| Title: | Assessing and Mitigating Major Adverse Liver Outcomes among patients with metabolic-associated steatotic liver diseases: risk factor analysis based on multi-dimensional data |
| Lead Institution: | Pennington Biomedical Research Center |
| Principal investigator: |
Application 177053
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About
Our research project aims to understand and prevent serious liver problems in people with liver diseases linked to metabolic issues, like obesity and diabetes. We plan to figure out what factors increase the risk of these liver problems, how to predict them, and the best ways to prevent them. Liver diseases related to metabolic issues, like too much fat in the liver, are becoming more common. These conditions can lead to serious health problems, including liver failure. However, it's tough to predict who will develop these severe problems and how to prevent them. Our project will use a mix of genetics, health data, and lifestyle information to get a clearer picture of these diseases. This approach is important because it looks at the whole picture, including how genes and lifestyle choices like diet and exercise affect liver health. We will use data from the UK Biobank, a large health database, to study people with these liver diseases. We'll look at their genetic information, health records, and lifestyle habits. We'll also use a method called Mendelian Randomization, which helps us understand if a certain factor (like a diet) actually causes liver problems or not. Plus, we'll use advanced computer techniques (machine learning) to analyze this data and predict who might be at risk for serious liver issues. Our research can have a big impact on public health. By understanding what causes serious liver problems in these patients, we can develop better ways to prevent and treat these conditions. This could mean fewer people suffering from severe liver diseases, less strain on healthcare systems, and more effective treatments. Also, our findings could help educate people about the risks of these liver conditions and how to avoid them, leading to healthier communities. n summary, our project aims to shed light on a growing health issue by combining genetics, health data, and computer analysis. Our goal is to improve the prevention and treatment of serious liver diseases related to metabolic issues, benefiting both individuals and the wider public health. The project is expected to take 36 months.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 16350 | Dynamic phenotypes of preclinical and clinical obesity in relation to new-onset cancer risk: A longitudinal analysis from the UK biobank | Manrong Xu (+5) | 2025 | Diabetes Obesity and Metabolism |
Enabling scientific discoveries that improve human health