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Metabolomic approach to identify causes of post liver transplant graft injury

Elisa Pasini, Cristina Baciu, Amir Amirhossein, Mamatha Bhat

Background: Graft viability after liver transplantation (LT) is dependent on prompt recognition of graft injury. There is a need for biomarkers that can differentiate between etiologies of injury early. We present preliminary findings of a metabolomic study characterizing molecular signatures arising in post-LT graft injury. Current analysis is limited to post-LT biliary injury, but our long-term goal is to identify signatures associated with multiple disease states that can be combined into a single assay.

Methods: From the UHN Transplant Biobank, we obtained 22 biopsy-matched serum samples for the control group, 27 with post-LT biliary injury, 25 with post-LT NAFLD/NASH, and 67 with rejection. A metabolomics direct injection mass spectrometry with reverse-phase LC-MS/MS assay was used to identify and quantify up to 143 different endogenous metabolites. Statistical and machine learning analyses were employed using MetaboAnalyst 5.0.

Results: After filtering and normalization, volcano plot analysis using Log2 fold-change threshold of 1.2 and t-test threshold of 0.05 identified 25 metabolites of interest. Partial least squares discriminant analysis was able to differentiate between controls and biliary injury with accuracy of 0.8, R2 0.9 and Q2 0.4. Metabolites increased in biliary injury included glutamic acid, C18:1, PC ae C36:0, C12:1, C16:1, C2, SM C20:2, and PC aa C40:2. Glutamic acid was most important with VIP score of 3.0. A sparse PLS-DA was also employed and demonstrated similar performance and feature ranking. Hierarchical clustering and heatmap utilizing features of interest demonstrated distinct separation between control and biliary injury samples.

Conclusion: These preliminary findings identify a metabolomic signature associated with post-LT biliary injury. Further analysis of collected samples may lead to unique signatures for other causes of graft injury (NASH, rejection). These could then be combined with the biliary signature to create a single assay capable of distinguishing between different etiologies at time of initial lab draw.