Understanding malignant hyperthermia : bioinformatic approaches to identify pathogenic genetic variants : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Biochemistry at Massey University, Palmerston North, New Zealand - Ormond, Shannon (Massey University, 2020)
Technological advances and decreasing costs in genome sequencing have greatly sped up the rate of identification of the genetic causes of inherited disease. One such human disorder in which genome sequencing is being applied in hope that the genetic causes will be identified is malignant hyperthermia (MH). MH is an autosomal dominant pharmacogenetic disorder which has long perplexed researchers due to its phenotypic and genetic complexity. Individuals susceptible to MH are at risk of a sometimes deadly hypermetabolic episode of skeletal muscle triggered by potent volatile general anaesthetic agents. Although the genetic origin of the disorder has been determined in over half of all MH families, there are many families for which the origin has not yet been elucidated. This research aimed to identify genetic variants that may be pathogenic for MH-susceptibility in six New Zealand families for which the genetic cause has not yet been identified. Targeted next-generation sequencing of the genome was undertaken on a number of individuals from each family. Bioinformatic approaches were developed and applied to identify candidate genetic variants. Segregation analysis was carried out for some of the identified candidate variants, which failed to establish an association with MH-susceptibility, although a number of variants were ruled out as being pathogenic for MH-susceptibility. Additionally, a common polymorphism that has been previously postulated to have a modifying effect on MH-susceptibility was identified within a large MH family. A genotype/phenotype association study was carried, however the study did not find an association. Overall, this work has reinforced that MH does not have a simple, easily identifiable genetic origin, suggesting there is one or more missing elements to the current understanding of MH. Importantly, it has established an effective MH-specific bioinformatic protocol that can be applied to other sequencing data in the future.
Keywords: 310204 Genomics and transcriptomics