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13 pages, 1752 KiB  
Article
The Role of Baseline Total Kidney Volume Growth Rate in Predicting Tolvaptan Efficacy for ADPKD Patients: A Feasibility Study
by Hreedi Dev, Zhongxiu Hu, Jon D. Blumenfeld, Arman Sharbatdaran, Yelynn Kim, Chenglin Zhu, Daniil Shimonov, James M. Chevalier, Stephanie Donahue, Alan Wu, Arindam RoyChoudhury, Xinzi He and Martin R. Prince
J. Clin. Med. 2025, 14(5), 1449; https://doi.org/10.3390/jcm14051449 - 21 Feb 2025
Viewed by 183
Abstract
Background/Objectives: Although tolvaptan efficacy in ADPKD has been demonstrated in randomized clinical trials, there is no definitive method for assessing its efficacy in the individual patient in the clinical setting. In this exploratory feasibility study, we report a method to quantify the [...] Read more.
Background/Objectives: Although tolvaptan efficacy in ADPKD has been demonstrated in randomized clinical trials, there is no definitive method for assessing its efficacy in the individual patient in the clinical setting. In this exploratory feasibility study, we report a method to quantify the change in total kidney volume (TKV) growth rate to retrospectively evaluate tolvaptan efficacy for individual patients. Treatment-related changes in estimated glomerular filtration rate (eGFR) are also assessed. Methods: MRI scans covering at least 1 year prior to and during treatment with tolvaptan were performed, with deep learning facilitated kidney segmentation and fitting multiple imaging timepoints to exponential growth in 32 ADPKD patients. Clustering analysis differentiated tolvaptan treatment “responders” and “non-responders” based upon the magnitude of change in TKV growth rate. Differences in rate of eGFR decline, urine osmolality, and other parameters were compared between responders and non-responders. Results: Eighteen (56%) tolvaptan responders (mean age 42 ± 8 years) were identified by k-means clustering, with an absolute reduction in annual TKV growth rate of >2% (mean = −5.1% ± 2.5% per year). Thirteen (44%) non-responders were identified, with <1% absolute reduction in annual TKV growth rate (mean = +2.4% ± 2.7% per year) during tolvaptan treatment. Compared to non-responders, tolvaptan responders had significantly higher mean TKV growth rates prior to tolvaptan treatment (7.1% ± 3.6% per year vs. 3.7% ± 2.4% per year; p = 0.003) and higher median pretreatment spot urine osmolality (Uosm, 393 mOsm/kg vs. 194 mOsm/kg, p = 0.03), confirmed by multivariate analysis. Mean annual rate of eGFR decline was less in responders than in non-responders (−0.25 ± 0.04, CI: [−0.27, −0.23] mL/min/1.73 m2 per year vs. −0.40 ± 0.06, CI: [−0.43, −0.37] mL/min/1.73 m2 per year, p = 0.036). Conclusions: In this feasibility study designed to assess predictors of tolvaptan treatment efficacy in individual patients with ADPKD, we found that high pretreatment levels of annual TKV growth rate and higher pretreatment spot urine osmolality were associated with a responder phenotype. Full article
(This article belongs to the Topic AI in Medical Imaging and Image Processing)
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23 pages, 1278 KiB  
Review
Advances and Challenges in Modeling Autosomal Dominant Polycystic Kidney Disease: A Focus on Kidney Organoids
by Jinglan Gu, Fei Liu, Lu Li and Jianhua Mao
Biomedicines 2025, 13(2), 523; https://doi.org/10.3390/biomedicines13020523 - 19 Feb 2025
Viewed by 299
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is a prevalent hereditary disorder characterized by distinct phenotypic variability that has posed challenges for advancing in-depth research. Recent advancements in kidney organoid construction technologies have enabled researchers to simulate kidney development and create simplified in vitro [...] Read more.
