Integrating genetic, clinical and phenotypic data to advance stratification, prediction and treatment in mental health.

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Mental ill health has a major impact on patients, their carers and the wider community. Psychiatric
disorders are estimated to cost the UK economy £70-100 Bn per year. Recently, large scale data sharing has allowed major progress to bemade in understanding the genetic basis of many major psychiatric disorders. The MRC Centre for Neuropsychiatric Genetics and Genomics (MRC CNGG) in Cardiff has played a leading role in driving this genomic progress. Key insights that have emerged include the polygenic nature of these conditions, the extensive overlap of risk across current diagnostic categories, and the convergence of risk factors onto specific biological processes. These advances in genetics offer major opportunities for improving stratification and treatment responses in mental disorders, as well as for the development of new biomarkers and biological models. However, to capitalise on this progress there is now a need to extend this large-scale data-driven approach forward by integrating genetic information with clinical, environmental, developmental and biological data at scale in mental health to transform the management of psychiatric disorders.
Our overall vision is to build key components of a platform that will enable the extension of the
collaborative efforts seen in psychiatric genetics into the clinical and biological platforms required for fundamental progress in psychiatric disorders. Our proposed programme comprises 4 Workstreams to achieve these aims:
Workstream (WS) 1. Development of a platform for integrating genomic and phenotypic data across large patient cohorts, including with electronic health records.
WS 2. Development of a school-based adolescent cohort for identifying the antecedents of early-onset psychiatric disorder.
WS 3. Developing a platform for advancing electrophysiological imaging biomarkers in mental
health disorders.
WS 4. Establishing methodologies for data sharing and standardisation in neuronal cellular model systems.