BACKGROUND. Because injury is universal in organ transplantation, heart transplant endomyocardial biopsies present an opportunity to explore response to injury in heart parenchyma. Histology has limited ability to assess injury, potentially confusing it with rejection, whereas molecular changes have potential to distinguish injury from rejection. Building on previous studies of transcripts associated with T cell–mediated rejection (TCMR) and antibody-mediated rejection (ABMR), we explored transcripts reflecting injury. METHODS. Microarray data from 889 prospectively collected endomyocardial biopsies from 454 transplant recipients at 14 centers were subjected to unsupervised principal component analysis and archetypal analysis to detect variation not explained by rejection. The resulting principal component and archetype scores were then examined for their transcript, transcript set, and pathway associations and compared to the histology diagnoses and left ventricular function. RESULTS. Rejection was reflected by principal components PC1 and PC2, and by archetype scores S2TCMR, and S3ABMR, with S1normal indicating normalness. PC3 and a new archetype score, S4injury, identified unexplained variation correlating with expression of transcripts inducible in injury models, many expressed in macrophages and associated with inflammation in pathway analysis. S4injury scores were high in recent transplants, reflecting donation-implantation injury, and both S4injury and S2TCMR were associated with reduced left ventricular ejection fraction. CONCLUSION. Assessment of injury is necessary for accurate estimates of rejection and for understanding heart transplant phenotypes. Biopsies with molecular injury but no molecular rejection were often misdiagnosed rejection by histology. TRAIL REGISTRATION. ClinicalTrials.gov NCT02670408 FUNDING. Roche Organ Transplant Research Foundation, the University of Alberta Hospital Foundation, and Alberta Health Services.
Philip F. Halloran, Jeff Reeve, Arezu Z. Aliabadi, Martin Cadeiras, Marisa G. Crespo-Leiro, Mario Deng, Eugene C. Depasquale, Johannes Goekler, Xavier Jouven, Daniel H. Kim, Jon Kobashigawa, Alexandre Loupy, Peter Macdonald, Luciano Potena, Andreas Zuckermann, Michael D. Parkes
Running average of LVEF versus archetype scores.