Autosomal dominant polycystic kidney disease (ADPKD) is a prevalent hereditary disorder characterized by distinct phenotypic variability that has posed challenges for advancing in-depth research. Recent advancements in kidney organoid construction technologies have enabled researchers to simulate kidney development and create simplified in vitro experimental environments, allowing for more direct observation of how genetic mutations drive pathological phenotypes and disrupt physiological functions. Emerging technologies, such as microfluidic bioreactor culture systems and single-cell transcriptomics, have further supported the development of complex ADPKD organoids, offering robust models for exploring disease mechanisms and facilitating drug discovery. Nevertheless, significant challenges remain in constructing more accurate ADPKD disease models. This review will summarize recent advances in ADPKD organoid construction, focusing on the limitations of the current techniques and the critical issues that need to be addressed for future breakthroughs. New and Noteworthy: This review presents recent advancements in ADPKD organoid construction, particularly iPSC-derived models, offering new insights into disease mechanisms and drug discovery. It focuses on challenges such as limited vascularization and maturity, proposing potential solutions through emerging technologies. The ongoing optimization of ADPKD organoid models is expected to enhance understanding of the disease and drive breakthroughs in disease mechanisms and targeted therapy development. Full article
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14 pages, 865 KiB  
Review
Autosomal Dominant Polycystic Kidney Disease Inflammation Biomarkers in the Tolvaptan Era
by Tânia Lapão, Rui Barata, Cristina Jorge, Carlos Flores and Joaquim Calado
Int. J. Mol. Sci. 2025, 26(3), 1121; https://doi.org/10.3390/ijms26031121 - 28 Jan 2025
Viewed by 539
Abstract
With the approval of tolvaptan as the first specific medicine for the treatment of rapidly progressive Autosomal Dominant Polycystic Kidney Disease (ADPKD), biomarker discovery has gained renewed interest as it is widely recognized that these will be crucial in clinical decision-making, serving as [...] Read more.
With the approval of tolvaptan as the first specific medicine for the treatment of rapidly progressive Autosomal Dominant Polycystic Kidney Disease (ADPKD), biomarker discovery has gained renewed interest as it is widely recognized that these will be crucial in clinical decision-making, serving as either prognostic or predictive tools. Since the marketing authorization was first issued in 2015 for ADPKD, tolvaptan has remained the sole pharmacological compound specifically targeting the disease. For ADPKD patients it is an invaluable medicine for retarding disease progression. Although the field of overall biomarker discovery and validation has been detailed in several publications, the role of inflammation remains largely overlooked in ADPKD. The current work aims to provide the reader with an updated review of inflammation biomarkers research in ADPKD, highlighting the role of urinary MCP-1 (monocyte chemoattractant protein-1) as the most promising tool. Full article
(This article belongs to the Special Issue A Molecular Perspective on the Genetics of Kidney Diseases)
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22 pages, 2506 KiB  
Article
Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume
by Ting-Wen Sheng, Djeane Debora Onthoni, Pushpanjali Gupta, Tsong-Hai Lee and Prasan Kumar Sahoo
Biomedicines 2025, 13(2), 263; https://doi.org/10.3390/biomedicines13020263 - 22 Jan 2025
Viewed by 530
Abstract
Background: Total Kidney Volume (TKV) is widely used globally to predict the progressive loss of renal function in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD). Typically, TKV is calculated using Computed Tomography (CT) images by manually locating, delineating, and segmenting the ADPKD [...] Read more.
