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Research Highlights

Issa, Fadi, PhD1

doi: 10.1097/TP.0000000000002456
In View: Research Highlights

1 Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.

Received 10 September 2018. Revision received 11 September 2018.

Accepted 12 September 2018.

The author declares no conflicts of interest.

Correspondence: Fadi Issa, MRCS, DPhil, Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom. (

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Molecular Pathways Underlying Adaptive Repair of the Injured Kidney: Novel Donation After Cardiac Death and Acute Kidney Injury Platforms

Orlando G, Danger R, Okut H, et al. Ann Surg. Published online July 24, 2018. DOI:10.1097/SLA.0000000000002946.

The donor organ shortage remains one of the most pressing issues in transplantation. There is an urgent need to expand the donor pool and explore methods for organ repair or preservation, allowing the use of high risk or “marginal organs.” In a proportion of transplanted kidneys, a form of transient acute injury manifests as delayed graft function (DGF) with most allografts undergoing intrinsic adaptive repair and recovery. Thus, there is a unique opportunity to explore the mechanisms that underlie this process aiming to identify targets that may be exploited for therapeutic purposes.

Overall, patients who receive a kidney from a living donor (LD) display a reduced propensity to DGF in comparison to those receiving a kidney after cardiac death (DCD) or a kidney that underwent acute kidney injury (AKI) either before or during procurement. There is currently a wealth of techniques available to analyze molecular pathways in transplantation, providing exceptionally detailed datasets for exploratory research.1 Here, Orlando and coinvestigators examined the peripheral blood of patients in the first 30 days after kidney transplantation to detect molecular changes that may be associated with transient kidney injury.2 Peripheral blood RNA from 15 patients was analyzed by microarray pretransplantation and at 11 further time points posttransplantation. Among these 15 patients, 2 experienced DGF. There were no episodes of acute rejection. In the longitudinal analysis, several gene transcripts were found to be differentially expressed between patients receiving LD grafts versus those receiving DCD or AKI grafts. Examining each group separately (LD, DCD, or AKI) revealed specific patterns. Differences between groups were always greatest in the first few days after transplantation, returning to baseline over time. This return to baseline was more rapid in the LD than the DCD/AKI group. Additionally, several genes that may be related to repair and regeneration were differentially expressed between these 2 groups. While the data require further extensive interrogation to identify pathways that are nonredundant and targetable, the technique used and the large data set generated are of enormous value to the community. The ability to use peripheral blood rather than kidney biopsies to examine broad transcriptomic changes posttransplantation is an advantage.

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  1. Menon MC, Keung KL, Murphy B, et al. The use of genomics and pathway analysis in our understanding and prediction of clinical renal transplant injury. Transplantation. 2016;100:1405–1414.
  2. Orlando G, Danger R, Okut H, et al. Molecular pathways underlying adaptive repair of the injured kidney: novel donation after cardiac death and acute kidney injury platforms. Ann Surg. 2018; Published online July 24, 2018. DOI:10.1097/SLA.0000000000002946.
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Pancreatic Islets Communicate With Lymphoid Tissues via Exocytosis of Insulin Peptides

Wan X, Zinselmeyer BH, Zakharov PN, et al. Nature. 2018;560:107-111.

Autoimmunity requires adaptive immune responses that recognize specific autoantigens by T cells. However, it is neither clear why tolerance to these antigen breaks nor why specific autoantigens are ‘triggering’ immune responses. In type 1 diabetes (T1D), the loss of pancreatic β cells is due to a destructive immune response against islet cell autoantigens mediated by both T cells and autoantibodies.1 A genetic risk therefore exists for certain HLA alleles encoding molecules that present islet autoantigens. Before clinical disease onset, autoantibodies can be detected in high-risk individuals heralding islet damage and indicating autoantigen recognition, a process that is distinct from injury. However, it is not clear why autoimmune responses directed against pancreatic islets are so frequent, and how T cells gain access to specific autoantigens. Wan and coinvestigators2 dissected some of those mechanisms in nonobese (NOD) mice. In NOD mice, there is a spontaneous presentation of insulin that sets in motion the development of pathology. A 12-20 segment of the insulin β-chain is recognized by autoreactive T cells, with this epitope generated from insulin peptides directly presented by antigen-presenting cells (APCs). Different segments are not recognized by these T cells, even if there is only a single residue shift. Here, the authors show that the 12-20 segment is transmitted via secreted exosomes and then presented by APCs to autoreactive CD4+ T cells. Notably, this process is not operative through the standard APC processing machinery. This bypassing “normal” processing pathways means that the epitope is not selected during lymphocyte development in the thymus, leading to the survival of autoreactive CD4+ T cells that recognize the 12 to 20 insulin β-chain segment. These catabolized insulin peptide fragments are also released in humans.

This landmark study highlights a previously undiscovered mechanism for autoimmune T-cell activation and provides important insight into the pathways underlying the development of T1D. The development of immune modulatory therapies that target T1D may benefit from taking those findings into consideration.

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  1. Pugliese A. Autoreactive Tcells in type 1 diabetes. J Clin Invest. 2017;127:2881–2891.
  2. Wan X, Zinselmeyer BH, Zakharov PN, et al. Pancreatic islets communicate with lymphoid tissues via exocytosis of insulin peptides. Nature. 2018;560:107–111.
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