Abstract:
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition affecting an estimated 1% of New Zealanders, characterised by difficulties in social communication and interaction in addition to repetitive activities. Although the condition is well studied abroad, little New Zealand-specific information exists on the genetics of the condition. Presented here is the development of a bioinformatic methodology used to aid in the interpretation of rare coding variants obtained from massively-parallel sequencing data. This methodology involves the annotation of variants with relevant information, the filtering of variants based on characteristics such as population frequency, and the ranking of variants based on their likelihood to be causative for a neurodevelopmental condition. This methodology was successfully verified using a family with a known causative variant. The methodology was then implemented to identify genetic variants causing sporadic ASD or a similar neurodevelopmental condition in five independent families. A causal variant was identified in four families. These include a previously identified pathogenic SHANK3 frameshift, a rare variant in ARHGEF6, and novel variants in DNMT3A and DMD. All discovered variants, and their segregation within the family, were confirmed through Sanger sequencing. These discovered variants, and the diagnoses that have arisen from them, add to the growing body of evidence of the utility of whole genome and whole exome sequencing in diagnosing sporadic neurodevelopmental conditions such as ASD.