Early Glomerular Filtration Rate Changes in Living Kidney Donors And Recipients: An Example Of Renal Plasticity

ABSTRACT

1. Background

In living kidney transplantation there are two different individuals, a healthy donor, and a renal transplant recipient. This is an excellent human model to study factors that influence kidney function in the context of reduced renal mass and the adaptation of two comparable kidneys to different metabolic demands.

2. Methods

We analyzed the changes in measured glomerular filtration rate (GFR, iohexol) from pretransplantation to 12 months after transplantation in 30 donor-recipient pairs. Each donor was compared with his/her recipient. We defined a priori three different groups based on GFR differences at 12 months: donor > recipient (Group A; 78 ± 8 versus 57 ± 8 mL/min), donor < recipient (Group B; 65 ± 11 versus 79 ± 11 mL/min) and donor≈recipient (Group C; 66 ± 7 versus 67 ± 7 mL/min). Other factors like donor/recipient mismatches in body mass index (BMI), surface area, and gender were evaluated.

3. Results

In Group A donors were mostly male and recipients were female (75% each). Donors had a higher baseline weight than their recipients. During follow-up, weight remained stable in donors but increased by 7% in recipients. In Group B donors were mostly female (60%) and recipients male. At baseline, donors had a lower weight than recipients. At 12 months, weight was stable in donors but increased in recipients. In Group C donors were mostly (75%) female and recipients male. At baseline, donors had a higher BMI than their recipients. At 12 months, BMI was stable in donors but increased by 14% in recipients. In multivariable analysis, higher GFR at 12 months was associated with higher baseline weight and GFR in donors and with male gender and higher baseline weight in recipients. Conclusions. Kidneys from living donors are more ‘plastic’ than originally thought and respond to metabolic demands and weight changes of their new host. These changes should be taken into account when assessing GFR outcomes in this population.

4. Keywords

body mass index, gender, glomerular filtration rate, kidney transplantation, and living donors.

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INTRODUCTION

Living donor kidney transplantation is the best therapeutic option for patients with advanced renal disease [1]. It is associated with better graft and patient survival compared with patients who receive a graft from deceased donors [1–3]. Potential healthy donors are rigorously screened and must meet strict eligibility criteria. An excellent health status must be proven and occult diseases must be ruled out. As expected, an accurate evaluation of renal function is mandatory to be certain that the glomerular filtration rate (GFR) is above an acceptable cut-off value for donation.

Also, living donor kidney transplantation is a unique situation in which two different individuals end up with a single kidney of the same origin. Thus two optimal kidneys are located in different environments: a healthy subject and a patient with chronic kidney disease. During follow-up, several factors may affect renal function in donors and recipients. Some pertain to the recipient, i.e. allograft rejection, infections, nephrotoxicity, and recurrent or de novo kidney disease. Others are common to donors and recipients, including smoking and metabolic syndrome factors, i.e. hypertension, hyperglycemia, dyslipidemia, and obesity [4–7]. Thus living donation could be considered a clinical model to study the adaptive capacity of two comparable kidneys placed in different environments as well as the impact of risk factors for renal dysfunction in subjects with reduced renal mass.

Obesity is a risk factor for renal disease [8]. However, not all obese individuals are at risk: patients with obesity and metabolic syndrome may be those with the highest risk for chronic kidney disease (CKD) [9]. Also, reduced renal mass may play a role in obesity-related renal disease [10]. Obesity is a major cause of proteinuria and renal function loss after nephrectomy [11]. In renal transplantation, indirect markers of nephron mass, such as gender and body surface area (BSA) mismatch between donors and recipients, could negatively affect graft function in the long term [12–14]. Previous studies have indicated that females may in general have a lower renal mass and renal function compared with men [12]. Thus transplantation from a female donor to a male recipient has been considered by some researchers a factor with a possible negative impact on graft function in the long term. However, how the impact of renal endowment and gender mismatch in GFR changes over time in donors and recipients has not been completely elucidated.

In this study, we evaluated the factors that influenced renal function changes in 30 pairs of living donors and recipients during the first 12 months after transplantation. GFR changes were analyzed in donors and their recipients to evaluate how both kidneys adapted to diverse environments and their changes over time.

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MATERIAL AND METHODS

1. Patients and design

In this observational prospective study, we analyzed the evolution of renal function in 30 donor-recipient pairs during the first year after transplantation. GFR was measured by the plasma clearance of iohexol before transplantation in donors and 12 months after transplantation in donors and recipients.

Inclusion criteria were the following: ≥18 years of age, donor-recipient pairs studied for living kidney donation at the Nephrology Department of the Hospital Universitario de Canarias (HUC), and 12 months of follow-up after donation. Exclusion criteria were a psychiatric disease that limits compliance with the protocol, inability to understand the protocol, paired-organ donation, allergy to iodine or contrast media, and pregnancy or lactation. The protocol was approved by the Ethics Committee of the Hospital Universitario de Canarias (Tenerife, Spain).

