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Background: The ability to discover genetic variants in a patient runs far ahead of the ability to interpret them. Databases with accurate descriptions of the causal relationship between the variants and the phenotype are valuable since these are critical tools in clinical genetic diagnostics. Here, we introduce a comprehensive and global genotype-phenotype database focusing on rare diseases., Methods: This database (CentoMD ® ) is a browser-based tool that enables access to a comprehensive, independently curated system utilizing stringent high-quality criteria and a quickly growing repository of genetic and human phenotype ontology (HPO)-based clinical information. Its main goals are to aid the evaluation of genetic variants, to enhance the validity of the genetic analytical workflow, to increase the quality of genetic diagnoses, and to improve evaluation of treatment options for patients with hereditary diseases. The database software correlates clinical information from consented patients and probands of different geographical backgrounds with a large dataset of genetic variants and, when available, biomarker information. An automated follow-up tool is incorporated that informs all users whenever a variant classification has changed. These unique features fully embedded in a CLIA/CAP-accredited quality management system allow appropriate data quality and enhanced patient safety., Results: More than 100,000 genetically screened individuals are documented in the database, resulting in more than 470 million variant detections. Approximately, 57% of the clinically relevant and uncertain variants in the database are novel. Notably, 3% of the genetic variants identified and previously reported in the literature as being associated with a particular rare disease were reclassified, based on internal evidence, as clinically irrelevant., Conclusions: The database offers a comprehensive summary of the clinical validity and causality of detected gene variants with their associated phenotypes, and is a valuable tool for identifying new disease genes through the correlation of novel genetic variants with specific, well-defined phenotypes.

Genetic testing for cystic fibrosis and CFTR-related disorders mostly relies on laborious molecular tools that use Sanger sequencing to scan for mutations in the CFTR gene. We have explored a more efficient genetic screening strategy based on next-generation sequencing (NGS) of the CFTR gene. We validated this approach in a cohort of 177 patients with previously known CFTR mutations and polymorphisms. Genomic DNA was amplified using the Ion AmpliSeq™ CFTR panel. The DNA libraries were pooled, barcoded, and sequenced using an Ion Torrent PGM sequencer. The combination of different robust bioinformatics tools allowed us to detect previously known pathogenic mutations and polymorphisms in the 177 samples, without detecting spurious pathogenic calls. In summary, the assay achieves a sensitivity of 94.45% (95% CI: 92% to 96.9%), with a specificity of detecting nonvariant sites from the CFTR reference sequence of 100% (95% CI: 100% to 100%), a positive predictive value of 100% (95% CI: 100% to 100%), and a negative predictive value of 99.99% (95% CI: 99.99% to 100%). In addition, we describe the observed allelic frequencies of 94 unique definitely and likely pathogenic, uncertain, and neutral CFTR variants, some of them not previously annotated in the public databases. Strikingly, a seven exon spanning deletion as well as several more technically challenging variants such as pathogenic poly-thymidine-guanine and poly-thymidine (poly-TG-T) tracts were also detected. Targeted NGS is ready to substitute classical molecular methods to perform genetic testing on the CFTR gene.

Molecular diagnostics of autosomal dominant polycystic kidney disease (ADPKD) relies on mutation screening of PKD1 and PKD2, which is complicated by extensive allelic heterogeneity and the presence of six highly homologous sequences of PKD1. To date, specific sequencing of PKD1 requires laborious long-range amplifications. The high cost and long turnaround time of PKD1 and PKD2 mutation analysis using conventional techniques limits its widespread application in clinical settings. We performed targeted next-generation sequencing (NGS) of PKD1 and PKD2. Pooled barcoded DNA patient libraries were enriched by in-solution hybridization with PKD1 and PKD2 capture probes. Bioinformatics analysis was performed using an in-house developed pipeline. We validated the assay in a cohort of 36 patients with previously known PKD1 and PKD2 mutations and five control individuals. Then, we used the same assay and bioinformatics analysis in a discovery cohort of 12 uncharacterized patients. We detected 35 out of 36 known definitely, highly likely, and likely pathogenic mutations in the validation cohort, including two large deletions. In the discovery cohort, we detected 11 different pathogenic mutations in 10 out of 12 patients. This study demonstrates that laborious long-range PCRs of the repeated PKD1 region can be avoided by in-solution enrichment of PKD1 and PKD2 and NGS. This strategy significantly reduces the cost and time for simultaneous PKD1 and PKD2 sequence analysis, facilitating routine genetic diagnostics of ADPKD.