Left-right asymmetry is an important feature of the human brain. One prominently asymmetric brain network underlies the uniquely human ability to speak and understand language. A lack of brain asymmetry is associated with variation in human cognitive abilities linked to language, and also susceptibility to cognitive disorders including language impairment and dyslexia. The genetic basis of human brain asymmetry is unknown, while links between asymmetric anatomy and function are poorly understood. It is likely that genes involved in brain asymmetry contain variants in the population that influence cognitive performance and cognitive disorders. We will test whether certain genetic profiles affect asymmetric brain structure and function particularly for regions involved in speaking and listening. We will also test whether these same genetic variations affect susceptibility to language-related disorders including dyslexia and Specific Language Impairment. Both can be severe disorders with lifelong impacts on achievement and mental health. Dyslexia is identified as a disability in the UK’s Equality Act 2010. According to the British Dyslexia Association, roughly 4% of the population has severely impaired reading ability. Each illiterate pupil, by age 37, is estimated to cost taxpayers an extra roughly 50,000GBP. Some brain regions are asymmetrical and important for speech and language. We will use Biobank brain imaging data in combination with genetic data to identify genomic profiles linked to the thickness, surface area and volumes of these regions. If possible, we will also do a similar analysis with Biobank MRI data that measures how active the language regions are during rest. We will follow up the findings in other cohorts of people with brain imaging and genetic data, and language-related disorders and genetic data. We are leading members of scientific consortia that study these questions with meta-analysis. Data will be used from all Biobank participants who have done MRI scans (roughly 5000 at the time of writing, September 2015). We will also need the genotype data of as many of these participants as possible. The larger the available dataset, the more statistical power there is to detect and measure the individual and pooled effects of genomic variants on brain anatomy and function.
