Living kidney donor evaluation and safety assessment
van Londen, Marco
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Tubular Maximum Phosphate
Reabsorption Capacity in
Living Kidney Donors is
Independently Associated with
One Year Recipient GFR
Marco van Londen1, MD, Brigitte M. Aarts, MD1, Jan-Stephan F. Sanders1, MD, PhD,Jan-Luuk Hillebrands2, PhD, Stephan J.L. Bakker1, MD, PhD, Gerjan Navis1, MD, PhD and
Martin H. de Borst1, MD, PhD
American Journal of Physiology Renal Physiology. 2018 Feb 1;314(2):F196-F202.
1 Department of Internal Medicine, Division of Nephrology, and
2 Department of Medical Biology and Pathology, University of Groningen, University Medical Center
Abstract
The donor glomerular filtration rate (GFR) measured before kidney donation is a strong determinant of recipient graft outcome. No tubular function markers have been identified that can similarly be used in donors to predict recipient outcomes. In the current study we investigated whether the predonation tubular maximum reabsorption capacity of phosphate (TmP-GFR), which may be considered as a functional tubular marker in healthy kidney donors, is associated with recipient GFR at one year after transplantation, a key determinant of long-term outcome. We calculated the predonation TmP-GFR from serum and 24h-urine phosphate and creatinine levels in 165 kidney donors, and recipient 125I-iothalamate GFR
and eGFR (CKD-EPI) at 12 months after transplantation. Kidney donors were 51±10 years old, 47% were men, and mean GFR was 118±26 mL/min. The donor TmP-GFR was associated with recipient GFR 12 months after transplantation (GFR 6.0 mL/min lower per 1 mg/dL decrement of TmP-GFR), which persisted after multivariable adjustment for donor age, sex, predonation GFR and blood pressure and other potential confounders. Results were highly similar when eGFR at 12 months was taken as the outcome. Tubular damage markers KIM-1 and NGAL were low and not associated with recipient GFR. A lower donor TmP-GFR before donation, which may be considered to represent a functional measure of tubular phosphate reabsorption capacity, is independently associated with a lower recipient GFR one year after transplantation. These data are the first to link donor tubular phosphate reabsorption with recipient GFR post-transplantation.
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Introduction
Kidney transplantation is considered the optimal treatment for patients with end-stage renal disease(37, 44). Living kidney donation has gained a central position in many transplant programs due to the excellent recipient outcomes as well as the favorable long term safety profile for the donor, facilitated by careful donor screening pre-donation(33). The elective setting of living donor kidney transplantation allows detailed studies of donor characteristics before kidney transplantation, enabling to predict post-transplantation renal function in the recipient. Previous studies identified donor age and pre-donation glomerular filtration rate (GFR), even within the normal range, as independent determinants of long-term graft survival after living donor kidney transplantation(27, 31). Whether this also holds true for donor tubular characteristics is unknown.
In both native chronic kidney disease and allograft injury following kidney transplantation, the severity of tubulo-interstitial damage is a strong predictor of subsequent progressive renal function loss(12, 23, 28). In line, non-invasive markers for tubular damage, such as urinary kidney injury molecule-1 (KIM-1) and NGAL measured after kidney transplantation have been identified as predictors of long-term graft loss(1, 5, 29, 38). Yet, whether differences in tubular characteristics in living kidney donors are predictive for recipient graft outcomes is unknown.
One of the primary functions of the tubular compartment is to regulate organic anions such as phosphate. Renal phosphate homeostasis is regulated primarily in proximal tubular epithelial cells by sodium phosphate cotransporters NaPi-IIa, NaPi-IIc and PiT-2(18, 20, 40). The renal tubular maximum reabsorption rate of phosphate to the glomerular filtration rate (TmP-GFR) represents the maximum renal capacity to reabsorb phosphate and may reflect tubular function(32). Previous studies demonstrated a loss of renal NaPi expression in response to renal injury(41, 45), and a lower TmP-GFR with age(8).
