Using AI to understand the biological factors behind exceptional longevity.
Official title: AI-powered cross-level cross-species omics data integration to elucidate mechanisms of EL
Funded at Hunter College · NIH-10729946 · Data updated 2026-11-12
This study is exploring how certain biological factors work together to help people live longer, with the hope that what we learn can lead to better treatments for age-related diseases like Alzheimer's.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Hunter College NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | August 15, 2023 |
| Project end | July 31, 2025 |
| Funding year | 2023 |
| Award (this year) | $458,510 |
| NIH project number | 1R21AG083302-01 |
| Project ID | NIH-10729946 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals interested in the biological aspects of aging and those with a family history of exceptional longevity or Alzheimer's disease.
✕Less likely to help
Patients with no interest in aging research or those who do not have a genetic predisposition to longevity or Alzheimer's may not benefit from this research.
What this research studies
This research aims to uncover the molecular mechanisms that contribute to exceptional longevity by integrating complex biological data from various sources. It employs advanced machine learning techniques to analyze multi-omics data, which includes genetic, RNA, protein, and metabolic information. By developing a deep learning framework, the project seeks to improve our understanding of how these molecular components interact and influence aging and longevity. Patients may benefit from insights gained that could lead to new therapeutic strategies for age-related diseases, particularly Alzheimer's.
Why it matters
Potential benefit: If successful, this research could lead to breakthroughs in understanding aging and developing treatments for age-related conditions like Alzheimer's disease.
How similar studies have gone: Other research has shown promise in using machine learning for biological data integration, but this specific approach to exceptional longevity is relatively novel.
Where this research is happening
-
Hunter College
New York, United States Active
Researchers
- Principal investigator: Xie, Lei — Hunter College
- Study coordinator: Xie, Lei
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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.