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Updated: Jan 8, 2026

Quantification of Circulating Pig-Specific DNA in the Blood of a Xenotransplantation Model
Published on: September 22, 2020
Periodic Trajectories of the Plasma Metabolome in a Pig-to-Non-Human Primate Cardiac Xenograft Model
Hao Cui1, Siyuan Huang1, Songren Shu1
1The Cardiomyopathy Research Group, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Introduction:
Cardiac xenotransplantation (CXTx) has the potential to increase the supply of donor organs; however, compared with clinical application research, studies on the mechanisms of injury following CXTx remain severely lacking. Plasma metabolite levels can accurately reflect the body's physiological state and serve as early predictors of potential adverse events. In this study, we established a heterotopic pig-to-non-human primate model and consecutively collected plasma samples for metabolomic analysis.
Methods:
Based on the type of donor porcine heart and postoperative management strategy, the experiment was divided into three groups: Group I, wild-type (WT) donor heart; Group II, alpha-1,3-galactosyltransferase gene knockout (GTKO) donor heart without immunosuppression; and Group III, GTKO donor heart with immunosuppression.
Results:
A total of 1215 metabolites were identified in recipient plasma following CXTx. Survival time was divided into three stages by hierarchical clustering, and that partial least squares discriminant analysis (PLS-DA) was used to visualize and rank metabolites contributing to these differences. Trajectory analysis identified six clusters with distinct temporal fluctuations in plasma metabolite levels after CXTx. Several plasma metabolites were found to rise prior to increases in troponin I levels, suggesting their potential as early biomarkers for predicting cardiac xenograft failure.
Conclusion:
In summary, this novel approach to studying CXTx revealed previously unrecognized characteristics and offers a potential strategy for the early prediction of xenograft failure.

