Publications by authors named "Helen V Firth"

80 Publications

Detecting cryptic clinically relevant structural variation in exome-sequencing data increases diagnostic yield for developmental disorders.

Am J Hum Genet 2021 11 8;108(11):2186-2194. Epub 2021 Oct 8.

Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Hinxton CB10 1SA, UK. Electronic address:

Structural variation (SV) describes a broad class of genetic variation greater than 50 bp in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DDs). Individuals presenting with DDs are often referred for diagnostic testing with chromosomal microarrays (CMAs) to identify large copy-number variants (CNVs) and/or with single-gene, gene-panel, or exome sequencing (ES) to identify single-nucleotide variants, small insertions/deletions, and CNVs. However, individuals with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the tool InDelible, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DDs recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 63 rare, damaging variants in genes previously associated with DDs missed by standard SNV, indel, or CNV discovery approaches. Clinical review of these 63 variants determined that about half (30/63) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21 and 500 bp in size and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.9%. Of particular interest were seven confirmed de novo variants in MECP2, which represent 35.0% of all de novo protein-truncating variants in MECP2 among DDD study participants. InDelible provides a framework for the discovery of pathogenic SVs that are most likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.
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http://dx.doi.org/10.1016/j.ajhg.2021.09.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8595893PMC
November 2021

Response to Biesecker et al.

Am J Hum Genet 2021 09;108(9):1807-1808

Departments of Pediatrics, Obstetrics and Gynecology, and Epidemiology, University of Florida College of Medicine and College of Public Health and Health Professions, Gainesville, FL 32610, USA.

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http://dx.doi.org/10.1016/j.ajhg.2021.07.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456153PMC
September 2021

Pathogenic SPTBN1 variants cause an autosomal dominant neurodevelopmental syndrome.

Nat Genet 2021 07 1;53(7):1006-1021. Epub 2021 Jul 1.

McMaster University, Hamilton, Ontario, Canada.

SPTBN1 encodes βII-spectrin, the ubiquitously expressed β-spectrin that forms micrometer-scale networks associated with plasma membranes. Mice deficient in neuronal βII-spectrin have defects in cortical organization, developmental delay and behavioral deficiencies. These phenotypes, while less severe, are observed in haploinsufficient animals, suggesting that individuals carrying heterozygous SPTBN1 variants may also show measurable compromise of neural development and function. Here we identify heterozygous SPTBN1 variants in 29 individuals with developmental, language and motor delays; mild to severe intellectual disability; autistic features; seizures; behavioral and movement abnormalities; hypotonia; and variable dysmorphic facial features. We show that these SPTBN1 variants lead to effects that affect βII-spectrin stability, disrupt binding to key molecular partners, and disturb cytoskeleton organization and dynamics. Our studies define SPTBN1 variants as the genetic basis of a neurodevelopmental syndrome, expand the set of spectrinopathies affecting the brain and underscore the critical role of βII-spectrin in the central nervous system.
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http://dx.doi.org/10.1038/s41588-021-00886-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273149PMC
July 2021

Novel compound heterozygous STN1 variants are associated with Coats Plus syndrome.

Mol Genet Genomic Med 2021 Jun 10:e1708. Epub 2021 Jun 10.

School of Clinical Medicine, Cambridge University, Cambridge, UK.

Aim: Coats plus syndrome (CP) is a rare autosomal recessive disorder, characterised by retinal telangiectasia exudates (Coats disease), leukodystrophy, distinctive intracranial calcification and cysts, as well as extra-neurological features including abnormal vasculature of the gastrointestinal tract, portal hypertension and osteopenia with a tendency to fractures. CP most frequently occurs due to loss-of-function mutations in CTC1. The encoded protein CTC1 constitutes part of the CST (CTC1-STN1-TEN1) complex, and three patients have been described with CP due to biallelic mutations in STN1. Together with the identification of homozygosity for a specific loss-of-function mutation in POT1 in a sibling pair, these observations highlight a defect in the maintenance of telomere integrity as the cause of CP, although the precise mechanism leading to the micro-vasculopathy seen at a pathological level remains unclear. Here, we present the investigation of a fourth child who presented to us with retinal exudates, intracranial calcifications and developmental delay, in keeping with a diagnosis of CP, and later went on to develop pancytopenia and gastrointestinal bleeding. Genome sequencing revealed compound heterozygous variants in STN1 as the likely genetic cause of CP in this present case.