In the current study we therefore investigated whether the TmP-GFR, measured before donation in living kidney donors, is independently associated with recipient GFR one year after transplantation, a critical indicator of long-term allograft outcome(14, 19).
Materials and Methods
In this study, 165 living kidney donors and their matched recipients were evaluated. All transplantations took place between 2008 and 2011 in the University Medical Center Groningen, The Netherlands, or in a collaborating center in The Netherlands on behalf of the Dutch living donor exchange program. Donors were selected from all transplantations in this period, based on sample availability. The study was approved by the institutional ethical review board (METc 2014/077). All procedures were conducted in accordance with the declaration of Helsinki and the declaration of Istanbul.
GFR measurements
GFR measurements were performed as part of the routine donor screening and early follow-up program at 6±7 months prior to and 2±0 months after kidney donation, and in recipients at one year after transplantation. GFR was measured by constant low-dose infusion of the radio-labeled tracer 125I-iothalamate as described previously(2). For the measurements,
subjects were seated in a quiet room, in a semi-supine position. After drawing a blank blood sample, the priming solution containing 0.04 mL/kg body weight of the infusion solution (0.04 MBq of 125I-iothalamate and 0.03 MBq of 131I-hippurate per mL saline) plus an extra
of 0.6 MBq of 125I-iothalamate was given, followed by constant infusion at 12 mL/h. To
achieve stable plasma concentrations of the tracers, a 2 hour stabilization period followed initial infusion, after which the clearance period started. Clearances were measured over the next 2 hours and calculated as (U*V)/P and (I*V)/P, where U*V represents the urinary excretion of the tracer, I*V the infusion rate of the tracer and P represents the tracer value in plasma at the end of each clearance period. The mGFR was calculated from (U*V)/P of 125I-iothalamate and corrected for voiding errors by multiplying the urinary clearance of 125I-iothalamate with the ratio of the plasma and urinary clearance of 131I-hippurate. The
day-to-day GFR variability is 2.5%(2).
Donor selection procedure
Donors with a GFR >80 mL/min were eligible for donation. Donors with antihypertensive drugs were allowed to donate, with a maximum of two antihypertensive drugs and provided that ambulatory blood pressure did not exceed 150/85 mmHg. Donors with a body mass index (BMI) exceeding 30 kg/m2 were encouraged to lose weight. No maximum age for
donors has been defined, however many older potential donors were excluded due to a low GFR or co-morbidities. Potential donors with a disturbed glucose tolerance test were rejected, as well as donors with severe atherosclerotic lesions. An abdominal CT scan was performed for all donors to reveal anatomy and the extent of atherosclerosis before surgery.
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Treatment after transplantation
Standard immunosuppression consisted of triple therapy with induction with basiliximab, with tacrolimus (Prograft® or Advagraf®, Astellas Pharma b.v., Leiden, The Netherlands; initial trough level 8-12 ng/mL) or cyclosporine microemulsion (Neoral®; Novartis Pharma b.v., Arnhem, The Netherlands; 2dd 4 mg/kg; initial trough level 200-250 ug/l), combined with mycophenolate mofetil (Cellcept®; Roche b.v., Woerden, The Netherlands; 2g/day or Myfortic®; Novartis b.v., Arnhem, The Netherlands; 1440 mg/day) and prednisolone. Upon clinical indication adaptations in the immunosuppression were made. Patients frequently visited our outpatient clinic; upon suspicion of allograft rejection, a renal biopsy was performed. Delayed graft function (defined as the requirement of dialysis within the first week after transplantation), episodes and type of rejection, graft failure (defined as end-stage renal disease requiring dialysis or retransplantation) and recipient mortality were registered. No recipients were lost to follow-up.
