Improving age prediction using DNA methylation data
Official title: Transfer learning and uncertainty quantification in epigenetic clocks
Funded at Rutgers Biomedical and Health Sciences · NIH-10933453 · Data updated 2026-11-12
This study is working on a new way to predict age more accurately using DNA information, especially for kids and teens, so that doctors and researchers can better understand how age affects health without needing personal details from individuals.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rutgers Biomedical and Health Sciences NIH-funded |
| Lab location | 1 site (Newark, UNITED STATES) |
| Project start | September 30, 2023 |
| Project end | May 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $156,658 |
| NIH project number | 5R21AG083364-02 |
| Project ID | NIH-10933453 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include children and adolescents, as well as adults who may benefit from improved age-related health assessments.
✕Less likely to help
Patients who do not fall within the age ranges of 0-21 years or those who are not interested in age-related health assessments may not benefit from this research.
What this research studies
This research aims to enhance the accuracy of age prediction by developing a transfer learning framework that refines existing DNA methylation clocks. It focuses on using data from different populations, including children and adolescents, to improve the adaptability of these age-related biomarkers. The project will also introduce methods to quantify uncertainty in age predictions, ensuring that results are communicated effectively within the scientific community. By leveraging existing data without needing to access individual-level information, this approach seeks to provide more reliable age assessments.
Why it matters
Potential benefit: If successful, this research could lead to more accurate age predictions, which may help in assessing age-related health risks and conditions.
How similar studies have gone: Other research has shown promise in using transfer learning for similar applications, indicating that this approach could yield significant advancements.
Where this research is happening
-
Rutgers Biomedical and Health Sciences
Newark, United States Active
Researchers
- Principal investigator: Luo, Lan — Rutgers Biomedical and Health Sciences
- Study coordinator: Luo, Lan
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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.