Citations

Background: Hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), and preterm delivery are associated with higher long-term cardiovascular, metabolic, and kidney disease risk. Their implications for living kidney donation remain uncertain. Methods: We conducted a retrospective cohort study of 498 female living kidney donors (2000–2017) from the Mayo Clinic Living Donor Program with documented pregnancy histories, pre-donation CT angiography, implantation kidney biopsy, and measured GFR. Donors with prior HDP (n=45), GDM (n=18), or preterm delivery (n=65) were compared with donors without adverse pregnancy outcomes (APO; n=385). Kidney morphometry, histology, and function were analyzed with adjustment for age at donation and first pregnancy, parity, and hypertension. Post-donation kidney outcomes were assessed using surveys and medical record review. Results: Donors with prior HDP and GDM had higher BMI at donation (+7.9% and +8.9%; p=0.006 and 0.04), whereas donors with preterm delivery had lower BMI (−4.8%; p=0.03) compared with donors with no APO. After adjustment, donors with HDP showed no differences in kidney volumes, biopsy features, or kidney function at donation or during follow-up. Donors with GDM had larger total and cortical kidney volumes (9.5–10%), less arterial luminal stenosis, and higher 5-year post-donation eGFR (+15%; p=0.03). Donors with preterm delivery had a lower risk of eGFR <45 mL/min/1.73 m 2 (HR 0.28; p=0.03). Conclusions: Prior adverse pregnancy outcomes were not associated with adverse kidney structure at donation or accelerated kidney function decline post-donation. These findings support that APO history alone should not preclude living kidney donation when other eligibility criteria are met.

Obesity is increasingly prevalent among living kidney donor candidates, presenting complex clinical, ethical, and logistical challenges. Although obesity is linked to increased post-donation hypertension, diabetes, proteinuria, and chronic kidney disease, the overall absolute risks are modest and may differ depending on metabolic health and patterns of fat distribution. Current reliance on body mass index alone fails to capture the full spectrum of obesity-related risks, leading to inconsistent donor selection practices and potential inequities. This review examines the pathophysiological mechanisms of obesity-related kidney injury and available evidence on comorbidities and postdonation outcomes related to obesity. We discuss tools for better risk stratification, such as imaging-based adiposity assessment and personalized weight management strategies, and note that some risks may remain after weight loss. Barriers such as rigid body mass index cutoffs, limited access to treatment, and lack of long-term follow-up exacerbate disparities in access to donation. We argue for a shift toward individualized, risk-based evaluation supported by multidisciplinary care. We underscore the importance of donor counseling and advocate for a comprehensive, rather than paternalistic approach to living kidney donor selection. Advancing safe and equitable living donation in the context of rising obesity rates will necessitate revised guidelines, improved access to treatment, and an ongoing commitment to donor well-being.

Key Points Increased protein expression of tissue inhibitor of metalloproteinase-3, glypican 6, synuclein γ , apolipoprotein A-4, and Ecto-5′-nucleotidase was observed in old adults compared with young adults. In old adults, overexpressed proteins were enriched in mitochondrial processes while under expressed proteins enriched in RNA metabolism. Validated differentially expressed proteins were not significantly correlated with kidney pathology after adjusting for age. Background Kidney aging is characterized by a loss of glomeruli, predominantly in the superficial cortex, with a resultant decline in GFR and an increased risk of various kidney-related diseases. The early molecular alterations in glomeruli associated with the aging process are not well studied. Methods We combined laser capture microdissection and mass spectrometry–based unbiased proteomic analysis of nonsclerosed, nonischemic glomeruli in the superficial cortex from young and old adults who underwent a radical nephrectomy for a tumor to understand the age-related molecular changes in glomeruli. Twenty-four young and 30 old adults were used for the discovery dataset, and the significant differentially expressed proteins were further validated using an independent set comprising six young and eight old adults. Results Kidneys from old adults had lower eGFR, less kidney parenchyma on computed tomography imaging, and more glomerulosclerosis and arteriosclerosis on histology. Quantitative proteomic analysis of nonsclerosed, nonischemic glomeruli identified increased expression of tissue inhibitor of metalloproteinase-3, glypican 6, synuclein γ , apolipoprotein A-4, and Ecto-5′-nucleotidase in old adults that were further validated in an independent set. Pathway analysis indicated that proteins with increased expression in old adults were enriched in mitochondrial translational processes, aerobic respiration, and TCA cycle, whereas proteins with decreased expression in old adults were enriched in mRNA splicing, mRNA processing, and nonsense mediated decay. Furthermore, validated differentially expressed proteins did not show any significant correlation with the kidney pathology independent of age group. Conclusions Overall, this study identified proteins that are specifically associated with the aging process in otherwise normal-appearing glomeruli.

