Multi-task heterogeneous graph learning on electronic health records.

Learning electronic health records (EHRs) has received emerging attention because of its capability to facilitate accurate medical diagnosis. Since the EHRs contain enriched information specifying complex interactions between entities, modeling EHRs with graphs is shown to be effective in practice. The EHRs, however, present a great degree of heterogeneity, sparsity, and complexity, which hamper the performance of most of the models applied to them. Moreover, existing approaches modeling EHRs often focus on learning the representations for a single task, overlooking the multi-task nature of EHR analysis problems and resulting in limited generalizability across different tasks. In view of these limitations, we propose a novel framework for EHR modeling, namely MulT-EHR (Multi-Task EHR), which leverages a heterogeneous graph to mine the complex relations and model the heterogeneity in the EHRs. To mitigate the large degree of noise, we introduce a denoising module based on the causal inference framework to adjust for severe confounding effects and reduce noise in the EHR data. Additionally, since our model adopts a single graph neural network for simultaneous multi-task prediction, we design a multi-task learning module to leverage the inter-task knowledge to regularize the training process. Extensive empirical studies on MIMIC-III and MIMIC-IV datasets validate that the proposed method consistently outperforms the state-of-the-art designs in four popular EHR analysis tasks - drug recommendation, and predictions of the length of stay, mortality, and readmission. Thorough ablation studies demonstrate the robustness of our method upon variations to key components and hyperparameters.

Critical but commonly neglected factors that affect contrast medium administration in CT.

OBJECTIVE: Past decades of research into contrast media injections and optimization thereof in radiology clinics have focused on scan acquisition parameters, patient-related factors, and contrast injection protocol variables. In this review, evidence is provided that a fourth bucket of crucial variables has been missed which account for previously unexplained phenomena and higher-than-expected variability in data. We propose how these critical factors should be considered and implemented in the contrast-medium administration protocols to optimize contrast enhancement. METHODS: This article leverages a combination of methodologies for uncovering and quantifying confounding variables associated with or affecting the contrast-medium injection. Engineering benchtop equipment such as Coriolis flow meters, pressure transducers, and volumetric measurement devices are combined with small, targeted systematic evaluations querying operators, equipment, and the physics and fluid dynamics that make a seemingly simple task of injecting fluid into a patient a complex and non-linear endeavor. RESULTS: Evidence is presented around seven key factors affecting the contrast-medium injection including a new way of selecting optimal IV catheters, degraded performance from longer tubing sets, variability associated with the mechanical injection system technology, common operator errors, fluids exchanging places stealthily based on gravity and density, wasted contrast media and inefficient saline flushes, as well as variability in the injected flow rate vs. theoretical expectations. CONCLUSION: There remain several critical, but not commonly known, sources of error associated with contrast-medium injections. Elimination of these hidden sources of error where possible can bring immediate benefits and help to drive standardized and optimized contrast-media injections. CRITICAL RELEVANCE STATEMENT: This review brings to light the commonly neglected/unknown factors negatively impacting contrast-medium injections and provides recommendations that can result in patient benefits, quality improvements, sustainability increases, and financial benefits by enabling otherwise unachievable optimization. KEY POINTS: How IV contrast media is administered is a rarely considered source of CT imaging variability. IV catheter selection, tubing length, injection systems, and insufficient flushing can result in unintended variability. These findings can be immediately addressed to improve standardization in contrast-enhanced CT imaging.

Deep Learning-Based Automated Imaging Classification of ADPKD.

Introduction: The Mayo imaging classification model (MICM) requires a prestep qualitative assessment to determine whether a patient is in class 1 (typical) or class 2 (atypical), where patients assigned to class 2 are excluded from the MICM application. Methods: We developed a deep learning-based method to automatically classify class 1 and 2 from magnetic resonance (MR) images and provide classification confidence utilizing abdominal T 2 -weighted MR images from 486 subjects, where transfer learning was applied. In addition, the explainable artificial intelligence (XAI) method was illustrated to enhance the explainability of the automated classification results. For performance evaluations, confusion matrices were generated, and receiver operating characteristic curves were drawn to measure the area under the curve. Results: The proposed method showed excellent performance for the classification of class 1 (97.7%) and 2 (100%), where the combined test accuracy was 98.01%. The precision and recall for predicting class 1 were 1.00 and 0.98, respectively, with F 1 -score of 0.99; whereas those for predicting class 2 were 0.87 and 1.00, respectively, with F 1 -score of 0.93. The weighted averages of precision and recall were 0.98 and 0.98, respectively, showing the classification confidence scores whereas the XAI method well-highlighted contributing regions for the classification. Conclusion: The proposed automated method can classify class 1 and 2 cases as accurately as the level of a human expert. This method may be a useful tool to facilitate clinical trials investigating different types of kidney morphology and for clinical management of patients with autosomal dominant polycystic kidney disease (ADPKD).

