Use of genome sequencing to hunt for cryptic second-hit variants: analysis of 31 cases recruited to the 100 000 Genomes Project.

BACKGROUND: Current clinical testing methods used to uncover the genetic basis of rare disease have inherent limitations, which can lead to causative pathogenic variants being missed. Within the rare disease arm of the 100 000 Genomes Project (100kGP), families were recruited under the clinical indication 'single autosomal recessive mutation in rare disease'. These participants presented with strong clinical suspicion for a specific autosomal recessive disorder, but only one suspected pathogenic variant had been identified through standard-of-care testing. Whole genome sequencing (WGS) aimed to identify cryptic 'second-hit' variants. METHODS: To investigate the 31 families with available data that remained unsolved following formal review within the 100kGP, SVRare was used to aggregate structural variants present in <1% of 100kGP participants. Small variants were assessed using population allele frequency data and SpliceAI. Literature searches and publicly available online tools were used for further annotation of pathogenicity. RESULTS: Using these strategies, 8/31 cases were solved, increasing the overall diagnostic yield of this cohort from 10/41 (24.4%) to 18/41 (43.9%). Exemplar cases include a patient with cystic fibrosis harbouring a novel exonic LINE1 insertion in CFTR and a patient with generalised arterial calcification of infancy with complex interlinked duplications involving exons 2-6 of ENPP1. Although ambiguous by short-read WGS, the ENPP1 variant structure was resolved using optical genome mapping and RNA analysis. CONCLUSION: Systematic examination of cryptic variants across a multi-disease cohort successfully identifies additional pathogenic variants. WGS data analysis in autosomal recessive rare disease should consider complex structural and small intronic variants as potentially pathogenic second hits.

Targeting de novo loss-of-function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project.

BACKGROUND: Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient's phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods. METHODS: The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient's diagnostic reports. RESULTS: 324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were "missed" by 100KGP standard analyses, which are now being returned to patients. CONCLUSION: We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered.

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project.

BACKGROUND: Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data. METHODS: Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon-intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon-intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies. RESULTS: We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed. CONCLUSIONS: Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases.

Alternative splicing of BUD13 determines the severity of a developmental disorder with lipodystrophy and progeroid features.

PURPOSE: In this study we aimed to identify the molecular genetic cause of a progressive multisystem disease with prominent lipodystrophy. METHODS: In total, 5 affected individuals were investigated using exome sequencing. Dermal fibroblasts were characterized using RNA sequencing, proteomics, immunoblotting, immunostaining, and electron microscopy. Subcellular localization and rescue studies were performed. RESULTS: We identified a lipodystrophy phenotype with a typical facial appearance, corneal clouding, achalasia, progressive hearing loss, and variable severity. Although 3 individuals showed stunted growth, intellectual disability, and died within the first decade of life (A1, A2, and A3), 2 are adults with normal intellectual development (A4 and A5). All individuals harbored an identical homozygous nonsense variant affecting the retention and splicing complex component BUD13. The nucleotide substitution caused alternative splicing of BUD13 leading to a stable truncated protein whose expression positively correlated with disease expression and life expectancy. In dermal fibroblasts, we found elevated intron retention, a global reduction of spliceosomal proteins, and nuclei with multiple invaginations, which were more pronounced in A1, A2, and A3. Overexpression of both BUD13 isoforms normalized the nuclear morphology. CONCLUSION: Our results define a hitherto unknown syndrome and show that the alternative splice product converts a loss-of-function into a hypomorphic allele, thereby probably determining the severity of the disease and the survival of affected individuals.

A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes.