Clinical and biochemical analysis
Data on the recipient’s kidney disease type, pre-emptive character of the transplantation, and ischemia times were collected for all transplantations. Blood samples were taken from kidney donors at 6±7 months prior to and 2±0 months after kidney donation, and in recipients at one year after transplantation, both after an 8 to 12 hour overnight fasting period. EDTA plasma samples were stored at -80°C until assessment of biochemical parameters for this study. Plasma C-terminal FGF23 levels were determined by sandwich ELISA (Immutopics, San Clemente, CA), with an intra-assay and interassay coefficient of variation of < 5% and < 16% respectively(15). Plasma creatinine concentration was determined using a modified version of the Jaffe method (MEGA AU 510, Merck Diagnostic, Darmstadt, Germany). Parathyroid hormone was measured using radioimmunoassay. Serum albumin, calcium, cholesterol, C-reactive protein, glucose, hemoglobin, phosphate, and urinary phosphate, sodium, total protein and urea were determined by routine laboratory measurements. Urinary levels of tubular damage markers Kidney Injury Molecule-1 (KIM-1) and Lipocalin-2/ Neutrophil Gelatinase-Associated Lipocalin (NGAL) were measured by sandwich ELISA (HaemoScan b.v., the Netherlands) as described previously(30). We considered 132 ng/ mL the upper normal value for urinary NGAL(9). Estimated GFR was calculated using the creatinine-based CKD-EPI formula(22). Fractional excretion (FE) of phosphate was calculated as:
FE of sodium (FEsodium) was calculated similarly. We calculated the FE of creatinine (FEcrea) using the iothalamate clearance and urinary and serum creatinine:
FEcrea (%) = Ucreatinine/ (Screatinine * iothalamate clearance) *100
The tubular maximum reabsorption of phosphate by GFR (TmP-GFR) essentially corresponds to the theoretical lower limit of serum phosphate below which all filtered phosphate is reabsorbed. The TmP-GFR was calculated using the following equations(4, 7), depending on the tubular reabsorption of phosphate (TRP):
TRP = 1 – ((Uphosphate / Pphosphate) * (Pcreatinine / (Ucreatinine * 1000))) If TRP was <= 0.86 TmP-GFR was calculated as:
TmP/GFR = TRP * Pphosphate
To follow the nomogram’s nonlinear part, if TRP was > 0.86 TmP-GFR was calculated as: 0.3 * TRP/(1-(0.8*TRP)) * Pphosphate
Statistical analysis
Variable distribution was tested with histograms and probability plots. Normally distributed variables are presented as mean±standard deviation, and non-normally distributed variables as median [first-third quartile], unless indicated otherwise. Non-normally distributed data were natural log-transformed for correlation analysis and linear regression analysis. We used ANOVA to calculate the difference in recipient GFR across tertiles of TmP-GFR. Independent correlates of TmP-GFR were identified using backward linear regression analyses). We explored donor age, sex, BMI, GFR, systolic blood pressure, diastolic blood pressure, donor serum and urinary levels of calcium, FGF23, hemoglobin, phosphate, PTH and creatinine as potential determinants. Donor, recipient and transplant characteristics were similarly analyzed to identify independent correlates of recipient GFR one year after transplantation. Subsequently, multivariable linear regression models were built, adjusting the association between donor TmP-GFR and recipient one-year GFR for potential confounders. Based on missing data analysis, we used listwise deletion for our analyses. Model 1 was adjusted for the major established donor determinants of recipient one-year GFR: donor age and sex, donor GFR, and donor systolic blood pressure. Subsequently, model 2 was further adjusted for additional established determinants of recipient GFR (i.e. donor smoking status, recipient primo CMV infection, acute rejection episodes or delayed graft function). Finally, in model 3, all additional donor factors that were associated with recipient GFR in univariate linear regression analysis were added to the model. Assumptions of homoscedasticity and normality of residuals for regression analysis were met. All statistical analyses were performed using SPSS 22.0 for Windows (IBM, Armonk,
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NY) and Graphpad Prism 6 for Windows (Graphpad, San Diego, CA). P-values <0.05 wereconsidered statistically significant.