Generative AI in Medical Imaging: Applications, Challenges, and Ethics.

Medical imaging is playing an important role in diagnosis and treatment of diseases. Generative artificial intelligence (AI) have shown great potential in enhancing medical imaging tasks such as data augmentation, image synthesis, image-to-image translation, and radiology report generation. This commentary aims to provide an overview of generative AI in medical imaging, discussing applications, challenges, and ethical considerations, while highlighting future research directions in this rapidly evolving field.

Association of Longitudinal Urinary Metabolic Biomarkers With ADPKD Severity and Response to Metformin in TAME-PKD Clinical Trial Participants.

Introduction: Dysregulated cellular metabolism contributes to autosomal dominant polycystic kidney disease (ADPKD) pathogenesis. The Trial of Administration of Metformin in Polycystic Kidney Disease (TAME-PKD) tested the effects of metformin treatment over 2 years in adult ADPKD patients with mild-moderate disease severity. Metformin was found to be safe and tolerable with an insignificant trend toward reduced estimated glomerular filtration rate (eGFR) decline compared to placebo. Here we tested whether targeted urinary metabolic biomarkers measured in TAME-PKD participants correlated with disease progression, severity, and metformin treatment in cross-sectional and longitudinal analyses. Methods: Concentrations of total protein, targeted metabolites (lactate, pyruvate, and succinate), and glycolytic enzymes (pyruvate kinase-M2, lactate dehydrogenase-A, and pyruvate dehydrogenase kinase-1) were measured and normalized by creatinine or osmolality in urine specimens and compared with height-adjusted total kidney volume (htTKV) and eGFR at the different study timepoints. Results: In cross-sectional analyses utilizing placebo group data, urinary succinate normalized by creatinine negatively correlated with ln (htTKV), whereas protein excretion strongly positively correlated with ln (htTKV), and negatively correlated with eGFR. Significant time-varying negative associations occurred with eGFR and the lactate/pyruvate ratio and with urine protein normalized by osmolality, indicating correlations of these biomarkers with disease progression. In secondary analyses, urinary pyruvate normalized by osmolality was preserved in metformin-treated participants but declined in placebo over the 2-year study period with a significant between-arm difference, suggesting time-dependent urinary pyruvate changes may serve as a discriminator for metformin treatment effects in this study population. Conclusion: Proteinuria with enhanced glycolytic and reduced oxidative metabolic markers generally correlated with disease severity and risk of progression in the TAME-PKD study population.

Utility of new image-derived biomarkers for autosomal dominant polycystic kidney disease prognosis using automated instance cyst segmentation.

New image-derived biomarkers for patients affected by autosomal dominant polycystic kidney disease are needed to improve current clinical management. The measurement of total kidney volume (TKV) provides critical information for clinicians to drive care decisions. However, patients with similar TKV may present with very different phenotypes, often requiring subjective decisions based on other factors (e.g., appearance of healthy kidney parenchyma, a few cysts contributing significantly to overall TKV, etc.). In this study, we describe a new technique to individually segment cysts and quantify biometric parameters including cyst volume, cyst number, parenchyma volume, and cyst parenchyma surface area. Using data from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study the utility of these new parameters was explored, both quantitatively as well as visually. Total cyst number and cyst parenchyma surface area showed superior prediction of the slope of estimated glomerular filtration rate decline, kidney failure and chronic kidney disease stages 3A, 3B, and 4, compared to TKV. In addition, presentations such as a few large cysts contributing significantly to overall kidney volume were shown to be much better stratified in terms of outcome predictions. Thus, these new image biomarkers, which can be obtained automatically, will have great utility in future studies and clinical care for patients affected by autosomal dominant polycystic kidney disease.

Evaluating the Safety and effectivenesS in adult KorEaN patients treated with Tolvaptan for management of autosomal domInAnt poLycystic kidney disease (ESSENTIAL): short-term outcomes during the titration period.

