Integrative analysis of disease association variants and electronic medical records to delineate the genetic mechanisms of human diseases, identify novel drug targets, and enable drug repositioning.
Principal Investigator:
Dr Rong Chen
Approved Research ID:
16013
Approval date:
February 1st 2016
Lay summary
Questions and hypotheses: Many genetic variants play a functional role in disease pathogenesis. While many of those variants are pathogenic, there are also variants protective of diseases. In addition, there could be overlap of genetic mechanisms between Mendelian disease and complex diseases. Specific Aims: (1). To identify protective alleles in carriers of high-risk variants in genes associated with complex diseases; (2). To identify loss-of-function genetic variants in drug target genes associated with complex diseases or phenotypic traits for drug repurposing; (3). To investigate if recessive Mendelian disease alleles are associated with increased risk of certain complex diseases. The proposed research objective and specific aims are to identify genetic determinants of human diseases and contribute to novel therapeutic development. This is consistent with UK Biobank's overall purpose to improve prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses including cancers, metabolic and renal disease, and CNS disease such as dementia. Aims: (1). To identify protective alleles in carriers of high-risk variants in genes associated with complex diseases; (2). To identify loss-of-function genetic variants in drug target genes associated with complex diseases or phenotypic traits for drug repurposing; (3). To investigate if recessive Mendelian disease alleles are associated with increased risk of certain complex diseases. Methods: Apply standard statistical tests such as logistic regression and fishers exact test to identify disease protective variants, or to identify loss-of-function variants or mendelian pathogenic variants associated with complex diseases. Currently we are interested in the following diseases, which will be based on diagnosis in electronic medical records available through UK Biobank: cancers, type 2 diabetes, cardiovascular diseases, and alzheimer's diseases. Because the novel data analysis approach we are applying can be applied to all diseases, we may request access to other disease types as well.