2. Demographic and clinical characteristics

Before transplantation, we collected data on age, gender, weight, height, body mass index (BMI), BSA, and laboratory analysis of donors and recipients. In particular, for donors, we collected information on arterial hypertension, dyslipidemia, medications, smoking status, and normal glucose metabolism based on glucose oral tolerance tests. Renal function was evaluated by measured and estimated GFR (mGFR, eGFR), serum creatinine, 24-h creatinine clearance, and albuminuria. Total kidney volume was calculated as the sum of the right and left kidney volumes by a high-resolution CT scan using Vitrea software (Vitrea, General Electric, Milwaukee, WI, USA). Data on recipients included the cause of renal disease, renal replacement therapy or a preemptive transplant, human leukocyte antigen (HLA) compatibility, concomitant diseases (i.e. hypertension, dyslipidemia, and diabetes), and cardiovascular events.

For donors, after transplantation, we collected early surgical complications, acute kidney injury (AKI), weight changes and hypertension (de novo or previous), dyslipidemia, hyperglycemia, and the use of medications. For recipients, we analyzed early surgical complications, acute rejection, obstructive uropathy, delayed graft function, BK virus nephropathy, levels of immunosuppressants, anticalcineurin toxicity, AKI, weight changes, hypertension, dyslipidemia and post-transplant diabetes mellitus (PTDM).

All data were stored in an online database designed ad hoc for the study using the web application provided by the RedCap Consortium. Based on the Spanish law for data protection, all data were anonymized and the identification of patients was stored and was not accessible from the Internet.

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3. Measured GFR with the plasma clearance of iohexol using dried blood spots

The procedure has been described elsewhere [15, 16]. In brief, 5 mL of iohexol solution (Omnipaque 300, GE Healthcare, Chicago, IL, USA) is injected intravenously in a forearm vein over 2 min. Then, 120 min after the injection, capillary blood (10 μL) is taken by finger prick, collected by a capillary pipette, and deposited on filter paper at 120, 150, 180, 210, and 240 min [15, 16]. If the subject has GFR values <40 mL/min, samples are taken at 120, 180, 240, 300, 360, and 420 min. Iohexol was measured in dried blood spots as previously described [15, 16] and iohexol clearance (mL/min) was calculated according to a one-compartment model and then corrected following BröchnerMortensen [17].

The plasma clearance of iohexol was performed in clinically stable patients, which means in the absence of acute episodes that may influence renal function, such as severe infectious disease, acute cardiovascular disease, AKI, or other acute intercurrent conditions. GFR was unadjusted to analyze the impact of weight changes on GFR without interference with the adjustment for BSA. The cut-off for donation in our center is 80 mL/min for donors >30 years of age and 90 mL/min for those younger [7, 18, 19]. All living donors in the HUC are selected based on mGFR and not eGFR.

4. Statistical analysis

This is an exploratory analysis. We aimed to analyze renal function changes in donors and recipients before and after transplantation. Each pair was evaluated individually and then grouped according to the evolution of mGFR. We foresaw a priori three different evolutions of renal function at 12 months in donors and their recipients: (Group A) mGFR higher in donors than recipients, (Group B) mGFR lower in donors than recipients, and (Group C) mGFR comparable between donors and recipients. The cut-off for defining a GFR higher or lower in a donor compared with its recipient was 10 mL/min, which is three times the reproducibility of mGFR in our laboratory (3%).

Univariable and multivariable regression analysis was used to test the impact of factors on GFR changes during the first 12 months after donation/transplantation and diverse linear regression models were developed in donors and recipients. The outcome was the GFR at 12 months. Covariates included age, gender, weight, BMI, and BSA at baseline and at 12 months, male donors who donated to female recipients, and female donors who donated to male recipients.

To evaluate the impact of renal endowment on renal function after donation, in a sensitivity analysis we evaluated the following groups: males who donated to females, females who donated to males, donors with a greater BSA than their recipients, and donors with a lesser BSA than their recipients.

To evaluate the impact of renal endowment on renal function after donation, in a sensitivity analysis we evaluated the following groups: males who donated to females, females who donated to males, donors with a greater BSA than their recipients, and donors with a lesser BSA than their recipients.

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DISCUSSION

We evaluated factors that may influence renal function after donation/transplantation and found that a higher GFR at 12 months in both donors and recipients was associated with a higher pretransplant weight. Also, in recipients, changes in weight during follow-up were associated with higher renal function at 12 months. Finally, BSA and gender mismatch between donors and recipients influenced GFR evolution in both groups.

