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To determine whether microstructural features on a kidney biopsy specimen obtained during kidney transplant surgery predict long-term risk of chronic kidney disease in the donor.
Patients and Methods
We studied kidney donors from May 1, 1999, through December 31, 2018, with a follow-up survey for the results of recent blood pressure and kidney function tests (estimated glomerular filtration rate [eGFR] and proteinuria). If not recently available, blood pressure and eGFRs were requested from a local clinic. Microstructural features on kidney biopsy at the time of donation were assessed as predictors of hypertension and kidney function after adjusting for years of follow-up, baseline age, sex, and clinical predictors.
There were 807 donors surveyed a mean 10.5 years after donation. An eGFR less than 45 mL/min/1.73 m2 in 6.4% (43/673) of donors was predicted by larger glomerular volume per standard deviation (odds ratio [OR], 1.48; 95% CI, 1.08 to 2.04) and nephron number below the age-specific 5th percentile (OR, 3.38; 95% CI, 1.31 to 8.72). An eGFR less than 60 mL/min/1.73 m2 in 42.5% (286/673) of donors was not predicted by any microstructural feature. Residual eGFR (postdonation/predonation eGFR) was predicted by nephron number below the age-specific 5th percentile (difference, −6.07%; 95% CI, −10.24% to −1.89%). Self-reported proteinuria in 5.1% (40/786) of donors was predicted by larger glomerular volume (OR, 1.42; 95% CI, 1.08 to 1.86). Incident hypertension in 18.8% (119/633) of donors was not predicted by any microstructural features.
Low nephron number for age and larger glomeruli are important microstructural predictors for long-term risk of chronic kidney disease after living kidney donation.
Living kidney donors undergo an exhaustive evaluation to ensure normal kidney function and exclude risk factors for chronic kidney disease (CKD). Despite careful selection, a small subset of donors has low renal function postdonation,
It also has been reported that specific donor populations, including African Americans, the obese, individuals with hypertension, or donors related to a recipient with end-stage renal disease have higher risk for kidney failure.
There may be subclinical microstructural features in the kidneys of these living donors that contribute toward risk for CKD after donation. The predonation computed tomography (CT) can detect kidney microstructural abnormalities, but there is often uncertainty regarding their clinical importance to donor selection.
A kidney biopsy may detect subclinical pathology but is not routinely available before transplantation. Thus, it is unclear whether the development of CKD in some living kidney donors is only related to events that occur after donation or is due to some extent to pathology already present at the time of donation.
The Aging Kidney Anatomy study has characterized microstructural kidney biopsy features of the living donor kidney at the time of kidney transplantation. Microstructural features can be classified into measures of nephron size, nephron number, or nephrosclerosis and associate with age, kidney function, and CKD risk factors of the donor, as well as with the macrostructure of the kidney.
Long-term follow-up is needed to more fully comprehend the clinical importance of baseline microstructural features in the kidney at the time of donation. Thus, we performed a cohort study from the living donors in the Aging Kidney Anatomy study to determine whether nephron size, nephron number per kidney, or nephrosclerosis at the time of donation predict a long-term risk for developing low GFR, self-reported proteinuria, or hypertension.
Patients and Methods
Study Design and Study Sample
This is a prospective cohort study of living kidney donors (aged ≥18 years) at the Mayo Clinic sites in Minnesota and Arizona from May 1, 1999, through December 31, 2018, in the Aging Kidney Anatomy Study.
Our inclusion criteria required a time-zero biopsy during the transplant surgery with 2 or more mm2 of nondistorted cortex with at least 4 glomeruli. To study long-term kidney function outcomes, we targeted donors with 5 or more years of follow-up for participation. The Mayo Clinic Survey Research Center contacted these donors using mailed surveys and follow-up telephone calls from April 1, 2017, to December 31, 2018, using Accurint (www.accurint.com, LexisNexis Risk Solutions) to find contact information. Donors were allowed to complete the survey by mail or telephone interview. Donors were asked to provide recent (within past 2 years) blood pressure readings, height, weight, and serum creatinine levels along with the dates of testing. Those lacking a recent blood pressure, height, weight, or serum creatinine value were offered remuneration to obtain these tests from a local provider. This study was completed under institutional review board approval with a signed consent form completed by each participant.
All kidney donors underwent a thorough medical evaluation before donation that included a prescheduled series of tests as previously described.
urinary iothalamate clearance to measure GFR, 24-hour urine albumin quantification, body mass index (BMI; calculated as the weight in kilograms divided by the height in meters squared), office blood pressure readings, and CT of the kidneys performed at the time of donor evaluation.
