DRAGON-Data: A platform and protocol for integrating genomic and phenotypic data across large psychiatric cohorts

Abstract

AbstractIntroductionCurrent psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptomatology and shared genetic liability is still poorly understood. Well-characterised, cross-disorder samples are needed to investigate this matter, but currently few exist, and severe mental disorders are poorly represented in existing biobanking efforts. Purposely curated and aggregated data from individual research groups can fulfil this unmet need, resulting in rich resources for psychiatric research.Methods and analysesAs part of the Cardiff MRC Mental Health Data Pathfinder, we have curated and harmonised phenotypic and genetic information from 15 studies within the MRC Centre for Neuropsychiatric Genetics and Genomics to create a new data repository, DRAGON-DATA. To date, DRAGON-DATA includes over 45,000 individuals: adults or children with psychiatric diagnoses, affected probands with family members and individuals who carry a known neurodevelopmental copy number variant (ND-CNV). We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all datasets with genotype information have undergone rigorous quality control, imputation, CNV calling and polygenic score generation.Ethics and DisseminationDRAGON-DATA combines genetic and non-genetic information and is available as a resource for research across traditional psychiatric diagnostic categories. Its structure and governance follow standard UK ethical requirements (at the level of participating studies and the project as a whole) and conforms to principles reflected in the EU data protection scheme (GDPR). Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with HDR UK.