BACKGROUND: Tolvaptan reduces height-adjusted total kidney volume (htTKV) and renal function decline in autosomal dominant polycystic kidney disease (ADPKD). This study was aimed at investigating the efficacy and safety of tolvaptan in Korean patients with ADPKD during the titration period. METHODS: This study is a multicenter, single-arm, open-label phase 4 study. We enrolled 108 patients with ADPKD (age, 19-50 years) with an estimated glomerular filtration rate (eGFR) of >30 mL/min/1.73 m2 and factors defined as indicative of rapid disease progression. After tolvaptan titration, we evaluated efficacy and side effects and assessed factors associated with the effects. RESULTS: After titration for 4 weeks, eGFR and htTKV decreased by 6.4 ± 7.9 mL/min/1.73 m2 and 16 ± 45 mL/m, respectively. No serious adverse drug reactions were observed during the titration period. The greatest eGFR decline was observed in the first week, with a starting tolvaptan dose of 45 mg. Multivariate linear regression for htTKV decline showed that the greater the change in urine osmolality (Uosm), the greater the decrease in htTKV (ß, 0.436; p = 0.009) in the 1D group stratified by the Mayo Clinic image classification. Higher baseline eGFR was related to a higher htTKV reduction rate in the 1E group (ß, -0.642; p = 0.009). CONCLUSION: We observed short-term effects and safety during the tolvaptan titration period. The decline of htTKV can be predicted as a short-term effect of tolvaptan by observing Uosm changes from baseline to end of titration in 1D and baseline eGFR in 1E groups.

A Deep Learning Approach for Automated Segmentation of Kidneys and Exophytic Cysts in Individuals with Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: Total kidney volume (TKV) is an important imaging biomarker in autosomal dominant polycystic kidney disease (ADPKD). Manual computation of TKV, particularly with the exclusion of exophytic cysts, is laborious and time consuming. METHODS: We developed a fully automated segmentation method for TKV using a deep learning network to selectively segment kidney regions while excluding exophytic cysts. We used abdominal T2 -weighted magnetic resonance images from 210 individuals with ADPKD who were divided into two groups: one group of 157 to train the network and a second group of 53 to test it. With a 3D U-Net architecture using dataset fingerprints, the network was trained by K-fold cross-validation, in that 80% of 157 cases were for training and the remaining 20% were for validation. We used Dice similarity coefficient, intraclass correlation coefficient, and Bland-Altman analysis to assess the performance of the automated segmentation method compared with the manual method. RESULTS: The automated and manual reference methods exhibited excellent geometric concordance (Dice similarity coefficient: mean±SD, 0.962±0.018) on the test datasets, with kidney volumes ranging from 178.9 to 2776.0 ml (mean±SD, 1058.5±706.8 ml) and exophytic cysts ranging from 113.4 to 2497.6 ml (mean±SD, 549.0±559.1 ml). The intraclass correlation coefficient was 0.9994 (95% confidence interval, 0.9991 to 0.9996; P<0.001) with a minimum bias of -2.424 ml (95% limits of agreement, -49.80 to 44.95). CONCLUSIONS: We developed a fully automated segmentation method to measure TKV that excludes exophytic cysts and has an accuracy similar to that of a human expert. This technique may be useful in clinical studies that require automated computation of TKV to evaluate progression of ADPKD and response to treatment.