Methods: We assessed the phenotype to be CP and undertook targeted sequencing.

Results: Whilst sequencing of CTC1 and POT1 was normal, we identified novel compound heterozygous variants in STN1 (previous gene symbol OBFC1): one loss-of-function--c.894dup (p.(Asp299Argfs*58)); and one missense--c.707T>C (p.(Leu236Pro)).

Conclusion: Given the clinical phenotype and identified variants we suggest that this is only the fourth patient reported to date with CP due to mutations in STN1.
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http://dx.doi.org/10.1002/mgg3.1708DOI Listing
June 2021

Non-coding region variants upstream of MEF2C cause severe developmental disorder through three distinct loss-of-function mechanisms.

Am J Hum Genet 2021 06 21;108(6):1083-1094. Epub 2021 May 21.

Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1RQ, UK; East Anglian Medical Genetics Service, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK.

Clinical genetic testing of protein-coding regions identifies a likely causative variant in only around half of developmental disorder (DD) cases. The contribution of regulatory variation in non-coding regions to rare disease, including DD, remains very poorly understood. We screened 9,858 probands from the Deciphering Developmental Disorders (DDD) study for de novo mutations in the 5' untranslated regions (5' UTRs) of genes within which variants have previously been shown to cause DD through a dominant haploinsufficient mechanism. We identified four single-nucleotide variants and two copy-number variants upstream of MEF2C in a total of ten individual probands. We developed multiple bespoke and orthogonal experimental approaches to demonstrate that these variants cause DD through three distinct loss-of-function mechanisms, disrupting transcription, translation, and/or protein function. These non-coding region variants represent 23% of likely diagnoses identified in MEF2C in the DDD cohort, but these would all be missed in standard clinical genetics approaches. Nonetheless, these variants are readily detectable in exome sequence data, with 30.7% of 5' UTR bases across all genes well covered in the DDD dataset. Our analyses show that non-coding variants upstream of genes within which coding variants are known to cause DD are an important cause of severe disease and demonstrate that analyzing 5' UTRs can increase diagnostic yield. We also show how non-coding variants can help inform both the disease-causing mechanism underlying protein-coding variants and dosage tolerance of the gene.
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http://dx.doi.org/10.1016/j.ajhg.2021.04.025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206381PMC
June 2021

The contribution of X-linked coding variation to severe developmental disorders.

Nat Commun 2021 01 27;12(1):627. Epub 2021 Jan 27.

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders.
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http://dx.doi.org/10.1038/s41467-020-20852-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840967PMC
January 2021

Evaluating variants classified as pathogenic in ClinVar in the DDD Study.

Genet Med 2021 03 5;23(3):571-575. Epub 2020 Nov 5.

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.

Purpose: Automated variant filtering is an essential part of diagnostic genome-wide sequencing but may generate false negative results. We sought to investigate whether some previously identified pathogenic variants may be being routinely excluded by standard variant filtering pipelines.

Methods: We evaluated variants that were previously classified as pathogenic or likely pathogenic in ClinVar in known developmental disorder genes using exome sequence data from the Deciphering Developmental Disorders (DDD) study.

Results: Of these ClinVar pathogenic variants, 3.6% were identified among 13,462 DDD probands, and 1134/1352 (83.9%) had already been independently communicated to clinicians using DDD variant filtering pipelines as plausibly pathogenic. The remaining 218 variants failed consequence, inheritance, or other automated variant filters. Following clinical review of these additional variants, we were able to identify 112 variants in 107 (0.8%) DDD probands as potential diagnoses.

Conclusion: Lower minor allele frequency (<0.0005%) and higher gold star review status in ClinVar (>1 star) are good predictors of a previously identified variant being plausibly diagnostic for developmental disorders. However, around half of previously identified pathogenic variants excluded by automated variant filtering did not appear to be disease-causing, underlining the continued need for clinical evaluation of candidate variants as part of the diagnostic process.
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http://dx.doi.org/10.1038/s41436-020-01021-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935711PMC
March 2021

Evidence for 28 genetic disorders discovered by combining healthcare and research data.

Nature 2020 10 14;586(7831):757-762. Epub 2020 Oct 14.

Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.

