Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases

Large-scale population-based genotyped biobanks with dense phenotypic information provide opportunities for genetic analysis at scale. However, the heterogeneous phenotypic data sources in such biobanks present challenges in disease case assertation. Here, we evaluated the consistencies of genetic associations identified from hospital records, questionnaire responses, and family history of diseases using genetic parameters, such as genetic correlation. We also showed the utility of combining the unstructured and heterogeneous data sources to improve the power of genetic analysis.