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Emerging biomarkers of delayed graft function in kidney transplantation

期刊

TRANSPLANTATION REVIEWS
卷 35, 期 4, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.trre.2021.100629

关键词

Biomarkers; DGF; Kidney; Transplantation; Omics

资金

  1. PhD program in Tissue and Organ trans-plantation and cellular therapies, University of Bari, Italy
  2. Italian Ministry of Health grant Ricerca Finalizzata-Young Researcher [GR-2016-02362239]
  3. European Union - European Social Fund, PON R&I 2014-2020, Azione I.2 Attrazione e Mobilita Internazionale dei Ricercatori [AIM 1810057]

向作者/读者索取更多资源

Delayed Graft Function (DGF) is a common early complication in kidney transplantation, associated with poor graft outcomes, prolonged post-operative hospitalization, and higher rejection rates. The use of nonstandard kidneys from ECD and DCD donors is expected to increase the incidence of DGF, highlighting the importance of using omics technologies to discover new biomarkers.
Delayed Graft Function (DGF) is one of the most common early complications in kidney transplantation, asso-ciated with poor graft outcomes, prolonged post-operative hospitalization and higher rejection rates. Given the severe shortage of high-quality organs for transplantation, DGF incidence is expected to raise in the next years because of the use of nonstandard kidneys from Extended Criteria Donors (ECD) and from Donors after Circu-latory Death (DCD). Alongside conventional methods for the evaluation of renal allograft [e.g. serum creatinine Glomerular Filtration Rate (GFR), needle biopsy], recent advancements in omics technologies, including pro-teomics, metabolomics and transcriptomics, may allow to discover novel biomarkers associated with DGF occurrence, in order to identify early preclinical signs of renal dysfunction and to improve the quality of graft management. Here, we gather contributions from basic scientists and clinical researchers to describe new omics studies in renal transplantation, reporting the emerging biomarkers of DGF that may implement and improve conventional approaches.

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