Volume Progression and Imaging Classification of Polycystic Liver in Early Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND AND OBJECTIVES: The progression of polycystic liver disease is not well understood. The purpose of the study is to evaluate the associations of polycystic liver progression with other disease progression variables and classify liver progression on the basis of patient's age, height-adjusted liver cystic volume, and height-adjusted liver volume. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Prospective longitudinal magnetic resonance images from 670 patients with early autosomal dominant polycystic kidney disease for up to 14 years of follow-up were evaluated to measure height-adjusted liver cystic volume and height-adjusted liver volume. Among them, 245 patients with liver cyst volume >50 ml at baseline were included in the longitudinal analysis. Linear mixed models on log-transformed height-adjusted liver cystic volume and height-adjusted liver volume were fitted to approximate mean annual rate of change for each outcome. The association of sex, body mass index, genotype, baseline height-adjusted total kidney volume, and Mayo imaging class was assessed. We calculated height-adjusted liver cystic volume ranges for each specific age and divided them into five classes on the basis of annual percentage increase in height-adjusted liver cystic volume. RESULTS: The mean annual growth rate of height-adjusted liver cystic volume was 12% (95% confidence interval, 11.1% to 13.1%; P<0.001), whereas that for height-adjusted liver volume was 2% (95% confidence interval, 1.9% to 2.6%; P<0.001). Women had higher baseline height-adjusted liver cystic volume than men, but men had higher height-adjusted liver cystic volume growth rate than women by 2% (95% confidence interval, 0.4% to 4.5%; P=0.02). Whereas the height-adjusted liver cystic volume growth rate decreased in women after menopause, no decrease was observed in men at any age. Body mass index, genotype, and baseline height-adjusted total kidney volume were not associated with the growth rate of height-adjusted liver cystic volume or height-adjusted liver volume. According to the height-adjusted liver cystic volume growth rate, patients were classified into five classes (number of women, men in each class): A (24, six); B (44, 13); C (43, 48); D (28, 17); and E (13, nine). CONCLUSIONS: Compared with height-adjusted liver volume, the use of height-adjusted liver cystic volume showed greater separations in volumetric progression of polycystic liver disease. Similar to the Mayo imaging classification for the kidney, the progression of polycystic liver disease may be categorized on the basis of patient's age and height-adjusted liver cystic volume.

Novel 3D capsule device to restrict kidney volume expansion on polycystic kidney progression: feasibility study in a rat model.

BACKGROUND: Cystogenesis in polycystic kidney disease (PKD) is likely accelerated by various renal insults, including crystal deposition, that activate renal tubule obstruction and dilation. We developed a capsule-based device that can be applied to cystic kidneys to restrict tubular lumen dilatation and cyst expansion. METHODS: Kidney capsule devices were designed from computed tomography images of wild-type and Cy/+ rats. Capsule devices were surgically implanted on kidneys in six surgical sessions over a period of 14 months in 7 wild-type rats of 6.5-8 weeks (3 sham operations, 2 right, 2 left) and 6 Cy/+ rats of 6.5 weeks (2 sham, 3 left, 1 bilateral). After surgery, the rats were followed for 5.4-12.4 weeks' growth and sacrificed to retrieve the kidneys. During the follow-up, serum creatinine was measured and retrieved kidneys were weighed. Histological analysis including cystic area measurement and immunohistochemistry was performed. RESULTS: Morphometric capsule devices were configured and developed by an image processing technique and produced using a 3D printer. Encapsulated Cy/+ kidneys (n = 5; mean weight 3.64 g) were consistently smaller in size (by 21-36%; p < 0.001) than unencapsulated Cy/+ kidneys (n = 7; mean weight 5.52 g). Encapsulated Cy/+ kidneys (mean %cyst area: 29.4%) showed smaller histological cystic area (by 28-58%; p < 0.001) than unencapsulated Cy/+ kidneys (mean %cyst area 48.6%). Cell proliferation and macrophages were also markedly reduced in encapsulated Cy/+ kidneys, compared to unencapsulated Cy/+ kidneys. CONCLUSIONS: We report a pilot feasibility study for the application of a novel morphometric 3D capsule device to the Cy/+ rat model showing restricted kidney volume expansion on polycystic kidney disease progression.

Association of Baseline Urinary Metabolic Biomarkers with ADPKD Severity in TAME-PKD Clinical Trial Participants.

