ORCID Profile
0000-0003-2958-5076
Current Organisations
University of Manchester
,
University of Cambridge
,
University of Exeter
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Publisher: Springer Science and Business Media LLC
Date: 08-2016
DOI: 10.1038/NG.3627
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 09-08-2017
DOI: 10.1212/WNL.0000000000004331
Abstract: To define a distinct SCN1A developmental and epileptic encephalopathy with early onset, profound impairment, and movement disorder. A case series of 9 children were identified with a profound developmental and epileptic encephalopathy and SCN1A mutation. We identified 9 children 3 to 12 years of age 7 were male. Seizure onset was at 6 to 12 weeks with hemiclonic seizures, bilateral tonic-clonic seizures, or spasms. All children had profound developmental impairment and were nonverbal and nonambulatory, and 7 of 9 required a gastrostomy. A hyperkinetic movement disorder occurred in all and was characterized by dystonia and choreoathetosis with prominent oral dyskinesia and onset from 2 to 20 months of age. Eight had a recurrent missense SCN1A mutation, p.Thr226Met. The remaining child had the missense mutation p.Pro1345Ser. The mutation arose de novo in 8 of 9 for the remaining case, the mother was negative and the father was unavailable. Here, we present a phenotype-genotype correlation for SCN1A . We describe a distinct SCN1A phenotype, early infantile SCN1A encephalopathy, which is readily distinguishable from the well-recognized entities of Dravet syndrome and genetic epilepsy with febrile seizures plus. This disorder has an earlier age at onset, profound developmental impairment, and a distinctive hyperkinetic movement disorder, setting it apart from Dravet syndrome. Remarkably, 8 of 9 children had the recurrent missense mutation p.Thr226Met.
Publisher: Springer Science and Business Media LLC
Date: 25-01-2017
DOI: 10.1038/NATURE21062
Publisher: Cold Spring Harbor Laboratory
Date: 29-12-2021
DOI: 10.1101/2021.12.28.21267792
Abstract: The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts. We convened a panel of clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups. We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight ex les of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for these variants. These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.
Publisher: Springer Science and Business Media LLC
Date: 26-09-2018
Publisher: Elsevier BV
Date: 06-2019
Publisher: Cold Spring Harbor Laboratory
Date: 04-05-2018
DOI: 10.1101/309070
Abstract: There are thousands of rare human disorders caused by a single deleterious, protein-coding genetic variant 1 . However, patients with the same genetic defect can have different clinical presentation 2–4 , and some in iduals carrying known disease-causing variants can appear unaffected 5 . What explains these differences? Here, we show in a cohort of 6,987 children with heterogeneous severe neurodevelopmental disorders expected to be almost entirely monogenic that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome wide common variant burden by showing that it is over-transmitted from parents to children in an independent s le of 728 trios from the same cohort. Our common variant signal is significantly positively correlated with genetic predisposition to fewer years of schooling, decreased intelligence, and risk of schizophrenia. We found that common variant risk was not significantly different between in iduals with and without a known protein-coding diagnostic variant, suggesting that common variant risk is not confined to patients without a monogenic diagnosis. In addition, previously published common variant scores for autism, height, birth weight, and intracranial volume were all correlated with those traits within our cohort, suggesting that phenotypic expression in in iduals with monogenic disorders is affected by the same variants as the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in disorders typically considered to be monogenic.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 07-12-2018
Abstract: The genetics of developmental disorders (DDs) is complex. Martin et al. wanted to determine the degree of recessive inheritance of DDs in protein-coding genes. They examined the exomes of more than 6000 families in populations with high and low proportions of consanguineous marriages. They found that 3.6% of DDs in in iduals of European ancestry involved recessive coding disorders, less than a tenth of the levels previously estimated. Furthermore, among South Asians with high parental relatedness, rather than most of the disorders arising from inherited variants, fewer than half had a recessive coding diagnosis. Science , this issue p. 1161
Publisher: Cold Spring Harbor Laboratory
Date: 24-07-2023
DOI: 10.1101/2023.07.24.23293070
