These authors have contributed equally to this work and share first authorship
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Graft survival after kidney transplantation is limited mainly for two reasons: first, chronic renal allograft dysfunction due to antibody-mediated rejection caused by development of
The soluble urokinase plasminogen activator receptor (suPAR) is the soluble form of uPAR, the membrane-bound receptor for uPA (urokinase). suPAR is a risk factor for kidney disease, both acute and chronic and a biomarker for innate activation of the immune system (
To date, no major study with long-term follow-up has investigated the value of suPAR for the prediction of cardiovascular events and cardiovascular mortality in recipients of kidney transplants. We studied the association between suPAR measured before or at year 1 after transplantation and outcomes in a total of 1,023 kidney transplant recipients.
SuPAR was measured pre-kidney transplant in cohort 1 consisting of 474 patients transplanted between 1988 and 2010 with the primary diagnosis of “focal sclerosis” or “chronic glomerulonephritis” from 37 participating centers that provided a pre-transplant serum from patients reported to the Collaborative Transplant Study (CTS,
The work of the CTS is approved by the Ethics Committee of the Medical Faculty of Heidelberg University (No. 083/2005) and performed in accordance with the World Medical Association Declaration of Helsinki Ethical Principles in the currently valid version.
Serum suPAR was measured in a blinded fashion using either the uPAR Quantikine® ELISA kit (R&D, Minneapolis, MN, United States; cohort 1) or the suPARnostic kit (ViroGates, Birkerød, Denmark; cohort 2) according to the manufacturer’s instructions. The lower detection limit is less than 33 and 100 pg/ml, the intra-assay variation less than 5 and 2.75%, and the inter-assay variation less than 5 and 9.17% for the uPAR Quantikine® ELISA and suPARnostic kit, respectively.
The information on date and cause of patient’s death was derived from CTS basic follow up forms that are filled out by participating centers at post-transplant months 3, 6, 12 and yearly thereafter.
Time to death was calculated from the serum collection date (cohort 1: serum collection date = transplant date, cohort 2: serum collection date = 1 year after transplantation). Multivariable Cox regression analysis was performed to account for the possible influence of the following confounders separately according to cohort: cohort number, transplant year, transplant number, recipient and donor age, recipient and donor sex, donor relationship, pre-transplant human leukocyte antigen (HLA) antibodies, cold ischemia time (deceased donor), time on dialysis, HLA A + B + DR mismatches, and existence of comorbidities (pretransplant cancer, diabetes mellitus, other reasons of moderate or poor evaluation of the patient as candidate for transplantation). Analysis in cohort 2 included the following additional variables which were not available in cohort 1: rejection treatment during first post-transplant year, 1-year serum creatinine, immunosuppressive therapy at year 1, and presence of an increased cardiovascular risk at year 1 (diabetes mellitus, hypertension, smoking, hypercholesterolemia, obesity). Survival rates were illustrated using the Kaplan-Meier method. The software package IBM SPSS Statistics (SPSS Inc., Chicago, IL, United States) was used.
SuPAR levels were measured in a total of 1,023 kidney transplant recipients either before (cohort 1,
Demographics of study patients,
Characteristic | Unknown (%) | Cohort 1 |
Cohort 2 |
|
---|---|---|---|---|
Geographical region | – | – | ||
Europe | 242 (51%) | 549 (100%) | ||
North America | 168 (35%) | – | ||
Other | 64 (14%) | – | ||
Transplant year | – | – | ||
Range | 1988–2010 | 2006–2015 | ||
Median | 2003 | 2011 | ||
Transplant number | – | 0.12 | ||
First transplant | 402 (85%) | 484 (88%) | ||
Retransplant | 72 (15%) | 65 (12%) | ||
Donor relationship | – | <0.001 | ||
Living | 120 (25%) | 217 (40%) | ||
Deceased | 354 (75%) | 332 (60%) | ||
Recipient sex | – | 0.001 | ||
Female | 155 (33%) | 233 (42%) | ||
Male | 319 (67%) | 316 (58%) | ||
Recipient age (years) | – | <0.001 | ||
<18 | 52 (11%) | – | ||
18–59 | 342 (72%) | 403 (73%) | ||
≥60 | 80 (17%) | 146 (27%) | ||
Mean ± SD | 41.8 ± 17.0 | 48.4 ± 14.1 | <0.001 | |
Donor age (years) | 0.3 | <0.001 | ||
<18 | 18 (8%) | 13 (2%) | ||
18–59 | 364 (77%) | 360 (66%) | ||
≥60 | 69 (15%) | 176 (32%) | ||
Mean ± SD | 42.2 ± 16.1 | 52.2 ± 14.8 | <0.001 | |
suPAR (ng/ml) | – | |||
Range | 1.0–26.4 | 1.1–18.1 | ||
Median (Tertiles) | 5.7 (4.9; 6.7) | 6.2 (5.2; 7.2) |
SD, standard deviation.
