Chebib, Fouad T.

Background: Total kidney volume (TKV), a prognostic biomarker in ADPKD, is used to stratify high risk individuals. eGFR measures may carry significant error in ADPKD compared to measured GFR(mGFR). This retrospective study investigates the association between height adjusted TKV (htTKV) and eGFR derived from race-free CKD-EPI equations utilizing creatinine and cystatin C. Methods: eGFR was calculated using 3 race-free CKD-EPI formulas: creatinine-based (CKD-EPI creatinine), cystatin C (CKD-EPI cys), and creatinine-cystatin C (CKD-EPI creatinine-cystatin C) equations on 697 Mayo Clinic ADPKD patients. Correlations between eGFR and TKV measures were estimated and stratified by MIC class risk groups and CKD. Linear regression models were computed to predict ln(htTKV) from the 3 eGFR data sets. The eGFR measures were compared to iothalamate-based mGFR in a subset of patients (n=50). Results: A correlation between eGFR measures and htTKV (Pearson correlation r of -0.53 to -0.54), varied by MIC stratification. Pearson correlation was -0.47 to -0.48 for MIC 1A and 1B, -0.67 to -0.71 for MIC 1C, and -0.67 to -0.68 for MIC 1D and 1E. All equations were significantly associated with htTKV levels, with similar adjusted beta values (95% CI) of -0.15 (-0.17 to -0.13), -0.14 (-0.16 to -0.12), -0.15 (-0.16 to -0.13), for CKD-EPI creatinine, CKD-EPI cystatin C, and CKD-EPI creatinine-cystatin C, respectively. Compared to mGFR, the CKD-EPI creatinine-cystatin C equation was the least biased (mean -0.86 (95% CI: -3.09 to 1.37)) versus CKD-EPI creatinine (2.31 (-0.73 to 5.34)) or CKD-EPI cystatin C (-3.54 (-5.86 to -1.21)), and most precise, with 1-P30 of 16% (95% CI 7.2% to 29.1%), compared to 18% (8.6% to 31.4%) for CKD-EPI creatinine, or 20% (10.0% to 33.7%) for CKD-EPI cystatin C. Conclusion: A moderate correlation between eGFR and htTKV associated with MIC stratification. Associations between htTKV and all 3 CKD-EPI equations were similar. CKDEPIcrcys tended to be the least biased and most precise equation when compared to mGFR and may be a reasonable alternative.

Renal water reabsorption is classically regulated by vasopressin V2 receptor (V2R) signaling through cyclic AMP and protein kinase A, driving apical accumulation of aquaporin-2 (AQP2). However, collecting duct water handling is also modulated by vasopressin-independent mechanisms. Here, we examined intracellular soluble urate as a vasopressin-independent regulator of AQP2 trafficking. Intracellular urate accumulation in collecting duct cells was mediated by enhanced apical urate uptake via GLUT9b and reduced apical urate efflux through ABCG2, triggering phosphodiesterase-4 activation, reduced cAMP, and downstream AMP-activated protein kinase (AMPK) activation. The resulting AQP2 accumulation at the apical membrane was independent of V2R signaling, required ongoing endocytosis, and was associated with features of postendocytic apical trafficking of internalized AQP2. In vivo ABCG2 inhibition with probenecid increased apical AQP2 abundance and markedly attenuated tolvaptan-induced polyuria in both wild-type and Pkd1 RC/RC autosomal dominant polycystic kidney disease (ADPKD) mice in a uricase-independent manner while preserving tolvaptan’s ADPKD-modifying efficacy. In a phase II trial with tolvaptan-treated patients with ADPKD, probenecid reduced urine volume and nocturia frequency. Together, these findings support a vasopressin-independent urate/AMPK/AQP2 pathway that regulates renal water handling and, in a preclinical ADPKD model, can uncouple cyst growth attenuation from the dose-limiting aquaretic effects of V2R antagonism.

Abstract Background Abdominal arterial calcification is a well-established predictor of cardiovascular events and mortality in kidney failure. Autosomal dominant polycystic kidney disease (ADPKD), a common genetic cause of kidney failure, presents with a distinct vascular profile. However, the burden of abdominal arterial calcification in ADPKD remains inadequately characterized. Clarifying these differences may improve cardiovascular risk stratification and transplant timing. Methods We conducted a retrospective cohort study of 4088 adult patients listed for kidney transplant at three Mayo Clinic sites (2005–2024). Patients were categorized by kidney failure cause: ADPKD vs. non-ADPKD. Abdominal arterial calcification was quantified on non-contrast computed tomography (CT) scans using a modified Agatston scoring method. Propensity score matching (1:1) adjusted for age, sex, race, lipid levels, left ventricular ejection fraction, dialysis exposure, coronary artery disease, neurovascular disease, and smoking history, was performed. Abdominal arterial calcification scores were compared between matched groups, and subgroup analyses evaluated abdominal arterial calcification severity across dialysis durations in ADPKD patients. Results After matching, 309 patients with ADPKD were compared with 309 non-ADPKD chronic kidney disease (CKD) controls. Abdominal arterial calcification scores were significantly lower in the ADPKD group (median: 425.3; IQR: 0.0–2033.5) than in the non-ADPKD group (median: 1256.8; IQR: 96.5–5033.8). Among ADPKD patients, abdominal arterial calcification scores increased with dialysis duration (P < .001). Conclusion ADPKD patients exhibit lower abdominal arterial calcification scores than their non-ADPKD counterparts after adjusting for clinical variables. Abdominal arterial calcification progression with dialysis highlights the importance of early transplant evaluation. This study introduces a novel adaptation of coronary calcium scoring software for quantifying abdominal calcification, offering a standardized approach to vascular risk assessment in kidney transplant candidates.

