Cardiovascular mortality is the major cause of death in end stage renal disease (ESRD) patients. Increased levels of IL6 and tumor necrosis factor-α (TNF-α) are markers of inflammation and are associated with cardiovascular disease in patients with normal kidney function.1
Studies have shown that plasma levels of IL6 and TNF-α are increased in patients with advanced kidney disease2 and ESRD3,4 and are associated with increased mortality from cardiovascular causes in this patient population,5 which may be further influenced by genetic background.6 A recent study has shown that IL6 and TNF-α are independently associated with all-cause mortality in patients with advanced chronic kidney disease,7 and in patients on maintenance hemodialysis.8 Previous data from a large prospective clinical trial (Assessment of LEscol in Renal Transplantation) showed that higher levels of IL6 and C-reactive protein (CRP) are independently associated with all-cause mortality9 and graft loss.10 Nevertheless, this study included selected incident patients and did not adjust for important donor related confounders or take into account competing risk phenomena.11
Accordingly, there is a lack of data examining the association between plasma levels of these inflammatory cytokines and mortality in prevalent kidney transplant recipients adjusting for important confounders such as donor related data. We hypothesized that increased levels of IL6 and TNF-α in prevalent renal transplant recipients are associated with increased all-cause and graft censored mortality as well as increased risk of graft loss. We conducted a single-center prospective cohort study at a transplant center in Hungary to test our hypothesis.
MATERIALS AND METHODS
Patient Population and Data Collection
All prevalent deceased-donor and living donor transplant recipients older than 18 years at the time of transplant (n = 1214) followed at the Semmelweis University, Department of Transplantation and Surgery (Budapest, Hungary) as of December 31, 2006, were invited to participate in the study. We have excluded recipients with recent kidney transplants (<3 months), biopsy-proven or clinically strongly suspected acute rejection episode within 4 weeks or those with current hospitalization, acute infection, or bleeding episodes.12-16 During the cohort's baseline assessment between February 2007 and August 2007, we collected detailed histories of sociodemographic, anthropometric and medical characteristics.12-16 Comorbid disease burden was calculated according to a modified Charlson Comorbidity Index.17 Renal function was estimated according to the Chronic Kidney Disease Epidemiology Collaboration estimated glomerular filtration rate (eGFR) formula.18 The study was approved by the Ethics Committee of the Semmelweis University (49/2006). Before enrolment, patients received detailed written and verbal information regarding the aims and protocol of the study and provided written consent to participate.
Laboratory Data
All laboratory data were collected and measured at the baseline clinic visit and included adipocytokines, abdominal circumference, TNF-α, IL-6, blood hemoglobin, serum CRP, serum creatinine, blood urea nitrogen, and serum albumin levels. Serum samples were also collected at the time of the baseline assessment and stored at −70°C for future use. Serum cytokine concentrations were measured using immunoassay kits based on solid-phase sandwich enzyme linked immunosorbent assay (R&D Systems, Minneapolis, MN; coefficient of variation <10%).
Transplantation-Related Data and Donor Characteristics
We performed a detailed review of the patients' medical records for transplant-related information, including medications and current immunosuppressive regimen, transplant vintage, length of renal replacement therapy before transplant, type of allograft, number of HLA mismatches, panel reactive antibodies titer, and any history of treated acute rejection(s) after transplantation; further, information about donor age, sex, and cold ischemia time at the time of transplantation.12-16 The immunosuppressive therapy at the time of the study's enrolment included prednisolone (5-10 mg/d), a calcineurin inhibitor with either tacrolimus or microemulsion formulation of cyclosporine-A (Neoral), with further addition of either mycophenolate mofetil, azathioprine, or sirolimus. In our center, antithymocyte globulin or interleukin-2 receptor antagonist were used for induction.
Statistical Analysis
Statistical analyses were carried out using STATA 13 (StataCorp, College Station, TX). Data were summarized using proportions, means (±SD) or medians (interquartile range) as appropriate. Categorical variables were compared with χ2 test and continuous variables were compared using Student t test or the Mann-Whitney U test, Kruskal-Wallis H test or ANOVA as appropriate. In all statistics, 2-sided tests were used, and the results were considered statistically significant if P value was less than 0.05.