De novo mutations in protein-coding genes are a well-established cause of developmental disorders. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent-offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders.
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http://dx.doi.org/10.1038/s41586-020-2832-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116826PMC
October 2020

Trappc9 deficiency causes parent-of-origin dependent microcephaly and obesity.

PLoS Genet 2020 09 2;16(9):e1008916. Epub 2020 Sep 2.

Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom.

Some imprinted genes exhibit parental origin specific expression bias rather than being transcribed exclusively from one copy. The physiological relevance of this remains poorly understood. In an analysis of brain-specific allele-biased expression, we identified that Trappc9, a cellular trafficking factor, was expressed predominantly (~70%) from the maternally inherited allele. Loss-of-function mutations in human TRAPPC9 cause a rare neurodevelopmental syndrome characterized by microcephaly and obesity. By studying Trappc9 null mice we discovered that homozygous mutant mice showed a reduction in brain size, exploratory activity and social memory, as well as a marked increase in body weight. A role for Trappc9 in energy balance was further supported by increased ad libitum food intake in a child with TRAPPC9 deficiency. Strikingly, heterozygous mice lacking the maternal allele (70% reduced expression) had pathology similar to homozygous mutants, whereas mice lacking the paternal allele (30% reduction) were phenotypically normal. Taken together, we conclude that Trappc9 deficient mice recapitulate key pathological features of TRAPPC9 mutations in humans and identify a role for Trappc9 and its imprinting in controlling brain development and metabolism.
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http://dx.doi.org/10.1371/journal.pgen.1008916DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467316PMC
September 2020

Genomically Aided Diagnosis of Severe Developmental Disorders.

Annu Rev Genomics Hum Genet 2020 08 18;21:327-349. Epub 2020 May 18.

Department of Clinical Genetics, Addenbrooke's Hospital, Cambridge CB2 0QQ, United Kingdom; email:

Our ability to make accurate and specific genetic diagnoses in individuals with severe developmental disorders has been transformed by data derived from genomic sequencing technologies. These data reveal both the patterns and rates of different mutational mechanisms and identify regions of the human genome with fewer mutations than would be expected. In outbred populations, the most common identifiable cause of severe developmental disorders is de novo mutation affecting the coding region in one of approximately 500 different genes, almost universally showing constraint. Simply combining the location of a de novo genomic event with its predicted consequence on the gene product gives significant diagnostic power. Our knowledge of the diversity of phenotypic consequences associated with comparable diagnostic genotypes at each locus is improving. Computationally useful phenotype data will improve diagnostic interpretation of ultrarare genetic variants and, in the long run, indicate which specific embryonic processes have been perturbed.
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http://dx.doi.org/10.1146/annurev-genom-120919-082329DOI Listing
August 2020

A framework for an evidence-based gene list relevant to autism spectrum disorder.

Nat Rev Genet 2020 06 21;21(6):367-376. Epub 2020 Apr 21.

The Centre for Applied Genomics, Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.

Autism spectrum disorder (ASD) is often grouped with other brain-related phenotypes into a broader category of neurodevelopmental disorders (NDDs). In clinical practice, providers need to decide which genes to test in individuals with ASD phenotypes, which requires an understanding of the level of evidence for individual NDD genes that supports an association with ASD. Consensus is currently lacking about which NDD genes have sufficient evidence to support a relationship to ASD. Estimates of the number of genes relevant to ASD differ greatly among research groups and clinical sequencing panels, varying from a few to several hundred. This Roadmap discusses important considerations necessary to provide an evidence-based framework for the curation of NDD genes based on the level of information supporting a clinically relevant relationship between a given gene and ASD.
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http://dx.doi.org/10.1038/s41576-020-0231-2DOI Listing
June 2020

Genomic variant sharing: a position statement.

Wellcome Open Res 2019 5;4:22. Epub 2019 Feb 5.

Department of Clinical Genetics, University of Cambridge Addenbrooke's Hospital Cambridge, Cambridge, UK.

