Comprehensive Database for Ryanodine Receptor-1 Related Disorders


Topic:

Other

Poster Number: 206

Author(s):

Tokunbor Lawal, PhD, National Institute of Nursing Research, Willa Riekhof, BS, National Institute of Nursing Research, Pooja Varma, BS, NIH, Nancy Terry, MLS, NIH Library, National Institutes of Health, Alexander Kushnir, MD PhD, NYU, Grossman School of Medicine, Michael Goldberg, MD, RYR-1 Foundation, Andrew Marks, MD, Columbia University College of Physicians and Surgeons, Joshua Todd, PhD, National Institute of Neurological Disorders and Stroke

Approximately 300 pathogenic RYR1 variants have been reported to date accounting for ~30% of congenital myopathies. RYR1 encodes the type one ryanodine receptor (RyR1), a 2.2 megadalton ion channel expressed in skeletal muscle that tightly regulates intracellular calcium flux. Pathogenic RYR1 variants result in a wide spectrum of monoallelic and biallelic congenital, late-onset, and triggered neuromuscular disease phenotypes for which there is no approved treatment. Moreover, the >2000 RYR1 variants of uncertain significance (VUS) present a diagnostic challenge since a majority remain uncharacterized in in vitro model systems, an issue compounded by limited utility of bioinformatic pathogenicity prediction tools for RYR1. In 2017, the RYR-1 Foundation provided seed funding for a RYR1-related disorders database with overarching goals to advance research and therapeutic development, support clinical interpretation, and inform the patient community. Two datasets have since been developed comprising (1) genotype-phenotype data on >2500 affected individuals, and (2) nonclinical data spanning >250 unique RYR1 variants and 16 cellular and animal model systems. Using commercially available variant curation software, human phenotype ontologies linked to RYR1 variants are extracted from published works on an ongoing basis and organized by MedDRA system organ class. A Boolean search strategy is used to extract relevant nonclinical published works from PubMed and EMBASE. The database taxonomy also incorporates genetic, bioinformatic, and structural data on each variant, as available. Feedback from the patient community, researchers, and medical professionals will be factored into the database build. We intend to leverage our cross-sector collaborative framework (government, academia, nonprofit, and industry) to launch a publicly available online database which will serve as impetus for international research collaboration and enhance clinical trial readiness for RYR1-related disorders.