Investigations of the genetic overlap between internalising psychiatric disorders and co-morbid physical health disorders.

Identify changes in DNA that increase the risk for psychiatric disorders alone (specifically the internalising disorders: depression, anxiety including OCD, and related disorders), and for these disorders in the presence of co-morbid physical disorders (autoimmune disorders, including rheumatoid arthritis, and non-immune disorders, including type 2 diabetes, migraine, chronic pain, obesity and body-mass index). Disorder status will be determined from the UK Biobank adjudicated health outcomes, including data from primary care , hospitals, and self-report. We will also explore whether the variants associated with each psychiatric disorder predict the likelihood that an individual has a given physical disorder. Understanding how genetics influence psychiatric disorders, and the relationship between psychiatric and physical disorders, will provide much-needed insight into the underlying biology. As well as increasing our understanding of interactions between the brain and body, this may identify target systems for the development of novel treatments in psychiatry; for example, the re-purposing of anti-inflammatory drugs for the treatment of schizophrenia and depression is a promising area of ongoing research. Furthermore, identification of shared genetic risk factors could assist in diagnosis by determining whether a given patient is high or low risk. Genotype information is being produced on the UK Biobank sample. We will use this to perform genome-wide association studies using publicly-available software packages, testing thousands of DNA variants for their association with different disorders. We will compare individuals with internalising disorders to controls, as well as comparing those with both a psychiatric and a physical disorder to those with only one (to identify genetic variants associated with having both disorders).
We will also explore the genetic overlap between a given psychiatric disorder and associated physical disorders, using the results from the association studies and publicly-available software packages. Full cohort