Abstract: Autosomal recessive (AR) coding variants are a well-known cause of rare disorders. We quantified the contribution of these variants to developmental disorders (DDs) in the largest and most ancestrally erse s le to date, comprising 29,745 trios from the Deciphering Developmental Disorders (DDD) study and the genetic diagnostics company GeneDx, of whom 20.4% have genetically-inferred non-European ancestries. The estimated fraction of patients attributable to exome-wide AR coding variants ranged from ∼2% to ∼18% across genetically-inferred ancestry groups, and was significantly correlated with the average autozygosity (r=0.99, p=5x10 -6 ). Established AR DD-associated (ARDD) genes explained 90% of the total AR coding burden, and this was not significantly different between probands with genetically-inferred European versus non-European ancestries. Approximately half the burden in these established genes was explained by variants not already reported as pathogenic in ClinVar. We estimated that ∼1% of undiagnosed patients in both cohorts were attributable to damaging biallelic genotypes involving missense variants in established ARDD genes, highlighting the challenge in interpreting these. By testing for gene-specific enrichment of damaging biallelic genotypes, we identified two novel ARDD genes passing Bonferroni correction, KBTBD2 (p=1x10 -7 ) and CRELD1 (p=9x10 -8 ). Several other novel or recently-reported candidate genes were identified at a more lenient 5% false-discovery rate, including ZDHHC16 and HECTD4 . This study expands our understanding of the genetic architecture of DDs across erse genetically-inferred ancestry groups and suggests that improving strategies for interpreting missense variants in known ARDD genes may allow us to diagnose more patients than discovering the remaining genes.
Publisher: Wiley
Date: 10-2009
DOI: 10.1111/J.1749-6632.2009.04942.X
Abstract: Public health is defined as the organized efforts of society to improve health. This is often framed in terms of prevention, with primary, secondary, and tertiary prevention representing, respectively, fundamental prevention through understanding of causation, to alteration of natural history, through understanding of pathophysiological mechanisms and palliation. Biomarkers play a role in all of these levels of prevention of dementias. The clearest application of biomarkers from a public health perspective is in the setting of screening. Screening has particular meaning for public health and includes early detection as a core element, coupled with treatments or preventative actions to reduce the burden of disease. Here, we will cover the range of evidence required if biomarkers are to play a part in population prevention of dementia, including scientific and technical aspects together with ethical, legal, and social considerations. Ensuring research activity that addresses these wider perspectives is essential.
Publisher: Springer Science and Business Media LLC
Date: 14-10-2020
Publisher: Springer Science and Business Media LLC
Date: 05-10-2015
DOI: 10.1038/NG.3410
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 05-2019
Publisher: Cold Spring Harbor Laboratory
Date: 25-04-2023
DOI: 10.1101/2023.04.20.23288860
Abstract: Recent work has revealed an important role for rare, incompletely penetrant inherited coding variants in neurodevelopmental disorders (NDDs). Additionally, we have previously shown that common variants contribute to risk for rare NDDs. Here, we investigate whether common variants exert their effects by modifying gene expression, using multi- cis -expression quantitative trait loci ( cis -eQTL) prediction models. We first performed a transcriptome-wide association study for NDDs using 6,987 probands from the Deciphering Developmental Disorders (DDD) study and 9,720 controls, and found one gene, RAB2A , that passed multiple testing correction (p = 6.7×10 −7 ). We then investigated whether cis -eQTLs modify the penetrance of putatively damaging, rare coding variants inherited by NDD probands from their unaffected parents in a set of 1,700 trios. We found no evidence that unaffected parents transmitting putatively damaging coding variants had higher genetically-predicted expression of the variant-harboring gene than their child. In probands carrying putatively damaging variants in constrained genes, the genetically-predicted expression of these genes in blood was lower than in controls (p = 2.7×10 −3 ). However, results for proband-control comparisons were inconsistent across different sets of genes, variant filters and tissues. We find limited evidence that common cis -eQTLs modify penetrance of rare coding variants in a large cohort of NDD probands.
Publisher: Cold Spring Harbor Laboratory
Date: 23-03-2020
DOI: 10.1101/2020.03.18.20037960
Abstract: Over 130 X-linked genes have been robustly associated with developmental disorders (DDs), and X-linked causes have been hypothesised to underlie the higher DD rates in males. We evaluated the burden of X-linked coding variation in 11,046 DD patients, and found 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 developed an improved strategy to detect novel X-linked DDs and identified 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 DD-associated genes. Importantly, we estimated that, in male probands, only 13% of inherited rare missense variants in known DD-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 in idual X-linked disorders.