The risk of mortality was significantly higher in patients in the high than in the medium or low tertiles (“normal”) of suPAR levels (cohort 1: hazard ratio (HR) 1.92, 95% confidence interval (CI) 1.20–3.08,
Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) on 5-year mortality post-transplant in cohort 1
Results of the multivariable Cox regression analysis for influence of suPAR on mortality after serum collection date.
Subpopulation | N | HR | 95% CI |
|
---|---|---|---|---|
All study patients | 1,023 | 2.14 | 1.48–3.08 |
|
Death due to CVD | 4.24 | 1.81–9.96 |
|
|
Death due to infection | 2.20 | 0.90–5.39 | 0.083 | |
Death due to cancer | 1.61 | 0.53–4.91 | 0.40 | |
Cohort 1 | 474 | 1.92 | 1.20–3.08 |
|
Cohort 2 | 549 | 2.78 | 1.51–5.13 |
|
Good kidney function | 255 | 5.40 | 1.42–20.5 |
|
Female patients | 388 | 1.91 | 0.97–3.76 | 0.061 |
Male patients | 635 | 2.41 | 1.56–3.73 |
|
Young patients <50 years | 584 | 3.38 | 1.81–6.34 |
|
Elderly patients ≥50 years | 439 | 1.73 | 1.10–2.71 |
|
Hazard ratios (HR) with 95% confidence interval (CI) of patients with high suPAR values (≥upper tertile) are shown. Significant
Due to the rather comparable risk and a similar distribution of suPAR levels in cohorts 1 and 2 (
Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) above the upper tertile (“High”) against suPAR values below the upper tertile (“Normal”) on 5-year mortality after serum collection date. Log rank
Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) on death with a functioning graft in the following 5 years after serum collection date as stratified by cause of death. Log rank
Kaplan-Meier curves demonstrating the impact of suPAR (ng/ml) on 5-years mortality after serum collection date as stratified by recipient sex
In this study of 1,023 patients, serum suPAR level was a robust predictor of all-cause mortality after kidney transplantation. A high compared to normal suPAR level was associated with more than doubled risk of mortality during follow-up. This finding was consistent and independent of the time of transplantation (cohort 1: 1988–2010, cohort 2: 2006–2015), the primary kidney disease (cohort 1: glomerulonephritis, cohort 2: various), the time of serum sampling (cohort 1: before transplantation, cohort 2: 1 year after transplantation), or the suPAR assay used (cohort 1: uPAR Quantikine® ELISA kit, cohort 2: suPARnostic kit). The findings were confirmed independently in female versus male, or elderly versus young patients, and most importantly, the influence of suPAR on mortality was constant in patients with different levels of kidney function (cohort 1: marginal kidney function; cohort 2: different levels of kidney function; subgroup of cohort 2 with good kidney function at year 1 and a serum creatinine <130 μmol/L). The main cause of mortality was cardiovascular death with a striking HR of 4.24 in patients with high suPAR level.