The association between baseline serum TNF-α and IL6 levels and death with a functioning graft and all-cause death (without censoring for graft loss) was assessed using Cox proportional regression analysis and Kaplan-Meier plots with the log rank test. Analogous analyses were also conducted for death-censored graft loss as a secondary outcome. Proportional hazards assumptions were tested using scaled Schoenfeld residuals. The association of continuous variables was presented with fractional polynomials and is shown as cubic splines. The variables entered in the multivariable-adjusted model were selected based on theoretical considerations; we included predictors in the final model which were known to be associated both with inflammation and with obesity based on scientific evidence, and which were available in our database. We did not adjust for variables which showed strong collinearity. The final model was adjusted for age, donor age, eGFR, total ESRD time (including total time on renal replacement therapy and time after being transplanted), Charlson Comorbidity Index, albumin, abdominal circumference, cold ischemia time, panel reactive antibody level and HLA mismatch. Because death with functioning graft and graft loss are competing events, a competing risk model was also used as sensitivity analysis to analyze the risk of death with a functioning graft using the Fine and Gray method.19 Our event of interest was death with functioning graft, and the competing event was graft failure. Only 5% of the data were missing in our final model, therefore missing values were not imputed in primary analyses.
RESULTS
Demographics and Baseline Characteristics
Of the 1214 potential patients 17% refused to participate in the study and 1% were excluded based on various inclusion/exclusion criteria. Sixteen subjects had missing data of TNF-α or IL6, resulting in a final study sample of 977 participants (Figure 1).
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FIGURE 1: Flowchart of patients' selection.
Baseline characteristics are shown in Table 1 and in Table 2 divided into tertiles according to TNF-α and IL6 levels, respectively. The mean age of the population was 51 ± 13 years, 57% were men, 21% had diabetes mellitus, 9% had coronary heart disease, and the median time since last kidney transplantation was 72 months. There were 181 deaths over a median follow-up period of 76 (interquartile range, 46-79) months; the rate of death with a functioning graft was 36 of 1000 patient-years (95% confidence interval [CI], 31-42), and there were 200 graft losses; the rate of graft loss was 40 of 1000 patient-years (95% CI, 35-46).
TABLE 1: Baseline characteristics of the 977 kidney transplant recipients divided by TNF-α tertiles
TABLE 2: Baseline characteristics of the 977 kidney transplant recipients divided by IL6 tertiles
TNF-α
Patients in the highest serum TNF-α tertile had been treated for end-stage renal disease longer, had significantly worse graft function and higher levels of inflammatory markers compared with recipients with lower serum TNF-α levels (Table 1). Serum TNF-α showed moderate negative correlation with eGFR and had mild positive correlations with C-reactive protein (Figure S1 A-C, SDC,https://links.lww.com/TP/B369).
Mortality
Median serum TNF-α concentrations were significantly higher in patients, who died with a functioning graft as compared with those who did not die during the follow-up period (TNF-α: median, 2.25 pg/mL; IQR, 1.63-3.08 pg/mL vs 1.92 pg/mL; interquartile range [IQR], 1.43-2.67 pg/mL, P < 0.001). Kaplan-Meier analyses indicated that the lowest serum TNF-α tertile separated from their counterparts suggesting better survival for patients with lower cytokine levels (Figure 2 Panel A). Compared with patients in the lowest serum TNF-α tertile, those in the middle tertile had similar mortality risk, whereas patients who were in the highest tertile had higher mortality risk in the multivariable adjusted model (Table 3).
FIGURE 2: Kaplan Meier curves of death with a functioning graft (panel A—Log-rank test: P = 0.009), all-cause mortality (panel B—Log-rank test: P = 0.001) and graft loss (panel C—Log-rank test: P < 0.001) for 977 kidney transplant recipients grouped according to TNF-α tertiles.
TABLE 3: Association between different TNF-α tertiles and per 1 pg/mL increments and outcomes in 977 kidney transplant recipients
Figure 3A shows a strong linear positive unadjusted association of serum TNF-α as a continuous variable with the risk of death with a functioning graft using fractional polynomials. A similar positive association was present after multivariable adjustment with each 1 pg/mL higher serum TNF-α level being associated with 19% higher risk of death with functioning graft (hazard ratio [HR], 1.19; 95% CI, 1.08-1.32) as shown in Table 3. Figures 4A-B show the association of TNF-α levels with death with a functioning graft (panel A) and all-cause mortality (panel B) in adjusted Cox regression final model in different subgroup of patients. The body mass index (BMI), eGFR, and history of rejection were significant effect modifiers in these analyses.
FIGURE 3: Association of TNF-α levels with death with a functioning graft (panel A—P < 0.001), all-cause mortality (panel B—P < 0.001) and graft loss (panel C—P < 0.001) in unadjusted Cox regression model in 977 kidney transplant recipients with additional distributional histograms of TNF-α.
FIGURE 4: Association of TNF-α levels with death with a functioning graft (panel A), all-cause mortality (panel B), and graft loss (panel C) in adjusted Cox regression final model in different subgroup of patients.