Publisher: Springer Science and Business Media LLC
Date: 21-09-2020
DOI: 10.1038/S41467-020-20852-3
Abstract: 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 in idual X-linked disorders.
Publisher: Cold Spring Harbor Laboratory
Date: 02-10-2020
DOI: 10.1101/2020.10.02.20194241
Abstract: Structural Variation (SV) describes a broad class of genetic variation greater than 50bps in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DD). Patients presenting with DD are often referred for diagnostic testing with chromosomal microarrays (CMA) 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, patients with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the novel 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 DD recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 64 rare, damaging variants in genes previously associated with DD missed by standard SNV, InDel or CNV discovery approaches. Clinical review of these 64 variants determined that about half (30/64) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21-500 bps in size, and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.3%. 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 patients. InDelible provides a framework for the discovery of pathogenic SVs that are likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.
Publisher: Cold Spring Harbor Laboratory
Date: 13-10-2017
DOI: 10.1101/201533
Abstract: Large exome-sequencing datasets offer an unprecedented opportunity to understand the genetic architecture of rare diseases, informing clinical genetics counseling and optimal study designs for disease gene identification. We analyzed 7,448 exome-sequenced families from the Deciphering Developmental Disorders study, and, for the first time, estimated the causal contribution of recessive coding variation exome-wide. We found that the proportion of cases attributable to recessive coding variants is surprisingly low in patients of European ancestry, at only 3.6%, versus 50% of cases explained by de novo coding mutations. Surprisingly, we found that, even in European probands with affected siblings, recessive coding variants are only likely to explain ~12% of cases. In contrast, they account for 31% of probands with Pakistani ancestry due to elevated autozygosity. We tested every gene for an excess of damaging homozygous or compound heterozygous genotypes and found three genes that passed stringent Bonferroni correction: EIF3F , KDM5B , and THOC6 . EIF3F is a novel disease gene, and KDM5B has previously been reported as a dominant disease gene. KDM5B appears to follow a complex mode of inheritance, in which heterozygous loss-of-function variants (LoFs) show incomplete penetrance and biallelic LoFs are fully penetrant. Our results suggest that a large proportion of undiagnosed developmental disorders remain to be explained by other factors, such as noncoding variants and polygenic risk.
Publisher: S. Karger AG
Date: 14-12-2011
DOI: 10.1159/000334436
Abstract: i Background: /i Medical risk prediction models estimate the likelihood of future health-related events. Many make use of information derived from analysis of the genome. Models predict health outcomes such as cardiovascular disease, stroke and cancer, and for some conditions several models exist. Although risk models can help decision-making in clinical medicine and public health, they can also be harmful, for ex le, by misdirecting clinical effort away from those who are most likely to benefit towards people with less need, thus exacerbating health inequalities. i Discussion: /i Risk prediction models need careful assessment before implementation, but the current approach to their development, evaluation and implementation is inappropriate. As a result, some models are pressed into use before it is clear whether they are suitable, while in other cases there is confusion about which model to use. This paper proposes an approach to the appraisal of risk-scoring models, based on a conference of UK experts. i Summary: /i By specifying what needs to be known before a model can be judged suitable for translation from research into practice, we can ensure that useful models are taken up promptly, that less well-proven ones undergo further evaluation and that resources are not wasted on ineffective ones.
Publisher: Cold Spring Harbor Laboratory
Date: 16-10-2019
DOI: 10.1101/797787
Abstract: De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, 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 dominant DDs.
Publisher: Cold Spring Harbor Laboratory
Date: 03-01-2025
DOI: 10.1101/2022.01.03.21268593
Abstract: Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research however, universal standards and terminologies to define the evidence base for the role of a gene in disease, and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed. The GenCC drafted harmonized definitions for differing levels of gene-disease validity based on existing resources, and performed a modified Delphi survey with three rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members. Based on 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contains 15,241 gene-disease assertions on 4,569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%. Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.
Publisher: Elsevier BV
Date: 04-2015
Publisher: Elsevier BV
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 24-12-2014
DOI: 10.1038/NATURE14135
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Caroline Wright.