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

Burden re-analysis of neurodevelopmental disorder cohorts for prioritization of candidate genes

This study aimed to uncover novel genes associated with neurodevelopmental disorders (NDD) by leveraging recent large-scale de novo burden analysis studies to enhance a virtual gene panel used in a diagnostic setting. We re-analyzed historical trio-exome sequencing data from 745 individuals with NDD according to the most recent diagnostic standards, resulting in a cohort of 567 unsolved individuals. Next, we designed a virtual gene panel containing candidate genes from three large de novo burden analysis studies in NDD and prioritized candidate genes by stringent filtering for ultra-rare de novo variants with high pathogenicity scores. Our analysis revealed an increased burden of de novo variants in our selected candidate genes within the unsolved NDD cohort and identified qualifying de novo variants in seven candidate genes: RIF1, CAMK2D, RAB11FIP4, AGO3, PCBP2, LEO1, and VCP. Clinical data were collected from six new individuals with de novo or inherited LEO1 variants and three new individuals with de novo PCBP2 variants. Our findings add additional evidence for LEO1 as a risk gene for autism and intellectual disability. Furthermore, we prioritize PCBP2 as a candidate gene for NDD associated with motor and language delay. In summary, by leveraging de novo burden analysis studies, employing a stringent variant filtering pipeline, and engaging in targeted patient recruitment, our study contributes to the identification of novel genes implicated in NDDs.

Exome Sequencing has a high diagnostic rate in sporadic congenital hypopituitarism and reveals novel candidate genes

CONTEXT

The pituitary gland is key for childhood growth, puberty, and metabolism. Pituitary dysfunction is associated with a spectrum of phenotypes, from mild to severe. Congenital Hypopituitarism (CH) is the most commonly reported pediatric endocrine dysfunction with an incidence of 1:4000, yet low rates of genetic diagnosis have been reported.

OBJECTIVE

We aimed to unveil the genetic etiology of CH in a large cohort of patients from Argentina.

METHODS

We performed whole exome sequencing of 137 unrelated cases of CH, the largest cohort examined with this method to date.

RESULTS

Of the 137 cases, 19.1% and 16% carried pathogenic or likely pathogenic variants in known and new genes, respectively, while 28.2% carried variants of uncertain significance. This high yield was achieved through the integration of broad gene panels (genes described in animal models and/or other disorders), an unbiased candidate gene screen with a new bioinformatics pipeline (including genes high loss of function intolerance), and analysis of copy number variants. Three novel findings emerged. First, the most prevalent affected gene encodes the cell adhesion factor ROBO1. Affected children had a spectrum of phenotypes, consistent with a role beyond pituitary stalk interruption syndrome. Second, we found that CHD7 mutations also produce a phenotypic spectrum, not always associated with full CHARGE syndrome. Third, we add new evidence of pathogenicity in the genes PIBF1 and TBC1D32, and report 13 novel candidate genes associated with CH (e.g. PTPN6, ARID5B).

CONCLUSION

Overall, these results provide an unprecedented insight into the diverse genetic etiology of hypopituitarism.

Modelling human genetic disorders in Xenopus tropicalis

Recent progress in human disease genetics is leading to rapid advances in understanding pathobiological mechanisms. However, the sheer number of risk-conveying genetic variants being identified demands in vivo model systems that are amenable to functional analyses at scale. Here we provide a practical guide for using the diploid frog species Xenopus tropicalis to study many genes and variants to uncover conserved mechanisms of pathobiology relevant to human disease. We discuss key considerations in modelling human genetic disorders: genetic architecture, conservation, phenotyping strategy and rigour, as well as more complex topics, such as penetrance, expressivity, sex differences and current challenges in the field. As the patient-driven gene discovery field expands significantly, the cost-effective, rapid and higher throughput nature of Xenopus make it an essential member of the model organism armamentarium for understanding gene function in development and in relation to disease.