Background: Total Kidney Volume (TKV) is widely used globally to predict the progressive loss of renal function in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD). Typically, TKV is calculated using Computed Tomography (CT) images by manually locating, delineating, and segmenting the ADPKD kidneys. However, manual localization and segmentation are tedious, time-consuming tasks and are prone to human error. Specifically, there is a lack of studies that focus on CT modality variation. Methods: In contrast, our work develops a step-by-step framework, which robustly handles both Non-enhanced Computed Tomography (NCCT) and Contrast-enhanced Computed Tomography (CCT) images, ensuring balanced sample utilization and consistent performance across modalities. To achieve this, Artificial Intelligence (AI)-enabled localization and segmentation models are proposed for estimating TKV, which is designed to work robustly on both NCCT and Contrast-Computed Tomography (CCT) images. These AI-based models incorporate various image preprocessing techniques, including dilation and global thresholding, combined with Deep Learning (DL) approaches such as the adapted Single Shot Detector (SSD), Inception V2, and DeepLab V3+. Results: The experimental results demonstrate that the proposed AI-based models outperform other DL architectures, achieving a mean Average Precision (mAP) of 95% for automatic localization, a mean Intersection over Union (mIoU) of 92% for segmentation, and a mean R2 score of 97% for TKV estimation. Conclusions: These results clearly indicate that the proposed AI-based models can robustly localize and segment ADPKD kidneys and estimate TKV using both NCCT and CCT images. Full article
(This article belongs to the Special Issue The Promise of Artificial Intelligence in Kidney Disease)
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20 pages, 977 KiB  
Systematic Review
Therapeutic Potential of Ketogenic Interventions for Autosomal-Dominant Polycystic Kidney Disease: A Systematic Review
by Donglai Li, Jessica Dawson and Jenny E. Gunton
Nutrients 2025, 17(1), 145; https://doi.org/10.3390/nu17010145 - 31 Dec 2024
Viewed by 1189
Abstract
Background: Recent findings have highlighted that abnormal energy metabolism is a key feature of autosomal-dominant polycystic kidney disease (ADPKD). Emerging evidence suggests that nutritional ketosis could offer therapeutic benefits, including potentially slowing or even reversing disease progression. This systematic review aims to synthesise [...] Read more.
Background: Recent findings have highlighted that abnormal energy metabolism is a key feature of autosomal-dominant polycystic kidney disease (ADPKD). Emerging evidence suggests that nutritional ketosis could offer therapeutic benefits, including potentially slowing or even reversing disease progression. This systematic review aims to synthesise the literature on ketogenic interventions to evaluate the impact in ADPKD. Methods: A systematic search was conducted in Medline, Embase, and Scopus using relevant Medical Subject Headings (MeSH) and keywords. Studies assessing ketogenic interventions in the management of ADPKD in both human and animal models were selected for data extraction and analysis. Results: Three animal reports and six human studies were identified. Ketogenic diets (KD) significantly slowed polycystic kidney disease (PKD) progression in rats with improved renal function and reduced cystic areas. There was reduced renal fibrosis and cell proliferation. The supplementation of beta-hydroxybutyrate (BHB) in rats also reduced PKD progression in a dose-dependent manner. Human studies (n = 129) on KD in ADPKD reported consistent body mass index (BMI) reduction across trials, with an average weight loss of ∼4 kg. Improvements in blood pressure were also noted. Ketosis was achieved in varying degrees. Effects on kidney function (eGFR) were beneficial. Results for kidney volume were mixed but most studies were underpowered for this outcome. Lipid profiles showed increases in total cholesterol (∼1 mmol/L) and LDL cholesterol (∼0.4 mmol/L) in most studies. Safety concerns such as “keto flu” symptoms, elevated uric acid levels, and occasional kidney stones were noted. Overall feasibility and adherence to the KD were rated positively by most participants. Conclusions: Human studies are promising; however, they have been limited by small sample sizes and short durations. Larger, long-term trials are needed to assess the efficacy, adherence, and safety of ketogenic diets in people with ADPKD. Full article
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10 pages, 3337 KiB  
Case Report
Typical Clinical Presentation of an Autosomal Dominant Polycystic Kidney Disease Patient with an Atypical Genetic Pattern
by Nenzi Marzano, Carlotta Caprara, Thiago Reis, Diego Pomarè Montin, Sofia Maria Pretto, Matteo Rigato, Anna Giuliani, Fiorella Gastaldon, Barbara Mancini, Claudio Ronco, Monica Zanella, Daniela Zuccarello and Valentina Corradi
Genes 2025, 16(1), 39; https://doi.org/10.3390/genes16010039 - 30 Dec 2024
Viewed by 789
Abstract
Background: Autosomal Dominant Polycystic Kidney Disease (ADPKD) is mainly characterized by renal involvement with progressive bilateral development of renal cysts and volumetric increase in the kidneys, causing a loss of renal function, chronic kidney disease (CKD), and kidney failure. The occurrence of [...] Read more.
