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SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis
(2023)
Arthur Stefanski
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Eduardo Pérez-Palma
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Tobias Brünger
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Ludovica Montanucci
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Cornelius Gati
<jats:title>Abstract</jats:title> <jats:p>Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making.</jats:p> <jats:p>We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches.</jats:p> <jats:p>The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10−3, 95% confidence interval: 1.5–15.3).</jats:p> <jats:p>In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).</jats:p>
Scopus© Citations 3 3
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Editorial: SLC6A1: the past, present and future
(2023)
Katrine M. Johannesen
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Eduardo Pérez-Palma
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Guido Rubboli
Scopus© Citations 2
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CNV-ClinViewer: enhancing the clinical interpretation of large copy-number variants online
(2023)
Marie Macnee
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Eduardo Pérez-Palma
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Tobias Brünger
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Chiara Klöckner
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Konrad Platzer
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Motivation</jats:title> <jats:p>Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype–phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Here, we introduce the CNV-ClinViewer, an open-source web application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment, the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators’ patient care and for basic scientists’ translational genomic research.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and implementation</jats:title> <jats:p>The web application is freely available at https://cnv-ClinViewer.broadinstitute.org and the open-source code can be found at https://github.com/LalResearchGroup/CNV-clinviewer.</jats:p> </jats:sec>
Scopus© Citations 13 15
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Identification and quantification of oligogenic loss-of-function disorders
(2022)
Arthur Stefanski
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Eduardo Pérez-Palma
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Marko Mrdjen
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Megan McHugh
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Costin Leu
Scopus© Citations 3 1
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Incidence and prevalence of major epilepsy-associated brain lesions
(2022)
Javier A. López-Rivera
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Victoria Smuk
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Costin Leu
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Gaelle Nasr
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Deborah Vegh
Scopus© Citations 15 1
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Analysing an allelic series of rare missense variants of CACNA1I in a Swedish schizophrenia cohort
(2021)
David Baez-Nieto
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Andrew Allen
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Seth Akers-Campbell
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Lingling Yang
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Nikita Budnik
<jats:title>Abstract</jats:title> <jats:p>CACNA1I is implicated in the susceptibility to schizophrenia by large-scale genetic association studies of single nucleotide polymorphisms. However, the channelopathy of CACNA1I in schizophrenia is unknown. CACNA1I encodes CaV3.3, a neuronal voltage-gated calcium channel that underlies a subtype of T-type current that is important for neuronal excitability in the thalamic reticular nucleus and other regions of the brain. Here, we present an extensive functional characterization of 57 naturally occurring rare and common missense variants of CACNA1I derived from a Swedish schizophrenia cohort of more than 10 000 individuals. Our analysis of this allelic series of coding CACNA1I variants revealed that reduced CaV3.3 channel current density was the dominant phenotype associated with rare CACNA1I coding alleles derived from control subjects, whereas rare CACNA1I alleles from schizophrenia patients encoded CaV3.3 channels with altered responses to voltages. CACNA1I variants associated with altered current density primarily impact the ionic channel pore and those associated with altered responses to voltage impact the voltage-sensing domain. CaV3.3 variants associated with altered voltage dependence of the CaV3.3 channel and those associated with peak current density deficits were significantly segregated across affected and unaffected groups (Fisher’s exact test, P = 0.034). Our results, together with recent data from the SCHEMA (Schizophrenia Exome Sequencing Meta-Analysis) cohort, suggest that reduced CaV3.3 function may protect against schizophrenia risk in rare cases. We subsequently modelled the effect of the biophysical properties of CaV3.3 channel variants on thalamic reticular nucleus excitability and found that compared with common variants, ultrarare CaV3.3-coding variants derived from control subjects significantly decreased thalamic reticular nucleus excitability (P = 0.011). When all rare variants were analysed, there was a non-significant trend between variants that reduced thalamic reticular nucleus excitability and variants that either had no effect or increased thalamic reticular nucleus excitability across disease status. Taken together, the results of our functional analysis of an allelic series of &gt;50 CACNA1I variants in a schizophrenia cohort reveal that loss of function of CaV3.3 is a molecular phenotype associated with reduced disease risk burden, and our approach may serve as a template strategy for channelopathies in polygenic disorders.</jats:p>
