Variant curation expert panel recommendations for RYR1 pathogenicity classifications in malignant hyperthermia susceptibility

Purpose As a ClinGen Expert Panel (EP) we set out to adapt the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) pathogenicity criteria for classification of RYR1 variants as related to autosomal dominantly inherited malignant hyperthermia (MH). Methods We specified ACMG/AMP criteria for variant classification for RYR1 and MH. Proposed rules were piloted on 84 variants. We applied quantitative evidence calibration for several criteria using likelihood ratios based on the Bayesian framework. Results Seven ACMG/AMP criteria were adopted without changes, nine were adopted with RYR1-specific modifications, and ten were dropped. The in silico (PP3 and BP4) and hotspot criteria (PM1) were evaluated quantitatively. REVEL gave an odds ratio (OR) of 23:1 for PP3 and 14:1 for BP4 using trichotomized cutoffs of >= 0.85 (pathogenic) and <= 0.5 (benign). The PM1 hotspot criterion had an OR of 24:1. PP3 and PM1 were implemented at moderate strength. Applying the revised ACMG/AMP criteria to 44 recognized MH variants, 29 were classified as pathogenic, 13 as likely pathogenic, and 2 as variants of uncertain significance. Conclusion Curation of these variants will facilitate classification of RYR1/MH genomic testing results, which is especially important for secondary findings analyses. Our approach to quantitatively calibrating criteria is generalizable to other variant curation expert panels.

Automated summary

The study aimed to adapt ACMG/AMP criteria for classification of RYR1 variants related to MH, which resulted in successfully identifying 29 pathogenic variants, 13 likely pathogenic variants, and 2 variants of uncertain significance through testing on 84 variants and fine-tuning of the criteria. The application of quantitative evidence calibration and Bayesian framework in this study is transferrable to other variant curation expert panels for genomic testing result classification.