Background: Autosomal Dominant Polycystic Kidney Disease (ADPKD) is mainly characterized by renal involvement with progressive bilateral development of renal cysts and volumetric increase in the kidneys, causing a loss of renal function, chronic kidney disease (CKD), and kidney failure. The occurrence of mosaicism may modulate the clinical course of the disease. Mosaicism is characterized by a few cell populations with different genomes. In these special cases, a genetic diagnosis could be challenging. Methods: Herein, we describe the case of a 47-year-old woman presenting with typical ultrasound and computed tomography features of ADPKD. She had stage 3b CKD and hypertension. There was no family history of ADPKD, prompting an investigation with a genetic test. Target next-generation sequencing (NGS) did not detect the presence of any genomic variants. Therefore, we carried out second-level genetic analysis to investigate the presence of a large rearrangement through a multiple ligation-dependent probe amplification (MLPA) analysis of PKD1 and PKD2 genes. Results: MLPA showed a large deletion (portion including exons 2–34 of PKD1) present in the heterozygosis with a percentage of cells close to the resolution limits of the technique used (<25–30%). We concluded that the large deletion identified was mosaicism. This variant is not reported in major ADPKD databases, but due to the type of mutation and the patient’s clinical picture, it should be considered as likely pathogenic. Conclusions: A stepwise genetic approach might be useful in those cases where standard methods do not allow one to reach a definitive diagnosis. Full article
(This article belongs to the Special Issue Feature Papers in Human Genomics and Genetic Diseases 2024)
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12 pages, 351 KiB  
Article
Abnormalities of IL-12 Family Cytokine Pathways in Autosomal Dominant Polycystic Kidney Disease Progression
by Corina-Daniela Ene, Ilinca Nicolae and Cristina Căpușă
Medicina 2024, 60(12), 1971; https://doi.org/10.3390/medicina60121971 - 30 Nov 2024
Viewed by 632
Abstract
Background and Objectives: Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most frequent genetic renal disease with a complex physiopathology. More and more studies sustain that inflammation plays a crucial role in ADPKD pathogenesis and progression. We evaluated IL-12 involvement in ADPKD pathophysiology [...] Read more.
Background and Objectives: Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most frequent genetic renal disease with a complex physiopathology. More and more studies sustain that inflammation plays a crucial role in ADPKD pathogenesis and progression. We evaluated IL-12 involvement in ADPKD pathophysiology by assessing the serum levels of its monomers and heterodimers. Materials and Methods: A prospective case-control study was developed and included 66 ADPKD subjects and a control group of 40 healthy subjects. The diagnosis of ADPKD was based on familial history clinical and imagistic exams. The study included subjects with eGFR > 60 mL/min/1.73 mp, with no history of hematuria or other renal disorders, with stable blood pressure in the last 6 months. We tested serum levels of monomers IL-12 p40 and IL-12 p35 and heterodimers IL-12 p70, IL-23, IL 35, assessed by ELISA method. Results: IL-12 family programming was abnormal in ADPKD patients. IL-12p70, IL-12p40, and IL-23 secretion increased, while IL-12p35 and IL-35 secretion decreased compared to control. IL-12p70, IL-12p40, and IL-23 had a progressive increase correlated with immune response amplification, a decrease of eGFR, an increase in TKV, and in albuminuria. On the other hand, IL-35 and IL-12p35 were correlated negatively with CRP and albuminuria and positively with eGFR in advanced ADPKD. Conclusions: The present study investigated IL-12 cytokine family members’ involvement in ADPKD pathogenesis, enriching our understanding of inflammation in the most common renal genetic disorder. Full article
(This article belongs to the Section Urology & Nephrology)
29 pages, 7459 KiB  
Article
Leveraging Explainable Artificial Intelligence (XAI) for Expert Interpretability in Predicting Rapid Kidney Enlargement Risks in Autosomal Dominant Polycystic Kidney Disease (ADPKD)
by Latifa Dwiyanti, Hidetaka Nambo and Nur Hamid
AI 2024, 5(4), 2037-2065; https://doi.org/10.3390/ai5040100 - 28 Oct 2024
Viewed by 1388
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is the predominant hereditary factor leading to end-stage renal disease (ESRD) worldwide, affecting individuals across all races with a prevalence of 1 in 400 to 1 in 1000. The disease presents significant challenges in management, particularly with [...] Read more.
