Functional Implications of Biochemical and Molecular Characteristics of Donation After Circulatory Death Livers

Background In aggregate, livers donated after circulatory death (DCD) provide lower rates of graft and patient survival compared to brain dead donors (DBD). A method to identify DCD livers likely to perform well would lead to better decision-making regarding which livers to use and which to discard and is an important unmet clinical need. We hypothesized that the ischemic time between extubation and cold perfusion in the donor leads to immediate and unique biochemical and molecular changes that could be used to predict subsequent function. Methods Biopsies from normal perfused liver, immediately after cold perfusion during DCD or DBD liver procurement, and during subsequent cold storage were analyzed and compared. Biochemical analysis included adenosine triphosphate (ATP), adenosine diphosphate, adenosine monophosphate, hypoxanthine, xanthine, inosine, nicotinamide adenine dinucleotide, and flavin adenine dinucleotide. Levels of these metabolites were compared to peak posttransplant aspartate aminotransferase as a marker of ischemic injury. Molecular analysis was performed by transcriptional profiling using high throughput sequencing. Results Immediately after cold perfusion in the donor, biochemical analysis revealed lower levels of ATP and adenosine diphosphate in DCD versus DBD liver samples (P < 0.01 in both cases). The ATP levels showed high negative correlation with peak aspartate aminotransferase levels in recipients (P = 0.029). Four hundred seventy genes showed differential expression in DCD but not DBD samples immediately after cold perfusion compared with normal liver samples. Upregulated genes function in inflammation and immunity, whereas downregulated genes function in translation. During cold storage, samples were transcriptionally inactive with no consistent changes in messenger RNA expression. Conclusion The ATP content of liver samples taken immediately postperfusion correlates with ischemic injury. Transcriptional profiling identifies biological process that may be relevant for enhancing function in DCD liver transplantation. Transcriptional inactivity of cold stored samples suggests messenger RNA levels over time are unlikely to provide prognostic data.

[1]  M. Perera,et al.  Comparison of energy metabolism in liver grafts from donors after circulatory death and donors after brain death during cold storage and reperfusion , 2014, The British journal of surgery.

[2]  M. Schnitzler,et al.  National assessment of early biliary complications following liver transplantation: Incidence and outcomes , 2014, Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society.

[3]  A. Israni,et al.  OPTN/SRTR 2012 Annual Data Report: Liver , 2014, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

[4]  Chen-Ching Lin,et al.  Dynamic protein interaction modules in human hepatocellular carcinoma progression , 2013, BMC Systems Biology.

[5]  G. Kazemier,et al.  MicroRNA profiles in graft preservation solution are predictive of ischemic-type biliary lesions after liver transplantation. , 2013, Journal of hepatology.

[6]  Cole Trapnell,et al.  TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions , 2013, Genome Biology.

[7]  Davis J. McCarthy,et al.  Count-based differential expression analysis of RNA sequencing data using R and Bioconductor , 2013, Nature Protocols.

[8]  A. Barritt,et al.  Declining liver utilization for transplantation in the United States and the impact of donation after cardiac death , 2013, Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society.

[9]  M. Yarmush,et al.  Excorporeal normothermic machine perfusion resuscitates pig DCD livers with extended warm ischemia. , 2012, The Journal of surgical research.

[10]  Davis J. McCarthy,et al.  Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation , 2012, Nucleic acids research.

[11]  R. Karchin,et al.  Integrating diverse genomic data using gene sets , 2011, Genome Biology.

[12]  Scott R. Johnson,et al.  Minimising cold ischaemic time is essential in cardiac death donor-associated liver transplantation. , 2011, HPB : the official journal of the International Hepato Pancreato Biliary Association.

[13]  O. Ciccarelli,et al.  Liver transplantation from donation after cardiac death donors: initial Belgian experience 2003–2007 , 2009, Transplant international : official journal of the European Society for Organ Transplantation.

[14]  Davis J. McCarthy,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[15]  C. Hughes,et al.  Liver transplantation using controlled donation after cardiac death donors: An analysis of a large single‐center experience , 2009, Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society.

[16]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[17]  Scott R. Johnson,et al.  Donor Postextubation Hypotension and Age Correlate With Outcome After Donation After Cardiac Death Transplantation , 2008, Transplantation.

[18]  J. Reyes,et al.  Ischemic cholangiopathy following liver transplantation from donation after cardiac death donors , 2008, Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society.

[19]  S. Miyagi,et al.  The Significance of Preserving the Energy Status and Microcirculation in Liver Grafts from Non-Heart-Beating Donor , 2008, Cell transplantation.

[20]  A. Catania,et al.  Alteration in the Transcriptional Profile of Livers from Brain-dead Organ Donors , 2006, Transplantation.

[21]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[22]  M. Simonson,et al.  Cold ischemia induces endothelin gene upregulation in the preserved kidney. , 1999, The Journal of surgical research.

[23]  J. McAnulty,et al.  Comparison of the effects of adenine-ribose with adenosine for maintenance of ATP concentrations in 5-day hypothermically perfused dog kidneys. , 1988, Cryobiology.

[24]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[25]  Robert Gentleman,et al.  Using GOstats to test gene lists for GO term association , 2007, Bioinform..

[26]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .