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Browsing by Author "May, Patrick"

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    CNV-ClinViewer: enhancing the clinical interpretation oflarge copy-number variants online
    (2023) Macnee, Marie; Pérez Palma, Eduardo; Brünger, Tobias; Klöckner, Chiara; Platzer, Konrad; Stefansk, Arthur; Montanucci, Ludovica; Bayat, Allan; Radtke, Maximilian; Collins, Ryan; Talkowski, Michael; Blankenberg, Daniel; Møller, Rikke; Lemke, Johannes; Nothnagel, Michael; May, Patrick; Lal, Dennis
    Motivation: 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. Results: 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.
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    Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes
    (2022) Brünger, Tobias; Pérez, Eduardo; Montanucci, Ludovica; Nothnagel, Michael; Møller, Rikke; Schorge, Stephanie; Zuberi, Sameer; Symonds, Joseph; Lemke, Johannes; Brunklaus, Andreas; Traynelis, Stephen; May, Patrick; Lal, Dennis
    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.
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    Data-driven historical characterization of epilepsy-associated genes
    (2022) Macnee, Marie; Pérez, Eduardo; López, Javier; Ivaniuk, Alina; May, Patrick; Møller, Rikke; Lal, Dennis
    Many epilepsy-associated genes have been identified over the last three decades, revealing a remarkable molecular heterogeneity with the shared outcome of recurrent seizures. Information about the genetic landscape of epilepsies is scattered throughout the literature and answering the simple question of how many genes are associated with epilepsy is not straightforward. Here, we present a computationally driven analytical review of epilepsy-associated genes using the complete scientific literature in PubMed. Based on our search criteria, we identified a total of 738 epilepsy-associated genes. We further classified these genes into two Tiers. A broad gene list of 738 epilepsy-associated genes (Tier 2) and a narrow gene list composed of 143 epilepsy-associated genes (Tier 1). Our search criteria do not reflect the degree of association. The average yearly number of identified epilepsy-associated genes between 1992 and 2021 was 4.8. However, most of these genes were only identified in the last decade (2010-2019). Ion channels represent the largest class of epilepsy-associated genes. For many of these, both gain- and loss-of-function effects have been associated with epilepsy in recent years. We identify 28 genes frequently reported with heterogenous variant effects which should be considered for variant interpretation. Overall, our study provides an updated and manually curated list of epilepsy-related genes together with additional annotations and classifications reflecting the current genetic landscape of epilepsy.
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    Delineation of functionally essential protein regions for 242 neurodevelopmental genes
    (2022) Iqbal, Sumaiya; Brünger, Tobias; Pérez, Eduardo; Macnee, Marie; Brunklaus, Andreas; Daly, Mark; Campbell, Arthur; Hoksza, David; May, Patrick; Lal, Dennis
    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 >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.
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    Genomic analysis of AlphaFold2-predicted structures identifies maps of 3D essential sites in 243 neurodevelopmental disorder-associated proteins
    (2022) Iqbal, Sumaiya; Brunger, Tobias; Pérez Palma, Eduardo; Hoksza, David; Campbell, Arthur; Daly, Mark; May, Patrick; Lal, Dennis
    We propose a new methodology to identify maps of essential sites (i.e., amino acid residues) in 3D, called Essential 3D sites.
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    SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis
    (2023) Stefanski, Arthur; Pérez Palma, Eduardo; Brünger, Tobias; Montanucci, Ludovica; Gati, Cornelius; Klöckner, Chiara; Johannesen, Katrine; Goodspeed, Kimberly; Macnee, Marie; Deng, Alexander; Aledo, Ángel; Borovikov,Artem; Kava, Maina; Bouman, Arjan; Hajianpour, M.; Pal, Deb; Engelen, Marc; Hagebeuk, Eveline; Shinawi, Marwan; Heidlebaugh, Alexis; Oetjens, Kathryn; Hoffman, Trevor; Striano, Pasquale; Freed, Amanda; Futtrup, Line; Balslev, Thomas; Abulí, Anna; Danvoye, Leslie; Lederer, Damien; Balci, Tugce; Nabavi, Maryam; Butler, Elizabeth; Drewes, Sarah; Van Engelen, Kalene; Howell, Katherine; Khoury, Jean; May, Patrick; Trinidad, Marena; Froelich, Steven; Lemke, Johannes
    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. 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. 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). 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/).

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