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Pre-transplant Renal Ex vivo Imaging and Multi-omics for Advanced Graft Evaluation
Funder: European CommissionProject code: 851368 Call for proposal: ERC-2019-STG
Funded under: H2020 | ERC | ERC-STG Overall Budget: 1,499,960 EURFunder Contribution: 1,499,960 EUR
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There is a considerable shortage of deceased donor kidneys. Hence, more organs of marginal quality need to be considered for transplantation. Transplant centers are increasingly utilizing ex vivo normothermic machine perfusion to better preserve donor kidneys prior to transplantation. Little is known about molecular pathways that are active while the organ is perfused ex vivo. Also, there is hardly any data on which molecular processes are relevant to assess organ quality during perfusion. I aim to determine the molecular mechanisms of ex vivo kidney perfusion prior to renal transplantation in order to develop breakthrough pre-transplant perfusion-based diagnostic markers that can indicate kidney transplant outcomes. First, a series of normothermic ex vivo porcine kidney perfusions will be conducted with repeated tissue and perfusate sampling. Ex vivo measurements will be contrasted with the contralateral kidney that remains in vivo. Genomics, transcriptomics, proteomics and metabolomics, as well as ex and in vivo magnetic resonance imaging followed by radiomics will be employed. Distinct molecular pathways will be identified which characterize an ex vivo perfused kidney, compared to the organ’s behaviour in vivo. Second, the discovered molecular pathways will be validated for human donor kidneys by performing ex vivo perfusions of discarded human organs followed by the same multi-omics approach. Finally, a prospective clinical study will be conducted with human kidneys that are perfused ex vivo prior to transplantation. With artificial intelligence analysis, tissue and perfusate multi-omics measurements and standard clinical variables will be associated with transplant results, to create advanced prediction models for post-transplant outcome. The high gain of my project will be a better understanding of molecular mechanisms during ex vivo kidney perfusion and advanced, personalized pre-transplant prediction models for post-transplant outcome.

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