BACKGROUND: Recent work suggests that dysregulated cellular metabolism may play a key role in the pathogenesis of autosomal dominant polycystic kidney disease (ADPKD). The TAME-PKD clinical trial is testing the safety, tolerability, and efficacy of metformin, a regulator of cell metabolism, in patients with ADPKD. This study investigates the cross-sectional association of urinary metabolic biomarkers with ADPKD severity among TAME-PKD trial participants at baseline. METHODS: Concentrations of total protein, targeted metabolites (lactate, pyruvate, succinate, and cAMP), and key glycolytic enzymes (pyruvate kinase M2 [PKM2], lactate dehydrogenase A [LDHA], and pyruvate dehydrogenase kinase 1 [PDK1]) were measured by ELISA, enzymatic assays, and immunoblotting in baseline urine specimens of 95 TAME-PKD participants. These analytes, normalized by urinary creatinine or osmolality to estimate excretion, were correlated with patients' baseline height-adjusted total kidney volumes (htTKVs) by MRI and eGFR. Additional analyses were performed, adjusting for participants' age and sex, using multivariable linear regression. RESULTS: Greater htTKV correlated with lower eGFR (r=-0.39; P=0.0001). Urinary protein excretion modestly correlated with eGFR (negatively) and htTKV (positively). Urinary cAMP normalized to creatinine positively correlated with eGFR. Among glycolytic enzymes, PKM2 and LDHA excretion positively correlated with htTKV, whereas PKM2 excretion negatively correlated with eGFR. These associations remained significant after adjustments for age and sex. Moreover, in adjusted models, succinate excretion was positively associated with eGFR, and protein excretion was more strongly associated with both eGFR and htTKV in patients <43 years old. CONCLUSIONS: Proteinuria correlated with ADPKD severity, and urinary excretion of PKM2 and LDHA correlated with ADPKD severity at baseline in the TAME-PKD study population. These findings are the first to provide evidence in human urine samples that upregulated glycolytic flux is a feature of ADPKD severity. Future analysis may reveal if metformin treatment affects both disease progression and the various urinary metabolic biomarkers in patients throughout the study.

Primary results of the randomized trial of metformin administration in polycystic kidney disease (TAME PKD).

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by growth of kidney cysts and glomerular filtration rate (GFR) decline. Metformin was found to impact cystogenesis in preclinical models of polycystic disease, is generally considered safe and may be a promising candidate for clinical investigation in ADPKD. In this phase 2 two-year trial, we randomly assigned 97 patients, 18-60 years of age, with ADPKD and estimated GFR over 50 ml/min/1.73 m2, in a 1:1 ratio to receive metformin or placebo twice daily. Primary outcomes were medication safety and tolerability. Secondary outcomes included estimated GFR decline, and total kidney volume growth. Thirty-eight metformin and 39 placebo participants still received study product at 24-months. Twenty-one participants in the metformin arm reduced drug dose due to inability to tolerate, compared with 14 in the placebo arm (not significant). Proportions of participants experiencing serious adverse events was similar between the groups. The Gastrointestinal Symptoms Rating Scale score was low at baseline and did not significantly change over time. The annual change for estimated GFR was -1.71 with metformin and -3.07 ml/min/1.73m2 per year with placebo (mean difference 1.37 {-0.70, 3.44} ml/min/1.73m2), while mean annual percent change in height-adjusted total kidney volume was 3.87% in metformin and 2.16% per year in placebo, (mean difference 1.68% {-2.11, 5.62}). Thus, metformin in adults with ADPKD was found to be safe and tolerable while slightly reducing estimated GFR decline but not to a significant degree. Hence, evaluation of efficacy requires a larger trial, with sufficient power to detect differences in endpoints.

Prognostic Value of Fibroblast Growth Factor 23 in Autosomal Dominant Polycystic Kidney Disease.

INTRODUCTION: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive cyst growth and a loss of functioning renal mass, but a decline in glomerular filtration rate (GFR) and onset of end-stage renal disease (ESRD) occur late in the disease course. There is therefore a great need for early prognostic biomarkers in this disorder. METHODS: We measured baseline serum fibroblast growth factor 23 (FGF23) levels in 192 patients with ADPKD from the Consortium for Radiologic Imaging Studies of PKD (CRISP) cohort that were followed for a median of 13 years and tested the association between FGF23 levels and change over time in height-adjusted total kidney volume (htTKV), GFR, and time to the composite endpoints of ESRD, death, and doubling of serum creatinine. RESULTS: Patients in the highest quartile for baseline FGF23 level had a higher rate of increase in htTKV (0.95% per year, P = 0.0016), and faster rate of decline in GFR (difference of -1.03 ml/min/1.73 m2 per year, P = 0.005) compared with the lowest quartile, after adjusting for other covariates, including htTKV and genotype. The highest quartile of FGF23 was also associated with a substantial increase in risk for the composite endpoint of ESRD, death, or doubling of serum creatinine (hazard ratio [HR] of 2.45 in the fully adjusted model, P = 0.03). CONCLUSION: FGF23 is a prognostic biomarker for disease progression and clinically important outcomes in ADPKD, and has additive value to established imaging and genetic biomarkers.

The value of genotypic and imaging information to predict functional and structural outcomes in ADPKD.