Sharing de-identified genetic variant data is essential for the practice of genomic medicine and is demonstrably beneficial to patients. Robust genetic diagnoses that inform medical management cannot be made accurately without reference to genetic test results from other patients, as well as population controls. Errors in this process can result in delayed, missed or erroneous diagnoses, leading to inappropriate or missed medical interventions for the patient and their family. The benefits of sharing individual genetic variants, and the harms of sharing them, are numerous and well-established. Databases and mechanisms already exist to facilitate deposition and sharing of pseudonomised genetic variants, but clarity and transparency around best practice is needed to encourage widespread use, prevent inconsistencies between different communities, maximise individual privacy and ensure public trust. We therefore recommend that widespread sharing of a small number of individual genetic variants associated with limited clinical information should become standard practice in genomic medicine. Information robustly linking genetic variants with specific conditions is fundamental biological knowledge, not personal information, and therefore should not require consent to share. For additional case-level detail about individual patients or more extensive genomic information, which is often essential for clinical interpretation, it may be more appropriate to use a controlled-access model for data sharing, with the ultimate aim of making as much information as open and de-identified as possible with appropriate consent.
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http://dx.doi.org/10.12688/wellcomeopenres.15090.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913213PMC
February 2019

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Am J Hum Genet 2019 11 10;105(5):933-946. Epub 2019 Oct 10.

Wellcome Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands.
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http://dx.doi.org/10.1016/j.ajhg.2019.09.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848993PMC
November 2019

Contribution of retrotransposition to developmental disorders.

Nat Commun 2019 10 11;10(1):4630. Epub 2019 Oct 11.

Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Hinxton, CB10 1SA, UK.

Mobile genetic Elements (MEs) are segments of DNA which can copy themselves and other transcribed sequences through the process of retrotransposition (RT). In humans several disorders have been attributed to RT, but the role of RT in severe developmental disorders (DD) has not yet been explored. Here we identify RT-derived events in 9738 exome sequenced trios with DD-affected probands. We ascertain 9 de novo MEs, 4 of which are likely causative of the patient's symptoms (0.04%), as well as 2 de novo gene retroduplications. Beyond identifying likely diagnostic RT events, we estimate genome-wide germline ME mutation rate and selective constraint and demonstrate that coding RT events have signatures of purifying selection equivalent to those of truncating mutations. Overall, our analysis represents a comprehensive interrogation of the impact of retrotransposition on protein coding genes and a framework for future evolutionary and disease studies.
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http://dx.doi.org/10.1038/s41467-019-12520-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789007PMC
October 2019

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

Front Genet 2019 29;10:611. Epub 2019 Jul 29.

Department of Medical Genetics, University of Antwerp, Antwerp, Belgium.

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.
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http://dx.doi.org/10.3389/fgene.2019.00611DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6681681PMC
July 2019

Genomics: the power, potential and pitfalls of the new technologies and how they are transforming healthcare.

Clin Med (Lond) 2019 07;19(4):269-272

St George's University Hospitals NHS Foundation Trust, London, UK and professor in clinical genetics and genomic education, St George's, University of London, London, UK and Joint Committee on Genomics in Medicine, Royal College of Physicians, London, UK

Powerful new genomic technologies are transforming healthcare. The faster, cheaper generation of genomic data is driving the integration of genomics into all healthcare specialties. Within the next decade, healthcare professionals will be using genomic data to diagnose and manage their patients.However, despite these exciting advances, few clinicians are aware of or prepared for this genomics-based future. Through five patient-focused scenarios with accompanying interviews, this article showcases new genomic technologies while highlighting the inherent challenges associated with complex genomic data.
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http://dx.doi.org/10.7861/clinmedicine.19-4-269DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752247PMC
July 2019

De Novo Variants Disturbing the Transactivation Capacity of POU3F3 Cause a Characteristic Neurodevelopmental Disorder.

Am J Hum Genet 2019 08 11;105(2):403-412. Epub 2019 Jul 11.

Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Japan.

