Miriam Cortes1, Eugenia Pareja1, Juan C García-Cañaveras2, M Teresa Donato2, Sandra Montero3, Jose Mir1, José V Castell2, Agustín Lahoz4. 1. Unidad de Hepatología Experimental, Instituto de Investigación Sanitaria - Fundación Hospital La Fe, Valencia, Spain. 2. Unidad de Hepatología Experimental, Instituto de Investigación Sanitaria - Fundación Hospital La Fe, Valencia, Spain; Departamento de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad de Valencia, CIBERehd, Centro de Investigaciones Biomédicas en Red de Enfermedades Hepáticas y Digestivas, FIS, Spain. 3. Unidad Analítica, Instituto de Investigación Sanitaria - Fundación Hospital La Fe, Valencia, Spain. 4. Unidad de Hepatología Experimental, Instituto de Investigación Sanitaria - Fundación Hospital La Fe, Valencia, Spain. Electronic address: agustin.lahoz@uv.es.
Abstract
BACKGROUND & AIMS: Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD. METHODS: A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients. RESULTS: A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4). CONCLUSIONS: A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant.
BACKGROUND & AIMS: Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD. METHODS: A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients. RESULTS: A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4). CONCLUSIONS: A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant.
Authors: Bote G Bruinsma; James H Avruch; Gautham V Sridharan; Pepijn D Weeder; Marie Louise Jacobs; Kerry Crisalli; Beth Amundsen; Robert J Porte; James F Markmann; Korkut Uygun; Heidi Yeh Journal: Transplantation Date: 2017-07 Impact factor: 4.939
Authors: Olga Hrydziuszko; M Thamara P R Perera; Richard Laing; Jennifer Kirwan; Michael A Silva; Douglas A Richards; Nick Murphy; Darius F Mirza; Mark R Viant Journal: PLoS One Date: 2016-11-11 Impact factor: 3.240
Authors: Bote G Bruinsma; Gautham V Sridharan; Pepijn D Weeder; James H Avruch; Nima Saeidi; Sinan Özer; Sharon Geerts; Robert J Porte; Michal Heger; Thomas M van Gulik; Paulo N Martins; James F Markmann; Heidi Yeh; Korkut Uygun Journal: Sci Rep Date: 2016-03-03 Impact factor: 4.379