BACKGROUNDA treatment option for autosomal dominant polycystic kidney disease (ADPKD) has highlighted the need to identify rapidly progressive patients. Kidney size/age and genotype have predictive power for renal outcomes, but their relative and additive value, plus associated trajectories of disease progression, are not well defined.METHODSThe value of genotypic and/or kidney imaging data (Mayo Imaging Class; MIC) to predict the time to functional (end-stage kidney disease [ESKD] or decline in estimated glomerular filtration rate [eGFR]) or structural (increase in height-adjusted total kidney volume [htTKV]) outcomes were evaluated in a Mayo Clinic PKD1/PKD2 population, and eGFR and htTKV trajectories from 20-65 years of age were modeled and independently validated in similarly defined CRISP and HALT PKD patients.RESULTSBoth genotypic and imaging groups strongly predicted ESKD and eGFR endpoints, with genotype improving the imaging predictions and vice versa; a multivariate model had strong discriminatory power (C-index = 0.845). However, imaging but not genotypic groups predicted htTKV growth, although more severe genotypic and imaging groups had larger kidneys at a young age. The trajectory of eGFR decline was linear from baseline in the most severe genotypic and imaging groups, but it was curvilinear in milder groups. Imaging class trajectories differentiated htTKV growth rates; severe classes had rapid early growth and large kidneys, but growth later slowed.CONCLUSIONThe value of imaging, genotypic, and combined data to identify rapidly progressive patients was demonstrated, and reference values for clinical trials were provided. Our data indicate that differences in kidney growth rates before adulthood significantly define patients with severe disease.FUNDINGNIDDK grants: Mayo DK058816 and DK090728; CRISP DK056943, DK056956, DK056957, and DK056961; and HALT PKD DK062410, DK062408, DK062402, DK082230, DK062411, and DK062401.

Expanded Imaging Classification of Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: The Mayo Clinic imaging classification of autosomal dominant polycystic kidney disease (ADPKD) uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk for disease progression. However, this classification applies only to patients with typical diffuse cystic disease (class 1). Because htTKV poorly predicts eGFR decline for the 5%-10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved. METHODS: Of 558 adults with ADPKD in the HALT-A study, we identified 25 patients of class 2A with prominent exophytic cysts (class 2Ae) and 43 patients of class 1 with prominent exophytic cysts; we recalculated their htTKVs to exclude exophytic cysts. Using original and recalculated htTKVs in association with imaging classification in logistic and mixed linear models, we compared predictions for developing CKD stage 3 and for eGFR trajectory. RESULTS: Using recalculated htTKVs increased specificity for developing CKD stage 3 in all participants from 82.6% to 84.2% after adjustment for baseline age, eGFR, BMI, sex, and race. The predicted proportion of class 2Ae patients developing CKD stage 3 using a cutoff of 0.5 for predicting case status was better calibrated to the observed value of 13.0% with recalculated htTKVs (45.5%) versus original htTKVs (63.6%). Using recalculated htTKVs reduced the mean paired difference between predicted and observed eGFR from 17.6 (using original htTKVs) to 4.0 ml/min per 1.73 m2 for class 2Ae, and from -1.7 (using original htTKVs) to 0.1 ml/min per 1.73 m2 for class 1. CONCLUSIONS: Use of a recalculated htTKV measure that excludes prominent exophytic cysts facilitates inclusion of class 2 patients and reclassification of class 1 patients in the Mayo classification model.

Detection and characterization of mosaicism in autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited, progressive nephropathy accounting for 4-10% of end stage renal disease worldwide. PKD1 and PKD2 are the most common disease loci, but even accounting for other genetic causes, about 7% of families remain unresolved. Typically, these unsolved cases have relatively mild kidney disease and often have a negative family history. Mosaicism, due to de novo mutation in the early embryo, has rarely been identified by conventional genetic analysis of ADPKD families. Here we screened for mosaicism by employing two next generation sequencing screens, specific analysis of PKD1 and PKD2 employing long-range polymerase chain reaction, or targeted capture of cystogenes. We characterized mosaicism in 20 ADPKD families; the pathogenic variant was transmitted to the next generation in five families and sporadic in 15. The mosaic pathogenic variant was newly discovered by next generation sequencing in 13 families, and these methods precisely quantified the level of mosaicism in all. All of the mosaic cases had PKD1 mutations, 14 were deletions or insertions, and 16 occurred in females. Analysis of kidney size and function showed the mosaic cases had milder disease than a control PKD1 population, but only a few had clearly asymmetric disease. Thus, in a typical ADPKD population, readily detectable mosaicism by next generation sequencing accounts for about 1% of cases, and about 10% of genetically unresolved cases with an uncertain family history. Hence, identification of mosaicism is important to fully characterize ADPKD populations and provides informed prognostic information.

