MOESM9 of Hypercholesterolemia-induced increase in plasma oxidized LDL abrogated pro angiogenic response in kidney grafts

Additional file 9: Figure S7. Hypercholesterolemia is associated with an upregulation of plasmatic TSP-1. Patients were classified in two groups in relation to their plasma cholesterol levels the day before renal transplantation and TSP-1 levels were measured (n=6–7). Values significantly different from the normocholesterolemic group are represented by * p < 0.05

The Alarmin Concept Applied to Human Renal Transplantation: Evidence for a Differential Implication of HMGB1 and IL-33

<div><p>The endogenous molecules high mobility group box 1 (HMGB1) and interleukin-33 (IL-33) have been identified as alarmins, capable of mediating danger signals during tissue damage. Here, we address their possible role as innate-immune mediators in ischemia-reperfusion injury (IRI) following human kidney transplantation. We analysed serum and urinary HMGB1 and IL-33 levels, all determined by enzyme-linked immunosorbent assay, in a cohort of 26 deceased renal transplant recipients. Urinary HMGB1 and IL-33 levels were significantly increased as soon as 30 min after reperfusion, as compared to those before treatment. Moreover, both serum and urinary IL-33 (but not HMGB1) increase was positively correlated with cold ischemia time, from 30 min to 3 days post-transplantation. <i>In vitro</i>, human umbilical vein endothelial cells subjected to hypoxia conditions released both HMGB-1 and IL-33, while only the latter was further increased upon subsequent re-oxygenation. Finally, we postulate that leukocytes from renal recipient patients are targeted by both HMGB1 and IL-33, as suggested by increased transcription of their respective receptors (TLR2/4 and ST2L) shortly after transplantation. Consistent with this view, we found that iNKT cells, an innate-like T cell subset involved in IRI and targeted by IL-33 but not by HMGB1 was activated 1 hour post-transplantation. Altogether, these results are in keeping with a potential role of IL-33 as an innate-immune mediator during kidney IRI in humans.</p></div

Partial plots for the continuous variables retained in the random survival forest analysis as predictors of graft failure.

<p>The vertical axis represents the predicted survival at 10 years for a given predictor, after adjusting for all other predictors. Points indicate partial values and dashed lines are ±2 standard error bars.</p

Out-of-bag data variable importance values obtained by random survival forest analysis.

<p>(A) full model and (B) final model. The log-rank splitting rule was used.</p

Kidney transplant characteristics of the development and validation databases.

<p>Kidney transplant characteristics of the development and validation databases.</p

Goodness-of-fit test for external validation of the AdGFS score.

<p>Goodness-of-fit test for external validation of the AdGFS score.</p

Serum creatinine clusters.

<p>(A) Mean trajectories of serum creatinine resulting from k-means for the longitudinal data clustering method superposed with individual profiles over the first 12 months post-transplantation. (B) Kaplan-Meier estimates (±95% confidence intervals) of graft survival according to the first-year creatinine profile cluster. The free graft failure survival was significantly associated with clusters (log-rank test, p<0.0001).</p

Conditional inference tree applied for graft survival with predicted Kaplan-Meier curves in the terminal nodes.

<p>The tree was obtained using recursive partitioning for censored response in a conditional inference framework implemented in ‘party’ R-package.</p

Performance characteristics of adjustable graft failure score (AdGFS) for cutpoints 0, 2, 4, 6, 8, 10 and for different times over 10 years post-transplantation.

<p>Performance characteristics of adjustable graft failure score (AdGFS) for cutpoints 0, 2, 4, 6, 8, 10 and for different times over 10 years post-transplantation.</p

Comparison of Kaplan-Meier graft survival curves for the four risk groups namely low-, intermediate-, high-, and very high- risk of graft loss in the development dataset (solid lines) and in the external validation dataset (dashed lines).

<p>Patients were partitioned according to the calculated score value: low risk (0), intermediate risk (2 or 4), high risk (6 or 8), and very high risk (10 or 12). Graft survival in the development and validation datasets did not differ within each of the four risk groups.</p