Key Points In a cohort of children, 79% of families with kidney cysts had a monogenic diagnosis. Resolved cases were more likely to have a family history of kidney cysts and unresolved cases more often had unilateral cysts. Broad genetic testing revealed genetic diversity and informed prognosis and clinical management in childhood kidney cysts. Background Pediatric kidney cysts may indicate an underlying genetic disorder, yet the full spectrum of causes remains incompletely defined. With advances in genetic testing enabling broader evaluation, this study assessed the diagnostic utility of comprehensive genetic testing in a broad pediatric cohort with kidney cysts and characterized the underlying etiological diversity. Methods This observational cohort study included patients younger than 18 years enrolled between January 2020 and June 2024 at a single tertiary center. Genetic testing used targeted multigene or custom curated exome/genome sequencing panels, with segregation analysis when available. Eligible participants had at least two cysts without family history, one cyst with positive family history, or enlarged echogenic kidneys on prenatal ultrasound; those with congenital anomalies of the kidney and urinary tract associated with cysts were excluded. Clinical presentation was categorized as symptomatic, incidental, prenatal, or family screening. Primary outcomes were diagnostic yield and distribution of pathogenic variants. Results Among 109 patients (median age 7.6 years, 53% female), genetic testing identified a definitive diagnosis in 81 of 100 tested patients (81%) from 72 families (79%; 14 disorders). PKD1 variants were most common (45%), while PKD2 accounted for 7%. Other causes included HNF1B or 17q12 deletions (13%), minor autosomal dominant polycystic kidney disease genes (11%; GANAB, NEK8, IFT140 ), monoallelic PKHD1 (3%), and biallelic PKHD1 (8%), while syndromic ciliopathy genes accounted for 5%. A positive family history of cystic kidney disease was more common among patients with a genetic diagnosis (54% versus 11%; P = 0.008). Patients without an identified genetic diagnosis more often had unilateral cysts (26% versus 4%; P = 0.53). Diagnosis by clinical symptoms was the most genetically diverse category. Conclusions Comprehensive genetic testing in pediatric kidney cysts achieved high diagnostic yield in a selected cohort and identified diverse causes beyond major autosomal dominant polycystic kidney disease/autosomal recessive polycystic kidney disease genes, supporting early evaluation to improve diagnostic accuracy, inform prognosis, and guide management, even in the absence of family history.

ABSTRACT Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disorder leading to kidney failure. Recent advancements in artificial intelligence (AI) are transforming the diagnosis, risk stratification, management and prognostication in ADPKD by enabling more accurate assessments and individualized care. AI-powered imaging tools enhance the measurement of total kidney volume (TKV), improving the precision and efficiency of monitoring disease progression and more reliable assessment of therapeutic response. Machine learning algorithms can integrate genetic, imaging and clinical data to predict kidney function decline, facilitating personalized treatment strategies. In addition, AI is being used to identify genetic variants and to refine genotype–phenotype relationships, offering deeper insights into disease variability. AI-enabled monitoring technologies can support longitudinal tracking of TKV measurements obtained through magnetic resonance imaging or computed tomography, thereby improving clinical decision-making and management. Furthermore, AI can optimize clinical trial design by improving patient selection, prediction of treatment responses and safety monitoring. Despite these promising developments, integrating AI into the clinical practice remains controversial and may pose several challenges. This review highlights the emerging clinical applications of AI in ADPKD, emphasizing its potential to advance precision medicine and improve patient outcomes.

