Using machine learning and genomics to understand aging and Alzheimer's disease
Official title: Team science approach to integrate machine-learning models and functional genomics to study aging in the context of Alzheimer's disease
Funded at Yale University · NIH-10931984 · Data updated 2026-11-12
This study is looking at how getting older impacts the risk of developing Alzheimer's disease by using advanced computer models and genetic information, and it hopes to find new ways to prevent and treat the disease that could help patients in the future.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project start | September 15, 2024 |
| Project end | June 30, 2026 |
| Funding year | 2024 |
| Award (this year) | $239,122 |
| NIH project number | 1R21AG087875-01 |
| Project ID | NIH-10931984 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals at risk for Alzheimer's disease, particularly those with a family history or genetic predisposition.
✕Less likely to help
Patients with advanced Alzheimer's disease or those who do not have any genetic risk factors for the condition may not benefit from this research.
What this research studies
This research investigates how aging affects the development of Alzheimer's disease by integrating machine-learning models with functional genomics. It aims to analyze large datasets to create a detailed model of brain aging and identify genetic factors that influence Alzheimer's risk. By studying both young and old human neurons and microglia, the research seeks to uncover the biological mechanisms that contribute to the disease. Patients may benefit from insights that could lead to better prevention and treatment strategies for Alzheimer's.
Why it matters
Potential benefit: If successful, this research could lead to improved understanding and potential new strategies for preventing or treating Alzheimer's disease.
How similar studies have gone: Other research has shown promise in using machine learning and genomics to study neurodegenerative diseases, indicating that this approach could yield valuable insights.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Brennand, Kristen Jennifer — Yale University
- Study coordinator: Brennand, Kristen Jennifer
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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.