Assessment of parental mosaicism rates in neurodevelopmental disorders caused by apparent de novo pathogenic variants using deep sequencing.

While de novo variants (DNV) are overall at low risk of recurrence in subsequent pregnancies, a subset is at high risk due to parental mosaicism. Accurately identifying cases of parental mosaicism is therefore important for genetic counseling in clinical care. Some studies have investigated the rate of parental mosaics, but most were either limited by the sensitivity of the techniques (i.e. exome or genome sequencing), or focused on specific types of disease such as epileptic syndromes. This study aimed to determine the proportion of parental mosaicism among the DNV causing neurodevelopmental disorders (NDDs) in a series not enriched in epilepsy syndromes. We collected 189 patients with NDD-associated DNV. We applied a smMIP enrichment method and sequenced parental blood DNA samples to an average depth of 7000x. Power simulation indicated that mosaicism with an allelic fraction of 0.5% would have been detected for 87% of positions with 90% power. We observed seven parental mosaic variants (3.7% of families), of which four (2.1% of families) had an allelic fraction of less than 1%. In total, our study identifies a relatively low proportion of parental mosaicism in NDD-associated DNVs and raises the question of a biological mechanism behind the higher rates of parental mosaicism detected in other studies, particularly those focusing on epileptic syndromes.

Cost-effective sequence analysis of 113 genes in 1,192 probands with retinitis pigmentosa and Leber congenital amaurosis.

Introduction: Retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA) are two groups of inherited retinal diseases (IRDs) where the rod photoreceptors degenerate followed by the cone photoreceptors of the retina. A genetic diagnosis for IRDs is challenging since >280 genes are associated with these conditions. While whole exome sequencing (WES) is commonly used by diagnostic facilities, the costs and required infrastructure prevent its global applicability. Previous studies have shown the cost-effectiveness of sequence analysis using single molecule Molecular Inversion Probes (smMIPs) in a cohort of patients diagnosed with Stargardt disease and other maculopathies. Methods: Here, we introduce a smMIPs panel that targets the exons and splice sites of all currently known genes associated with RP and LCA, the entire RPE65 gene, known causative deep-intronic variants leading to pseudo-exons, and part of the RP17 region associated with autosomal dominant RP, by using a total of 16,812 smMIPs. The RP-LCA smMIPs panel was used to screen 1,192 probands from an international cohort of predominantly RP and LCA cases. Results and discussion: After genetic analysis, a diagnostic yield of 56% was obtained which is on par with results from WES analysis. The effectiveness and the reduced costs compared to WES renders the RP-LCA smMIPs panel a competitive approach to provide IRD patients with a genetic diagnosis, especially in countries with restricted access to genetic testing.

Using single molecule Molecular Inversion Probes as a cost-effective, high-throughput sequencing approach to target all genes and loci associated with macular diseases.

Macular degenerations (MDs) are a subgroup of retinal disorders characterized by central vision loss. Knowledge is still lacking on the extent of genetic and nongenetic factors influencing inherited MD (iMD) and age-related MD (AMD) expression. Single molecule Molecular Inversion Probes (smMIPs) have proven effective in sequencing the ABCA4 gene in patients with Stargardt disease to identify associated coding and noncoding variation, however many MD patients still remain genetically unexplained. We hypothesized that the missing heritability of MDs may be revealed by smMIPs-based sequencing of all MD-associated genes and risk factors. Using 17,394 smMIPs, we sequenced the coding regions of 105 iMD and AMD-associated genes and noncoding or regulatory loci, known pseudo-exons, and the mitochondrial genome in two test cohorts that were previously screened for variants in ABCA4. Following detailed sequencing analysis of 110 probands, a diagnostic yield of 38% was observed. This established an ''MD-smMIPs panel," enabling a genotype-first approach in a high-throughput and cost-effective manner, whilst achieving uniform and high coverage across targets. Further analysis will identify known and novel variants in MD-associated genes to offer an accurate clinical diagnosis to patients. Furthermore, this will reveal new genetic associations for MD and potential genetic overlaps between iMD and AMD.

Next-generation cytogenetics: Comprehensive assessment of 52 hematological malignancy genomes by optical genome mapping.

Somatic structural variants (SVs) are important drivers of cancer development and progression. In a diagnostic set-up, especially for hematological malignancies, the comprehensive analysis of all SVs in a given sample still requires a combination of cytogenetic techniques, including karyotyping, FISH, and CNV microarrays. We hypothesize that the combination of these classical approaches could be replaced by optical genome mapping (OGM). Samples from 52 individuals with a clinical diagnosis of a hematological malignancy, divided into simple (<5 aberrations, n = 36) and complex (≥5 aberrations, n = 16) cases, were processed for OGM, reaching on average: 283-fold genome coverage. OGM called a total of 918 high-confidence SVs per sample, of which, on average, 13 were rare and >100 kb. In addition, on average, 73 CNVs were called per sample, of which six were >5 Mb. For the 36 simple cases, all clinically reported aberrations were detected, including deletions, insertions, inversions, aneuploidies, and translocations. For the 16 complex cases, results were largely concordant between standard-of-care and OGM, but OGM often revealed higher complexity than previously recognized. Detailed technical comparison with standard-of-care tests showed high analytical validity of OGM, resulting in a sensitivity of 100% and a positive predictive value of >80%. Importantly, OGM resulted in a more complete assessment than any previous single test and most likely reported the most accurate underlying genomic architecture (e.g., for complex translocations, chromoanagenesis, and marker chromosomes). In conclusion, the excellent concordance of OGM with diagnostic standard assays demonstrates its potential to replace classical cytogenetic tests as well as to rapidly map novel leukemia drivers.

National external quality assessment for next-generation sequencing-based diagnostics of primary immunodeficiencies.

Dutch genome diagnostic centers (GDC) use next-generation sequencing (NGS)-based diagnostic applications for the diagnosis of primary immunodeficiencies (PIDs). The interpretation of genetic variants in many PIDs is complicated because of the phenotypic and genetic heterogeneity. To analyze uniformity of variant filtering, interpretation, and reporting in NGS-based diagnostics for PID, an external quality assessment was performed. Four main Dutch GDCs participated in the quality assessment. Unannotated variant call format (VCF) files of two PID patient analyses per laboratory were distributed among the four GDCs, analyzed, and interpreted (eight analyses in total). Variants that would be reported to the clinician and/or advised for further investigation were compared between the centers. A survey measuring the experiences of clinical laboratory geneticists was part of the study. Analysis of samples with confirmed diagnoses showed that all centers reported at least the variants classified as likely pathogenic (LP) or pathogenic (P) variants in all samples, except for variants in two genes (PSTPIP1 and BTK). The absence of clinical information complicated correct classification of variants. In this external quality assessment, the final interpretation and conclusions of the genetic analyses were uniform among the four participating genetic centers. Clinical and immunological data provided by a medical specialist are required to be able to draw proper conclusions from genetic data.