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.

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.

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.

Polycystic kidney disease (PKD) is a genetic disorder characterized by progressive kidney cyst formation and eventual kidney failure. Emerging evidence suggests that plant-based diets may confer therapeutic benefits in patients with PKD by modulating mTOR and AMPK signaling, reducing oxidative stress and inflammation, while improving metabolic and cardiovascular profiles. These diets, which are low in animal protein and rich in antioxidants, may help lower uric acid levels and support blood pressure control, thereby potentially reducing fibrosis. However, careful planning is required to avoid nutritional deficiencies. Well-designed clinical trials are warranted to validate their role in ADPKD management.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder and a leading cause of kidney failure worldwide. Disease progression is driven by cyst expansion, tubular injury, and maladaptive metabolic and hemodynamic changes. Tolvaptan remains the only US Food and Drug Administration–approved disease-modifying therapy, however its tolerability and safety profile highlight the need for additional strategies. Sodium-glucose cotransporter 2 inhibitors (SGLT2is), initially developed for glycemic control, have demonstrated robust kidney-protective and cardioprotective effects across diverse patient populations, including those without diabetes. By lowering intraglomerular pressure, metabolic reprogramming, and attenuating hypoxic microenvironment and inflammation, SGLT2is target mechanisms that are relevant to ADPKD. However, concerns that SGLT2i may provoke osmotic diuresis and activate vasopressin led to systematic exclusion of patients with ADPKD from pivotal outcome trials. The 2025 Kidney Disease Improving Global Outcomes ADPKD guidelines explicitly advise against the use of SGLT2i for slowing kidney function decline in ADPKD. In this review, we examine mechanistic intersections between SGLT2i and ADPKD pathophysiology, summarize available preclinical and early clinical data, and discuss ongoing large trials designed to address safety and efficacy of SGLT2i in patients with ADPKD. We also highlight the importance of genetic heterogeneity, as most ongoing trials are enriched for rapid progressors carrying PKD1 or PKD2 pathogenic variants, while other genotypes such as DNAJB11 , ALG8 , and ALG9 , often associated with greater interstitial fibrosis, are underrepresented. Substratification of patients by genotype, risk of progression, and comorbidities will be essential to guide precision application of SGLT2i. Whether SGLT2i can ultimately be positioned as an adjunctive or standalone therapy for ADPKD remains unresolved.

Key Points BeWell360-PKD shows that integrating certified health and wellness coaches and augmenting patients' personal capacity as part of autosomal dominant polycystic kidney disease care is feasible and acceptable. Embedding BeWell360 coaches reduced care burden, improved caregiver self-efficacy, and enhanced care engagement by patients with autosomal dominant polycystic kidney disease and by their informal caregivers. This aligns with evolving care standards and guidelines promoting sustainable healthy lifestyle changes through tailored, integrative behavior-change centered interventions. Background Autosomal dominant polycystic kidney disease (ADPKD) imposes substantial care burden on patients and their informal caregivers (CGs), often contributing to nonadherence and impaired quality of life. Existing care models insufficiently address the behavioral and psychosocial dimensions of this burden. To evaluate the feasibility and effect of BeWell360-PKD , a person-centered intervention integrating Health and Wellness Coaching and capacity-workload support into ADPKD care, on care burden, adherence, self-efficacy, activation, and resilience. Methods In this 6-month, single-arm, mixed-methods pilot study, seven patient-CG dyads were enrolled from tertiary care polycystic kidney disease clinic. Board-certified Health and Wellness Coachings delivered individualized coaching within routine nephrology care, emphasizing capacity-building, goal setting, and care enactment support. Primary outcomes included changes in treatment burden (treatment burden questionnaire, ADPKD impact scale) and CG burden (burden scale for family CGs short version). Secondary outcomes included patient activation and resilience and CG self-efficacy. Semistructured interviews explored participant experiences. Results Patients experienced reduced treatment burden (treatment burden questionnaire mean change −9.3) and modest, domain-specific improvements in physical and fatigue-related ADPKD symptom burden. CG self-efficacy improved (+2.4), while CG burden increased (+14.8), and patient activation declined (−6.6). Qualitative themes reflected disease burden, emotional adaptation, and the perceived value of coaching in promoting behavior change and relational support. Conclusions BeWell360-PKD was feasible to implement and demonstrated early signals of benefit in reducing patient burden and improving CG self-efficacy. Increased CG burden and declining activation highlight the complexity of dyadic adaptation in ADPKD and the need for larger, controlled studies to refine and tailor coaching interventions.

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.