Approved Research

Associations of genetic factors, healthy lifestyle behavior, testosterone level and sleep traits with human healthspan

Lay summary

Life expectancy has increased dramatically since the last century, while the quality of life for the elderly has not increased proportionally. These challenges call for longevity research to focus on understanding the pathways controlling healthspan.

Previous studies have found that endogenous testosterone concentrations, lifestyle behaviors, and sleep traits are associated with the risk of various cancers and chronic diseases, while the relationship between them and healthspan is still unknown.

Complex mechanisms driven by a combination of genetic, environmental, and lifestyle factors cause differences in individual healthspan. UK Biobank cohort, a large dataset with both environmental exposures and genomics data, has an incomparable advantage to systematically identify the risk factors for short healthspan.

We estimate that we will complete the majority of data analysis and finish the publication of the relevant results in 18 months. For these aims, we propose to:

1. investigate the associations and the causal relationships between testosterone level, sleep traits, healthy lifestyle index (HLI), and healthspan;

2. develop a polygenic risk score (PRS) for human healthspan based on reported healthspan-associated genetic variants;

3. use the above results to generate a health prediction model to establish new strategies for extending healthspan.

Our study will help to promote the understanding of aging and longevity, and the model could be used in identifying groups of individuals who are at high risk of short healthspan and more likely to benefit from interventions.

Scope extension:

This project aims to answer the following questions:

1. To investigate the associations between testosterone level, sleep traits, healthy lifestyle index (HLI), and healthspan, and to assess causality using Mendelian randomization (MR).
2. To develop a polygenic risk score (PRS) for human healthspan in the UK biobank.
3. To generate a healthspan prediction model to identify individuals who may be at high risk of short healthspan and more likely to benefit from interventions.
4. To explore the association between genetic variations (i.e., common and low-frequency variants, mosaic chromosomal alterations) and the outcomes of healthspan, such as solid cancers, cardiovascular diseases and other chronic diseases.
5. To investigate the association between diet (mainly meat, egg and dairy products), air pollution and healthspan, and to assess causality using Mendelian randomization (MR).