Acceptance criteria for donation varied by site and era, but in general included 24-hour urine albumin excretion less than 30 mg and a measured GFR normal for age. Mild hypertension in older donors and moderate obesity (BMI of 30-35 kg/m2; occasionally up to 40 kg/m2 in older donors) were allowed. Hypertension was defined as a preexisting diagnosis of hypertension, an office systolic blood pressure (SBP) of 140 mm Hg or greater or diastolic blood pressure (DBP) of 90 mm Hg or greater or use of antihypertensive medication(s) to treat hypertension. Acceptable predonation “mild” hypertension was defined by either 140 to 159/90 to 99 mm Hg or controlled with 1 antihypertensive medication (with or without a thiazide diuretic). Potential donors with more severe hypertension or with evidence of target organ damage were excluded from donation. Patients with diabetes mellitus or cardiovascular disease were not acceptable candidates. Related donors were defined by being a blood relative of the kidney recipient. Tobacco smoking status was identified from the medical records at the time of donor evaluation.
Microstructural Features on Biopsy
As part of routine clinical care, an intraoperative needle core biopsy of the renal cortex was performed at the time of transplantation. The tissue specimen was fixed in formalin and embedded in paraffin. Two sections (2- to 3-μm thickness) from the biopsy core were stained, 1 with periodic acid–Schiff and 1 with Masson trichrome, and were subsequently scanned into high-resolution digital images (Aperio XT digital scanner; Leica Biosystems). Nephron size on biopsy was characterized by mean nonsclerotic glomerular volume, cortex volume per glomerulus (reciprocal of nonsclerotic glomerular volumetric density), and mean cross-sectional tubular area as previously described (Supplemental Figures 1 and 2, available online at http://www.mayoclinicproceedings.org).
Nephrosclerosis on biopsy was characterized by the percentage of glomeruli that were globally sclerosed, the percentage of interstitial fibrosis/tubular atrophy (IF/TA) of the cortex area, the number of distinct IF/TA foci, and the severity of arteriosclerosis.
The severity of arteriosclerosis was determined by the percentage of luminal stenosis due to intimal thickening in the small-medium artery (if any present) most orthogonal to its axis (Supplemental Figure 3, available online at http://www.mayoclinicproceedings.org). These were perfromed by personnel unaware of the donors' characteristics and outcomes. Detection of arteriolar hyalinosis required review of all 12 biopsy section slides by a pathologist (data available for only Mayo Clinic in Minnesota). The Supplemental Methods (available online at http://www.mayoclinicproceedings.org) provide further details on measuring and calculating microstructural features from kidney biopsy images.
Images from predonation CT from the angiogram/cortical phase were downloaded onto a workstation for processing. Kidney cortical volumes were segmented using a semiautomated algorithm (ITK-SNAP software, version 2.2; University of Pennsylvania; Supplemental Figure 4, available online at http://www.mayoclinicproceedings.org).
Residual eGFR was calculated by follow-up eGFR divided by the predonation eGFR × 100%. We assessed for a follow-up eGFR less than 45 mL/min/1.73 m2 as an outcome in addition to eGFR less than 60 mL/min/1.73 m2; this lower threshold is considered a more clinically significant definition of CKD after a nephrectomy.
To assess the validity of self-reported serum creatinine level, we correlated the self-reported serum creatinine level to the temporally closest available electronic serum creatinine level in the local donor subset with laboratory testing (within the Mayo Clinic Health System).
Hypertension after donation was identified by a diagnosis by a health care provider, SBP of 140 mm Hg or greater, DBP of 90 mm Hg or greater, or use of antihypertensive medication(s) to treat hypertension. We were concerned that requiring a prospective standardized assessment of proteinuria among all participants would decrease participation. Instead, proteinuria was determined by a survey question “Has a care provider informed you about abnormal protein in your urine?”
Nephron size measures were analyzed as continuous variables. Each microstructural feature was evaluated for its association with each outcome. With a single follow-up survey, a time-to-event analysis was not feasible. Instead, linear regression was used for predicting residual eGFR and logistic regression for predicting eGFR less than 45 or less than 60 mL/min/1.73 m2, self-reported proteinuria, and hypertension at follow-up. The risk for hypertension was only assessed in donors who did not have baseline hypertension. Multivariate imputation by chained equations was used to impute missing covariate values (Supplemental Table 3, available online at http://www.mayoclinicproceedings.org).
Models were unadjusted, then adjusted for age, sex, and follow-up time, or further adjusted for clinical characteristics that also predicted the outcome. Statistical analyses were performed using R (RStudio), version 3.4.2.
