In search of better biomarkers of aging
The authors wish to thank their colleague Max Guo, health scientist administrator, Division of Aging Biology, for his collaboration on this post.
Statistical trends show that by 2050, approximately a quarter of the world population will consist of older adults. This forecast highlights the need for strategies to promote healthy aging and the development of biological markers that can identify which individuals are at increased risk for age-related conditions and disabilities.
The risk and progression of multiple aging conditions can be influenced by several fundamental mechanisms and processes such as damage and repair of tissue components, alterations in cellular bioenergetics, and changes in genomic structure and function. Thus, the discovery of biomarkers — whether circulating in the body or in specific organs and tissues — can help us track and better understand how these mechanisms and processes affect long-term health outcomes. Biomarkers could also lead to better ways of testing new therapies to treat or prevent age-related conditions.
With this immense scientific potential in mind, NIA seeks to support technological innovations that make new biomarker discoveries possible. Among the areas we hope to develop are:
- High-throughput ways to analyze blood and its components
- Translational research on crucial methodologic issues for collection and storage conditions for human biospecimens to assess the activity of specific cellular pathways
- Development of statistical methods that will help researchers evaluate the relationships of mechanistic markers to aging-related outcomes
- Research to understand the relationships between levels of a marker in one tissue compared with other organs and tissues
NIA’s Predictive Biomarkers Initiative
In 2019, NIA launched the Predictive Biomarkers Initiative and established an innovative research network focusing on the development and validation of high-throughput assays to examine several aging-related processes through biomarker detection and validation. This network is currently assessing and refining analytical methods, developing and validating markers of multiple aging mechanisms, testing variability of markers in human populations, and establishing relationships between biomarkers and aging-related traits from a variety of longitudinal cohort studies and/or clinical trials.
There is exciting progress being made already! Project highlights include:
- Biomarkers focusing on cell-specific profiles and mechanistic measures in blood and skeletal muscle biopsies
- Validating and optimizing the use of the epigenetic clock as a biomarker of healthspan and lifespan using blood and saliva samples
- Applying state-of-the-art proteomics technologies to identify and refine robust senescence-related biomarkers
- Investigating viral burden and systemic inflammation as predictive biomarkers for chronic disease and frailty
- Validating non-invasive single-cell imaging technologies as reliable biomarkers
Interested? Check out our cleared concepts and webinars
We were pleased to see three research concepts related to predictive biomarkers approved at our fall National Advisory Council on Aging meeting. These concepts could grow into future funding opportunities and are an excellent gateway to learning more about this exciting field:
- Cytosolic DNA Sensing as an Integrating Point of the Aging Hallmarks
- Inter-Organelle Communication as a Platform to Interrogate the Interactions of Hallmarks of Aging
- Mapping Interconnectivity Among Hallmarks of Aging Under Lifespan Modifications
NIA’s Research Centers Collaborative Network (RCCN) works to make NIA-supported resources like the Predictive Biomarkers Initiative available to the broader aging science community, and foster collaborations across other NIH-funded programs. If you’d like to dive deeper, we hold biannual webinars in partnership with the RCCN. Our most recent webinar is archived and viewable online at www.rccn-aging.org/oct-23-2020-rccn-webinar.
We are ready to collaborate with interested investigators! Visit the Predictive Biomarkers Initiative site to learn more or leave a question or comment below.