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  • 1
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 98, No. 11 ( 2022-03-15), p. e1163-e1174
    Abstract: Pathogenic variants in the neuronal sodium channel α1 subunit gene ( SCN1A ) are the most frequent monogenic cause of epilepsy. Phenotypes comprise a wide clinical spectrum, including severe childhood epilepsy; Dravet syndrome, characterized by drug-resistant seizures, intellectual disability, and high mortality; and the milder genetic epilepsy with febrile seizures plus (GEFS+), characterized by normal cognition. Early recognition of a child's risk for developing Dravet syndrome vs GEFS+ is key for implementing disease-modifying therapies when available before cognitive impairment emerges. Our objective was to develop and validate a prediction model using clinical and genetic biomarkers for early diagnosis of SCN1A -related epilepsies. Methods We performed a retrospective multicenter cohort study comprising data from patients with SCN1A -positive Dravet syndrome and patients with GEFS+ consecutively referred for genetic testing (March 2001–June 2020) including age at seizure onset and a newly developed SCN1A genetic score. A training cohort was used to develop multiple prediction models that were validated using 2 independent blinded cohorts. Primary outcome was the discriminative accuracy of the model predicting Dravet syndrome vs other GEFS+ phenotypes. Results A total of 1,018 participants were included. The frequency of Dravet syndrome was 616/743 (83%) in the training cohort, 147/203 (72%) in validation cohort 1, and 60/72 (83%) in validation cohort 2. A high SCN1A genetic score (133.4 [SD 78.5] vs 52.0 [SD 57.5] ; p 〈 0.001) and young age at onset (6.0 [SD 3.0] vs 14.8 [SD 11.8] months; p 〈 0.001) were each associated with Dravet syndrome vs GEFS+. A combined SCN1A genetic score and seizure onset model separated Dravet syndrome from GEFS+ more effectively (area under the curve [AUC] 0.89 [95% CI 0.86–0.92] ) and outperformed all other models (AUC 0.79–0.85; p 〈 0.001). Model performance was replicated in both validation cohorts 1 (AUC 0.94 [95% CI 0.91–0.97] ) and 2 (AUC 0.92 [95% CI 0.82–1.00]). Discussion The prediction model allows objective estimation at disease onset whether a child will develop Dravet syndrome vs GEFS+, assisting clinicians with prognostic counseling and decisions on early institution of precision therapies (http://scn1a-prediction-model.broadinstitute.org/). Classification of Evidence This study provides Class II evidence that a combined SCN1A genetic score and seizure onset model distinguishes Dravet syndrome from other GEFS+ phenotypes.
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
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  • 2
    In: Brain, Oxford University Press (OUP), Vol. 143, No. 4 ( 2020-04-01), p. 1099-1105
    Abstract: A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall’s τ = 0.093, P-value = 6.9 × 10−6). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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  • 3
    In: Brain, Oxford University Press (OUP), Vol. 145, No. 11 ( 2022-11-21), p. 3816-3831
    Abstract: Brain voltage-gated sodium channel NaV1.1 (SCN1A) loss-of-function variants cause the severe epilepsy Dravet syndrome, as well as milder phenotypes associated with genetic epilepsy with febrile seizures plus. Gain of function SCN1A variants are associated with familial hemiplegic migraine type 3. Novel SCN1A-related phenotypes have been described including early infantile developmental and epileptic encephalopathy with movement disorder, and more recently neonatal presentations with arthrogryposis. Here we describe the clinical, genetic and functional evaluation of affected individuals. Thirty-five patients were ascertained via an international collaborative network using a structured clinical questionnaire and from the literature. We performed whole-cell voltage-clamp electrophysiological recordings comparing sodium channels containing wild-type versus variant NaV1.1 subunits. Findings were related to Dravet syndrome and familial hemiplegic migraine type 3 variants. We identified three distinct clinical presentations differing by age at onset and presence of arthrogryposis and/or movement disorder. The most severely affected infants (n = 13) presented with congenital arthrogryposis, neonatal onset epilepsy in the first 3 days of life, tonic seizures and apnoeas, accompanied by a significant movement disorder and profound intellectual disability. Twenty-one patients presented later, between 2 weeks and 3 months of age, with a severe early infantile developmental and epileptic encephalopathy and a movement disorder. One patient presented after 3 months with developmental and epileptic encephalopathy only. Associated SCN1A variants cluster in regions of channel inactivation associated with gain of function, different to Dravet syndrome variants (odds ratio = 17.8; confidence interval = 5.4–69.3; P = 1.3 × 10−7). Functional studies of both epilepsy and familial hemiplegic migraine type 3 variants reveal alterations of gating properties in keeping with neuronal hyperexcitability. While epilepsy variants result in a moderate increase in action current amplitude consistent with mild gain of function, familial hemiplegic migraine type 3 variants induce a larger effect on gating properties, in particular the increase of persistent current, resulting in a large increase of action current amplitude, consistent with stronger gain of function. Clinically, 13 out of 16 (81%) gain of function variants were associated with a reduction in seizures in response to sodium channel blocker treatment (carbamazepine, oxcarbazepine, phenytoin, lamotrigine or lacosamide) without evidence of symptom exacerbation. Our study expands the spectrum of gain of function SCN1A-related epilepsy phenotypes, defines key clinical features, provides novel insights into the underlying disease mechanisms between SCN1A-related epilepsy and familial hemiplegic migraine type 3, and identifies sodium channel blockers as potentially efficacious therapies. Gain of function disease should be considered in early onset epilepsies with a pathogenic SCN1A variant and non-Dravet syndrome phenotype.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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  • 4
    In: Brain, Oxford University Press (OUP), Vol. 146, No. 3 ( 2023-03-01), p. 923-934
    Abstract: Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. As a consequence, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion-channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated. We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion-channel families. We collected and curated 3049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12 546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures. We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis centre and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and functional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1422 neurodevelopmental disorder pathogenic patient variants and 679 electrophysiological experiments, we show that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain versus loss-of-channel function. In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional readouts and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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  • 5
