Multi-level evidence of an allelic hierarchy of USH2A variants in hearing, auditory processing and speech/language outcomes.

Language development builds upon a complex network of interacting subservient systems. It therefore follows that variations in, and subclinical disruptions of, these systems may have secondary effects on emergent language. In this paper, we consider the relationship between genetic variants, hearing, auditory processing and language development. We employ whole genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. These investigations indicate that USH2A variants are associated with altered low-frequency sound perception which, in turn, increases the risk of developmental language disorder. We further show that Ush2a heterozygote mice have low-level hearing impairments, persistent higher-order acoustic processing deficits and altered vocalizations. These findings provide new insights into the complexity of genetic mechanisms serving language development and disorders and the relationships between developmental auditory and neural systems

Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being 'pathogenic' or 'benign' is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as 'pathogenic' or 'likely pathogenic'; one in five of these cases could lead to new or refined diagnoses

Molecular diagnoses in the congenital malformations caused by ciliopathies cohort of the 100,000 Genomes Project

Background Primary ciliopathies represent a group of inherited disorders due to defects in the primary cilium, the ‘cell’s antenna’. The 100,000 Genomes Project was launched in 2012 by Genomics England (GEL), recruiting National Health Service (NHS) patients with eligible rare diseases and cancer. Sequence data were linked to Human Phenotype Ontology (HPO) terms entered by recruiting clinicians. Methods Eighty-three prescreened probands were recruited to the 100,000 Genomes Project suspected to have congenital malformations caused by ciliopathies in the following disease categories: Bardet-Biedl syndrome (n=45), Joubert syndrome (n=14) and ‘Rare Multisystem Ciliopathy Disorders’ (n=24). We implemented a bespoke variant filtering and analysis strategy to improve molecular diagnostic rates for these participants. Results We determined a research molecular diagnosis for n=43/83 (51.8%) probands. This is 19.3% higher than previously reported by GEL (n=27/83 (32.5%)). A high proportion of diagnoses are due to variants in non-ciliopathy disease genes (n=19/43, 44.2%) which may reflect difficulties in clinical recognition of ciliopathies. n=11/83 probands (13.3%) had at least one causative variant outside the tiers 1 and 2 variant prioritisation categories (GEL’s automated triaging procedure), which would not be reviewed in standard 100,000 Genomes Project diagnostic strategies. These include four structural variants and three predicted to cause non-canonical splicing defects. Two unrelated participants have biallelic likely pathogenic variants in LRRC45, a putative novel ciliopathy disease gene. Conclusion These data illustrate the power of linking large-scale genome sequence to phenotype information. They demonstrate the value of research collaborations in order to maximise interpretation of genomic data

A clinical and molecular characterisation of CRB1-associated maculopathy

To date, over 150 disease-associated variants in CRB1 have been described, resulting in a range of retinal disease phenotypes including Leber congenital amaurosis and retinitis pigmentosa. Despite this, no genotype–phenotype correlations are currently recognised. We performed a retrospective review of electronic patient records to identify patients with macular dystrophy due to bi-allelic variants in CRB1. In total, seven unrelated individuals were identified. The median age at presentation was 21 years, with a median acuity of 0.55 decimalised Snellen units (IQR = 0.43). The follow-up period ranged from 0 to 19 years (median = 2.0 years), with a median final decimalised Snellen acuity of 0.65 (IQR = 0.70). Fundoscopy revealed only a subtly altered foveal reflex, which evolved into a bull’s-eye pattern of outer retinal atrophy. Optical coherence tomography identified structural changes—intraretinal cysts in the early stages of disease, and later outer retinal atrophy. Genetic testing revealed that one rare allele (c.498_506del, p.(Ile167_Gly169del)) was present in all patients, with one patient being homozygous for the variant and six being heterozygous. In trans with this, one variant recurred twice (p.(Cys896Ter)), while the four remaining alleles were each observed once (p.(Pro1381Thr), p.(Ser478ProfsTer24), p.(Cys195Phe) and p.(Arg764Cys)). These findings show that the rare CRB1 variant, c.498_506del, is strongly associated with localised retinal dysfunction. The clinical findings are much milder than those observed with bi-allelic, loss-of-function variants in CRB1, suggesting this in-frame deletion acts as a hypomorphic allele. This is the most prevalent disease-causing CRB1 variant identified in the non-Asian population to date

100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care — Preliminary Report

BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.)

