Sadhasivam S, Brandom BW, Henker RA, McAuliffe JJ. Bayesian modeling to predict malignant hyperthermia susceptibility and pathogenicity of
RYR1,
CACNA1S and
STAC3 variants.
Pharmacogenomics 2019;
20:989-1003. [PMID:
31559918 PMCID:
PMC7006767 DOI:
10.2217/pgs-2019-0055]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 07/17/2019] [Indexed: 11/21/2022] Open
Abstract
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.
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