In sensitivity analysis, we assessed the association between serum TNF-α levels and all-cause mortality not censored for graft loss, showing similar associations (Figure 3B, Table 3). Moreover, competing risk regression analysis also indicated qualitatively similar results (Table S1, SDC,https://links.lww.com/TP/B369).
Graft Loss
Figure 2C shows the risk of death censored graft loss in patients with different serum TNF-α tertiles. Compared with patients in the lowest serum TNF-α tertile, those in the middle tertile had similar risk of graft loss, whereas patients who were in the highest tertile had higher risk of graft loss in the multivariable adjusted model (Table 3).
Figure 3C shows a linear unadjusted association of serum TNF-α as a continuous variable with the risk of graft loss using fractional polynomials. After multivariable adjustment each 1 pg/mL higher serum TNF-α level was modestly associated with the risk of graft loss (HR, 1.03; 95% CI, 1.03-1.26) as shown in Table 3. Figure 4C shows the association of TNF-α levels with graft loss in adjusted Cox regression final model in different subgroup of patients.
IL6
Patients in the highest serum IL6 tertile were older, less likely to be male and more likely to have coronary heart disease; had significantly worse graft function; and had higher levels of inflammatory markers, BMI and abdominal circumference compared to recipients with lower serum IL6 levels (Table 2). Serum IL6 levels showed moderate negative correlation with eGFR and had mild positive correlations with BMI and C-reactive protein (Figure S2 A-C, SDC,https://links.lww.com/TP/B369).
Mortality
Median serum IL6 concentrations were significantly higher in patients who died with a functioning graft as compared with those who did not die during the follow-up period (IL6: median, 2.81 pg/mL; IQR, 1.65-4.97 pg/mL vs median, 1.91 pg/mL; IQR, 1.21-3.02 pg/mL, P < 0.001). Kaplan-Meier analysis indicated that the lowest serum IL6 tertile separated from their counterparts suggesting better survival for patients with lower cytokine levels (Figure 5A). Patients in the lowest serum IL6 tertile compared with those in the middle tertile had similar mortality, whereas patients who were in the highest tertile had higher mortality risk in the multivariable adjusted model (Table 4).
FIGURE 5: Kaplan Meier curves of death with a functioning graft (panel A—Log-rank test: P < 0.001), all-cause mortality (panel B—Log-rank test: P < 0.001) and graft loss (panel C—Log-rank test: P = 0.008) for 977 kidney transplant recipients grouped according to IL6 tertiles.
TABLE 4: Association between different IL6 tertiles and per 1 pg/mL increments and outcomes in 977 kidney transplant recipients
Figure 6A shows a strong linear positive unadjusted association of serum IL6 levels as a continuous variable with the risk of death with a functioning graft using fractional polynomials. A similar positive trend was present after multivariable adjustment with each 1 pg/mL higher serum IL6 after multivariable adjustment: HR, 1.03; 95% CI, 0.99-1.06) (Table 4). Figures 7A-B show the association of IL6 levels with death with a functioning graft (panel A) and all-cause mortality (panel B) in adjusted Cox regression final model in different subgroup of patients. The eGFR was significant effect modifiers in these analyses.
FIGURE 6: Association of IL6 levels with death with a functioning graft (panel A—P < 0.001), all-cause mortality (panel B—P < 0.001), and graft loss (panel C—P = 0.285) in unadjusted Cox regression model in 977 kidney transplant recipients with additional distributional histograms of IL6.
FIGURE 7: Association of IL6 levels with death with a functioning graft (panel A), all-cause mortality (panel B) and graft loss (panel C) in adjusted Cox regression final model in different subgroup of patients.
In sensitivity analysis, we assessed the association between serum IL6 levels and all-cause mortality not censored for graft loss, showing similar associations (Figure 6B, Table 4). Moreover, competing risk regression analysis also indicated qualitatively similar trends (Table S2, SDC,https://links.lww.com/TP/B369).
Graft Loss
Figure 5C shows the death censored graft loss risk in patients with different serum IL6 tertiles. Patients in the lowest serum IL6 tertile compared with those in the middle tertile had similar risk of graft loss, whereas patients who were in the highest tertile had higher risk of graft loss in the multivariable adjusted model (Table 4).
Figure 6C shows a reverse J shape association of serum IL6 as a continuous variable with the risk of graft loss using fractional polynomials. After multivariable adjustment higher serum IL6 level was not associated with the risk of graft loss (HR [95% CI] associated with each 1 pg/m: higher IL6: 1.02 [0.98-1.06]) as shown in Table 4. Figure 7C shows the association of IL6 levels with graft loss in adjusted Cox regression final model in different subgroup of patients.