Results
Donor, recipient and transplant characteristics
Clinical and biochemical characteristics of kidney donors before donation are summarized in Table 1. Kidney donors were 51±10 years old, 47% were men. 125I-iothalamate GFR
was 118±26 mL/min. The predonation TmP-GFR was 2.98±0.83 mg/dL (0.96±0.27 mmol/L). Predonation TmP-GFR was inversely associated with FENa (st. β -0.21, P=0.01) and showed a trend towards a positive associaton with FEcrea (st. β 0.20, P=0.10). In multivariable regression analysis, serum phosphate (st. β -0.76, P<0.001), serum creatinine (st. β -0.18, P<0.001) and urinary concentrations of phosphate (st. β -0.47, P<0.001), and
Table 1. Predonation donor characteristics (N=165) and their univariate association with recipient GFR one year after transplantation
Mean St. beta P Age, y 51 ± 10 -0.28 <0.001 Sex, n (%) male 79 (47%) -0.04 0.59 BMI, kg/m2 26.0 ± 3.5 -0.02 0.84 mGFR, mL/min 118 ± 26 0.27 <0.001 SBP, mmHg 125 ± 14 -0.17 0.04 DBP, mmHg 76 ± 9 -0.16 0.05
Smoking status, n (%) smokers 37 (26%) 0.12 0.18
Serum calcium, mg/dL 9.2 ± 0.4 0.07 0.39 Serum albumin, mg/dL 4.5 ± 0.3 0.16 0.06 Serum phosphate, mg/dL 3.3 ± 0.6 0.17 0.03 Hemoglobin, mg/dL 14.3 ± 1.2 -0.03 0.70 Parathyroid hormone, pg/mL 31 [25-41] 0.13 0.17 FGF23, RU/ml 77 [62-97] 0.06 0.37 TmP-GFR, mg/dL 2.98 ± 0.83 0.25 0.002
Urinary phosphate excretion, mg/day 720 ± 450 -0.14 0.16
Fractional phosphate excretion, % 16.7 ± 11.0 -0.19 0.02
Fractional sodium excretion, % 78.2 ± 29.3 -0.14 0.10
Fractional creatinine excretion, % 68.4 ± 29.3 0.17 0.04
Values indicated as mean ± SD, median [IQR] or n (%), and standardized beta and p values for univariate association with recipient GFR at one year post-transplantation. BMI, body mass index; mGFR, glomerular filtration rate using 125I-iothalamate infusion; SBP, systolic blood pressure; DBP,
diastolic blood pressure; FGF23, fibroblast growth factor 23; TmP-GFR, tubular maximum reabsorption of phosphate by glomerular filtration rate.
creatinine (st. β -0.40, P<0.001) were independently associated with donor TmP-GFR (R2=0.94). Donor predonation PTH was associated with donor TmP-GFR (st. β -0,26,
P=0.003), but this association was lost upon adjustment for serum and urinary phosphate and creatinine. There was no correlation between donor TmP-GFR and recipient PTH (st. β -0,04, P=0.61). Results were similar when GFR was forced in the model. Transplant and recipient characteristics are presented in Table 2. During the first year after transplantation, five recipients (4%) died, and three (2%) developed graft failure.
