Better genetic methods to understand and predict cancer and heart disease
Quantitative Methods for Genetic Epidemiology
['FUNDING_OTHER'] · MAYO CLINIC ROCHESTER · NIH-11074647
Researchers are building statistical tools and software to combine genetic and health data so doctors can more accurately understand and predict cancers and heart conditions.
Quick facts
| Phase | ['FUNDING_OTHER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | MAYO CLINIC ROCHESTER (nih funded) |
| Locations | 1 site (ROCHESTER, UNITED STATES) |
| Trial ID | NIH-11074647 on ClinicalTrials.gov |
What this research studies
This project develops new statistical methods and software to combine large genetic datasets with health information to improve understanding of human diseases. The team focuses on four areas: analyzing multiple related traits together, pinpointing which genetic variants are truly responsible, studying how genetic effects work through biological pathways, and improving polygenic risk scores for prediction. They will integrate annotation data and multivariate approaches to make risk predictions more accurate and to reveal shared biological mechanisms across conditions. Methods will be released as software so other researchers and clinicians can apply them to cancer, cardiac, and other disease data.
Who could benefit from this research
Good fit: People with or at risk for cancer or heart disease, or individuals who have genetic test results or are willing to share health and genetic data, would be most relevant to the work.
Not a fit: People without available genetic data or whose conditions are not influenced by inherited genetic variation may not directly benefit from this project.
Why it matters
Potential benefit: If successful, these tools could lead to more accurate genetic risk predictions and clearer identification of which genetic changes drive cancers and heart disease.
How similar studies have performed: Related efforts like polygenic risk scoring and fine-mapping have shown promise for prediction and finding likely causal variants, but combining multivariate, mediation, and annotation-informed approaches remains an active and evolving area.
Where this research is happening
ROCHESTER, UNITED STATES
- MAYO CLINIC ROCHESTER — ROCHESTER, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: SCHAID, DANIEL J. — MAYO CLINIC ROCHESTER
- Study coordinator: SCHAID, DANIEL J.
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 below.
Conditions: Cancers, Cardiac Diseases, Cardiac Disorders