Autosomal dominant polycystic kidney disease (ADPKD) is the predominant hereditary factor leading to end-stage renal disease (ESRD) worldwide, affecting individuals across all races with a prevalence of 1 in 400 to 1 in 1000. The disease presents significant challenges in management, particularly with limited options for slowing cyst progression, as well as the use of tolvaptan being restricted to high-risk patients due to potential liver injury. However, determining high-risk status typically requires magnetic resonance imaging (MRI) to calculate total kidney volume (TKV), a time-consuming process demanding specialized expertise. Motivated by these challenges, this study proposes alternative methods for high-risk categorization that do not rely on TKV data. Utilizing historical patient data, we aim to predict rapid kidney enlargement in ADPKD patients to support clinical decision-making. We applied seven machine learning algorithms—Random Forest, Logistic Regression, Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), Gradient Boosting Tree, XGBoost, and Deep Neural Network (DNN)—to data from the Polycystic Kidney Disease Outcomes Consortium (PKDOC) database. The XGBoost model, combined with the Synthetic Minority Oversampling Technique (SMOTE), yielded the best performance. We also leveraged explainable artificial intelligence (XAI) techniques, specifically Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP), to visualize and clarify the model’s predictions. Furthermore, we generated text summaries to enhance interpretability. To evaluate the effectiveness of our approach, we proposed new metrics to assess explainability and conducted a survey with 27 doctors to compare models with and without XAI techniques. The results indicated that incorporating XAI and textual summaries significantly improved expert explainability and increased confidence in the model’s ability to support treatment decisions for ADPKD patients. Full article
(This article belongs to the Special Issue Interpretable and Explainable AI Applications)
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21 pages, 1885 KiB  
Review
PKD2: An Important Membrane Protein in Organ Development
by Shuo Wang, Yunsi Kang and Haibo Xie
Cells 2024, 13(20), 1722; https://doi.org/10.3390/cells13201722 - 17 Oct 2024
Cited by 1 | Viewed by 1282
Abstract
PKD2 was first identified as the pathogenic protein for autosomal dominant polycystic kidney disease (ADPKD) and is widely recognized as an ion channel. Subsequent studies have shown that PKD2 is widely expressed in various animal tissues and plays a crucial role in tissue [...] Read more.
PKD2 was first identified as the pathogenic protein for autosomal dominant polycystic kidney disease (ADPKD) and is widely recognized as an ion channel. Subsequent studies have shown that PKD2 is widely expressed in various animal tissues and plays a crucial role in tissue and organ development. Additionally, PKD2 is conserved from single-celled organisms to vertebrates. Here, we provide an overview of recent advances in the function of PKD2 in key model animals, focusing on the establishment of left–right organ asymmetry, renal homeostasis, cardiovascular development, and signal transduction in reproduction and mating. We specifically focus on the roles of PKD2 in development and highlight future prospects for PKD2 research. Full article
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14 pages, 1370 KiB  
Review
Reactive Oxygen Species in Cystic Kidney Disease
by Sanat Subhash, Sonya Vijayvargiya, Aetan Parmar, Jazlyn Sandhu, Jabrina Simmons and Rupesh Raina
Antioxidants 2024, 13(10), 1186; https://doi.org/10.3390/antiox13101186 - 30 Sep 2024
Viewed by 1856
Abstract
Polycystic kidney disease (PKD) is a rare but significant renal condition with major implications for global acute and chronic patient care. Oxidative stress and reactive oxygen species (ROS) can significantly alter its pathophysiology, clinical outcomes, and treatment, contributing to negative outcomes, including hypertension, [...] Read more.