Table 2: Transplant and recipient characteristics and their univariate association with recipient GFR one year after transplantation
St. beta P
Transplant characteristics
Cold ischemia time, min 153] [137-173 -0.05 0.58 Total warm ischemia time, min 46 [40-51] -0.06 0.46 Pre-emptive transplantation, n (%) 62 (37%) -0.04 0.62 Primary CMV infection, n (%) 20 (12%) 0.08 0.30 Number of HLA-AB mismatches, % 0.08 0.35
0 15.7
1 14.4
2 39.9
3 17.0
4 13.1
HLA-DR number of mismatches, % 0.06 0.46
0 24.2
1 52.3
2 23.5
Donor type, n (%) related 79 (47%) 0.03 0.71
Recipient characteristics at time of transplantation
Recipient age, y 48 ± 13 -0.20 0.17 Recipient sex, % male 88 (53%) -0.21 0.008 Recipient BMI, kg/m2 24.7 ± 4.4 0.21 0.01
Etiology of kidney disease, n (%)
Primary glomerular disease 18 (11%) -0.05 0.56 Glomerulonephritis 39 (23%) 0.02 0.79 Polycystic renal disease 30 (18%) 0.03 0.68 Dysplasia/hypoplasia 3 (2%) 0.02 0.84 Renovascular disease 19 (11%) 0.07 0.43 Diabetic nephropathy 20 (12%) 0.05 0.54 Tubulo-interstitial nephritis 4 (2%) -0.06 0.49 Other/unknown causes 34 (20%) -0.15 0.07
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St. beta P
Recipient characteristics at one year post-transplantation
Systolic blood pressure, mmHg 136 ± 18 - Diastolic blood pressure, mmHg 83 ± 10 -0.02 0.85 Serum creatinine, mg/dL 1.38 [1.17-1.68] -0.04 0.66 Serum calcium, mg/dL 10.0 ± 0.6 -0.61 <0.001 Serum albumin, mg/dL 4.4 ± 0.3 -0.08 0.32 Serum phosphate, mg/dL 3.1 ± 0.6 0.02 0.82 Serum glucose, mg/dL 111 ± 51 -0.27 0.001 Hemoglobin, mg/dL 14.4 ± 12.4 0.16 0.06 Parathyroid hormone, pg/mL 114 [72-162] -0.08 0.36 Proteinuria, mg/24h 0.2 [0.0-0.3] -0.33 <0.001 TmP-GFR, mg/dL 4.5 ± 1.8 -0.19 0.02 Urinary phosphate excretion, mg/day 781 ± 310 0.23 0.01 Fractional phosphate excretion, % 28.5 ± 11.6 0.22 0.02 Systolic blood pressure, mmHg 136 ± 18 -0.33 <0.001
Recipient medication use at one year post-transplantation
Number of antihypertensives, n (%) -0.02 0.86 0 26 (16%) 1 54 (32%) 2 37 (22%) 3 22 (13%) 4+ 7 (4%) Beta-blocker, n (%) 85 (51%) -0.09 0.30 ACE inhibitor, n (%) 27 (16%) 0.03 0.68 Angiotensin receptor blocker, n (%) 18 (11%) 0.01 0.96 Thiazide diuretic, n (%) 17 (10%) -0.06 0.49 Loop diuretic, n (%) 21 (13%) -0.19 0.02 Calcium channel blocker, n (%) 35 (21%) 0.11 0.18 Alpha-blocker, n (%) 17 (10%) 0.16 0.06 Statin, n (%) 74 (44%) -0.06 0.49 Cyclosporin use, n (%) 77 (46%) 0.06 0.48 Tacrolimus use, n (%) 61 (37%) -0.09 0.27 Everolimus use, n (%) 4 (2%) 0.16 0.06 Azathioprine, n (%) 10 (6%) -0.05 0.54 Mycophonolate mofetil, n (%) 132 (80%) 0.06 0.50 Prednisolone, mg/d 10 [7.5-10] 0.04 0.60
Post-transplantation events in the first year
Primary cytomegalovirus infection, n (%) 18 (11%) 0.09 0.30 Delayed graft function, n (%) 3 (2%) -0.07 0.42 Biopsy-proven acute cellular rejection, n (%) 34 (20%) -0.26 0.002 Graft failure within 1 year, n (%) 3 (2%) N/A N/A Mortality within 1 year, n (%) 5 (3%) N/A N/A Values indicated as mean ± SD, median [IQR] or n (%), and standardized beta and p values for univariate association with recipient GFR at one year post-transplantation. BMI, body mass index; mGFR, glomerular filtration rate using
Predonation TmP-GFR and recipient renal function one year after
transplantation