POU3F3, also referred to as Brain-1, is a well-known transcription factor involved in the development of the central nervous system, but it has not previously been associated with a neurodevelopmental disorder. Here, we report the identification of 19 individuals with heterozygous POU3F3 disruptions, most of which are de novo variants. All individuals had developmental delays and/or intellectual disability and impairments in speech and language skills. Thirteen individuals had characteristic low-set, prominent, and/or cupped ears. Brain abnormalities were observed in seven of eleven MRI reports. POU3F3 is an intronless gene, insensitive to nonsense-mediated decay, and 13 individuals carried protein-truncating variants. All truncating variants that we tested in cellular models led to aberrant subcellular localization of the encoded protein. Luciferase assays demonstrated negative effects of these alleles on transcriptional activation of a reporter with a FOXP2-derived binding motif. In addition to the loss-of-function variants, five individuals had missense variants that clustered at specific positions within the functional domains, and one small in-frame deletion was identified. Two missense variants showed reduced transactivation capacity in our assays, whereas one variant displayed gain-of-function effects, suggesting a distinct pathophysiological mechanism. In bioluminescence resonance energy transfer (BRET) interaction assays, all the truncated POU3F3 versions that we tested had significantly impaired dimerization capacities, whereas all missense variants showed unaffected dimerization with wild-type POU3F3. Taken together, our identification and functional cell-based analyses of pathogenic variants in POU3F3, coupled with a clinical characterization, implicate disruptions of this gene in a characteristic neurodevelopmental disorder.
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http://dx.doi.org/10.1016/j.ajhg.2019.06.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698880PMC
August 2019

Exome-wide assessment of the functional impact and pathogenicity of multinucleotide mutations.

Genome Res 2019 07 21;29(7):1047-1056. Epub 2019 Jun 21.

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, United Kingdom.

Approximately 2% of de novo single-nucleotide variants (SNVs) appear as part of clustered mutations that create multinucleotide variants (MNVs). MNVs are an important source of genomic variability as they are more likely to alter an encoded protein than a SNV, which has important implications in disease as well as evolution. Previous studies of MNVs have focused on their mutational origins and have not systematically evaluated their functional impact and contribution to disease. We identified 69,940 MNVs and 91 de novo MNVs in 6688 exome-sequenced parent-offspring trios from the Deciphering Developmental Disorders Study comprising families with severe developmental disorders. We replicated the previously described MNV mutational signatures associated with DNA polymerase zeta, an error-prone translesion polymerase, and the APOBEC family of DNA deaminases. We estimate the simultaneous MNV germline mutation rate to be 1.78 × 10 mutations per base pair per generation. We found that most MNVs within a single codon create a missense change that could not have been created by a SNV. MNV-induced missense changes were, on average, more physicochemically divergent, were more depleted in highly constrained genes (pLI ≥ 0.9), and were under stronger purifying selection compared with SNV-induced missense changes. We found that de novo MNVs were significantly enriched in genes previously associated with developmental disorders in affected children. This shows that MNVs can be more damaging than SNVs even when both induce missense changes, and are an important variant type to consider in relation to human disease.
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http://dx.doi.org/10.1101/gr.239756.118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6633265PMC
July 2019

A cellular census of human lungs identifies novel cell states in health and in asthma.

Nat Med 2019 07 17;25(7):1153-1163. Epub 2019 Jun 17.

Allergic Inflammation Discovery Performance Unit, Respiratory Therapy Area, GlaxoSmithKline, Stevenage, UK.

Human lungs enable efficient gas exchange and form an interface with the environment, which depends on mucosal immunity for protection against infectious agents. Tightly controlled interactions between structural and immune cells are required to maintain lung homeostasis. Here, we use single-cell transcriptomics to chart the cellular landscape of upper and lower airways and lung parenchyma in healthy lungs, and lower airways in asthmatic lungs. We report location-dependent airway epithelial cell states and a novel subset of tissue-resident memory T cells. In the lower airways of patients with asthma, mucous cell hyperplasia is shown to stem from a novel mucous ciliated cell state, as well as goblet cell hyperplasia. We report the presence of pathogenic effector type 2 helper T cells (T2) in asthmatic lungs and find evidence for type 2 cytokines in maintaining the altered epithelial cell states. Unbiased analysis of cell-cell interactions identifies a shift from airway structural cell communication in healthy lungs to a T2-dominated interactome in asthmatic lungs.
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http://dx.doi.org/10.1038/s41591-019-0468-5DOI Listing
July 2019

Meta-analysis and multidisciplinary consensus statement: exome sequencing is a first-tier clinical diagnostic test for individuals with neurodevelopmental disorders.

Genet Med 2019 11 11;21(11):2413-2421. Epub 2019 Jun 11.

Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA.

Purpose: For neurodevelopmental disorders (NDDs), etiological evaluation can be a diagnostic odyssey involving numerous genetic tests, underscoring the need to develop a streamlined algorithm maximizing molecular diagnostic yield for this clinical indication. Our objective was to compare the yield of exome sequencing (ES) with that of chromosomal microarray (CMA), the current first-tier test for NDDs.