DISCUSSION
To the best of our knowledge, this is one of the first observational cohort studies demonstrating that higher serum inflammatory markers, such as IL6 and TNF-α, are independently associated with higher risk of all-cause mortality and higher risk of death with functioning graft in a large cohort of prevalent kidney transplant recipients. Both inflammatory markers showed strong negative association with residual graft function. Specifically, each 1 pg/mL higher serum TNF-α and each 1 pg/ml higher serum IL6 level was associated with 21% and 6% higher risk of death with functioning graft in unadjusted models, and 18% and 2% higher risk of mortality after adjustment for the residual graft function, as well as other important confounders (such as donor related data) in our prevalent cohort. Patients with the highest level of serum IL6 and TNF-α reported the highest risk of graft loss after adjustment for important confounders, such as residual graft function, other inflammatory markers, and donor related data.
There was strong positive association between serum TNF-α and IL6 level and risk of death with functioning graft. Previous studies found associations between increased level of TNF-α and IL6 with higher risk of mortality in patients with end stage renal disease.20 Kimmel et al20 reported 65% higher risk of death with each higher log-unit of TNF-α and 56% higher risk of death with each higher log-unit of IL6 in 230 ESRD patients. Moreover, data from a large prospective clinical trial (Assessment of LEscol in Renal Transplantation) showed that higher levels of IL6 and CRP are independently associated with all-cause mortality9 and graft loss.10
There are several potential explanations why elevated levels of these cytokines are associated with higher mortality risk. These include the development of protein energy wasting (PEW) syndrome and atherosclerosis, through insulin resistance and endothelial dysfunction.4 This is perhaps corroborated by the fact that the nontraditional inflammatory marker serum albumin tracks inversely the TNF-α levels and IL6 levels as do C-reactive protein levels (Tables 1 and 2).
We previously presented data that the severity of PEW is independently associated with mortality in renal transplant recipients.16 TNF-α and IL6 might affect the presence of PEW and nutritional status in many different ways. In the central nervous system, TNF-α and IL6 suppress appetite by the induction of leptin synthesis and by the activation of the anorexic pathways in the hypothalamus.21,22 In in vitro experiments TNF-α and IL6 induce muscle protein destruction through myostatin and insulin receptor substrate 1 leading to weight loss and malnutrition.23,24 The association of TNF-α and IL6 with malnutrition has also been investigated in several observational studies. In human subjects without kidney disease, the synthesis of TNF-α decreased in fat tissue after significant weight loss.25 According to Oner-Iyidogan et al,26 there is a strong correlation between elevated TNF-α, IL6 levels and loss of appetite in chronic kidney disease patients accompanied by elevated serum ghrelin levels. This association is also observed in patients with failed kidney allograft.27 In an earlier article of ours, we already demonstrated the link between nutrition and inflammation, including TNF-α and IL6 in kidney transplant recipients.28 In ESRD patients, proinflammatory cytokines may play an important role in PEW syndrome and anorexia, further connecting malnutrition, TNF-α and IL6; however, these findings are controversial at the present time.22,29-31 Moreover, in an observational study in ESRD patients anorexia and the loss of appetite was associated with a fourfold higher risk of malnutrition, mortality risk and hospitalization rate during a follow-up period of only 1 year.31 Furthermore, Beberashvili et al32 found significant correlations between higher IL6 level and decreased daily calorie intake and serum albumin reduction in 85 hemodialysis patients; additionally, 1 pg/mL higher IL6 level was also associated with 6% higher mortality risk.
The presence of insulin resistance is an important predictor of mortality in kidney transplant recipients.33 TNF-α was the first cytokine that linked nutrition to inflammation via insulin resistance, prompting a plethora of investigations on this subject. Several studies revealed the possible molecular pathways that induce insulin resistance, namely the I κ-β-kinase complex and the c-Jun-terminal-kinases 1 and 2 pathways.34,35 TNF-α is known to stimulate macrophage migration through chemokines, specifically by monocyte chemoattractant protein 1 that is responsible for insulin resistance in rodents.36 Despite these molecular pathways in vivo experiments have not proven that neutralization of TNF-α reduces insulin resistance in human subjects.37 However, IL6 therapy seems to be more effective in the modulation of insulin resistance, suggesting an important role in its pathophysiology. Application of IL6 in human subjects induces hyperglycemia, because it causes insulin resistance in adipocytes.38,39 Unfortunately, we do not have data regarding insulin resistance or new onset diabetes mellitus to test this hypothesis in our cohort.