Scopus© Citations 22 1
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Development and Validation of a Prediction Model for Early Diagnosis of SCN1A-Related Epilepsies
(2022)
Andreas Brunklaus
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Eduardo Pérez-Palma
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Ismael Ghanty
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Ji Xinge
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Eva Brilstra
<jats:sec><jats:title>Background and Objectives</jats:title><jats:p>Pathogenic variants in the neuronal sodium channel α1 subunit gene (<jats:italic>SCN1A</jats:italic>) 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 <jats:italic>SCN1A</jats:italic>-related epilepsies.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We performed a retrospective multicenter cohort study comprising data from patients with <jats:italic>SCN1A</jats:italic>-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 <jats:italic>SCN1A</jats:italic> 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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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 <jats:italic>SCN1A</jats:italic> genetic score (133.4 [SD 78.5] vs 52.0 [SD 57.5]; <jats:italic>p</jats:italic> < 0.001) and young age at onset (6.0 [SD 3.0] vs 14.8 [SD 11.8] months; <jats:italic>p</jats:italic> < 0.001) were each associated with Dravet syndrome vs GEFS+. A combined <jats:italic>SCN1A</jats:italic> 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; <jats:italic>p</jats:italic> < 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]).</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>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 (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" specific-use="external-ds" ext-link-type="uri" xlink:href="http://scn1a-prediction-model.broadinstitute.org/">http://scn1a-prediction-model.broadinstitute.org/</jats:ext-link>).</jats:p></jats:sec><jats:sec><jats:title>Classification of Evidence</jats:title><jats:p>This study provides Class II evidence that a combined <jats:italic>SCN1A</jats:italic> genetic score and seizure onset model distinguishes Dravet syndrome from other GEFS+ phenotypes.</jats:p></jats:sec>
9Scopus© Citations 64
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Epilepsy Genetics and Precision Medicine in Adults: A New Landscape for Developmental and Epileptic Encephalopathies
(2022)
Álvaro Beltrán-Corbellini
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Ángel Aledo-Serrano
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Rikke S. Møller
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Eduardo Pérez-Palma
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Irene García-Morales
<jats:p>This review aims to provide an updated perspective of epilepsy genetics and precision medicine in adult patients, with special focus on developmental and epileptic encephalopathies (DEEs), covering relevant and controversial issues, such as defining candidates for genetic testing, which genetic tests to request and how to interpret them. A literature review was conducted, including findings in the discussion and recommendations. DEEs are wide and phenotypically heterogeneous electroclinical syndromes. They generally have a pediatric presentation, but patients frequently reach adulthood still undiagnosed. Identifying the etiology is essential, because there lies the key for precision medicine. Phenotypes modify according to age, and although deep phenotyping has allowed to outline certain entities, genotype-phenotype correlations are still poor, commonly leading to long-lasting diagnostic odysseys and ineffective therapies. Recent adult series show that the target patients to be identified for genetic testing are those with epilepsy and different risk factors. The clinician should take active part in the assessment of the pathogenicity of the variants detected, especially concerning variants of uncertain significance. An accurate diagnosis implies precision medicine, meaning genetic counseling, prognosis, possible future therapies, and a reduction of iatrogeny. Up to date, there are a few tens of gene mutations with additional concrete treatments, including those with restrictive/substitutive therapies, those with therapies modifying signaling pathways, and channelopathies, that are worth to be assessed in adults. Further research is needed regarding phenotyping of adult syndromes, early diagnosis, and the development of targeted therapies.</jats:p>
36Scopus© Citations 24

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