Bayesian modeling to predict malignant hyperthermia susceptibility and pathogenicity of RYR1, CACNA1S and STAC3 variants.

Aim: Identify variants in RYR1, CACNA1S and STAC3, and predict malignant hyperthermia (MH) pathogenicity using Bayesian statistics in individuals clinically treated as MH susceptible (MHS). Materials & methods: Whole exome sequencing including RYR1, CACNA1S and STAC3 performed on 64 subjects with: MHS; suspected MH event or first-degree relative; and MH negative. Variant pathogenicity was estimated using in silico analysis, allele frequency and prior data to calculate Bayesian posterior probabilities.

Results

Bayesian statistics predicted CACNA1S variant p.Thr1009Lys and RYR1 variants p.Ser1728Phe and p.Leu4824Pro are likely pathogenic, and novel STAC3 variant p.Met187Thr has uncertain significance. Nearly a third of MHS subjects had only benign variants.

Conclusion

Bayesian method provides new approach to predict MH pathogenicity of genetic variants.