Abstract
Biobanks collect data across multiple phenotypic domains, often leveraging data collected as part of routine clinical care, and link these data to multiple “omics” data sources. These data differ from data collected in traditional epidemiological studies and are ideal for studies of clinical comorbidities in psychiatric disorders, treatment response, and disease trajectories over time. Challenges in defining psychiatric outcomes reflect the inherent diagnostic complexity of psychiatric disorders and are being addressed by novel algorithmic phenotyping efforts. Moreover, biobank data enable hypothesis-generating research designs such as the phenome-wide and lab-wide association study, which can test relationships between mental health and outcomes or biomarkers that are rarely collected together. Despite the relative recency of biobanks, we have made great progress toward using these resources to improve the lives of people with psychiatric disorders. More work lies ahead, and it is an exciting time to be working in psychiatric genomics and precision psychiatry.
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