Comprehensive evaluation of causal relationship among different phenotypes and disease traits by Mendelian Randomization using Genetic Instruments
Most of the previous studies focused on the association between several risk factors and disease traits. Few studies demonstrated the cause-and-effect relationship, especially in a larger population. Our previous studies based on large-scale datasets suggested significant associations among different types of diseases and cancers. This suggests that an individual who has one type of disease/cancer (primary disease) may be at increased risk for another type of diseases/cancer (secondary disease). Such associations may be caused by potential biological mechanisms common in both diseases and shared environmental factors such as smoking. Therefore, in the current study, we aim to assess the causal relationship between exposures (such as disease traits etc.) and other diseases adjusting for potential shared factors (such as smoke, alcohol, blood glucose, etc.) by using a new statistical approach: Mendelian Randomization (MR). Such an approach allows us to interpret the causal relationship between two components: exposures and outcomes.
We will spend 36 months to perform this comprehensive analysis.
Results from our study will have several public health impacts: 1) the causal relationship between one disease and another disease may help us apply early protection/screening in patients with the disease; 2) the causal relationship may provide important evidence of biological mechanisms worth further investigation via a series of experiments, and may help us target important genetic variants associated with the diseases.