We investigated the impact of metabolic factors in GFR changes in pairs of donors and recipients, considering them a clinical model of reduced renal mass. To avoid the error of eGFR by formulas, we measured GFR with the plasma clearance of iohexol. Also, renal function was not adjusted by BSA since it artificially reduces GFR in obese subjects and increases GFR in lean subjects [20]. Finally, GFR changes were compared in each donor and the corresponding recipient.

We observed that at 12 months after transplantation, recipients could have higher, lower, or similar GFR values than their donors and tried to evaluate the factors related to these changes. A GFR higher in recipients than in their donors seems counterintuitive (Group B). A lower GFR in donors could not be attributed to borderline GFR predation, reduced renal volume, or adverse events that could have affected renal function after donation. All donors had excellent levels of renal function evaluated with a gold standard procedure (98 ± 13 mL/min; Group B: Table 2) and the average decrease in GFR after donation was about 25–30%, which is in line with the change reported in the literature [21, 22]. However, the main characteristics of this group of donors were reduced weight and BSA compared with their recipients and the lack of weight increase after donation. Also, recipients were mostly males (90%), with greater weight and BSA pre-donation, and importantly, experienced a further increase in weight after transplantation. This finding was confirmed in a multivariable analysis showing that in recipients, a higher GFR at 12 months was associated with male gender, greater weight, and BSA at pretransplant. Finally, in the subanalysis of recipients larger than their donors (BSA mismatch) or those males who received a kidney from a female donor (gender mismatch), recipients had a higher GFR at 12 months. Thus, in this group, the grafts were exposed to different factors that can increase GFR. First, kidneys were implanted in patients with a larger metabolic demand (high body weight and BSA). Second, recipients experienced a major increase in weight and 50% of them developed PTDM, two factors related to glomerular hyperfiltration during follow-up.

In contrast, some recipients had lower GFR than their donors (Group A). This could not be explained by adverse events in recipients or donors. Three recipients in this group had episodes of acute rejection, calcineurin toxicity, and AKI. However, the differences in GFR compared with the donors persisted after the exclusion of these patients. In contrast, in this group, recipients were mainly females with lower weight and BSA than their donors and without relevant weight change after transplantation. Moreover, donors were mainly males, had the highest weight and BSA than the other groups, and had higher GFR and renal volume than subjects in Group C. In the multivariable analysis in donors, a higher GFR at 12 months was associated with male gender and greater weight and BSA at pretransplant. This finding was supported by the subanalysis of donors larger than their recipients (BSA mismatch) or males who donated a kidney to a female (gender mismatch). Thus, opposite to the previous groups, the grafts were not exposed to a larger metabolic demand or a major increase in weight during follow-up. The lack of these stimuli may have determined the lower GFR in recipients at 12 months compared with their donors.

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In a wide range of mammals, including humans, there is a direct relationship between body size and metabolic rate [23]. From a physiological perspective, the kidney contributes to the excretion of metabolic waste products, so the increased metabolic demand of a large body will induce an increase in GFR. It is known from renal physiology that metabolic demand sets GFR [23]. It may be plausible that the kidneys of small donors grafted in large recipients adapted to the higher metabolic demands by increasing GFR. This adaptive capacity may depend on the renal endowment, renal reserve, and baseline GFR. The renal reserve was not measured in our study, but we might assume that renal endowment was acceptable, as reflected by the excellent level of GFR before donation. The renal reserve may indicate a better capacity to adapt to a major reduction of nephron mass, i.e. nephrectomy. However, some studies have indicated that renal reserve has no or minimal impact on renal function in the long term [24]. In any case, the scarce studies in the field preclude a definitive conclusion. Interestingly, donors in Group C showed lower total kidney volume and GFR than donors in Group A, which may reflect a lower renal endowment even in subjects with excellent GFR. However, these kidneys adapted well to the change in weight of their recipients, as reflected in a comparable mGFR at 12 months between both groups. On the other hand, kidneys from large donors transplanted into small recipients may have downregulated GFR to the lower metabolic demands of a smaller body size. This could also be considered an adaptive capacity of the graft. The relevance of metabolic demand in living kidney donors deserves attention in future studies.

Adaptation to metabolic demand is not the only factor that can influence renal function in donors and recipients. Obesity is associated with metabolic changes like hyperglycemia, diabetes, dyslipidemia, hyperinsulinemia, insulin resistance, and increased levels of angiotensin-converting enzyme and aldosterone [25–28]. In the kidney, these factors promote changes that may increase GFR, i.e. proximal sodium reabsorption, changes in the macula densa, resetting of tubularglomerular feedback, imbalance of the afferent and efferent arterioles, and others. All of the above may explain, at least in part, the increase in GFR in recipients who gained weight and developed PTDM after transplantation, as in the case of recipients in Group B. This may be considered a case of relative glomerular hyperfiltration in patients with reduced renal mass. On the other hand, in donors, being overweight may determine the decrease in renal reserve after donation, a fact that may reduce the capacity of single kidneys to adapt to a new environment [29].

