United States
- Esquivel, Carlos R., University of South Florida Morsani College of Medicine, Tampa, Florida, United States
- Wang, Lei, University of South Florida Morsani College of Medicine, Tampa, Florida, United States
Background
The highest incidences of kidney injury and chronic renal failure occur after liver transplantation. More than 50% of patients get affected by chronic kidney diseases within 5 years of liver transplantation, adding to the burden of kidney transplantation, for which more than 80,000 people are already waiting for a donor. Early identification and management of kidney injury after liver transplantation can increase the success rate and long-term survival of the patients. Therefore, we planned a detailed multi-omics study to understand the mechanisms behind the liver-kidney crosstalk and identify the early markers of kidney injury following liver transplantation.
Methods
To study this we used two animal models. We performed orthotopic liver transplantation (OLT) using inbred male C57BL/6 mice and liver ischemia (LI) in female pigs for 45 mins. Blood, urine, kidney and liver samples were collected. Liver chemistry and kidney injury markers were measured in the blood plasma and urine samples. Unsupervised multi-omics factor analysis (MOFA) integrating RNA-seq, proteomics, lipidomics and metabolomics data identified four latent factors.
Results
Factor 1 explained the majority of shared variance and showed clear separation between liver and kidney tissue. Factor 2 had a significant correlation with the groups. Factor 2 identifies multi-omics features for kidney specific acute phase response like P450 and mitochondrial enzymes that did not show in the grafted liver. Spatial transcriptomics further validated the results and localization of the markers in the kidneys. Liver ischemia pig model also shows similar pathways using RNAseq and proteomics integrated analysis using MOFA.
Conclusion
Multi-omics analysis revealed coordinated changes in liver and kidney. The results were promising and provided a foundation for understanding the acute phase response of kidney after liver transplantation. These features have potential to reveal the liver kidney crosstalk mechanisms after liver transplantation. This has implications for finding underlying mechanisms and planning therapeutic targets in clinical studies.