In this study, we will use the various correlated data in the UK Biobank (UKB) to explore the genetic mechanisms of human diseases, including close and distant genetic relatives, temporally repeated measures and phenotyping, and molecularly relevant omic information. The target phenotypes and conditions under active study in my lab include cardiovascular diseases (including arrhythmia and cardiac artery disease), metabolic traits and disorder (obesity, circulating lipids, diabetes mellitus, and metabolic syndrome), mental disorder (mood disorder and eating disorders), neurodegenerative diseases (Alzheimer’s and Parkinson’s disease), infectious diseases (pneumonia and viral hepatitis) and medical images. Specifically, we will:
1. Develop and apply emerging genome shared segment approaches that leverage relatedness and segmental sharing patterns to identify, characterize, and validate trait-associated loci.
2. Integrate and compare the associated loci identified by shared segment approaches with those from traditional variant-based genomic approaches.
3. Investigate phenotype trajectories to expand our knowledge of genetic effects over time.
4. Compare the identified loci/genes from longitudinal phenotypes with results from cross-sectional phenotypes.
5. Implement a cross-sectional multi-omic profiling approach to find co-regulated gene/molecules sets important in disease pathogenesis.
6. Develop and apply an integration model that uses both longitudinal and multi-omic data to further investigate the genetic mechanisms of disease transition, development, and progression
7. Conduct a cross-population comparison with other biobank, such as All of Us, Taiwan Biobank, and Taiwan Precision Medicine Initiative.
