Could a new framework for aging biomarkers revolutionize how we understand and treat the aging process?

In a recent review published in the journal Cell, a group of authors established a comprehensive framework for the terminology, characterization, and validation of aging biomarkers to facilitate their integration into clinical research and practice.

Study: Biomarkers of aging for the identification and evaluation of longevity interventions. Image Credit: tomertu / ShutterstockStudy: Biomarkers of aging for the identification and evaluation of longevity interventions. Image Credit: tomertu / Shutterstock


Over time, organisms experience changes from genetics and accumulated damage, defining aging. Despite interventions in animal models suggesting aging modulation, human translation is intricate. Since the 1960s, while the need for aging biomarkers has been recognized, standardization has been lacking. The biomarkers of aging consortium, leveraging past research, present a vital framework for these biomarkers, aiming to integrate them clinically and optimize aging intervention evaluations.

Biomarker classifications

For clarity, biomarkers of aging can be categorized as molecular, biological, functional, clinical, and phenotypic. The United States Food and Drug Administration (FDA) has further classifications such as molecular, physiological, histologic, or radiographic. Molecular biomarkers, a significant category, can be founded on omics or specific molecules. Physiological biomarkers relate to functional performance or physical characteristics. Moreover, emerging digital health technologies (DHTs) offer a new type of biomarker, using wearables and non-wearables to collect health and aging data. However, histologic and radiographic biomarkers, requiring specialized equipment and expertise, remain underutilized.

Clinical applications of biomarkers

Biomarkers also vary based on clinical application. Predictive biomarkers identify individuals susceptible to certain treatments or events. The NIA Predictive Biomarkers Initiative promotes the development and validation of these. Prognostic biomarkers, on the other hand, predict disease course in already diseased individuals. Response biomarkers indicate an individual's reaction to treatments or exposures. Surrogate endpoint biomarkers, once validated, can substitute direct patient measurements in clinical trials. Lastly, discovering biomarkers linked to biological pathways helps identify new therapeutic targets for aging-related diseases. 

With these classifications and applications, researchers aim for a harmonized approach to aging biomarker research, bridging the gap between various definitions and approaches.

Criteria for assessing biomarkers of aging

While there have been proposals over the decades regarding the ideal biomarkers of aging, no single biomarker captures all facets of biological aging. The criteria discussed offer a framework to gauge a biomarker's feasibility, validity, and applicability in a given context.

Feasibility criteria 

Biomarker measurements should ensure animal safety and minimal human invasiveness for ethical and widespread use. Consistency over time and quick measurement relative to an organism's lifespan is essential for reliability and practicality.

Validity criteria

A valuable biomarker captures the biological effects of aging rather than just indicating chronological age. It must link directly to the aging process and anticipate age-related outcomes.

Integrative biomarkers

Integrative biomarkers provide a comprehensive view of aging, highlighting the accumulated biological damage and its pace. This dual insight offers a holistic perspective, facilitating better understanding and intervention in the aging process.

Mechanistic considerations

Biomarkers must be reflective of the underlying biology of aging, such as cellular and molecular processes that determine aging phenotypes. As the understanding of the pillars of aging advances, recent endeavors lean towards the development of mechanistically informative biomarkers. For instance, epigenetic clocks and plasma proteomics are emerging as promising mechanistic biomarkers of aging, indicating the intricate cellular processes they represent.

Generalizability across contexts

Biomarkers should ideally be functional across various settings. This includes applying to different cell types, organs, species, and even diverse human populations. A true biomarker should be valid for both humans and model organisms, supporting the consistency in aging processes across species. However, understanding the boundaries of a biomarker's applicability is crucial, especially when considering variations among different populations or species.

Responsiveness to aging modifiers

Aging biomarkers should be sensitive to conditions that modify the aging rate. For instance, they should indicate accelerated aging in adverse conditions or reflect the beneficial effects of interventions known to extend lifespan. This ensures that the biomarkers remain relevant and dynamic, truly capturing the biological changes that result from varied life circumstances or therapeutic interventions.

Validation of biomarkers

Analytical Validation 

Biomarkers play a crucial role in medical research and diagnostics. Their reliability is paramount, necessitating rigorous analytical validation. This process ensures that biomarkers have minimal error, a robust signal, and negligible technical variation. Precision is a cornerstone of this validation, ensuring consistent results in both repeated tests and under varied conditions. Beyond precision, the accuracy of the biomarker is vital. It is about measuring how closely the observed value mirrors the true value. While sensitivity and specificity are standard metrics, continuous processes like aging need more nuanced measures. Integral to this process are proper sample handling, the use of sophisticated assays, and the employment of precise methods for interpretation, ranging from straightforward thresholds to intricate deep-learning techniques.

Clinical Validation in Biomarker Research

Clinical validation serves as a keystone in translating biomarker research into practical medical applications. Its core objective is to evaluate the real-world effectiveness and relevance of biomarkers within human clinical trials. Central to this is the concept of a surrogate endpoint. If alterations in a biomarker's levels can reliably forecast tangible clinical benefits, such as decreased susceptibility to age-associated ailments or improved survival rates, its validation becomes more substantial. Biomarkers don various hats – they can predict future health conditions, offer prognostic insights, or indicate responses to treatments. Notably, methylation-centric biomarkers have been encouraging in preliminary studies. However, a broader and more extensive validation landscape is necessary to ascertain their pivotal role in age-defying interventions.

Challenges and prospects in aging biomarker research

The science of aging is complex, with challenges in differentiating true age-related changes from mere associations. Current biomarkers often equate biological to chronological age, a potentially flawed method. The type of biological sample used also matters; what is observed in blood might not represent slower-regenerating organs. For clinical use, standardizing measurements is vital. Researchers should also consider both an individual's biological age and their aging rate for a comprehensive view. As we push forward, it is essential not only to focus on mortality but also on functional outcomes and quality of life to truly understand and address aging.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    


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