In any case, it can be difficult to separate the effect of metabolic demands and obesity in GFR. However, not all the recipients in our study were under the influence of high metabolic demand. Recipients from Group C showed low BMI at transplantation but experienced a large increase in weight on follow-up (from 24 to 28 kg/m2 on average). So in this group, the GFR increase could be attributed only to obesity-induced GFR changes. Taken together, these results seem to indicate that kidneys from living donors with excellent pre-transplant GFR are more plastic than expected, showing the capacity to respond to stimuli like metabolic rate and obesity. The long-term impact of this phenomenon is worth investigating.

Previous studies evaluated the impact of BSA and gender mismatch in living kidney donors and recipients. Tent et al. [12], in an elegant study, analyzed almost 300 donor-recipient pairs at baseline and 88 during follow-up with mGFR before and after transplantation. In line with our study, recipients larger than their donors showed an increase in GFR over time and those smaller than their donors showed a mild decrease in GFR, which may reflect the adaptation of the kidney to metabolic demands. Contrary to our results, the authors categorized pairs into those with greater or lesser BSA between donors and recipients using a BSA ratio >1 or <1. The mGFR was not different among groups. Cases with a ratio around 1, i.e. 1.1 or 0.9, may not represent major differences in BSA, a fact that may have minimized possible differences in mGFR between groups. We preferred to analyze donor-recipient pairs based on the observed GFR at 12 months and to select extreme cases of BSA mismatches. So we individualized a subgroup of donors and recipients in whom a greater effect of BSA and weight changes on GFR is expected. Other studies have evaluated renal function in terms of BSA or gender mismatch among donors and recipients but used eGFR, in general, adjusted by BSA, which precludes comparison of these studies with ours [30].

This study has limitations. First, it is an exploratory analysis with a limited number of cases. However, the results are in line with other publications, which seems to support the validity of our results [12]. In any case, our results must be tested in larger groups. Second, this is a short-term study, so a longer follow-up is needed to analyze the impact of early GFR changes beyond 12 months.

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CONCLUSION

In conclusion, in living kidney donation, kidneys are more plastic than expected and suffer the impact of metabolic demands and weight changes of their new host. The long-term consequences of this finding deserve special attention in ad hoc designed studies. Furthermore, the observed differences should be taken into account when assessing GFR outcomes in this population.

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Ana González Rinne1, Cristian Acosta Sorensen1, Sergio Luis Lima 2, Marta Gómez Gil3, Natalia Negrín Mena4,5, Laura Díaz Martín4,5, Ana Ramírez6, Adelaida Morales7, Nicanor Vega8, Eduardo Gallego9, Edduin Martín Izquierdo10, Elisa Cabello10, Ana Elena Rodríguez Rodríguez 11, Jesús Pimentel González12, Beatriz Escamilla1, Coriolano Cruz4,5, Lourdes Pérez Tamajón1, Armando Torres Ramírez1,13, Flavio Gaspari5, Alberto Ortiz 2,14 and Esteban Porrini4,5,12,13

1 Department of Nephrology, University Hospital of the Canary Islands, Tenerife, Spain,

2 IIS-Fundación Jiménez Diaz, Department of Medicine, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain,

3 Radiology Department, Hospital Universitario de Canarias, Tenerife, Spain,

4 Research Unit Department, Unidad de Investigación Clínica y Ensayos Clínicos, Hospital Universitario de Canarias, Tenerife, Spain,

5 LFR Laboratorio de Función Renal, Universidad de La Laguna, Tenerife, Spain,

6 Nephrology Department, Hospital Universitario Insular, Las Palmas de Gran Canaria, Spain,

7 Nephrology Department, Hospital General de Lanzarote, Arrecife, Spain,

8 Nephrology Department, Hospital Universitario Doctor Negrín, Las Palmas de Gran Canaria, Spain,

9 Nephrology Department, Hospital Universitario Nuestra Señora de Candelaria, Tenerife, Spain,

10 Nephrology Department, Hospital General de La Palma, Santa Cruz de La Palma, Spain,

11 Fundación General de la Universidad de La Laguna, Tenerife, Spain,

12 Faculty of Medicine, University of La Laguna, Tenerife, Spain,

13 Internal Medicine Department, Universidad de La Laguna, ITB Instituto de Tecnologías Biomédicas, Tenerife, Spain

14 Red de Investigación Renal, Instituto Carlos III-FEDER, Madrid, Spain