Diagnostic yield of massively parallel sequencing in patients with chronic kidney disease of unknown etiology:rationale and design of a national prospective cohort study

INTRODUCTION: Chronic kidney disease (CKD) can be caused by a variety of systemic or primary renal diseases. The cause of CKD remains unexplained in approximately 20% of patients. Retrospective studies indicate that massively parallel sequencing (MPS)-based gene panel testing may lead to a genetic diagnosis in 12%–56% of patients with unexplained CKD, depending on patient profile. The diagnostic yield of MPS-based testing in a routine healthcare setting is unclear. Therefore, the primary aim of the VARIETY (Validation of algoRithms and IdEnTification of genes in Young patients with unexplained CKD) study is to prospectively address the diagnostic yield of MPS-based gene panel testing in patients with unexplained CKD and an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m(2) before the age of 50 years in clinical practice. METHODS AND ANALYSIS: The VARIETY study is an ongoing, prospective, nationwide observational cohort study to investigate the diagnostic yield of MPS-based testing in patients with unexplained CKD in a routine healthcare setting in the Netherlands. Patients are recruited from outpatient clinics in hospitals across the Netherlands. At least 282 patients will be included to meet the primary aim. Secondary analyses include subgroup analyses according to age and eGFR at first presentation, family history, and the presence of extrarenal symptoms. ETHICS AND DISSEMINATION: Ethical approval for the study has been obtained from the institutional review board of the University Medical Center Groningen. Study findings should inform physicians and policymakers towards optimal implementation of MPS-based diagnostic testing in patients with unexplained CKD

Pregnancy in Advanced Kidney Disease:Clinical Practice Considerations on a Challenging Combination

Background:Thanks to the advances in care, pregnancy is now attainable for the majority of young female CKD patients, although it is still a high-risk endeavor. Clinical decision-making in these cases is impacted by a myriad of factors, making (pre)pregnancy counseling a complex process. The complexities, further impacted by limited data and unknown risks regarding outcome, can cause discussions when deciding on the best care for a specific patient. Objectives:In this article, we provide an overview of the considerations and dilemmas we encounter in preconception counseling and offer our perspective on how to deal with them in daily clinical practice. Methods:The main topics we discuss in our counseling are (1) the high risk of pregnancy complications, (2) the risk of permanent CKD deterioration due to pregnancy and subsequent decreased life expectancy, (3) appropriate changes in renal medication, and (4) assisted reproduction, genetic testing, and prenatal or preimplantation genetic diagnostics. Results and Conclusions:In our clinic, we openly address moral dilemmas arising in clinical practice in pregnancy and CKD, both within the physician team and with the patient. We do this by ensuring an interpretive physician-patient interaction and shared decision-making, deliberating in a multidisciplinary setting and, if needed, with input from an expert committee

Preimplantation Genetic Testing for Monogenic Kidney Disease

BACKGROUND AND OBJECTIVES: A genetic cause can be identified for an increasing number of pediatric and adult-onset kidney diseases. Preimplantation genetic testing (formerly known as preimplantation genetic diagnostics) is a reproductive technology that helps prospective parents to prevent passing on (a) disease-causing mutation(s) to their offspring. Here, we provide a clinical overview of 25 years of preimplantation genetic testing for monogenic kidney disease in The Netherlands. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This is a retrospective cohort study of couples counseled on preimplantation genetic testing for monogenic kidney disease in the national preimplantation genetic testing expert center (Maastricht University Medical Center+) from January 1995 to June 2019. Statistical analysis was performed through chi-squared tests. RESULTS: In total, 98 couples were counseled regarding preimplantation genetic testing, of whom 53% opted for preimplantation genetic testing. The most frequent indications for referral were autosomal dominant polycystic kidney disease (38%), Alport syndrome (26%), and autosomal recessive polycystic kidney disease (9%). Of couples with at least one preimplantation genetic testing cycle with oocyte retrieval, 65% experienced one or more live births of an unaffected child. Of couples counseled, 38% declined preimplantation genetic testing for various personal and technical reasons. CONCLUSIONS: Referrals, including for adult-onset disease, have increased steadily over the past decade. Though some couples decline preimplantation genetic testing, in the couples who proceed with at least one preimplantation genetic testing cycle, almost two thirds experienced at least one live birth rate

KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p

KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p

KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p

KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p

KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p

Outcomes of Surgical Management of Familial Intrahepatic Cholestasis 1 and Bile Salt Export Protein Deficiencies

Progressive familial intrahepatic cholestasis (PFIC) with normal circulating gamma-glutamyl transpeptidase levels can result from mutations in the ATP8B1 gene (encoding familial intrahepatic cholestasis 1 [FIC1] deficiency) or the ABCB11 gene (bile salt export protein [BSEP] deficiency). We investigated the outcomes of partial external biliary diversion, ileal exclusion, and liver transplantation in these two conditions. We conducted a retrospective multicenter study of 42 patients with FIC1 deficiency (FIC1 patients) and 60 patients with BSEP deficiency (BSEP patients) who had undergone one or more surgical procedures (57 diversions, 6 exclusions, and 57 transplants). For surgeries performed prior to transplantation, BSEP patients were divided into two groups, BSEP-common (bearing common missense mutations D482G or E297G, with likely residual function) and BSEP-other. We evaluated clinical and biochemical outcomes in these patients. Overall, diversion improved biochemical parameters, pruritus, and growth, with substantial variation in individual response. BSEP-common or FIC1 patients survived longer after diversion without developing cirrhosis, being listed for or undergoing liver transplantation, or dying, compared to BSEP-other patients. Transplantation resolved cholestasis in all groups. However, FIC1 patients commonly developed hepatic steatosis, diarrhea, and/or pancreatic disease after transplant accompanied by biochemical abnormalities and often had continued poor growth. In BSEP patients with impaired growth, this generally improved after transplantation. Conclusion: Diversion can improve clinical and biochemical status in FIC1 and BSEP deficiencies, but outcomes differ depending on genetic etiology. For many patients, particularly BSEP-other, diversion is not a permanent solution and transplantation is required. Although transplantation resolves cholestasis in patients with FIC1 and BSEP deficiencies, the overall outcome remains unsatisfactory in many FIC1 patients; this is mainly due to extrahepatic manifestations.Peer reviewe

An update on the use of tolvaptan for autosomal dominant polycystic kidney disease: consensus statement on behalf of the ERA Working Group on Inherited Kidney Disorders, the European Rare Kidney Disease Reference Network and Polycystic Kidney Disease International

Approval of the vasopressin V2 receptor antagonist tolvaptan-based on the landmark TEMPO 3:4 trial-marked a transformation in the management of autosomal dominant polycystic kidney disease (ADPKD). This development has advanced patient care in ADPKD from general measures to prevent progression of chronic kidney disease to targeting disease-specific mechanisms. However, considering the long-term nature of this treatment, as well as potential side effects, evidence-based approaches to initiate treatment only in patients with rapidly progressing disease are crucial. In 2016, the position statement issued by the European Renal Association (ERA) was the first society-based recommendation on the use of tolvaptan and has served as a widely used decision-making tool for nephrologists. Since then, considerable practical experience regarding the use of tolvaptan in ADPKD has accumulated. More importantly, additional data from REPRISE, a second randomized clinical trial (RCT) examining the use of tolvaptan in later-stage disease, have added important evidence to the field, as have post hoc studies of these RCTs. To incorporate this new knowledge, we provide an updated algorithm to guide patient selection for treatment with tolvaptan and add practical advice for its use