| Title: | Systematical analysis of risk factors for hematopetic malignancies |
| Lead Institution: | Ruijin Hospital |
| Principal investigator: |
Application 176137
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
Our research aims to understand why and how blood cancers, including leukemia, lymphoma, and myeloma, develop. We're using a massive database called the UK Biobank, which contains information from a diverse group of people. By looking at the genes, environment, and lifestyles of individuals in this database, we hope to identify the factors that increase the risk of these blood cancers. Imagine trying to solve a complex puzzle. Hematopoietic malignancies are like puzzles, and each person's puzzle is unique. Our goal is to piece together the patterns hidden in the data to find out what makes some people more likely to develop these blood cancers. We'll be using advanced statistical methods to analyze the data and understand how different factors, like our genes or where we live, contribute to the risk of blood cancers. We'll also explore if these factors vary among different types of blood cancers, providing a more detailed picture. Our study doesn't just stop at understanding the risk factors. We want to know if these risk factors have changed over time and what this means for preventing these blood cancers. Additionally, we'll dive into the molecular level, exploring the tiny details in our genes and cells, to understand the biological reasons behind these cancers. Our research has a real-world impact. By understanding the risks better, we hope to develop models that can predict who might be at a higher risk of these blood cancers. This could lead to personalized strategies for prevention and early detection, ultimately improving public health outcomes. This project is like searching for clues in a giant library of information, and we believe the answers we find will bring us closer to reducing the impact of blood cancers on people's lives. The project will take a few years, and the information we gather will contribute to the ongoing efforts to make our communities healthier and safer.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17581 | Plasma proteomic profiling with machine learning identifies immunometabolic perturbations associated with smoking and smoking cessation | Jinghao Ma (+8) | 2026 | iScience |
Enabling scientific discoveries that improve human health