Key Points Automated cyst segmentation in autosomal dominant polycystic kidney disease could transform care by enabling precise monitoring of cyst progression with minimal manual effort. This technology can facilitate more consistent assessments of cyst burden across patients. Translating these segmentation models from magnetic resonance imaging to computed tomography is crucial for providing comprehensive, modality-independent evaluations. Background Total kidney and liver volumes are key image-based biomarkers to predict the severity of kidney and liver phenotype in autosomal dominant polycystic kidney disease (ADPKD). However, magnetic resonance (MR) imaging-based advanced biomarkers like total cyst number and cyst parenchyma surface area have been shown to more accurately assess cyst burden and improve the prediction of disease progression. The main aim of this study was to extend the calculation of advanced biomarkers to other imaging modalities; thus, we propose a fully automated model to segment kidney and liver cysts in computed tomography (CT) images. Methods Abdominal CTs of patients with ADPKD were gathered retrospectively between 2001 and 2018. A three-dimensional deep learning method using the nnU-Net architecture was trained to learn cyst edges-cores and the noncystic kidney/liver parenchyma. Separate segmentation models were trained for kidney cysts in contrast-enhanced CTs and liver cysts in noncontrast CTs using an active learning approach. Two experienced research fellows manually generated the reference standard segmentation, which were reviewed by an expert radiologist for accuracy. Results Two-hundred CT scans from 148 patients (mean age, 51.2±14.1 years; 48% male) were used for model training (80%) and testing (20%). In the test set, both models showed good agreement with the reference standard segmentations, similar to the agreement between two independent human readers (model versus reader: TCN kidney/liver r =0.96/0.97 and CPSA kidney r =0.98, inter-reader: TCN kidney/liver r =0.96/0.98 and CPSA kidney r =0.99). Conclusions Our study demonstrates that automated models can segment kidney and liver cysts accurately in CT scans of patients with ADPKD.

Artificial neural networks are now used across many fields, from medicine to chatbots. However, they are often complicated and give “black-box” predictions. To better understand these models, we outline some of the terminology, provide example applications in solid organ transplantation, and offer recommendations for those interested in starting to use such models. Examples and definitions are sourced from PubMed searches as well as a review of several applied texts in machine and deep learning. Neural networks have been applied in transplantation since the 1990s, but more recent applications involve their use to process nontabular data, such as images and text. Although interpretations of model results should take context into account, the power of these models holds great potential for the future in transplantation.

ABSTRACT Background Morphology and morphometric evaluation of lesions beyond conventional parameters can inform the pathophysiology of chronic kidney disease (CKD). We sought to determine whether the occurrence of glomerulotubular neck stenoses associates with progressive CKD. Methods We evaluated the normal parenchyma from radical nephrectomies removed for tumor between 2000 and 2021 and analyzed cortex for stenoses of the glomerulotubular neck. Stenosis of the glomerulotubular neck is defined a focal narrowing for which the draining tubule has a greater diameter than at the neck. Progressive CKD was defined as dialysis, kidney transplantation, sustained estimated glomerular filtration rate (eGFR) &lt;10 mL/min/1.73 m2 or sustained 40% decline from the post-nephrectomy eGFR. Each case of progressive CKD was age- and sex-matched to two controls without progressive CKD. Logistic regression models assessed the risk of progressive CKD with stenotic necks adjusting for other histological features, kidney function and CKD risk factors. Results There were 65 cases with a mean of 255 glomeruli and 130 controls with a mean of 329 glomeruli. Among both cases and controls, 5% of glomeruli showed visible glomerulotubular necks. The proportion of necks that were stenotic was higher in cases than controls (35% vs 11%, P &lt; .0001). Stenotic necks associated with progressive CKD independent of other histologic and clinical characteristics. Conclusion Glomerulotubular neck stenosis is associated with development of progressive CKD.

