Cancer is the leading cause of reduced quality of life and premature death. The incidence of cancer is rising in the UK and worldwide. The development of cancer is influenced by a number of factors, including genetics, environment, lifestyle, age and so on. However, its association with image derived phenotypes has been little studied. Since magnetic resonance imaging is a non-invasive technique, and mental health is another dimension that is different from the physical state, combining image derived phenotypes, mental health and multi-omics can identify people at high risk of pan-cancer from more perspectives.
Moreover, Mendelian randomization analysis can investigate the casual relationship between exposure and outcome using genetic variants as instrumental variables. It can provide evidence for causality in observational studies and is less likely to be influenced by confounders. Thus, we can analyze the causality of pan-cancer with the exposures mentioned above.
We expect to use 36 months to complete the project. Our research will help to advance understanding of the effects of cancer on cardiac size and function, mental health and brain health. We also hope to develop a higher precision risk prediction model on pan-cancer based on multi-modal data to identify people at high risk of cancer.
