Background and objectives Cystinuria is a rare inherited renal stone disease. Mutations in the amino acid exchanger System b 0,+ , the two subunits of which are encoded by SLC3A1 and SLC7A9, predominantly underlie this disease. The work analyzed the epidemiology of cystinuria and the influence of mutations in these two genes on disease severity in a United Kingdom cohort.Design, setting, participants, & measurements Prevalent patients were studied from 2012 to 2014 in the northeast and southwest of the United Kingdom. Clinical phenotypes were defined, and genetic analysis of SLC3A1 and SLC7A9 combining Sanger sequencing and multiplex ligation probe-dependent amplification was performed.Results In total, 76 patients (42 men and 34 women) were studied. All subjects had proven cystine stones. Median age of presentation (first stone episode) was 24 years old, but 21% of patients presented after 40 years old. Patients had varied clinical courses, with 37% of patients having $10 stone episodes; 70% had evidence of CKD, and 9% had reached ESRD as a result of cystinuria and its complications. Patients with cystinuria received a variety of different therapies, with no obvious treatment consensus. Notably, 20% of patients had staghorn calculi, with associated impaired renal function in 80% of these patients. Genetic analysis revealed that biallelic mutations were present in either SLC3A1 (n=27) or SLC7A9 (n=20); 22 patients had only one mutated allele detected (SLC3A1 in five patients and SLC7A9 in 17 patients). In total, 37 different mutant variant alleles were identified, including 12 novel mutations; 22% of mutations were caused by large gene rearrangements. No genotypephenotype association was detected in this cohort.Conclusions Patients with cystinuria in the United Kingdom often present atypically with staghorn calculi at $40 years old and commonly develop significant renal impairment. There is no association of clinical course with genotype. Treatments directed toward reducing stone burden need to be rationalized and developed to optimize patient care.

BackgroundThere are many single-gene causes of steroid-resistant nephrotic syndrome (SRNS) and the list continues to grow rapidly. Prompt comprehensive diagnostic testing is key to realising the clinical benefits of a genetic diagnosis. This report describes a bespoke-designed, targeted next-generation sequencing (NGS) diagnostic gene panel assay to detect variants in 37 genes including the ability to identify copy number variants (CNVs).MethodsThis study reports results of 302 patients referred for SRNS diagnostic gene panel analysis. Phenotype and clinical impact data were collected using a standard proforma. Candidate variants detected by NGS were confirmed by Sanger sequencing/Multiplex Ligation-dependent Probe Amplification with subsequent family segregation analysis where possible.ResultsClinical presentation was nephrotic syndrome in 267 patients and suspected Alport syndrome (AS) in 35. NGS panel testing determined a likely genetic cause of disease in 44/220 (20.0%) paediatric and 10/47 (21.3%) adult nephrotic cases, and 17/35 (48.6%) of haematuria/AS patients. Of 71 patients with genetic disease, 32 had novel pathogenic variants without a previous disease association including two with deletions of one or more exons of NPHS1 or NPHS2.ConclusionGene panel testing provides a genetic diagnosis in a significant number of patients presenting with SRNS or suspected AS. It should be undertaken at an early stage of the care pathway and include the ability to detect CNVs as an emerging mechanism for genes associated with this condition. Use of clinical genetic testing after diagnosis of SRNS has the potential to stratify patients and assist decision-making regarding management.

ObjectiveTo describe national patterns of National Health Service (NHS) analysis of mismatch repair (MMR) genes in England using individual-level data submitted to the National Disease Registration Service (NDRS) by the NHS regional molecular genetics laboratories.DesignLaboratories submitted individual-level patient data to NDRS against a prescribed data model, including (1) patient identifiers, (2) test episode data, (3) per-gene results and (4) detected sequence variants. Individualised per-laboratory algorithms were designed and applied in NDRS to extract and map the data to the common data model. Laboratory-level MMR activity audit data from the Clinical Molecular Genetics Society/Association of Clinical Genomic Science were used to assess early years’ missing data.ResultsIndividual-level data from patients undergoing NHS MMR germline genetic testing were submitted from all 13 English laboratories performing MMR analyses, comprising in total 16 722 patients (9649 full-gene, 7073 targeted), with the earliest submission from 2000. The NDRS dataset is estimated to comprise >60% of NHS MMR analyses performed since inception of NHS MMR analysis, with complete national data for full-gene analyses for 2016 onwards. Out of 9649 full-gene tests, 2724 had an abnormal result, approximately 70% of which were (likely) pathogenic. Data linkage to the National Cancer Registry demonstrated colorectal cancer was the most frequent cancer type in which full-gene analysis was performed.ConclusionThe NDRS MMR dataset is a unique national pan-laboratory amalgamation of individual-level clinical and genomic patient data with pseudonymised identifiers enabling linkage to other national datasets. This growing resource will enable longitudinal research and can form the basis of a live national genomic disease registry.

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