Polycystic kidney disease (PKD) is a rare but significant renal condition with major implications for global acute and chronic patient care. Oxidative stress and reactive oxygen species (ROS) can significantly alter its pathophysiology, clinical outcomes, and treatment, contributing to negative outcomes, including hypertension, chronic kidney disease, and kidney failure. Inflammation from ROS and existing cysts propagate the generation and accumulation of ROS, exacerbating kidney injury, pro-fibrotic signaling cascades, and interstitial fibrosis. Early identification and prevention of oxidative stress and ROS can contribute to reduced cystic kidney disease progression and improved longitudinal patient outcomes. Increased research regarding biomarkers, the pathophysiology of oxidative stress, and novel therapeutic interventions alongside the creation of comprehensive guidelines establishing methods of assessment, monitoring, and intervention for oxidative stress in cystic kidney disease patients is imperative to standardize clinical practice and improve patient outcomes. The integration of artificial intelligence (AI), genetic editing, and genome sequencing could further improve the early detection and management of cystic kidney disease and mitigate adverse patient outcomes. In this review, we aim to comprehensively assess the multifactorial role of ROS in cystic kidney disease, analyzing its pathophysiology, clinical outcomes, treatment interventions, clinical trials, animal models, and future directions for patient care. Full article
(This article belongs to the Special Issue Oxidative Stress in Renal Health)
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30 pages, 1570 KiB  
Review
Trigger Warning: How Modern Diet, Lifestyle, and Environment Pull the Trigger on Autosomal Dominant Polycystic Kidney Disease Progression
by Melina Messing, Jacob A. Torres, Nickolas Holznecht and Thomas Weimbs
Nutrients 2024, 16(19), 3281; https://doi.org/10.3390/nu16193281 - 27 Sep 2024
Viewed by 4718
Abstract
Understanding chronic kidney disease (CKD) through the lens of evolutionary biology highlights the mismatch between our Paleolithic-optimized genes and modern diets, which led to the dramatically increased prevalence of CKD in modern societies. In particular, the Standard American Diet (SAD), high in carbohydrates [...] Read more.
Understanding chronic kidney disease (CKD) through the lens of evolutionary biology highlights the mismatch between our Paleolithic-optimized genes and modern diets, which led to the dramatically increased prevalence of CKD in modern societies. In particular, the Standard American Diet (SAD), high in carbohydrates and ultra-processed foods, causes conditions like type 2 diabetes (T2D), chronic inflammation, and hypertension, leading to CKD. Autosomal dominant polycystic kidney disease (ADPKD), a genetic form of CKD, is characterized by progressive renal cystogenesis that leads to renal failure. This review challenges the fatalistic view of ADPKD as solely a genetic disease. We argue that, just like non-genetic CKD, modern dietary practices, lifestyle, and environmental exposures initiate and accelerate ADPKD progression. Evidence shows that carbohydrate overconsumption, hyperglycemia, and insulin resistance significantly impact renal health. Additionally, factors like dehydration, electrolyte imbalances, nephrotoxin exposure, gastrointestinal dysbiosis, and renal microcrystal formation exacerbate ADPKD. Conversely, carbohydrate restriction, ketogenic metabolic therapy (KMT), and antagonizing the lithogenic risk show promise in slowing ADPKD progression. Addressing disease triggers through dietary modifications and lifestyle changes offers a conservative, non-pharmacological strategy for disease modification in ADPKD. This comprehensive review underscores the urgency of integrating diet and lifestyle factors into the clinical management of ADPKD to mitigate disease progression, improve patient outcomes, and offer therapeutic choices that can be implemented worldwide at low or no cost to healthcare payers and patients. Full article
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6 pages, 195 KiB  
Case Report
New Mutation Associated with Polycystic Kidney Disease Type I: A Case Report
by Vanya Rai, Manisha Singh and Joseph H. Holthoff
Genes 2024, 15(10), 1262; https://doi.org/10.3390/genes15101262 - 27 Sep 2024
Viewed by 1272
Abstract
Introduction: Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent heritable disorders, characterized by the progressive development of kidney cysts leading to renal failure. It is primarily caused by mutations in the PKD1 and PKD2 genes, which account for approximately [...] Read more.