    In: Human Mutation, Hindawi Limited, Vol. 41, No. 2 ( 2020-02), p. 363-374
    Type of Medium: Online Resource
    ISSN: 1059-7794 , 1098-1004
    URL: Issue
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 1498165-8
    SSG: 12
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  • 6
    In: European Journal of Paediatric Neurology, Elsevier BV, Vol. 24 ( 2020-01), p. 35-39
    Type of Medium: Online Resource
    ISSN: 1090-3798
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 2009085-7
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  • 7
    In: Brain, Oxford University Press (OUP), Vol. 146, No. 2 ( 2023-02-13), p. 519-533
    Abstract: Neurodevelopmental disorders (NDDs), including severe paediatric epilepsy, autism and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are ‘variants of uncertain significance’. To safely enrol patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can ‘tolerate’ missense variants and which ones are ‘essential’ and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the 3D structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14 377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including & gt;360 000 NDD patients and population controls, we found that missense variants at Essential3D sites are 8-fold enriched in patients. In summary, we developed a comprehensive protein structure set for 242 NDDs and identified 14 377 Essential3D sites in these. All data are available at https://es-ndd.broadinstitute.org for interactive visual inspection to enhance variant interpretation and development of mechanistic hypotheses for 242 NDDs genes. The provided resources will enhance clinical variant interpretation and in silico drug target development for NDD-associated genes and encoded proteins.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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  • 8
    In: Brain, Oxford University Press (OUP), Vol. 145, No. 12 ( 2022-12-19), p. 4275-4286
    Abstract: Pathogenic variants in the voltage-gated sodium channel gene family lead to early onset epilepsies, neurodevelopmental disorders, skeletal muscle channelopathies, peripheral neuropathies and cardiac arrhythmias. Disease-associated variants have diverse functional effects ranging from complete loss-of-function to marked gain-of-function. Therapeutic strategy is likely to depend on functional effect. Experimental studies offer important insights into channel function but are resource intensive and only performed in a minority of cases. Given the evolutionarily conserved nature of the sodium channel genes, we investigated whether similarities in biophysical properties between different voltage-gated sodium channels can predict function and inform precision treatment across sodium channelopathies. We performed a systematic literature search identifying functionally assessed variants in any of the nine voltage-gated sodium channel genes until 28 April 2021. We included missense variants that had been electrophysiologically characterized in mammalian cells in whole-cell patch-clamp recordings. We performed an alignment of linear protein sequences of all sodium channel genes and correlated variants by their overall functional effect on biophysical properties. Of 951 identified records, 437 sodium channel-variants met our inclusion criteria and were reviewed for functional properties. Of these, 141 variants were epilepsy-associated (SCN1/2/3/8A), 79 had a neuromuscular phenotype (SCN4/9/10/11A), 149 were associated with a cardiac phenotype (SCN5/10A) and 68 (16%) were considered benign. We detected 38 missense variant pairs with an identical disease-associated variant in a different sodium channel gene. Thirty-five out of 38 of those pairs resulted in similar functional consequences, indicating up to 92% biophysical agreement between corresponding sodium channel variants (odds ratio = 11.3; 95% confidence interval = 2.8 to 66.9; P & lt; 0.001). Pathogenic missense variants were clustered in specific functional domains, whereas population variants were significantly more frequent across non-conserved domains (odds ratio = 18.6; 95% confidence interval = 10.9–34.4; P & lt; 0.001). Pore-loop regions were frequently associated with loss-of-function variants, whereas inactivation sites were associated with gain-of-function (odds ratio = 42.1, 95% confidence interval = 14.5–122.4; P & lt; 0.001), whilst variants occurring in voltage-sensing regions comprised a range of gain- and loss-of-function effects. Our findings suggest that biophysical characterisation of variants in one SCN-gene can predict channel function across different SCN-genes where experimental data are not available. The collected data represent the first gain- versus loss-of-function topological map of SCN proteins indicating shared patterns of biophysical effects aiding variant analysis and guiding precision therapy. We integrated our findings into a free online webtool to facilitate functional sodium channel gene variant interpretation (http://SCN-viewer.broadinstitute.org).
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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  • 9
    In: Science Translational Medicine, American Association for the Advancement of Science (AAAS), Vol. 12, No. 556 ( 2020-08-12)
    Abstract: Malfunctions of voltage-gated sodium and calcium channels (encoded by SCNxA and CACNA1x family genes, respectively) have been associated with severe neurologic, psychiatric, cardiac, and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) that often corresponds not only to clinical disease manifestations but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. On the basis of known gene-disease mechanisms of 19 different diseases, we inferred LOF ( n = 518) and GOF ( n = 309) likely pathogenic variants from the disease phenotypes of variant carriers. By training a machine learning model on sequence- and structure-based features, we predicted LOF or GOF effects [area under the receiver operating characteristics curve (ROC) = 0.85] of likely pathogenic missense variants. Our LOF versus GOF prediction corresponded to molecular LOF versus GOF effects for 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and was validated in exome-wide data from 21,703 cases and 128,957 controls. We showed respective regional clustering of inferred LOF and GOF nucleotide variants across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCNxA/CACNA1x family genes.
    Type of Medium: Online Resource
    ISSN: 1946-6234 , 1946-6242
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2020
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