PURPOSE: Exome and genome sequencing have drastically accelerated novel disease gene discoveries. However, discovery is still hindered by myriad variants of uncertain significance found in genes of undetermined biological function. This necessitates intensive functional experiments on genes of equal predicted causality, leading to a major bottleneck. METHODS: We apply the loss-of-function observed/expected upper-bound fraction metric of intolerance to gene inactivation to curate a list of predicted haploinsufficient disease genes. Using data from the 100,000 Genomes Project, we adopt a gene-to-patient approach that matches de novo loss-of-function variants in constrained genes to patients with rare disease. Through large-scale aggregation of data, we reduce excess analytical noise currently hindering novel discoveries. RESULTS: Results from 13,949 trios revealed 643 rare, de novo predicted loss-of-function events filtered from 1044 loss-of-function observed/expected upper-bound fraction-constrained genes. A total of 168 variants occurred within 126 genes without a known disease-gene relationship. Of these, 27 genes had >1 kindred affected, and for 18 of these genes, multiple kindreds had overlapping phenotypes. Two years after initial analysis, 11 of 18 (61%) of these genes have been independently published as novel disease gene discoveries. CONCLUSION: Using large cohorts and adopting gene-based approaches can rapidly and objectively accelerate dominantly inherited novel gene discovery by targeting the most appropriate genes for functional validation.

Scaling national and international improvement in virtual gene panel curation via a collaborative approach to discordance resolution.

Clinical validity assessments of gene-disease associations underpin analysis and reporting in diagnostic genomics, and yet wide variability exists in practice, particularly in use of these assessments for virtual gene panel design and maintenance. Harmonization efforts are hampered by the lack of agreed terminology, agreed gene curation standards, and platforms that can be used to identify and resolve discrepancies at scale. We undertook a systematic comparison of the content of 80 virtual gene panels used in two healthcare systems by multiple diagnostic providers in the United Kingdom and Australia. The process was enabled by a shared curation platform, PanelApp, and resulted in the identification and review of 2,144 discordant gene ratings, demonstrating the utility of sharing structured gene-disease validity assessments and collaborative discordance resolution in establishing national and international consensus.

STAG1 mutations cause a novel cohesinopathy characterised by unspecific syndromic intellectual disability.

BACKGROUND: Cohesinopathies are rare neurodevelopmental disorders arising from a dysfunction in the cohesin pathway, which enables chromosome segregation and regulates gene transcription. So far, eight genes from this pathway have been reported in human disease. STAG1 belongs to the STAG subunit of the core cohesin complex, along with five other subunits. This work aimed to identify the phenotype ascribed to STAG1 mutations. METHODS: Among patients referred for intellectual disability (ID) in genetics departments worldwide, array-comparative genomic hybridisation (CGH), gene panel, whole-exome sequencing or whole-genome sequencing were performed following the local diagnostic standards. RESULTS: A mutation in STAG1 was identified in 17 individuals from 16 families, 9 males and 8 females aged 2-33 years. Four individuals harboured a small microdeletion encompassing STAG1; three individuals from two families had an intragenic STAG1 deletion. Six deletions were identified by array-CGH, one by whole-exome sequencing. Whole-exome sequencing found de novo heterozygous missense or frameshift STAG1 variants in eight patients, a panel of genes involved in ID identified a missense and a frameshift variant in two individuals. The 17 patients shared common facial features, with wide mouth and deep-set eyes. Four individuals had mild microcephaly, seven had epilepsy. CONCLUSIONS: We report an international series of 17 individuals from 16 families presenting with syndromic unspecific ID that could be attributed to a STAG1 deletion or point mutation. This first series reporting the phenotype ascribed to mutation in STAG1 highlights the importance of data sharing in the field of rare disorders.

Quantitative measurements of alternating finger tapping in Parkinson's disease correlate with UPDRS motor disability and reveal the improvement in fine motor control from medication and deep brain stimulation.

The Unified Parkinson's Disease Rating Scale (UPDRS) is the primary outcome measure in most clinical trials of Parkinson's disease (PD) therapeutics. Each subscore of the motor section (UPDRS III) compresses a wide range of motor performance into a coarse-grained scale from 0 to 4; the assessment of performance can also be subjective. Quantitative digitography (QDG) is an objective, quantitative assessment of digital motor control using a computer-interfaced musical keyboard. In this study, we show that the kinematics of a repetitive alternating finger-tapping (RAFT) task using QDG correlate with the UPDRS motor score, particularly with the bradykinesia subscore, in 33 patients with PD. We show that dopaminergic medication and an average of 9.5 months of bilateral subthalamic nucleus deep brain stimulation (B-STN DBS) significantly improve UPDRS and QDG scores but may have different effects on certain kinematic parameters. This study substantiates the use of QDG to measure motor outcome in trials of PD therapeutics and shows that medication and B-STN DBS both improve fine motor control.