Methods: We performed a PubMed scoping review and meta-analysis investigating the diagnostic yield of ES for NDDs as the basis of a consensus development conference. We defined NDD as global developmental delay, intellectual disability, and/or autism spectrum disorder. The consensus development conference included input from genetics professionals, pediatric neurologists, and developmental behavioral pediatricians.

Results: After applying strict inclusion/exclusion criteria, we identified 30 articles with data on molecular diagnostic yield in individuals with isolated NDD, or NDD plus associated conditions (such as Rett-like features). Yield of ES was 36% overall, 31% for isolated NDD, and 53% for the NDD plus associated conditions. ES yield for NDDs is markedly greater than previous studies of CMA (15-20%).

Conclusion: Our review demonstrates that ES consistently outperforms CMA for evaluation of unexplained NDDs. We propose a diagnostic algorithm placing ES at the beginning of the evaluation of unexplained NDDs.
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http://dx.doi.org/10.1038/s41436-019-0554-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6831729PMC
November 2019

Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP.

Nat Commun 2019 05 30;10(1):2373. Epub 2019 May 30.

MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine at the University of Edinburgh, Edinburgh, EH4 2XU, UK.

We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P ( www.ebi.ac.uk/gene2phenotype ) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2P; 2044 entries). VEP-G2P shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.
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http://dx.doi.org/10.1038/s41467-019-10016-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542828PMC
May 2019

Towards controlled terminology for reporting germline cancer susceptibility variants: an ENIGMA report.

J Med Genet 2019 06 8;56(6):347-357. Epub 2019 Apr 8.

Faculty of Medicine, University of Southampton, Southampton, UK.

The vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid expansion of genetic testing brought about by wide availability of high-throughput massively parallel sequencing platforms, accurate variant interpretation has become a major issue. The vocabulary used to describe single genetic variants in silico, in vitro, in vivo and as a contributor to human disease uses terms in common, but the meaning is not necessarily shared across all these contexts. In the setting of cancer genetic tests, the added dimension of using data from genetic sequencing of tumour DNA to direct treatment is an additional source of confusion to those who are not experienced in cancer genetics. The language used to describe variants identified in cancer susceptibility genetic testing typically still reflects an outdated paradigm of Mendelian inheritance with dichotomous outcomes. Cancer is a common disease with complex genetic architecture; an improved lexicon is required to better communicate among scientists, clinicians and patients, the risks and implications of genetic variants detected. This review arises from a recognition of, and discussion about, inconsistencies in vocabulary usage by members of the ENIGMA international multidisciplinary consortium focused on variant classification in breast-ovarian cancer susceptibility genes. It sets out the vocabulary commonly used in genetic variant interpretation and reporting, and suggests a framework for a common vocabulary that may facilitate understanding and clarity in clinical reporting of germline genetic tests for cancer susceptibility.
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http://dx.doi.org/10.1136/jmedgenet-2018-105872DOI Listing
June 2019

Pathogenicity and selective constraint on variation near splice sites.

Genome Res 2019 02 26;29(2):159-170. Epub 2018 Dec 26.

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom.

Mutations that perturb normal pre-mRNA splicing are significant contributors to human disease. We used exome sequencing data from 7833 probands with developmental disorders (DDs) and their unaffected parents, as well as more than 60,000 aggregated exomes from the Exome Aggregation Consortium, to investigate selection around the splice sites and quantify the contribution of splicing mutations to DDs. Patterns of purifying selection, a deficit of variants in highly constrained genes in healthy subjects, and excess de novo mutations in patients highlighted particular positions within and around the consensus splice site of greater functional relevance. By using mutational burden analyses in this large cohort of proband-parent trios, we could estimate in an unbiased manner the relative contributions of mutations at canonical dinucleotides (73%) and flanking noncanonical positions (27%), and calculate the positive predictive value of pathogenicity for different classes of mutations. We identified 18 patients with likely diagnostic de novo mutations in dominant DD-associated genes at noncanonical positions in splice sites. We estimate 35%-40% of pathogenic variants in noncanonical splice site positions are missing from public databases.
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http://dx.doi.org/10.1101/gr.238444.118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360807PMC
February 2019

Quantifying the contribution of recessive coding variation to developmental disorders.

Science 2018 12 8;362(6419):1161-1164. Epub 2018 Nov 8.