Introduction: Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent heritable disorders, characterized by the progressive development of kidney cysts leading to renal failure. It is primarily caused by mutations in the PKD1 and PKD2 genes, which account for approximately 85% and 15% of cases, respectively. This case report describes a previously unreported mutation in the PKD1 gene, identified in a family involving an aunt and her niece with ADPKD. Case Presentation: The index case, a 56-year-old female with chronic kidney disease stage 3b secondary to ADPKD and hypertension, exhibited a strong family history of polycystic kidney disease (PKD). Initial genetic evaluations did not identify any recognized pathogenic mutations, leading to a more detailed investigation which revealed a novel mutation in the PKD1 gene. This mutation was also found in her niece, who presented with early-onset disease. Conclusions: The identification of a heterozygous six-nucleotide deletion, c.2084_2089del, resulting in the in-frame deletion of two amino acids, p.Pro695_Ala696del, in the PKD1 gene, has been linked with ADPKD in these patients. This report emphasizes the need for continuous updates to genetic data for a deeper understanding of the diagnosis and prognosis of ADPKD that could potentially aid in targeted therapy. Full article
(This article belongs to the Section Human Genomics and Genetic Diseases)
16 pages, 2605 KiB  
Article
Applying a Deep Learning Model for Total Kidney Volume Measurement in Autosomal Dominant Polycystic Kidney Disease
by Jia-Lien Hsu, Anandakumar Singaravelan, Chih-Yun Lai, Zhi-Lin Li, Chia-Nan Lin, Wen-Shuo Wu, Tze-Wah Kao and Pei-Lun Chu
Bioengineering 2024, 11(10), 963; https://doi.org/10.3390/bioengineering11100963 - 26 Sep 2024
Viewed by 1228
Abstract
Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary renal disease leading to end-stage renal disease. Total kidney volume (TKV) measurement has been considered as a surrogate in the evaluation of disease severity and prognostic predictor of ADPKD. However, the [...] Read more.
Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary renal disease leading to end-stage renal disease. Total kidney volume (TKV) measurement has been considered as a surrogate in the evaluation of disease severity and prognostic predictor of ADPKD. However, the traditional manual measurement of TKV by medical professionals is labor-intensive, time-consuming, and human error prone. Materials and methods: In this investigation, we conducted TKV measurements utilizing magnetic resonance imaging (MRI) data. The dataset consisted of 30 patients with ADPKD and 10 healthy individuals. To calculate TKV, we trained models using both coronal- and axial-section MRI images. The process involved extracting images in Digital Imaging and Communications in Medicine (DICOM) format, followed by augmentation and labeling. We employed a U-net model for image segmentation, generating mask images of the target areas. Subsequent post-processing steps and TKV estimation were performed based on the outputs obtained from these mask images. Results: The average TKV, as assessed by medical professionals from the testing dataset, was 1501.84 ± 965.85 mL with axial-section images and 1740.31 ± 1172.21 mL with coronal-section images, respectively (p = 0.73). Utilizing the deep learning model, the mean TKV derived from axial- and coronal-section images was 1536.33 ± 958.68 mL and 1636.25 ± 964.67 mL, respectively (p = 0.85). The discrepancy in mean TKV between medical professionals and the deep learning model was 44.23 ± 58.69 mL with axial-section images (p = 0.8) and 329.12 ± 352.56 mL with coronal-section images (p = 0.9), respectively. The average variability in TKV measurement was 21.6% with the coronal-section model and 3.95% with the axial-section model. The axial-section model demonstrated a mean Dice Similarity Coefficient (DSC) of 0.89 ± 0.27 and an average patient-wise Jaccard coefficient of 0.86 ± 0.27, while the mean DSC and Jaccard coefficient of the coronal-section model were 0.82 ± 0.29 and 0.77 ± 0.31, respectively. Conclusion: The integration of deep learning into image processing and interpretation is becoming increasingly prevalent in clinical practice. In our pilot study, we conducted a comparative analysis of the performance of a deep learning model alongside corresponding axial- and coronal-section models, a comparison that has been less explored in prior research. Our findings suggest that our deep learning model for TKV measurement performs comparably to medical professionals. However, we observed that varying image orientations could introduce measurement bias. Specifically, our AI model exhibited superior performance with axial-section images compared to coronal-section images. Full article
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21 pages, 6221 KiB  
Article
STING Promotes the Progression of ADPKD by Regulating Mitochondrial Function, Inflammation, Fibrosis, and Apoptosis
by Jiao Wu, Shasha Cheng, Geoffray Lee, Ewud Agborbesong, Xiaoyan Li, Xia Zhou and Xiaogang Li
Biomolecules 2024, 14(10), 1215; https://doi.org/10.3390/biom14101215 - 26 Sep 2024
Cited by 1 | Viewed by 1695
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is a predominant genetic disease, which is caused by mutations in PKD genes and is associated with DNA damage in cystic cells. The intrinsic stimulator of interferon genes (STING) pathway is crucial for recognizing damaged DNA in [...] Read more.