The other possible pathophysiologic mechanism for proinflammatory cytokines to affect clinical outcomes in patients with kidney graft is cardiovascular impairment. TNF-α activates the nicotinamide adenine dinucleotide phosphate oxidative and NF-κB transcription pathways, reducing the activity of endothelial nitric oxide synthase leading to reduction in the synthesis of nitrogen oxide, and elevation in the activity of reactive oxygen species; moreover, it promotes the expression of cell adhesion molecules and fibrotic tissue factors.40 In rodents, continuous infusion of TNF-α led to heart failure through impairment of ventricular function.41 It should also be noted, that in healthy populations, TNF-α predicts increased cardiovascular mortality risk. Tuomisto et al42 showed in a prospective cohort, that subjects in the highest quartile of TNF-α had a twofold higher risk of incident cardiovascular events. IL6 also has atherosclerosis-inducing effects by upregulation of adhesion molecules, induction chemokine production and by blocking the endothelial nitric oxide synthase enzyme leading to endothelial dysfunction.43,44 Moreover, observations in ESRD patients found a connection between IL6 and the development of carotid atherosclerosis.45 According to Rao et al46 hemodialysis patients with 1 log-unit higher IL6 had a 46% higher chance for cardiovascular mortality. Likewise, Tripepi et al47 demonstrated that IL6 has 2 times higher predictive value compared to CRP and other proinflammatory cytokines (including TNF-α) to predict cardiovascular death in hemodialysis patients.
We also found similar associations between elevated levels of these inflammatory cytokines and higher risk of graft loss. Each 1 pg/ml elevation of serum TNF-α was associated with 19% higher risk of graft loss in the unadjusted model, which remained significant even after multivariable adjustments. These proinflammatory cytokines might lead to renal injury via inflammatory and vascular effects, resulting in mesangial proliferation and fibrosis in the kidneys. Finally, there is growing evidence that IL6 plays an important role in allograft rejection. IL6 alongside with tissue growth factor β promote T cell differentiation to CD4+ Th17 cells instead of turning them into regulatory T cells. T regulatory cells suppress the inflammatory processes, whereas CD4+ Th17 cells might provoke allograft rejection.48,49 Serum and urine IL6 levels are elevated in patients undergoing acute rejection and immediately after transplantation.50,51 Along the same lines, Sonkar et al52 found in 90 renal transplant recipients that serum IL6 levels in stable patients are not different from healthy controls, but patients experiencing rejection demonstrate significantly higher levels. Also a notable finding by Dahle et al10 demonstrated a 54% higher chance of graft loss associated with each log-unit higher serum IL6 in a relatively large renal transplant cohort. Likewise, serum TNF-α levels are also elevated in patients with rejection compared to healthy controls or stable transplanted patient even after adjustment for renal function.52 Moreover, Wiggins et al53 suggested that TNF-α levels are elevated 2 days before the clinical manifestation of rejection, though the examined population was small. These findings suggest that TNF-α plays an important role in graft failure, but more observational studies are required to confirm this association.
The strength of our study includes its relatively large size with minimal missing data and relatively long follow-up. Furthermore, in our analyses, we have carefully accounted for important confounders of IL6 and TNF-α associated mortality, such as residual graft function, donor characteristics, anthropometrics, nutritional markers, and comorbid conditions.
We also recognize the limitations of our study. Among these, the most important is that we have measured IL6 and TNF-α level only once at baseline; accordingly, we cannot account for any potential changes of these over time. We have used a prevalent cohort approach with the potential for selection bias introduced in the interpretation of the data. Nevertheless, the majority of the patients in a real clinical practice are prevalent patients, and data from incident populations might not be applicable to these. Our statistical models could only be adjusted for confounders that were available, and we cannot rule out a potential impact of other important unmeasured variables such as proteinuria,54 on these outcomes. Some of our conclusions may be limited by era effect, that is, the prevailing practice of using less tacrolimus and more mTOR inhibitors during the baseline period of this study in 2007, than currently practiced in Hungary. Finally, due to lack of availability of information on cause-specific mortality, we cannot investigate further a specific mechanism linking elevated IL6 and TNF-α with all-cause mortality.
CONCLUSIONS
In our large and contemporary cohort of almost a thousand prevalent kidney transplant recipients, serum IL6 and TNF-α showed significant associations with residual graft function. In addition, we detected strong, positive linear associations between serum IL6 and TNF-α level and mortality and significant associations between highest tertiles of serum IL6 and TNF-α level and subsequent graft loss. Further studies are needed to better understand the mechanisms behind these observations.
ACKNOWLEDGMENTS
The authors thank the patients and the staff in the Department of Transplantation and Surgery, Semmelweis University Budapest.
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