Baseline Characteristics and Patient-Reported Outcomes of ADPKD Patients in the Multicenter TAME-PKD Clinical Trial.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) has been associated with metabolic disturbances characterized by downregulation of AMP-activated protein kinase (AMPK), a critical sensor of the cellular energy status. Therapeutic activation of AMPK by metformin could inhibit cyst enlargement by inhibition of both the mammalian target of rapamycin pathway and fluid secretion via the CFTR chloride channel. METHODS: We designed a phase-2, randomized, placebo-controlled, clinical trial to assess the safety, tolerability, and efficacy of metformin on total kidney volume in adults without diabetes (age 18-60 years) with ADPKD and eGFR of ≥50 ml/min per 1.73 m2. There were no eligibility criteria relating to kidney volume. In addition to demographics and clinical/family history, baseline parameters included eGFR, total kidney and liver volumes measured by MRI, and patient-reported outcomes were ascertained by the Medical Outcomes Study Short Form-36, the Gastrointestinal Safety Rating Scale, and the HALT-PKD pain questionnaire. RESULTS: We successfully randomized 97 participants recruited from two university-based clinical sites in Baltimore and Boston. The mean age of participants was 41.9 years, 72% were female, and 94% of participants were White. The majority of study participants had early stage disease, with a mean eGFR of 86.8±19.0 ml/min per 1.73 m2. Approximately half of the study participants (48%) were classified as high risk for progression (Mayo imaging classes 1C, 1D, or 1E). There was no correlation between kidney and/or liver size and health-related quality of life (HRQoL) or gastrointestinal symptom severity. CONCLUSIONS: We report successful recruitment in this ongoing, novel, clinical trial of metformin in ADPKD, with a study sample comprising patients with early stage disease and nearly a half of participants considered at high estimated risk for progression. Participants reported a low gastrointestinal symptom burden at baseline, and HRQoL similar to that of the general population, with no differences in symptoms or HRQoL related to organomegaly. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Metformin as a Novel Therapy for Autosomal Dominant Polycystic Kidney Disease (TAME), NCT02656017.

Growth Pattern of Kidney Cyst Number and Volume in Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND AND OBJECTIVES: To evaluate the growth pattern of kidney cyst number and cyst volume in association with kidney size, demographics, and genotypes in autosomal dominant polycystic kidney disease. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Kidney cyst number and cyst volume were measured from serial magnetic resonance images, giving a maximum follow-up of 14.23 years, from 241 patients with autosomal dominant polycystic kidney disease (15-46 years old at baseline). The growth pattern was analyzed, in association with sex, age, height-adjusted total kidney volume, and genotype, using linear mixed models of repeated measurements and tests of interactions with age (as a time-dependent covariate) to assess rates of change over time. Models were also fit using Irazabal class. Genotypic groups were characterized as either (1) PKD1 truncating, PKD1 nontruncating, and PKD2 plus patients with no mutation detected; or (2) in combination with PKD1 mutation strength groups. RESULTS: Imaging and genetic data were collected (at least one visit) for 236 participants. The mean height-adjusted total cyst number increased exponentially over time from a baseline value of 762 to 1715 at the last clinic visit, while the mean height-adjusted total cyst volume increased exponentially from 305 to 770 ml. Height-adjusted total kidney volume, height-adjusted total cyst number, and height-adjusted total cyst volume were all highly correlated over time. Female participants and participants with larger height-adjusted total kidney volume at baseline showed smaller rates of change in the log of height-adjusted total cyst number and cyst volume. PKD1 was associated with significant increases in both cyst number and volume at a given age, but genotype did not significantly affect the rate of growth. CONCLUSIONS: Both height-adjusted total cyst number and height-adjusted total cyst volume increased exponentially and more than doubled over 14.23 years of follow-up. Compared with PKD2 plus no mutation detected, PKD1 was associated with a greater cyst number and volume at a given age, but no significant difference in the rate of growth.