Approved Research
Development of an improved biological age estimation method incorporating multi-omics data
Lay summary
- Aims:
To develop new algorithm for biological age evaluation and disease risk prediction utilizing multi-omics data, and search for disease-related and aging biomarkers, further to translate findings to clinical practice.
- Scientific rationale:
Importantly, the role of genetic background in the aging process has been largely overlooked, representing a crucial knowledge gap. The project seeks to address this gap by developing innovative methods that incorporate genetic information and multi-omics data for more accurate BA estimation.
The emerging field of multi-omics provides a comprehensive approach to explore aging across diverse organs and systems. This approach is poised to advance our understanding of the intricate interplay between genetics and aging processes, contributing valuable insights into the factors influencing BA and organ-specific aging across diverse biological systems.
- Project duration:
It will take about 3 years to complete our project.
- Public heath impact:
Accurate estimation of biological age, incorporating genetic information and multi-omics data, can inform healthcare planning by identifying individuals who may be at a higher risk of age-related diseases. This information can guide resource allocation and targeted interventions, optimizing healthcare delivery.
The study's focus on incorporating genetic information into biological age estimation aligns with the principles of precision medicine. Tailoring healthcare interventions based on an individual's genetic makeup and multi-omics profile can enhance treatment efficacy and minimize adverse effects.