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Abstracts

Identification of Shared Genotype-phenotype Correlation Pattern Across Epilepsy-associated Calcium and Sodium Channelopathies

Abstract number : 3.374
Submission category : 12. Genetics / 12A. Human Studies
Year : 2022
Submission ID : 2204571
Source : www.aesnet.org
Presentation date : 12/5/2022 12:00:00 PM
Published date : Nov 22, 2022, 05:25 AM

Authors :
Alina Ivaniuk, MD – Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA; Tobias Brünger, MS – Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany; Eduardo Pérez-Palma, PhD – Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana. Santiago, Chile; Ludovica Montanucci, PhD – Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA; Nisha Bhattarai, PhD – Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA; Katrine Johannesen, MD, PhD – Danish Epilepsy Centre, Filadelfia, Dianalund, Denmark; Jen Pan, PhD – Stanley Center for Psychiatric Research, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Patrick May, PhD – Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Henrike Heyne, MD – Hasso Plattner Institute, Mount Sinai School of Medicine, New York, NY 10029, USA; Ingo Helbig, MD – Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Stephanie Schorge, PhD – Department of Neuroscience, Physiology and Pharmacology, UCL, London WC1E 6BT, UK; Andreas Brunklaus, MD, MRCPCH – The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK; Rikke Møller, PhD – Danish Epilepsy Centre, Filadelfia, Dianalund, Denmark; Dennis Lal, PhD – Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA

Rationale: The CACNA1x and SCNxA gene families encode for voltage-dependent Ca2+ and Na+ channels, respectively. Pathogenic variants in these genes are associated with epilepsies and seizure disorders along with non-epileptic disease phenotypes. Variant pathogenicity classification is challenging, and genotype, molecular, and clinical phenotype associations are incompletely understood for the majority of these channelopathies. Identification of clinical criteria that allow inferences of each variant’s disease mechanisms could overcome current limitations and reduce barriers to patient enrollment in precision medicine trials. Here, we explore genotype-phenotype-based correlations between variants across CACNA1x and SCNxA gene families to further guide such inferences.

Methods: We collected patient missense variants for CACNA1x and SCNxA genes from the literature, patient registries, and ClinVar and HGMD databases as well as population variants from gnomAD. We screened the literature for phenotypes with high gene-disease association validity and curated variants and phenotypes. We mapped variants onto gene family-based 3D structure alignment and identified spatially correlated variants and phenotypes. The structure-correlated phenotype features, as well as biophysical properties, were used to develop prediction models that predict variant pathogenicity and phenotype groups.

Results: After quality control, 4,177 patient variants from six CACNA1x and nine SCNxA genes and 28818 population variants were available for analysis. The patient variants were grouped into 47 well-established phenotypes (median of 3 phenotypes per gene). Performing a sliding-window based patient vs. population burden analysis, we identified 17 hotspots that were enriched for patient variants across both gene families. Across the CACNA1x and SCNxA gene family, we observed 59 nominal significant disorder correlations based on the similar variant position on protein structure at conserved protein sites (e.g., the position of SCN1A Dravet syndrome variants was correlated with SCN5A variants causing Brugada syndrome and SCN2A variants causing autism).

Conclusions: Epilepsy-associated genetic variants in CACNA1x and SCNxA have structure position correlates in other genes expressed in different tissues, indicating conserved mechanisms contributing to different phenotypes. Insights from related genes may be used for building mechanism prediction models, developing criteria for paralog-based mechanism inference, and justifying the design of precision therapies with similar mechanisms in seemingly unrelated disorders.

Funding: This abstract received no funding support.
Genetics