Autosomal dominant polycystic kidney disease (ADPKD) is a predominant genetic disease, which is caused by mutations in PKD genes and is associated with DNA damage in cystic cells. The intrinsic stimulator of interferon genes (STING) pathway is crucial for recognizing damaged DNA in the cytosol, triggering the expression of inflammatory cytokines to activate defense mechanisms. However, the precise roles and mechanisms of STING in ADPKD remain elusive. In this study, we show that Pkd1 mutant mouse kidneys show upregulation of STING, which is stimulated by the DNAs of nuclear and mitochondrial origin. The activation of STING promotes cyst growth through increasing (1) the activation of NF-κB in Pkd1 mutant cells and (2) the recruitment of macrophages in the interstitial and peri-cystic regions in Pkd1 mutant mouse kidneys via NF-κB mediating the upregulation of TNF-α and MCP-1. Targeting STING with its specific inhibitor C-176 delays cyst growth in an early-stage aggressive Pkd1 conditional knockout mouse model and a milder long-lasting Pkd1 mutant mouse model. Targeting STING normalizes mitochondrial structure and function, decreases the formation of micronuclei, induces Pkd1 mutant renal epithelial cell death via p53 signaling, and decreases renal fibrosis in Pkd1 mutant mouse kidneys. These results support that STING is a novel therapeutic target for ADPKD treatment. Full article
(This article belongs to the Section Cellular Biochemistry)
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18 pages, 1639 KiB  
Review
The Influence of Non-Pharmacological and Pharmacological Interventions on the Course of Autosomal Dominant Polycystic Kidney Disease
by Karolina Kędzierska-Kapuza, Inga Łopuszyńska, Grzegorz Niewiński, Edward Franek and Małgorzata Szczuko
Nutrients 2024, 16(18), 3216; https://doi.org/10.3390/nu16183216 - 23 Sep 2024
Viewed by 2757
Abstract
Polycystic kidney disease (PKD) includes autosomal dominant (ADPKD) and autosomal recessive (ARPKD) forms, both of which are primary genetic causes of kidney disease in adults and children. ADPKD is the most common hereditary kidney disease, with a prevalence of 329 cases per million [...] Read more.
Polycystic kidney disease (PKD) includes autosomal dominant (ADPKD) and autosomal recessive (ARPKD) forms, both of which are primary genetic causes of kidney disease in adults and children. ADPKD is the most common hereditary kidney disease, with a prevalence of 329 cases per million in Europe. This condition accounts for 5–15% of end-stage chronic kidney disease (ESKD) cases, and in developed countries such as Poland, 8–10% of all dialysis patients have ESKD due to ADPKD. The disease is caused by mutations in the PKD1 and PKD2 genes, with PKD1 mutations responsible for 85% of cases, leading to a more aggressive disease course. Recent research suggests that ADPKD involves a metabolic defect contributing to cystic epithelial proliferation and cyst growth. Aim: This review explores the interplay between metabolism, obesity, and ADPKD, discussing dietary and pharmacological strategies that target these metabolic abnormalities to slow disease progression. Conclusion: Metabolic reprogramming therapies, including GLP-1 analogs and dual agonists of GIP/GLP-1 or glucagon/GLP-1 receptors, show promise, though further research is needed to understand their potential in ADPKD treatment fully. Full article
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