Patients who received a kidney from a donor in the lowest TmP-GFR tertile had a lower GFR one year after kidney transplantation (54±17 mL/min), compared with those receiving a kidney from a donor with TmP-GFR in the middle tertile (GFR 63±16 mL/min; compared to lowest tertile P=0.02), or from a donor in the highest TmP-GFR tertile (GFR 65±19 mL/ min; compared to lowest tertile P=0.002; Figure 1). In univariable analysis, predonation donor TmP-GFR as well as donor age, GFR, systolic and diastolic blood pressure, serum phosphate, and fractional phosphate excretion were associated with recipient GFR one year after transplantation (for standardized beta’s of these associations see Table 1). The unstandardized beta (β or effect size, not shown in Table 1) of donor predonation TmP-GFR on GFR of the recipient was 6.0 [95% CI 2.7-9.3] mL/min per mg/dL, indicating that for every 1 mg/dL decrease in predonation TmP-GFR, the recipient 1-year GFR was 6.0 mL/min lower. Donor plasma fibroblast growth factor 23 (FGF23) measured before donation was not associated with recipient GFR one year post-transplantation.
Figure 1. Predonation donor TmP-GFR and recipient GFR one year after kidney transplantation Kidney transplant recipients that received from a donor with a predonation TmP-GFR in the lowest tertile display a lower GFR at one year after transplantation than a recipient who received from a donor with a TmP-GFR in the intermediate (P=0.02) or highest (P=0.002) tertiles. The mean predonation GFR was similar over the tertiles of donor TmP-GFR: the lowest TmP-GFR tertile had a mean GFR of 115 (25) mL/min, the intermediate tertile 117 (27) mL/min (P=0.87 vs. lowest tertile), and the highest tertile 121 (25) mL/min (P=0.41 vs. lowest tertile, P=0.73 vs. intermediate tertile). Data in figure presented as individual values with the mean. Differences were tested with a one-way ANOVA.
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Subsequently, multivariate linear regression analysis revealed that the association betweendonor TmP-GFR and recipient one-year GFR was independent of donor age and sex, GFR, and blood pressure (Table 3, model 1). The association remained significant upon further adjustment for additional established determinants of recipient GFR and for additional associates of recipient GFR in univariate analyses (Table 3, models 2 and 3). When adding TmP-GFR to the regression models, a small, but consistent increase in R2 was observed.
As expected, besides the TmP-GFR, most of the established determinants of recipient GFR showed (a trend towards) an association with recipient one-year GFR. When forced into the final regression model, neither serum calcium, albumin, hemoglobin, urinary (fractional) phosphate excretion, nor the number of HLA mismatches contributed to the model. No collinearity between donor TmP-GFR and donor GFR was found (tolerance 1.00, variance inflation factor=1.00, Pearson r=0.13, P=0.11; Figure 2). In the final regression model, an interaction term for TmP-GFR and GFR was not significant (P=0.09). In the main analysis, we included patients who developed graft failure in the first year (n=3) as having a one-year GFR of 0 mL/min. When excluding these patients in another sensitivity analysis, the association between TmP-GFR and recipient GFR one year after transplantation remained materially similar (final model R2=0.44, standardized β 0.21, P=0.004). If GFR was
normalized for body surface area, results were similar (crude model R2=0.05, standardized β
0.23, P=0.005). If eGFRCKD-EPI was used instead of mGFR, the association was highly similar (crude model R2=0.08, standardized β 0.27, P<0.001). There was no association between
donor phosphatonins (PTH, FGF23) and recipient GFR (Table 1). We found no association between donor TmP-GFR and donor pre- and postdonation mGFR (Figure 2).
Figure 2. Donor TmP-GFR is not associated with donor predonation mGFR
In living kidney donors, no association between donor TmP-GFR and donor predonation mGFR (A) and postdonation mGFR (B) was found. The association was analyzed using linear regression analysis.