There were 807 living kidney donors studied (Figure), of whom 673 had a follow-up serum creatinine level. The survey was completed a mean of 10.5 years postdonation. Baseline clinical and biopsy characteristics of the cohort are shown in Table 1. The donors who responded to the survey were more likely to be older, women, nonsmokers, and unrelated to the recipient and have lower eGFRs and more nephrosclerosis on biopsy than nonresponders (Supplemental Table 4, available online at http://www.mayoclinicproceedings.org). None of the donors reported renal replacement therapy during the follow-up period.
Table 1Baseline Characteristics of the 807 Donors Studied
After excluding donors with baseline hypertension, 18.8% (n=119 of 633) developed hypertension during follow-up. Mean SBP of those who did vs did not develop hypertension was 130 vs 117 mm Hg (P<.001). Clinical predictors of developing hypertension were longer time since donation, male sex, higher baseline BMI, and higher baseline blood pressure (Table 2). Biopsy measures of larger nephron size predicted hypertension but not after adjusting for BMI and baseline blood pressure. Nephron number and nephrosclerosis did not predict hypertension before or after adjusting for clinical characteristics (Table 2).
Table 2Predictors of Incident Hypertension That Occurred in 119 of 633 Donors (18.8%) Without Baseline Hypertension
There was good correlation (r=0.85; 95% CI, 0.77 to 0.90) and no bias (0.01 mg/dL; P=.65) between the serum creatinine level obtained from the survey and that in the medical record among the subset of 82 donors with local care (Supplemental Figure 5, available online at http://www.mayoclinicproceedings.org). Donors who reported a follow-up serum creatinine level on survey (n=673) were more likely to be older, be women, and have a lower baseline eGFR compared with those who did not report a follow-up serum creatinine level (n=134; Supplemental Table 5, available online at http://www.mayoclinicproceedings.org).
There were 43 of 673 (6.4%) donors who developed eGFRs less than 45 mL/min/1.73 m2. Clinical predictors of eGFR less than 45 mL/min/1.73 m2 were older age, hypertension, and lower baseline eGFR (Table 3). In unadjusted analysis, larger glomerular volume, larger cortex per glomerulus, and low nephron number for age predicted a postdonation eGFR less than 45 mL/min/1.73 m2. After adjusting for clinical predictors, only larger glomerular volume and low nephron number for age predicted an eGFR less than 45 mL/min/1.73 m2.
Table 3Predictors of eGFR Less Than 45 mL/min/1.73 m2 That Occurred in 43 of 673 Donors (6.4%) With Follow-up Serum Creatinine Levels
There were 286 of 673 (42.5%) donors who developed eGFRs less than 60 mL/min/1.73 m2. Clinical predictors of an eGFR less than 60 mL/min/1.73 m2 were less time since donation, older age, nonsmoker, hypertension, higher blood pressure, and lower baseline eGFR (Table 4). In unadjusted analysis, IF/TA foci higher than expected for age predicted eGFR less than 60 mL/min/1.73 m2. After adjusting for clinical predictors, no microstructural feature predicted eGFR less than 60 mL/min/1.73 m2.
Table 4Predictors of eGFR Less Than 60 mL/min/1.73 m2 That Occurred in 286 of 673 Donors (42.5%) with Follow-up Serum Creatinine Levels
The mean residual eGFR was 74.8%. Clinical predictors of a lower residual eGFR were shorter follow-up time and baseline older age, nonsmoker, and higher eGFR (consistent with regression to the mean; Table 5). In unadjusted analysis, microstructural predictors of lower residual eGFR were not evident, but after adjusting for clinical predictors, low nephron number for age predicted a lower residual eGFR (Table 5).
Table 5Predictors of Residual eGFR (postdonation eGFR/predonation eGFR × 100%) Among 673 Donors With Follow-up Serum Creatinine Levels
Of the surveyed donors, 40 of 786 (5.1%) reported being diagnosed with abnormal proteinuria during follow-up. Clinical predictors of abnormal self-reported proteinuria were younger age, male sex, predonation hypertension, and higher DBP (Table 6). Larger glomerular volume predicted self-reported proteinuria, and this association remained evident after adjusting for all clinical characteristics. Low nephron number and nephrosclerosis did not predict proteinuria before or after adjusting for clinical characteristics (Table 6).
