Mutation detection through exome sequencing allows simultaneous analysis of all coding sequences of genes. However, it cannot yet replace Sanger sequencing (SS) in diagnostics because of incomplete representation and coverage of exons leading to missing clinically relevant mutations. Targeted next‐generation sequencing (NGS), in which a selected fraction of genes is sequenced, may circumvent these shortcomings. We aimed to determine whether the sensitivity and specificity of targeted NGS is equal to those of SS. We constructed a targeted enrichment kit that includes 48 genes associated with hereditary cardiomyopathies. In total, 84 individuals with cardiomyopathies were sequenced using 151 bp paired‐end reads on an Illumina MiSeq sequencer. The reproducibility was tested by repeating the entire procedure for five patients. The coverage of ≥30 reads per nucleotide, our major quality criterion, was 99% and in total ∼21,000 variants were identified. Confirmation with SS was performed for 168 variants (155 substitutions, 13 indels). All were confirmed, including a deletion of 18 bp and an insertion of 6 bp. The reproducibility was nearly 100%. We demonstrate that targeted NGS of a disease‐specific subset of genes is equal to the quality of SS and it can therefore be reliably implemented as a stand‐alone diagnostic test.

Clinical and genetic heterogeneity in monogenetic disorders represents a major diagnostic challenge. Although the presence of particular clinical features may aid in identifying a specific cause in some cases, the majority of patients remain undiagnosed. Here, we investigated the utility of whole-exome sequencing as a diagnostic approach for establishing a molecular diagnosis in a highly heterogeneous group of patients with varied intellectual disability and microcephaly. Whole-exome sequencing was performed in 38 patients, including three sib-pairs, in addition to or in parallel with genetic analyses that were performed during the diagnostic work-up of the study participants. In ten out of these 35 families (29 %), we found mutations in genes already known to be related to a disorder in which microcephaly is a main feature. Two unrelated patients had mutations in the ASPM gene. In seven other patients we found mutations in RAB3GAP1, RNASEH2B, KIF11, ERCC8, CASK, DYRK1A and BRCA2. In one of the sib-pairs, mutations were found in the RTTN gene. Mutations were present in seven out of our ten families with an established etiological diagnosis with recessive inheritance. We demonstrate that whole-exome sequencing is a powerful tool for the diagnostic evaluation of patients with highly heterogeneous neurodevelopmental disorders such as intellectual disability with microcephaly. Our results confirm that autosomal recessive disorders are highly prevalent among patients with microcephaly.

We present Gene-Aware Variant INterpretation (GAVIN), a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%. This accuracy is unmatched by 12 other tools. We provide GAVIN as an online MOLGENIS service to annotate VCF files and as an open source executable for use in bioinformatic pipelines. It can be found at http://molgenis.org/gavin .

Newborn screening (NBS) aims to identify neonates with severe conditions for whom immediate treatment is required. Currently, a biochemistry-first approach is used to identify these disorders, which are predominantly inherited meta1bolic disorders (IMD). Next-generation sequencing (NGS) is expected to have some advantages over the current approach, for example the ability to detect IMDs that meet all screening criteria but lack an identifiable biochemical footprint. We have now designed a technical study to explore the use of NGS techniques as a first-tier approach in NBS. Here, we describe the aim and set-up of the NGS-first for the NBS (NGSf4NBS) project, which will proceed in three steps. In Step 1, we will identify IMDs eligible for NGS-first testing, based on treatability. In Step 2, we will investigate the feasibility, limitations and comparability of different technical NGS approaches and analysis workflows for NBS, eventually aiming to develop a rapid NGS-based workflow. Finally, in Step 3, we will prepare for the incorporation of this workflow into the existing Dutch NBS program and propose a protocol for referral of a child after a positive NGS test result. The results of this study will be the basis for an additional analytical route within NBS that will be further studied for its applicability within the NBS program, e.g., regarding the ethical, legal, financial and social implications.

In this study, we compare next-generation sequencing (NGS) approaches (targeted panel (tNGS), whole exome sequencing (WES), and whole genome sequencing (WGS)) for application in newborn screening (NBS). DNA was extracted from dried blood spots (DBS) from 50 patients with genetically confirmed inherited metabolic disorders (IMDs) and 50 control samples. One hundred IMD-related genes were analyzed. Two data-filtering strategies were applied: one to detect only (likely) pathogenic ((L)P) variants, and one to detect (L)P variants in combination with variants of unknown significance (VUS). The variants were filtered and interpreted, defining true/false positives (TP/FP) and true/false negatives (TN/FN). The variant filtering strategies were assessed in a background cohort (BC) of 4833 individuals. Reliable results were obtained within 5 days. TP results (47 patient samples) for tNGS, WES, and WGS results were 33, 31, and 30, respectively, using the (L)P filtering, and 40, 40, and 38, respectively, when including VUS. FN results were 11, 13, and 14, respectively, excluding VUS, and 4, 4, and 6, when including VUS. The remaining FN were mainly samples with a homozygous VUS. All controls were TN. Three BC individuals showed a homozygous (L)P variant, all related to a variable, mild phenotype. The use of NGS-based workflows in NBS seems promising, although more knowledge of data handling, automated variant interpretation, and costs is needed before implementation.

Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed. NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies. NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.