| Title: | Decoding Cardio-Renal Crosstalk in Coronary Artery Disease Using UK Biobank's Multi-Organ Imaging and Multi-Omics Data |
| Lead Institution: | Tianjin University of Traditional Chinese Medicine |
| Principal investigator: |
Application 778385
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
This 3-year project aims to address critical challenges in the diagnosis and treatment of atherosclerotic cardiovascular disease (ASCVD). Specifically, we will focus on the early detection of heart and kidney damage, the classification of disease risk types, and the understanding of underlying mechanisms driving disease progression. This research will also explore the development of AI tools that could significantly improve the accuracy of ASCVD diagnosis and treatment. The need for this research arises from the limitations of current medical tests, which often assess heart and kidney health in isolation. Many ASCVD patients experience the interplay of multiple organ systems, resulting in a high rate of misdiagnosis. By combining heart MRI scans and kidney function data, along with genetic, lifestyle, and other factors, we aim to improve diagnostic accuracy and offer earlier interventions. Our research will also explore modifiable risk factors, such as specific metabolic abnormalities, which could provide new therapeutic targets to protect both heart and kidney function.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 21571 | Triglyceride-glucose normalized creatinine-to-cystatin C ratio (TyG-NCCR) predicts cardiovascular-kidney-metabolic syndrome (CKM) stage progression: evidence from CHARLS and UK biobank | Xinying Liu (+11) | 2026 | Cardiovascular Diabetology |
Enabling scientific discoveries that improve human health