Genetics of traits associated with autism
Principal Investigator:
Professor Simon Baron-Cohen
Approved Research ID:
23787
Approval date:
June 1st 2016
Lay summary
We aim to investigate the genetics of traits that are associated with autism including excellence in science, technology, engineering and maths, and relationships with family and friends. This will help us understand if genetic variants that contribute to autism also contribute to specific areas of talents and difficulties seen in individuals with autism. Autism is a condition affecting approximately 1% of the population. 50 - 90% of the variance in autism can be attributed to genetics, and a large fraction of that to common genetic variants. Individuals with autism have difficulties and strengths in various social and non-social domains. Understanding the genetics of these domains will help us to better understand the genetic architecture of autism, identify altered biological pathways, and, perhaps, stratify individuals within the autism spectrum to better understand and work with their specific needs and abilities. 1) We will conduct a genome-wide association study of traits related to autism such as STEM ability, social skills; 2) Using the autism data from the psychiatric genomics consortium, we will identify correlation between these traits and autism, and with other traits related to autism (such as empathy and systemizing) that we have access to; 3) In conjunction with data from NDAR and SSC, we will construct polygenic risk scores and use this to investigate if individuals within the spectrum can be clustered; 4) Heritability, pathway and tissue enrichment will be calculated. Due to the small effect sizes of the SNPs involved in these traits, we request genetic data from all the participants phenotyped. We request genetic data that will be released later on in 2016 as well. Depending on the sample size, cohort will be split into two groups. The first will be a discovery cohort, and the second will be a replication cohort. We will finally conduct a meta-analysis of both the cohorts to increase the power of the final analysis.