Predonation tubular damage markers and recipient GFR one year after
transplantation
We also investigated the association of two established tubular biomarkers, i.e. Kidney Injury Molecule-1 (KIM-1) and Neutrophil Gelatinase-Associated Lipocalin (NGAL), with recipient GFR one year after transplantation. Donor predonation urinary KIM-1 was 0.20 [0.13-0.32] ng/mL, and urinary NGAL was 5.37 [2.73-11.88] ng/mL. Only one donor had a urinary NGAL level above 132 ng/mL. Predonation TmP-GFR was neither associated with KIM-1 (r=0.04, P=0.66) nor with NGAL (r=0.06, P=0.24). Neither KIM-1 (r=0.02, P=0.11) nor NGAL (r=0.03, P=0.07) was significantly associated with recipient GFR one year after transplantation and recipient GFR was not different between KIM-1 and NGAL tertiles (Figure 3). KIM-1 and NGAL did not contribute to the final regression model (Table 3) or influenced the association between donor TmP-GFR and recipient GFR. When the 24h-excretion instead of the concentration of the tubular markers was considered, results remained similar.
Discussion
In this analysis of 165 living kidney donors and their respective recipients, we found an association between donor TmP-GFR, measured before donation, and recipient GFR one year after kidney transplantation. A lower TmP-GFR, reflecting a lower maximum tubular reabsorption capacity, was associated with a lower recipient one-year GFR. This association was independent of established donor and recipient determinants and other potential confounders.
Table 3. Multivariable regression analysis of recipient GFR 1 year after transplantation
St. beta P value R 2 without TmP-GFR R 2 with TmP-GFR Donor TmP-GFR (crude) 0.25 0.002 - 0.08 Multivariable model 1 0.22 0.004 0.20 0.24 Multivariable model 2 0.23 0.02 0.22 0.26 Multivariable model 3 0.25 0.005 0.37 0.43
Multivariable model 1: Donor TmP-GFR + adjustment for donor determinants of recipient GFR at one year post-transplantation (donor age, donor sex, GFR, systolic blood pressure).
Multivariable model 2: model 1 + adjustment for univariate correlates of recipient GFR at one year prost transplantation (CMV infection, acute rejection, delayed graft function) and donor PTH.
Multivariable model 3: model 2 + adjustment for other established determinants of recipient GFR at one year post-transplantation (recipient age, recipient sex, BMI, proteinuria, parathyroid hormone). Values are indicated by standardized beta and P values for multivariable associations with GFR at one year post-transplantation. The R squared value is shown with and without TmP-GFR.
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We found no significant association between the TmP-GFR and GFR before donation,in line with the concept that the TmP-GFR is not primarily driven by glomerular function. Instead, the TmP-GFR primarily represents renal phosphate reabsorption and as such, we propose it can be considered a functional tubular parameter. In the selected healthy population of living kidney donors, with a normal GFR, so far no markers related to tubular properties have been related to recipient renal outcomes. In this population, biomarkers for tubular damage are low and thus unsuitable to serve as risk predictors. Indeed, we did not observe associations of urinary NGAL or KIM1 with recipient GFR, which were present in very low concentrations, similar to a previous study(5). In chronic kidney disease patients and renal transplant recipients, in contrast, high urinary excretion of these markers has been associated with a higher rate of renal function decline, independent of renal function itself(1, 10, 11, 17, 25, 38). Assuming that the TmP-GFR represents a functional tubular parameter, this parameter may indicate discrete changes in tubular function in living donors that could contribute to a lower GFR after transplantation. This concept is supported by the observed associations between the predonation TmP-GFR and FENa as well as FEcrea, which may be considered functional tubular markers as well(39). A similar but weaker (borderline significant) association between predonation TmP-GFR and postdonation GFR was observed in donors (Figure 2); the discrepancy could be explained by differences in the post-transplant GFR course between donors and recipients. Data in experimental animals,
Figure 3. Donor predonation urinary levels of kidney damage markers KIM-1 and Lipocalin-2/ NGAL
(A) Recipient GFR one year after transplantation did not differ between tertiles of donor pre-donation urinary KIM-1. (B) Recipient GFR one year after transplantation did not differ between tertiles of donor pre-donation urinary NGAL. Data in figure presented as mean±SEM. Differences were tested with a one-way ANOVA.
