Biological markers linked to human lifespan and healthy aging
Official title: Human Longevity Associations, Trajectories and Predictions
Funded at Translational Genomics Research Inst · NIH-11195698 · Data updated 2026-11-12
This project uses large health and biological databases to find which genes, proteins, and blood measures best predict how long and how healthily people live.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Translational Genomics Research Inst NIH-funded |
| Lab location | 1 site (Phoenix, United States) |
| Project start | September 30, 2004 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $954,081 |
| NIH project number | 5U19AG023122-17 |
| Project ID | NIH-11195698 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are older adults or people from diverse backgrounds who are already part of long-term health cohorts or who have linked health records and biological samples.
✕Less likely to help
People without any long-term health records, biological samples, or interest in research follow-up are unlikely to benefit directly from this project.
What this research studies
From a patient's perspective, researchers combine genetic, protein, and metabolite data with long-term health records to see which biological signals relate to living longer and staying healthier. They bring together many past studies and Medicare records, standardize those data, and follow people over time to track health and death outcomes. Advanced statistics and machine learning will look for patterns that differ by sex, ancestry, and environment. The goal is to separate signs of aging from markers that actually predict future health and lifespan.
Why it matters
Potential benefit: If successful, this work could point to tests or targets that help predict and possibly prevent age-related decline, supporting more personalized plans to extend healthy years.
How similar studies have gone: Previous large studies have found many aging-related biomarkers, but combining diverse datasets and using new machine learning methods to predict longevity across populations is a more recent and evolving approach.
Where this research is happening
-
Translational Genomics Research Inst
Phoenix, United States Active
Researchers
- Principal investigator: Lapidus, Jodi a — Translational Genomics Research Inst
- Study coordinator: Lapidus, Jodi a
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.