Pathogenic intronic splice-affecting variants in MYBPC3 in three patients with hypertrophic cardiomyopathy

Genetic variants in MYBPC3 are one of the most common causes of hypertrophic cardiomyopathy (HCM). While variants in MYBPC3 affecting canonical splice site dinucleotides are a well-characterised cause of HCM, only recently has work begun to investigate the pathogenicity of more deeply intronic variants. Here, we present three patients with HCM and intronic splice-affecting MYBPC3 variants and analyse the impact of variants on splicing using in vitro minigene assays. We show that the three variants, a novel c.927-8G>A variant and the previously reported c.1624+4A>T and c.3815-10T>G variants, result in MYBPC3 splicing errors. Analysis of blood-derived patient RNA for the c.3815-10T>G variant revealed only wild type spliced product, indicating that mis-spliced transcripts from the mutant allele are degraded. These data indicate that the c.927-8G>A variant of uncertain significance and likely benign c.3815-10T>G should be reclassified as likely pathogenic. Furthermore, we find shortcomings in commonly applied bioinformatics strategies to prioritise variants impacting MYBPC3 splicing and re-emphasise the need for functional assessment of variants of uncertain significance in diagnostic testing

Novel PEX11B Mutations Extend the Peroxisome Biogenesis Disorder 14B Phenotypic Spectrum and Underscore Congenital Cataract as an Early Feature

Purpose: Peroxisomes perform complex metabolic and catabolic functions essential for normal growth and development. Mutations in 14 genes cause a spectrum of peroxisomal disease in humans. Most recently, PEX11B was associated with an atypical peroxisome biogenesis disorder (PBD) in a single individual. In this study, we identify further PEX11B cases and delineate associated phenotypes. Methods: Probands from three families underwent next generation sequencing (NGS) for diagnosis of a multisystem developmental disorder. Autozygosity mapping was conducted in one affected sibling pair. ExomeDepth was used to identify copy number variants from NGS data and confirmed by dosage analysis. Biochemical profiling was used to investigate the metabolic signature of the condition. Results: All patients presented with bilateral cataract at birth but the systemic phenotype was variable, including short stature, skeletal abnormalities, and dysmorphism—features not described in the original case. Next generation sequencing identified biallelic loss-of-function mutations in PEX11B as the underlying cause of disease in each case (PEX11B c.235C>T p.(Arg79Ter) homozygous; PEX11B c.136C>T p.(Arg46Ter) homozygous; PEX11B c.595C>T p.(Arg199Ter) heterozygous, PEX11B ex1-3 del heterozygous). Biochemical studies identified very low plasmalogens in one patient, whilst a mildly deranged very long chain fatty acid profile was found in another. Conclusions: Our findings expand the phenotypic spectrum of the condition and underscore congenital cataract as the consistent primary presenting feature. We also find that biochemical measurements of peroxisome function may be disturbed in some cases. Furthermore, diagnosis by NGS is proficient and may circumvent the requirement for an invasive skin biopsy for disease identification from fibroblast cells

Validation of copy number variation analysis for next-generation sequencing diagnostics

Although a common cause of disease, copy number variants (CNVs) have not routinely been identified from next-generation sequencing (NGS) data in a clinical context. This study aimed to examine the sensitivity and specificity of a widely used software package, ExomeDepth, to identify CNVs from targeted NGS data sets. We benchmarked the accuracy of CNV detection using ExomeDepth v1.1.6 applied to targeted NGS data sets by comparison to CNV events detected through whole-genome sequencing for 25 individuals and determined the sensitivity and specificity of ExomeDepth applied to these targeted NGS data sets to be 100% and 99.8%, respectively. To define quality assurance metrics for CNV surveillance through ExomeDepth, we undertook simulation of single-exon (n=1000) and multiple-exon heterozygous deletion events (n=1749), determining a sensitivity of 97% (n=2749). We identified that the extent of sequencing coverage, the inter- and intra-sample variability in the depth of sequencing coverage and the composition of analysis regions are all important determinants of successful CNV surveillance through ExomeDepth. We then applied these quality assurance metrics during CNV surveillance for 140 individuals across 12 distinct clinical areas, encompassing over 500 potential rare disease diagnoses. All 140 individuals lacked molecular diagnoses after routine clinical NGS testing, and by application of ExomeDepth, we identified 17 CNVs contributing to the cause of a Mendelian disorder. Our findings support the integration of CNV detection using ExomeDepth v1.1.6 with routine targeted NGS diagnostic services for Mendelian disorders. Implementation of this strategy increases diagnostic yields and enhances clinical care