Team science approach to study aging and Alzheimer’s disease with machine learning and functional genomics
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-11537711 · Data updated 2026-11-12
A combined team effort will use advanced computer models and brain cell data to understand how aging influences Alzheimer’s disease.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| 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, 2029 |
| Funding year | 2026 |
| Award (this year) | $792,447 |
| NIH project number | 4R33AG087875-03 |
| Project ID | NIH-11537711 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals at risk for or diagnosed with Alzheimer’s disease, and those contributing neural cells (from donors) for research.
✕Less likely to help
People not affected by Alzheimer’s or without interest in contributing samples or data will not directly benefit.
What this research studies
This project brings together experts to build cell-type specific networks that explain how aging processes and genetic risk shape Alzheimer’s disease. They will use large-scale brain datasets to connect aging signals with disease biology and create a model of how normal aging affects brain cells differently in people who develop Alzheimer’s. The work will generate new data from donor-derived neurons and microglia to map regulatory elements that change with age and impact disease risk. The plan includes sharing findings and datasets to help researchers pursue targeted therapies.
Why it matters
Potential benefit: If successful, it could identify aging-related mechanisms driving Alzheimer’s and point toward new therapeutic targets to slow or prevent dementia.
How similar studies have gone: Previous studies show that integrating epigenomic and transcriptomic data can reveal mechanisms of aging and disease, with growing evidence of usefulness for Alzheimer’s.
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.