Key Points Morphometry allows for a more prognostic multidimensional quantification of interstitial fibrosis and tubular atrophy (IFTA) in kidneys than does visual inspection. The density of IFTA foci is determined by dividing the number of contiguous IFTA patches in the kidney cortex by the area of cortex. Higher density of IFTA foci significantly predicted renal allograft failure beyond %IFTA and other biopsy and clinical characteristics. Background Contraction of interstitial fibrosis and tubular atrophy (IFTA) may cause %IFTA to under-represent the severity of nephron loss. Higher density of IFTA foci is an important predictor of progressive CKD in native kidneys independent of %IFTA. Methods We studied kidney transplant recipients transplanted between 2000 and 2013 who had a 5-year surveillance kidney biopsy and subsequent follow-up. Banff ci score (interstitial fibrosis) was obtained from the pathology reports. After digitizing the biopsies, we traced cortex area and each distinct IFTA focus on a single trichrome-stained section. Percent IFTA area and IFTA foci density (count of IFTA foci/cortex area) were calculated. Cox models assessed the risk of death-censored graft failure after the 5-year biopsy with Banff ci score, morphometric %IFTA, and IFTA foci density. Results There were 58 death-censored allograft failures among 835 kidney recipients during the 5 years of follow-up. Biopsies from grafts that failed had higher mean Banff ci score (1.5 versus 0.7, P < 0.0001), %IFTA (22.6% versus 7.0%, P < 0.0001), and IFTA foci density (1.3/mm 2 versus 0.4/mm 2 , P < 0.0001). After adjusting for other Banff scores or clinical variables, Banff ci did not correlate with allograft failure, but both higher %IFTA (hazard ratio = 1.56, P < 0.0001) and higher IFTA foci density (hazard ratio = 2.34, P < 0.0001) did. All but four allograft failures by 10 years had biopsies in the top quartile of either %IFTA or IFTA foci density at 5 years. A model using just these two morphometric measures without clinical characteristics resulted in a c-statistic of 0.891 with respect to allograft failure. Conclusions Morphometric characterization of IFTA foci density is a strong predictor of death-censored allograft failure not captured in current Banff classification for grading of kidney fibrosis.

Background. Mesangial expansion (ME) is an understudied histologic lesion in renal allografts. The current Banff mm score is not reproducible and may miss important ME features. The study aimed to improve the quantification of ME using morphometry, assess changes over time, and determine its association with allograft loss. Methods. We studied ME in 1-y and 5-y surveillance biopsies in 835 kidney transplants performed between January 2000 and December 2013. ME was assessed using the Banff mm score by a central pathologist and by morphometry. We derived 3 different morphometric measures: (1) %ME mm (%glomeruli with ME in ≥2 lobules, like Banff mm); (2) %MEany (%glomeruli with any ME lesion); and (3) %ME area (sum of all ME areas/all glomerular tuft areas). Unadjusted and adjusted Cox models assessed the risk of death-censored allograft loss. Results. From 1- to 5-y biopsies, the mean Banff mm score increased from 0.18 to 0.34, whereas %ME mm increased from 2.5% to 13.3%. Banff mm score had modest correlations with morphometric ME measures. Moderate-severe %ME mm was present in 20.1% of 5-y biopsies, whereas only 6.6% of Banff mm scores were. In general, higher ME on both 1- and 5-y biopsies was associated with a deceased donor, older recipient age, recipient diabetes/obesity (present in >50% of severely affected biopsies), higher hemoglobin A1c at 5 y posttransplant, and recurrent kidney disease. Higher ME on 5-y biopsies was associated with delayed graft function. A higher Banff mm score at 1-y biopsy and morphometry ME measures at 5-y biopsy were associated with rejection during the first year posttransplant. Morphometric ME measures were associated with allograft loss independent of Banff scores and all clinical characteristics, including kidney function and recurrent disease. The model with %MEany had the highest c-statistic (0.872). Conclusions. Banff mm score underestimates the pervasiveness of ME in 5-y biopsies. ME is common and associated with alloimmune and nonalloimmune causes of graft loss.