A new review published in Genomic Psychiatry calls into question the reliability of widely used measures for assessing biological aging. The analysis, led by Dr. Dan Ehninger and Dr. Maryam Keshavarz from the German Center for Neurodegenerative Diseases (DZNE), argues that common proxies such as lifespan extension, epigenetic clocks, frailty indices, and the hallmarks of aging framework may not accurately distinguish between true changes in aging processes and general physiological effects unrelated to age.
The authors conducted a cross-species analysis to understand what causes death in different organisms as they age. In humans, cardiovascular disease is responsible for 35 to 70 percent of deaths among older adults. Even centenarians who appeared healthy before death were found to have died from identifiable diseases rather than simply old age. In contrast, mice primarily die from neoplasia, with cancer accounting for up to 89 percent of age-related deaths. Dogs also show high rates of cancer-related mortality in old age, while captive nonhuman primates often die from cardiovascular disease similar to humans. For invertebrates like Drosophila and C. elegans, organ-specific failures or infections are the main limiting factors.
"This pattern illustrates that interventions targeting specific pathologies can extend lifespan by addressing critical bottlenecks to survival, but they do not necessarily slow the overall aging process," wrote Drs. Ehninger and Keshavarz.
The review points out that increases in human lifespan over recent centuries have mostly resulted from reductions in infectious disease mortality due to advances such as vaccines and antibiotics. These improvements changed the primary causes of death but did not fundamentally alter the rate at which biological aging occurs.
According to the authors, this distinction is important when interpreting research on longevity interventions. If an intervention extends mouse lifespan by delaying cancer onset but does not affect other aspects of aging physiology, it differs significantly from one that slows systemic decline—even if both result in longer life.
Aging clocks based on DNA methylation patterns are now popular tools for estimating biological age and evaluating interventions' effectiveness. While useful for risk prediction and population studies, these molecular markers may only reflect correlations with age rather than causally influencing aging itself. The authors note that "estimating age based on facial images can be highly predictive, yet wrinkles and gray hair offer limited insight into the biological processes driving aging." Recent genetic studies suggest traditional clocks do not target features with causal roles in aging.
Frailty indices face similar challenges because they aggregate diverse traits into single scores without considering whether improvements reflect broad antiaging effects or just isolated pathology reduction.
The review also critically examines evidence supporting the hallmarks of aging framework—a set of twelve categories believed to underlie biological aging processes—and finds methodological gaps in many supporting studies. Most experiments cited only assessed aged animals without including young treated groups; where young groups were included, most intervention effects appeared regardless of age group.
"Consequently, the evidence cited for most hallmarks supports the presence of general physiological effects rather than true antiaging mechanisms," concluded Drs. Ehninger and Keshavarz.
To address these issues, the authors propose a framework distinguishing between three types of intervention effects: rate effects (slowing age-dependent change), baseline effects (age-independent shifts), and mixed effects (changes seen at all ages but more pronounced with age). They recommend researchers include both young- and old-treated groups when testing interventions and classify outcomes accordingly instead of assuming all changes reflect slowed aging.
Recent experimental work using deep phenotyping has shown that established pro-longevity treatments—such as intermittent fasting or rapamycin—mainly produce baseline shifts rather than slowing rates of change across many phenotypes associated with aging.
The review highlights unresolved questions about why tissues within an organism may age at different rates and whether systemic or cell-autonomous mechanisms drive these differences across species whose life-limiting pathologies vary widely.
By synthesizing data across multiple species and reviewing methodological approaches used throughout the field, Drs. Ehninger and Keshavarz argue that better study designs are needed to clarify what current biomarkers actually measure—and ultimately guide resources toward interventions capable of modifying fundamental aspects of biological aging rather than merely treating symptoms or extending lifespan through pathology management alone.
"Refining both discovery pipelines and intervention testing frameworks will support a more mechanistic understanding of aging by enabling researchers to distinguish between interventions that simply extend lifespan or improve isolated age-sensitive phenotypes, and those that fundamentally modify the biological processes driving age-related decline," they write.
Drs. Ehninger’s laboratory focuses on uncovering mechanisms behind healthy lifespan extension at DZNE in Bonn; Dr. Keshavarz performed much of the systematic literature analysis underpinning this work. Their research was supported by funding from the European Union’s Horizon Europe Marie Sklodowska-Curie Actions Doctoral Networks under grant agreement number 101072759.