SuPAR had been implicated as a biomarker for cardiovascular events and cardiovascular death in the general population as well as in patients with specific diseases, such as type 1 diabetes mellitus and coronary artery disease, or in patients undergoing coronary angiography (
Several points are particularly noteworthy in our study. First, regardless of the suPAR assay used, uPAR Quantikine® ELISA kit or suPARnostic kit, the serum suPAR levels in our study were with a median of 5.7 in cohort 1 and 6.2 ng/ml in cohort 2 higher than the median levels reported in other cardiovascular mortality studies with, i.e., a median suPAR level of 3.0 ng/ml in the study by Sommerer et al. (
Among the influential factors that were considered in the multivariable analysis, recipient age, suPAR level, and transplant year had the strongest impact on mortality. Pre-transplant cancer, diabetes mellitus, and other reasons of moderate or poor evaluation of the patient as candidate for transplantation (for cohorts 1 and 2), and presence of an increased cardiovascular risk at year 1 (for cohort 2 only) were also considered; however, none of them showed a significant influence. Limitations of the current study include the selection of different cohorts of patients with different underlying diseases (“focal sclerosis” or “chronic glomerulonephritis” in cohort 1 versus various kidney diseases in cohort 2), different timing of serum sample collection (pre-transplant in cohort 1 versus 1 year post-transplant in cohort 2), and the use of different assays for suPAR measurements (uPAR Quantikine® ELISA kit in cohort 1 versus suPARnostic kit in cohort 2). However, as suPAR levels were distributed similarly and not normally in both cohorts and the outcome was similar when cohorts 1 and 2 were analyzed separately, we felt that it was justified to combine both cohorts for further in depth analysis. Moreover, that suPAR levels predicted inferior outcome independent of the primary kidney disease, the time of serum sampling, or the assay, especially in the highest tertile of patients, can also be interpreted as a strength that underlines the robustness of our findings.
In conclusion, a high serum suPAR level was found to be a strong and robust predictor of all-cause and cardiovascular mortality in kidney transplant recipients that may allow for better risk stratification and early intervention in high-risk patients. Most importantly, prediction of risk by suPAR was independent of kidney function at baseline.
The soluble urokinase plasminogen activator receptor (suPAR) is a risk factor for cardiovascular disease and cardiovascular death in chronic kidney disease and non-chronic kidney disease populations. In hemodialysis patients, the risk of death was almost two times higher in patients with suPAR levels in the highest compared to the lowest tertile with a significantly increased risk of cardiovascular death. So far, no study examined the association of high suPAR levels with overall and cardiovascular mortality in kidney transplant recipients. In two independent cohorts with a total of 1,023 kidney transplant recipients a serum suPAR level in the highest compared to the two lower tertiles was a strong predictor of death, predominantly from cardiovascular cause. These findings were confirmed in different subcohorts. Most importantly, prediction of overall and cardiovascular death was independent of the baseline kidney function indicating that mortality may not be related to a decreased kidney function, but rather to an unrelated process such as chronic inflammation. SuPAR may help to identify kidney transplant recipients at a high risk of cardiovascular death and enable to provide them with the best follow-up and post-transplant care.
The raw data are available upon request to the Collaborative Transplant Study in accordance with the consents of the patients and the participating transplant centers and registries.
The studies involving human participants were reviewed and approved by Ethics committee of the University of Heidelberg. The patients/participants provided their written informed consent to participate in this study.
CM, BD, CSü created the figures. CM, SH, JR, CSü designed the study. CM, BD, CN, CSo, MZ collected the data, and all authors performed the literature search, data analysis, data interpretation, and writing.
CM and MZ, together with the University of Heidelberg, are co-founders of TolerogenixX GmbH, Heidelberg, Germany, a biotechnology company that holds licenses for cell therapies. CM, CSü, and MZ filed a patent application for a cell therapy. JR is cofounder of Trisaq, a biotechnology company developing drugs targeting suPAR. SH and JR are members of the scientific advisory board of Trisaq. JR holds patents and licenses related to suPAR.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We wish to thank all staff members at the 37 participating laboratories and clinical units for supplying us with sera and clinical follow-up data: Baracaldo, Brussels, Budapest, Cagliari, Cape Town, Cardiff, Dallas, Freiburg, Geneva, Giessen, Glasgow, Goteborg, Halle, Heidelberg, Helsinki, Izmir, Karachi, Kentucky, Leuven, Liege, Mainz, Mannheim, Medellin, Mexico City, Phoenix, Portland, Quebec, Reims, Rijeka, Sao Paulo, Seoul, Stuttgart, Torino, Ulm, Valencia, Zagreb, Zürich.
The Supplementary Material for this article can be found online at:
CI, confidence interval; CTS, Collaborative Transplant Study; HR, hazard ratio; HLA, human leukocyte antigen; suPAR, soluble urokinase plasminogen activator receptor; uPA, urokinase.