Key Points Data were collected from a cohort of 759 patients with autosomal dominant polycystic kidney disease that were followed for a median of 10.2 years. Prognostic models were developed to predict kidney failure using routinely obtained clinical information and externally validated. Risk predictions had good discrimination and calibration over a time horizon of 15 years. Background Autosomal dominant polycystic kidney disease (ADPKD) is a common cause of kidney failure. Progression is highly variable, and accurate prognostic information is needed to guide early treatment decisions. The objective of this study was to develop a multivariable predictive model for progression to kidney failure. Methods We developed prognostic models using Cox regression for the outcome of kidney failure, defined as eGFR <15 ml/min per 1.73 m 2 , dialysis, or kidney transplantation. The development dataset consisted of participants in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) and Halt Progression of Polycystic Kidney Disease study A (HALT-A) studies. The validation dataset consisted of patients with ADPKD in the Mayo clinical registry aged 15–49 years, with eGFR ≥60 ml/min per 1.73 m 2 . Predictor variables in the base model were age, sex, creatinine or eGFR, ADPKD genotype, and Mayo Imaging Class. Clinical and laboratory data were evaluated in the full model. Results The development cohort included 759 patients with baseline eGFR of 91±29 ml/min per 1.73 m 2 (mean±SD), of whom 16% reached end point after median (interquartile range) follow-up of 10.2 (5.5–16.7) years. The validation cohort included 535 patients with baseline eGFR of 90±31 ml/min per 1.73 m 2 (mean±SD), of whom 11% reached end point after median (interquartile range) follow-up of 5.5 (1.5–13.7) years. The full model, including age, sex, serum creatinine, Mayo Imaging Class, total carbon dioxide, hemoglobin, diastolic BP, and body mass index, had a C-index of 0.81 (95% confidence interval, 0.72 to 0.90) in the validation cohort and 0.75 (95% confidence interval, 0.62 to 0.88) when ADPKD genotype was also included. Risk predictions from base and full models were well-calibrated out to 15 years. Conclusions In persons with early ADPKD and preserved eGFR, a model using routinely obtained clinical information quantified risk of kidney failure over 15 years.

Autosomal dominant polycystic kidney disease is the most common inherited kidney disorder and a leading monogenic cause of kidney failure. Reduction or loss of polycystin-1 and polycystin-2 function disrupts ciliary calcium signaling, elevates cyclic AMP (cAMP), reprograms cellular metabolism, and activates proliferative cascades that drive cyst expansion. Tolvaptan, a vasopressin V2 receptor antagonist, established cAMP modulation as a disease-modifying strategy but is limited by aquaretic effects and hepatotoxicity risk. This review highlights emerging therapeutic strategies in clinical trial development that extend beyond vasopressin antagonism. Gene-directed therapies aim to restore polycystin dosage, including anti–miR-17 oligonucleotides ( e.g ., farabursen) and pharmacochaperones that rescue misfolded polycystin-1 and restore trafficking in select PKD1 missense variants ( e.g ., VX-407). Paracrine signaling can be modulated with anti–pregnancy-associated plasma protein A antibodies that reduce insulin-like growth factor-1 bioavailability in cystic microenvironments. Metabolic reprogramming is targeted by agents such as metformin, bempedoic acid, glucagon-like peptide-1 receptor agonists, and structured dietary interventions. Sodium-glucose cotransporter 2 inhibitors hold theoretical promise but await definitive results from ongoing trials. A novel cAMP-lowering strategy through phosphodiesterase-4 activation is advancing toward clinical testing. Looking ahead, gene therapy, and genome editing offer the potential to raise polycystin levels above the threshold for cystogenesis, although challenges in vector capacity, kidney-specific delivery, and durability remain. Artificial intelligence–guided discovery, coupled with human organoid platforms, is accelerating therapeutic repurposing and rational combination design. Collectively, these advances signal a transition toward a layered, mechanism-guided framework in which vasopressin blockade is integrated with metabolic, other signaling, and genotype-specific therapies. As biomarkers and risk stratification tools mature, autosomal dominant polycystic kidney disease management is poised to become increasingly precise, tolerable, and effective.

Key Points Genetic testing in CKD showed diagnostic and clinical utility in the year following reporting of test results. Genetic testing was helpful for or changed management in 86% of patients with a positive finding and 42% with a negative finding. Clinical utility was seen across 12 clinical cohorts, including CKD of unknown etiology and hypertension or diabetes-related nephropathy. Background CKD is a significant public health burden, affecting >800 million people worldwide with significant cost to the health care system. CKD is a disease process with substantial genetic and phenotypic heterogeneity that can obscure a definitive diagnosis, resulting in suboptimal management. Recent guidelines support greater adoption of genetic testing in CKD. We assessed the diagnostic and clinical utility in the year following broad-panel CKD genetic testing. Methods The Renasight Clinical Application, Review, and Evaluation (RenaCARE) study (NCT05846113) was a single-arm, interventional, prospective, multicenter study evaluating the utility of genetic testing with a 385-gene panel on the diagnosis and management of CKD. Clinical history was collected before testing, and nephrologists responded to questionnaires at both 1 month and 1 year after testing. The impact of genetic testing on CKD diagnosis and management were assessed in active study patients at the 1-year time point. Results In a cohort of 1388 CKD patients with 13 pretest clinical categories of CKD, 335 (24%) patients had a positive genetic finding; 1174 had a questionnaire completed at 1 year and were included in the analysis. Genetic testing was reported helpful for clinical management and/or led to a change in management in 86% of patients with a positive test finding and 42% of patients with a negative test finding. In addition, genetic testing resulted in a change in the physician estimation of the 5-year prognosis for 55% of patients with a positive test finding and 18% of those with a negative test finding. Conclusions Supporting the previous results of the RenaCARE study at 1 month, this report demonstrated that genetic testing was helpful in the clinical management and estimated prognosis of patients with CKD. Clinical Trial registry name and registration number: ClinicalTrials.gov, NCT05846113.