A Panel-Agnostic Strategy 'HiPPo' Improves Diagnostic Efficiency in the UK Genomic Medicine Service

Genome sequencing is available as a clinical test in the UK through the Genomic Medicine Service (GMS). The GMS analytical strategy predominantly filters genome data on preselected gene panels. Whilst this reduces variants requiring assessment by reporting laboratories, pathogenic variants outside applied panels may be missed, and variants in genes without established disease-gene relationships are largely ignored. This study compares the analysis of a research exome to a GMS clinical genome for the same patients. For the research exome, we applied a panel-agnostic approach filtering for variants with High Pathogenic Potential (HiPPo) using ClinVar, allele frequency, and in silico prediction tools. We then restricted HiPPo variants to Gene Curation Coalition (GenCC) disease genes. These results were compared with the GMS genome panel-based approach. Twenty-four participants from eight families underwent parallel research exome and GMS genome sequencing. Exome HiPPo analysis identified a similar number of variants as the GMS panel-based approach. GMS genome analysis returned two pathogenic variants and one de novo variant. Exome HiPPo analysis returned the same variants plus an additional pathogenic variant and three further de novo variants in novel genes, where case series are underway. When HiPPo was restricted to GenCC disease genes, statistically fewer variants required assessment to identify more pathogenic variants than reported by the GMS, giving a diagnostic rate per variant assessed of 20% for HiPPo versus 3% for the GMS. With UK plans to sequence 5 million genomes, strategies are needed to optimise genome analysis beyond gene panels whilst minimising the burden of variants requiring clinical assessment.

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

BACKGROUND

Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome.

METHODS

We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants.

RESULTS

Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving.

CONCLUSIONS

Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.

A retrospective analysis of phosphatase catalytic subunit gene variants in patients with rare disorders identifies novel candidate neurodevelopmental disease genes

Rare genetic disorders represent some of the most severe and life-limiting conditions that constitute a considerable burden on global healthcare systems and societies. Most individuals affected by rare disorders remain undiagnosed, highlighting the unmet need for improved disease gene discovery and novel variant interpretation. Aberrant (de) phosphorylation can have profound pathological consequences underpinning many disease processes. Numerous phosphatases and associated proteins have been identified as disease genes, with many more likely to have gone undiscovered thus far. To begin to address these issues, we have performed a systematic survey of de novo variants amongst 189 genes encoding phosphatase catalytic subunits found in rare disease patients recruited to the 100,000 Genomes Project (100 kGP), the largest national sequencing project of its kind in the United Kingdom. We found that 49% of phosphatases were found to carry de novo mutation(s) in this cohort. Only 25% of these phosphatases have been previously linked to genetic disorders. A gene-to-patient approach matching variants to phenotypic data identified 9 novel candidate rare-disease genes: PTPRD, PTPRG, PTPRT, PTPRU, PTPRZ1, MTMR3, GAK, TPTE2, PTPN18. As the number of patients undergoing whole genome sequencing increases and information sharing improves, we anticipate that reiterative analysis of genomic and phenotypic data will continue to identify candidate phosphatase disease genes for functional validation. This is the first step towards delineating the aetiology of rare genetic disorders associated with altered phosphatase function, leading to new biological insights and improved clinical outcomes for the affected individuals and their families.

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.

De novo putative loss-of-function variants in TAF4 are associated with a neuro-developmental disorder

TATA-binding protein associated factor 4 (TAF4) is a subunit of the Transcription Factor IID (TFIID) complex, a central player in transcription initiation. Other members of this multimeric complex have been implicated previously as monogenic disease genes in human developmental disorders. TAF4 has not been described to date as a monogenic disease gene. We here present a cohort of eight individuals, each carrying de novo putative loss-of-function (pLoF) variants in TAF4 and expressing phenotypes consistent with a neuro-developmental disorder (NDD). Common features include intellectual disability, abnormal behavior, and facial dysmorphisms. We propose TAF4 as a novel dominant disease gene for NDD, and coin this novel disorder "TAF4-related NDD" (T4NDD). We place T4NDD in the context of other disorders related to TFIID subunits, revealing shared features of T4NDD with other TAF-opathies.