Clinical Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK.

We estimated the genome-wide contribution of recessive coding variation in 6040 families from the Deciphering Developmental Disorders study. The proportion of cases attributable to recessive coding variants was 3.6% in patients of European ancestry, compared with 50% explained by de novo coding mutations. It was higher (31%) in patients with Pakistani ancestry, owing to elevated autozygosity. Half of this recessive burden is attributable to known genes. We identified two genes not previously associated with recessive developmental disorders, and , and functionally validated them with mouse and cellular models. Our results suggest that recessive coding variants account for a small fraction of currently undiagnosed nonconsanguineous individuals, and that the role of noncoding variants, incomplete penetrance, and polygenic mechanisms need further exploration.
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http://dx.doi.org/10.1126/science.aar6731DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726470PMC
December 2018

Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.

Nature 2018 10 26;562(7726):268-271. Epub 2018 Sep 26.

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.

There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants. However, patients with the same genetic defect can have different clinical presentations, and some individuals who carry known disease-causing variants can appear unaffected. Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic.
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http://dx.doi.org/10.1038/s41586-018-0566-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726472PMC
October 2018

Registered access: authorizing data access.

Eur J Hum Genet 2018 12 2;26(12):1721-1731. Epub 2018 Aug 2.

Vanderbilt University Medical Center, Nashville, TN, USA.

The Global Alliance for Genomics and Health (GA4GH) proposes a data access policy model-"registered access"-to increase and improve access to data requiring an agreement to basic terms and conditions, such as the use of DNA sequence and health data in research. A registered access policy would enable a range of categories of users to gain access, starting with researchers and clinical care professionals. It would also facilitate general use and reuse of data but within the bounds of consent restrictions and other ethical obligations. In piloting registered access with the Scientific Demonstration data sharing projects of GA4GH, we provide additional ethics, policy and technical guidance to facilitate the implementation of this access model in an international setting.
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http://dx.doi.org/10.1038/s41431-018-0219-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244209PMC
December 2018

De novo mutations in regulatory elements in neurodevelopmental disorders.

Nature 2018 03 21;555(7698):611-616. Epub 2018 Mar 21.

Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.

We previously estimated that 42% of patients with severe developmental disorders carry pathogenic de novo mutations in coding sequences. The role of de novo mutations in regulatory elements affecting genes associated with developmental disorders, or other genes, has been essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 patients with developmental disorders. Here we show that de novo mutations in highly evolutionarily conserved fetal brain-active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant twofold enrichment of recurrently mutated elements. We estimate that, genome-wide, 1-3% of patients without a diagnostic coding variant carry pathogenic de novo mutations in fetal brain-active regulatory elements and that only 0.15% of all possible mutations within highly conserved fetal brain-active elements cause neurodevelopmental disorders with a dominant mechanism. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasize the importance of combining functional and evolutionary evidence to identify regulatory causes of genetic disorders.
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http://dx.doi.org/10.1038/nature25983DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912909PMC
March 2018

Paediatric genomics: diagnosing rare disease in children.

Nat Rev Genet 2018 05 19;19(5):325. Epub 2018 Feb 19.

This corrects the article DOI: 10.1038/nrg.2017.116.
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http://dx.doi.org/10.1038/nrg.2018.12DOI Listing
May 2018

Paediatric genomics: diagnosing rare disease in children.

Nat Rev Genet 2018 05 5;19(5):253-268. Epub 2018 Feb 5.

Cambridge University Hospitals National Health Service Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK.

The majority of rare diseases affect children, most of whom have an underlying genetic cause for their condition. However, making a molecular diagnosis with current technologies and knowledge is often still a challenge. Paediatric genomics is an immature but rapidly evolving field that tackles this issue by incorporating next-generation sequencing technologies, especially whole-exome sequencing and whole-genome sequencing, into research and clinical workflows. This complex multidisciplinary approach, coupled with the increasing availability of population genetic variation data, has already resulted in an increased discovery rate of causative genes and in improved diagnosis of rare paediatric disease. Importantly, for affected families, a better understanding of the genetic basis of rare disease translates to more accurate prognosis, management, surveillance and genetic advice; stimulates research into new therapies; and enables provision of better support.
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http://dx.doi.org/10.1038/nrg.2017.116DOI Listing
May 2018
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