Discovery of biomarkers for chronic and complex diseases risk predict based on biobank data
As life expectancy has increased, healthy longevity has become a major factor to one's quality of life socially. Given the situation, diseases that could still burden the society and the individual quality of life still exist, typically in the form of a chronic(all cancer) or complex diseases(dementia, cardiovascular disease).
The aim of this study is to (1) identify biomarkers of the disease to determine which of them are associated, (2) calculate the 5- year incidence risk using cohort data, (3) compare the progress using prediction model with the results from the deep learning technique.
The main outcome of this study is a cancer, dementia and cardiovascular diseases.
We require clinical, medical history and sociodemographic outcomes and genetic data from UK Biobank. This would enable us to identify and evaluate genetic mutations for pre-diagnosis of diseases using personalized risk score, further validate the analysis results using the Korea Biobank.
The project is planned to take approximately 36 months to complete.
Public health impact:
As a consequence of identifying the genomic biomarker that considers an individual's environmental factors, the research would predict the length of time one can stay healthy and disease-free and suggest modifiable factors, providing personalized treatment recommendations.