Promoting Healthy Longevity: Implementation Recommendations for the Hevolution Alliance for Aging Biomarkers Initiative

Academic Background and Research Motivation

With the intensification of global population aging, human life expectancy has significantly increased, but the growth in healthy life expectancy (i.e., years lived in good health) has been relatively limited. This trend indicates that while people are living longer, they are also spending more time with illnesses. To change this situation, healthcare needs to shift from merely treating diseases to prioritizing prevention. The Geroscience hypothesis proposes that by intervening in the molecular damage that leads to aging, it is possible to extend healthy life expectancy, thereby stopping or even reversing the expansion of morbidity. However, to achieve this goal, reliable biomarkers must be developed to assess biological age and the rate of aging, and interventions that can slow down biological aging must be identified.

The Hevolution Foundation was established in 2021 to promote research on healthy longevity, providing resources to support innovative geroscience research. One of its key initiatives is the establishment of the Hevolution Alliance for Aging Biomarkers (HAAB), aimed at accelerating the translation of the geroscience hypothesis into clinical applications. The alliance’s goal is to develop a new generation of human aging biomarkers that not only assess biological age but also predict important health outcomes and respond to interventions.

Paper Source

This paper, titled “Recommendations for Implementing the Hevolution Alliance for Aging Biomarkers Initiative,” was co-authored by experts from various institutions, including the National Institute on Aging (NIA), Hevolution Foundation, Harvard Medical School, and others. It was published in the journal Nature Aging in January 2024.

Main Points and Discussion

1. Limitations of Current Aging Biomarkers

Current aging biomarkers have several limitations: - First and Second Generation Biomarkers: Based on epigenetic markers or clinical tests, their predictive validity is fair, but their biological mechanisms are unclear. - Cross-sectional Studies: Most biomarkers were developed in cross-sectional studies, and whether they can track longitudinal changes in biological aging or respond to interventions remains unclear. - Lack of Population Diversity: The predictive validity of these biomarkers has primarily been tested in populations of European descent, often using non-comparable methods. - Negative Event-oriented Outcomes: Currently used validation outcomes are mostly negative health events (such as death, chronic diseases), and it is unclear whether they can predict positive health dimensions (such as preserved functional ability, cognitive reserve, or well-being). - Single Omics Data: Existing approaches typically use only one type of omics data, and biomarkers built on different omics with similar predictive validity tend to be poorly correlated. Combining multiple omics data through deep learning or artificial intelligence could improve predictive accuracy. - Unclear Causal Relationships: It is unclear whether these molecular biomarkers directly cause negative aging outcomes or reflect the activation of mechanisms underlying biological resilience.

2. Design and Features of the HAAB Initiative

To overcome these limitations, the HAAB initiative proposes the following design elements: - Diversity and Representativeness: Cohorts participating in the database should cover diverse populations worldwide to ensure sample diversity. Each cohort should have at least three measurements over a period of at least six years (ideally ten years) to reliably estimate trajectory changes. - Core Variables and Specific Domains: All participating cohorts should provide core variables (such as age, sex, race/ethnicity, education, smoking history, vital status) and measure specific aging features (such as physical function, cognitive function, metabolic state). Emphasis is placed on longitudinal data because they can capture the temporal progression of health changes, aiding early prevention. - Biomarker Selection: Priority will be given to plasma and serum proteomics and DNA methylation data extracted from blood samples. Other omics data (such as metabolomics and transcriptomics) may be considered in the future. Participating cohorts should already have high-quality biomarker measurements or stored biospecimens available for analysis. - Data Coordination and Sharing: A data coordinating center will be established to handle data collection, quality control, standardization, and sharing. Lessons will be drawn from existing open databases (such as Gateway to Global Aging Data, Global Neurodegeneration Proteomics Consortium) to ensure wide availability and privacy protection of the data.

3. Specific Measures for Data Coordination and Sharing

• Role of the Data Coordinating Center: The data coordinating center will determine which cohorts meet project requirements and will be responsible for data transfer, quality control, standardization, and storage. It will optimize data coordination processes by referencing existing database infrastructures.
• Data Access and Sharing: A data access committee will ensure researchers have appropriate qualifications. A tiered or controlled access model will be adopted to ensure data security and privacy. Participating cohorts will have advance access before public release to incentivize participation.
• Synthetic Cohorts and Digital Twins: For privacy restrictions in certain countries or studies, synthetic cohorts or digital twins will be considered to maintain privacy while meeting research needs.

Research Significance and Value

The HAAB initiative is an ambitious project with the potential to make unique contributions to the translational application of the geroscience hypothesis. Beyond substantial financial investment, it requires the collaborative efforts of researchers and healthcare professionals from various disciplines. By establishing a large, diverse longitudinal cohort database, HAAB will provide a solid foundation for developing a new generation of aging biomarkers, thus advancing research and practice in healthy longevity.

Additionally, this project will facilitate the development and testing of biomarker algorithms, helping identify individuals who maintain good health over extended periods and uncovering the biological mechanisms of healthy aging. Ultimately, these research findings will provide new tools for clinical applications and offer scientific evidence for personalized prevention and treatment strategies.

Research Highlights

• Comprehensive Coverage of the Life Cycle: By integrating data from multiple global cohorts, the entire adult lifespan is covered, ensuring the effectiveness of biomarkers across different age groups.
• Diverse Population Participation: Emphasizing the diversity and representativeness of cohorts ensures the effectiveness of biomarkers across different races, genders, and socioeconomic backgrounds.
• Longitudinal Data Analysis: Utilizing longitudinal data to capture the temporal progression of health changes aids early prevention and intervention.
• Multi-omics Data Integration: Combining multiple omics data improves predictive accuracy and explores complex relationships between biomarkers and health outcomes.
• Data Sharing and Openness: Establishing an open data-sharing platform promotes collaboration and exchange among researchers globally, maximizing the application value of research results.

The HAAB initiative not only provides new directions for aging research but also lays a solid foundation for achieving healthy longevity.