In this project, we aim to address the following issues mainly in the area of liver diseases, e.g., non-alcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH), cirrhosis, liver cancer.
1. Find tools/indicators to identify who is more likely to develop NAFLD from obese or to develop NASH from NAFLD and etc.;
2. Find tools/indicators in assisting the clinical diagnosis of NAFLD, NASH and etc.;
3. Find tools/indicators to identify stages of NAFLD, NASH and etc.;
4. Find the best treatments for different individuals with liver diseases;
5. Infer the impact of medical history (e.g., NAFLD, NASH) on the prognosis and endpoints of COVID-19 infections.
Current NAFLD diagnosis relies on highly invasive and risky liver biopsies which cannot be applied to all patients at risk, and in addition, it cannot predict disease progression and remains unknown which patients develop NAFLD secondary to obesity. Hence, there is a need to identify tools/indictors which can better identify the disease, who should be targeted for interventions, what the risks are and differential response to therapy response and etc.
Whole body MRI facilitates the visualization of total body fat and lean mass distribution, which is associated with the risk of obesity related diseases and abnormal metabolic processes, while retina fundus (eye) images have been used to diagnose and predict disease (e.g. Type 2 diabetes, Cardiovascular diseases, Major Adverse Cardiovascular Events). In addition, many of the classical indictors for liver dysfunction are known to be in the category of plasma proteins. Hence, we envision to apply statistical and machine learning approaches to gain knowledge in MRI, retina fundus images and proteomics to improve the diagnosis and prediction of liver diseases.
To achieve these aims, we want to access annotated image, gene and proteomics data from the UK Biobank. We believe that these high dimensional data in UK biobank has the potential to improve the current diagnosis, prediction and treatment selection methods to liver diseases.
This project is an on-going project and the first stage would be 3 years.