Table 6Predictors of Self-reported Proteinuria That Occurred in 40 of 786 (5.1%) Donors
Clinical factors such as GFR, obesity, and blood pressure are carefully considered when evaluating the long-term risks with kidney donation. Despite this, subclinical microstructural features in the donated kidney at the time of transplantation are still predictive of developing CKD a decade after donation. Specifically, larger glomerular volume predicts an increased risk for eGFR less than 45 mL/min/1.73 m2 or self-reported proteinuria and low nephron number predicts an increased risk for eGFR less than 45 mL/min/1.73 m2 or lower residual eGFR (ie, a larger decline in eGFR). These risks are small and would probably not justify performing kidney biopsies before donation. However, they provide insights into the microstructural features in the kidney that are important to long-term kidney health among relatively healthy individuals.
Whether living kidney donation causes hypertension has been debated.
However, in this current study, arteriosclerosis did not predict new-onset hypertension at a mean of 10.5 years after donation. This suggests that with the passage of time, other factors predominately determine the risk for hypertension after donation. Interestingly, although age did not predict hypertension, longer time since donation predicted hypertension. This may be related to the selection for good health at the time of donation for both younger and older donors. As others have found,
We found that several measures of larger nephron size predicted hypertension but not in models that further adjusted for BMI. This may be consistent with larger nephron size being part of the pathway by which obesity contributes to risk for hypertension.
Long after kidney donation, eGFR continues to increase in most donors,
we found larger glomeruli to predict a long-term risk for low eGFR (<45 mL/min/1.73 m2) after donation. A plausible explanation for this is that with further hyperfiltration after uninephrectomy, enlarged glomeruli may be more prone to collapse and sclerosis, leading to lower eGFR. Alternatively, the development of lower eGFR with larger glomeruli may have occurred even without the nephrectomy. Importantly, this risk for eGFR less than 45 mL/min/1.73 m2 with larger glomeruli persisted even after adjusting for baseline clinical characteristics, including hypertension. A high proportion of donors had eGFRs less than 60 mL/min/1.73 m2 at follow-up that was not predicted by any microstructural feature. An eGFR of 45 to 59 mL/min/1.73 m2 may just be the direct effect of a nephrectomy rather than a kidney disease per se.
Low nephron number for age also associates with lower residual eGFR and low eGFR at follow-up. This was evident even after adjusting for baseline eGFR and other clinical predictors. In this healthy population, nephron number is reflective of nephron endowment and nephron loss from nephrosclerosis (global glomerulosclerosis in particular). Because nephrosclerosis measures did not predict lower residual eGFR or low eGFR, low nephron endowment may be the primary contributor to this risk for lower residual eGFR or low eGFR. Birth weight correlates with nephron endowment
This study found that IF/TA was a predictor of eGFR decline during follow-up. Consistent with this prior study, we found that IF/TA greater than the 95th percentile for age trended in the same direction as in the prior study but was not statistically significant (P=.11).
There were potential limitations to this study, including reliance on a survey for outcomes. Previous studies have shown that with regard to hypertension, the concordance between a survey-reported diagnosis and a confirmed diagnosis of hypertension is high.
It is also reassuring that serum creatinine values on medical record review were well correlated with those on the surveys in the local subset. Another limitation in our study was the reliance on self-reporting for being diagnosed with abnormal proteinuria. There may have been underdetection of proteinuria due to lack of testing or lack of awareness of the proteinuria result even if testing was done. However, because donors and providers were unaware of the microstructural findings on the biopsy (pathology report did not include morphometry and was in the recipient’s medical record), a differential bias with respect to glomerular volume and risk for self-reported proteinuria is unlikely. There were some baseline differences in characteristics between those who responded to the survey vs nonresponders and between those who reported a follow-up serum creatinine level and those who did not. A larger sample size with more events is needed adjust for more covariates in the models. The donors studied were predominately White, and further work is needed to determine whether prediction of outcomes by kidney microstructural characteristics differs by race.
In summary, lower nephron number and larger glomerular volume were long-term predictors of CKD in kidney donors after donation, independent of other clinical predictors. Whether the donor nephrectomy itself contributes to this finding is unclear. Nephron number and glomerular volume are not typically reported by pathologists on biopsy reports. Further studies are needed to determine how these subclinical microstructural kidney features increase the long-term susceptibility for CKD in otherwise healthy adults. Ideally, less invasive biomarkers are needed to detect these microstructural features to make their evaluation feasible in more clinical settings.
Grant Support: This study was supported with funding from the National Institutes of Health (NIH), National Institute of Diabetes and Digestive and Kidney Diseases ( R01 DK090358 ). This study was supported by NIH T32 training grant 5T32DK007013. This publication was made possible by Clinical and Translational Science Awards grant number UL1 TR002377 from the National Center for Advancing Translational Sciences , a component of the NIH. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIH.
Potential Competing Interests: The authors declare no competing interests.