showing reduced renal NaPi expression in response to renal injury indeed suggest that low TmP-GFR is a marker of subclinical tubular damage(21, 34). In line, in patients with isolated tubular dysfunction, the TmP-GFR has been reported to be a marker of tubular (dys)function(24, 26). To our knowledge, the current study would be the first to identify a functional tubular parameter in donors as a risk factor for recipient outcome. It should be noted that phosphate transport is only one function of renal tubule and call for exploration of other parameters that may reflect tubular transport capacity.
Alternatively, the observed association between donor TmP-GFR and recipient renal function could be related to renal phosphate metabolism itself. Deregulated phosphate metabolism in the post-transplant setting, accompanied by hyperphosphatemia and high FGF23 and PTH levels, has been associated with adverse outcomes(3, 43). In addition, elevated FGF23 levels have been associated with accelerated renal function loss in CKD(13). In our cohort of living kidney donors, TmP-GFR but not FGF23 or PTH was associated with recipient GFR. The absence of an association between donor phosphatonins and recipient GFR one year after transplantation may be explained by the fact that both FGF23 and PTH levels were within the normal range in our cohort of healthy kidney donors, limiting their predictive value. This is corroborated by the fact that FGF23 levels start to increase when the (estimated) GFR decreases below 60 mL/min and PTH levels even in a lower GFR range(16).
We specifically focused on renal handling of phosphate given several previous publications demonstrating a relationship between phosphate metabolism and renal outcomes in renal transplant recipients(35, 42, 43). Our findings may at first glance seem in contrast with a recent publication reporting increased tubular reabsorption of phosphate during the proteinuric phase in children with nephrotic syndrome, compared with the remission phase(35). The authors also show a positive association between proteinuria and serum phosphate, as well as FGF23 in patients with chronic kidney disease. However, it should be taken into account that our population of kidney donors was a priori selected to have an excellent renal function and no proteinuria.
Limitations of our study include the sample size of the cohort, single measurement and the limited follow-up. On the other hand, our study was of sufficient size to identify donor TmP-GFR as a determinant of recipient TmP-GFR one year after transplantation, a critical indicator of long-term allograft outcome(14, 19). Yet, larger studies with longer follow-up are needed to confirm and extend our results towards long-term complications such as graft failure. Furthermore, our study was restricted to a Caucasian population and to transplant recipients who survived up to one year after transplantation, which may limit external validity. The
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absence of vitamin D concentrations is another limitation. Strengths of the study include theuse of measured GFR, the gold standard to assess renal function, especially in living kidney donors(36), the robust statistical analyses adjusting for several potential confounders. Replacing mGFR with eGFRCKD-EPI led to similar results. Moreover, the other determinants of recipient GFR were in line with prior studies(6, 31), supporting the generalizability of our data. Finally, phosphate transport represents only one of the many tubular processes; other functional tubular markers in donors may also be associated with the recipient GFR. In conclusion, this is the first study to identify a lower donor TmP-GFR, considered to reflect a reduced maximum tubular reabsorption capacity, as a potential risk factor for a lower GFR after living kidney transplantation, independent of established risk factors, including donor GFR, age and blood pressure. We speculate that the donor TmP-GFR could represent a functional tubular marker, which would underline the importance of tubular function as a prognostic determinant in the kidney transplantation setting. Whether the donor TmP-GFR may serve as an adjunct screening tool to estimate recipient renal function after living donor kidney transplantation should be addressed in future studies with larger sample size, particularly in donors with marginal GFR.
Acknowledgments
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