Analyzing genetic data linked to health records for better disease understanding.
Official title: Multi-Trait Analysis in Large-Scale Biobank Datasets Linked to Electronic Health Records.
Funded at Columbia University Health Sciences · NIH-10866025 · Data updated 2026-11-12
This study is looking to make it easier to predict disease risks by using health data from large databases, and it’s designed for anyone interested in understanding how their health history and genetics might affect their chances of getting certain diseases.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia University Health Sciences NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 20, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $122,234 |
| NIH project number | 1K99HG013546-01 |
| Project ID | NIH-10866025 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with a history of chronic diseases or those interested in understanding their genetic predispositions to various health conditions.
✕Less likely to help
Patients without access to electronic health records or those with rare diseases that are not well represented in biobank datasets may not benefit from this research.
What this research studies
This research investigates how to improve disease risk prediction by analyzing large-scale biobank datasets linked to electronic health records. It aims to develop a new model called the Liability Threshold-based Phenotypic Integration (LTPI) that captures a comprehensive view of individual disease histories. By integrating information from both target and non-target traits, the study seeks to enhance the accuracy of disease association mapping and risk prediction. Patients' health data will be utilized to identify shared genetic factors that contribute to various conditions.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of disease risk, enabling personalized medicine approaches for patients.
How similar studies have gone: Previous research using similar multi-trait analysis approaches has shown promising results in improving disease risk prediction accuracy.
Where this research is happening
-
Columbia University Health Sciences
New York, United States Active
Researchers
- Principal investigator: Lee, Hyunkyu — Columbia University Health Sciences
- Study coordinator: Lee, Hyunkyu
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.