Background A considerable minority of patients on waiting lists for kidney transplantation either have no diagnosis (and fall into the subset of undiagnosed cases) because kidney biopsy was not performed or histological findings were non-specific, or do not fall into any well-defined clinical category. Some of these patients might be affected by a previously unrecognised monogenic disease. Methods Through a multidisciplinary cooperative effort, we built an analytical pipeline to identify patients with chronic kidney disease (CKD) with a clinical suspicion of a monogenic condition or without a well-defined diagnosis. Following the stringent phenotypical and clinical characterization required by the flowchart, candidates meeting these criteria were further investigated by clinical exome sequencing followed by in silico analysis of 225 kidney-disease-related genes. Results By using an ad hoc web-based platform, we enrolled 160 patients from 13 different Nephrology and Genetics Units located across the Piedmont region over 15 months. A preliminary “remote” evaluation based on well-defined inclusion criteria allowed us to define eligibility for NGS analysis. Among the 138 recruited patients, 52 (37.7%) were children and 86 (62.3%) were adults. Up to 48% of them had a positive family history for kidney disease. Overall, applying this workflow led to the identification of genetic variants potentially explaining the phenotype in 78 (56.5%) cases. Conclusions These results underline the importance of clinical exome sequencing as a versatile and highly useful, non-invasive tool for genetic diagnosis of kidney diseases. Identifying patients who can benefit from targeted therapies, and improving the management of organ transplantation are further expected applications.
Purpose Inherited kidney diseases are among the leading causes of kidney failure in children, resulting in increased mortality, high healthcare costs and need for organ transplantation. Next-generation sequencing technologies can help in the diagnosis of rare monogenic conditions, allowing for optimized medical management and therapeutic choices. Methods Clinical exome sequencing (CES) was performed on a cohort of 191 pediatric patients from a single institution, followed by Sanger sequencing to confirm identified variants and for family segregation studies. Results All patients had a clinical diagnosis of kidney disease: the main disease categories were glomerular diseases (32.5%), ciliopathies (20.4%), CAKUT (17.8%), nephrolithiasis (11.5%) and tubular disease (10.5%). 7.3% of patients presented with other conditions. A conclusive genetic test, based on CES and Sanger validation, was obtained in 37.1% of patients. The highest detection rate was obtained for ciliopathies (74.4%), followed by nephrolithiasis (45.5%), tubular diseases (45%), while most glomerular diseases and CAKUT remained undiagnosed. Conclusions Results indicate that genetic testing consistently used in the diagnostic workflow of children with chronic kidney disease can (i) confirm clinical diagnosis, (ii) provide early diagnosis in the case of inherited conditions, (iii) find the genetic cause of previously unrecognized diseases and (iv) tailor transplantation programs.
Background and Aims Autosomal dominant PKD determines formation of multiple cysts predominantly in the kidneys and usually becomes symptomatic during adulthood and can lead to renal failure. In contrast, in autosomal recessive PKD cysts occur in both the kidneys and the liver and usually presents an earlier onset. Obtaining genetic diagnosis is important to confirm clinical diagnosis and is required before treating with vasopressin 2 receptor blockers, which are the only drugs known to slow down the disease. Furthermore, in the case of kidney transplant from a living family member it is essential to exclude the presence of the mutation in the donor. We used clinical exome sequencing to provide genetic diagnosis to a cohort of patients with a clinical suspicion of PKD. Method 175 patients were referred to the Immunogenetics and Transplant Biology Service of the Turin University Hospital through a network of nephrology centers operating in the Piedmont region. Some patients were referred following genetic counseling. All patients signed an informed consent and the referring physicians provided relevant clinical data. DNA from eligible patients was extracted, checked for integrity, quantified and used for library preparation. A clinical exome sequencing (CES) kit by Illumina was used, allowing the analysis of 6,700 clinically relevant genes. Results Out of the 175 recruited patients eligible for CES, 38 (21.7%) had a clinical suspicion or diagnosis of PKD, with 50% of them presenting family history. The majority of the cohort was represented by male subjects (60.5%) and included both children (34.2%) and adults. The analytical approach was based on initial analysis of genes responsible for PKD (PKD1, PKD2 and PKHD1). If no mutation could be identified, analysis was then extended to a panel of 99 genes responsible for ciliopathies. This approach led to the identification of causative variants in 33/38 (86.8%) of the PKD cohort, while no variant could be identified in 5/38 patients. In 5/33 (15.2%) patients, mutations were inconclusive as found in heterozygosity in genes known to have an autosomal recessive mode of inheritance, while 27/33 (81.8%) were in line with the initial clinical suspicion/diagnosis. Of these, the majority was represented by missense mutations (12), followed by frameshift and nonsense mutations (6 each) and 3 splicing variants. As expected, the majority of mutations were found in PKD1 17/27 (63%), PKD2 3/27 (11.1%) and PKHD1 2/27 (7.4%). In these two latter patients, variants were found as compound heterozygosity. We also found mutations in other genes known to cause cysts, including TSC2 and CPT2. Of note, in 7 patients carrying PKD1 mutations, we found a second variant in PKD1 or PKHD1. Interestingly, when looking at patients characterized by kidney failure but lacking a clinical suspicion at recruitment or diagnosed with other phenotypes (66/175), we found variants in PKD1 and in PKD2 in 11 patients (9 and 2, respectively). Of all identified variants in PKD1, PKD2 and PKHD1 genes, 17.6% were annotated as pathogenic (C5), 41.2% were likely pathogenic (C4) and 41.2% were variants of unknown significance (C3). 19 variants in these genes were not previously reported. All the variants found in genes responsible for PKD were validated and confirmed by Sanger sequencing. Family segregation studies are ongoing. Finally, it is worth mentioning that in a portion of cases (5/38) with clinical and phenotypic features of PKD, supported also by a positive family history, we could not detect mutations in causative genes. These results may be explained by the presence of intronic variants, in line with data reported in literature. Conclusion These results demonstrate that CES may be applied to PKD patients to identify causative variants during their routine diagnostic flow. Furthermore, CES may be a useful tool to detect mutations in PKD-related genes in patients with undiagnosed diseases, considering its rapidly decreasing costs.
Background and Aims next-generation sequencing (NGS) technologies are becoming a powerful diagnostic tool in precision medicine. Specifically, exome sequencing can help in the diagnosis of selected diseases, in their medical management and therapeutic choices. Inherited kidney diseases (IKD) are among the major causes for kidney failure, both in children and adults, resulting in increased mortality, high health care costs and need for organ transplantation. In addition, it is worth mentioning that a significant proportion of patients in the kidney transplant lacks a clear diagnosis. This subset of diseases may thus benefit from the application of NGS technology, as the simultaneous investigation of hundreds of genes can lead to the identification of causative variants in a vast population of patients. The aim of this study is to validate the use of a clinical exome sequencing approach in the diagnostic flow for kidney diseases leading to organ failure to i) confirm the clinical diagnosis, ii) find the genetic cause of previously unrecognized diseases and iii) improve the outcome of organ transplantation by excluding live-donors carrying the same mutational burden. Method 160 patients were recruited, directly or following a genetic counseling, exploiting a network of 21 nephrology centers spread across the Piedmont region, coordinated by the “Centro Regionale Trapianti (CRT)” of Torino. Patients were then evaluated for NGS eligibility. DNA extracted from blood samples was checked for integrity, quantified and used for library preparation. A clinical exome sequencing (CES) kit by Illumina was used, allowing for targeted capture, enrichment and sequencing of 6700 clinically relevant genes. Reads were aligned to hg37 reference genome using the Isaac enrichment tool and variants filtered using an ad-hoc set up pipeline of analysis. Results clinical exome sequencing was performed on a diagnostic cohort of 138 patients, both children (37.7%) and adults (62.3%), with a prevalence of male subjects (56.5%). The majority of the cohort (51.5%) presented a positive family history for kidney disease, while 22 patients were excluded from the study as organ failure was most likely the result of secondary events. The cohort was highly heterogeneous with 21% of patients presenting with ciliopathies, 18.1% with glomerular disease, 7.2% with tubular disease while the remaining cohort presented other diseases or was undiagnosed (44.3%). An ad hoc analytical pipeline was designed, based on selected genotype-phenotype correlation database, filter-in metrics, inheritance model and annotation of variants based on public databases and in-silico prediction tools. By adopting well defined criteria of recruitment and analysis, causative genes were identified in 61.6% of cases and in the 57.3% of cases results were in line with the original diagnostic hypothesis. Moreover, 50.8% of cases with organ failure for unknown reasons were solved with the identification of causative genes. Out of the 133 total variants found in the cohort, 63 were classified as pathogenic or likely pathogenic. The remaining 70 identified variants were annotated as variant of unknown significance and will be further investigated. Conclusion Taken together, these results show that CES is a powerful non-invasive tool for the genetic diagnosis of IKD. Identification of disease causative variants may represent a critical step for the diagnosis, clinical management of the patients, and potentially for optimal live-donor selection.
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