Precision Geromedicine Needs a Bioenergetic Foundation

A recent perspective by Ferrucci, Donega, Maier, and Kroemer makes an important argument: medicine must move toward precision geromedicine—an approach that identifies individualized aging trajectories, detects early loss of resilience, and intervenes before frailty and multimorbidity become established.

Their proposal shifts aging medicine away from a simple disease-by-disease model. Instead of waiting until clinical decline appears, precision geromedicine aims to understand which biological pathway is failing first, in which person, and at what stage of life.

The figure here captures this transition clearly.

Traditional medicine often intervenes after clinical manifestations have already emerged—when multimorbidity, frailty, and exhausted resilience limit treatment response.

Precision geromedicine, by contrast, begins earlier with multidimensional phenotyping: biological assessment, clinical assessment, and digital assessment. These data are then used to identify specific failing pathways, such as mitochondrial dysfunction, chronic inflammation, or proteostasis failure, and to match intervention to the dominant biological trajectory.

This is a major conceptual advance.

Aging is not presented as one uniform process. It is framed as a dynamic balance between damage and resilience.

Damage accumulates continuously, but disease and functional decline appear only when biological systems can no longer compensate, repair, adapt, and recover.

Yet this framing raises a deeper question:

What determines whether resilience succeeds, persists, or fails?

This is where the ERM, stress-adaptation, and bioenergetic-constraint frameworks can fill an important gap.

Resilience is often discussed as if it were a general biological capacity.

But resilience is not abstract. It is metabolically expensive.

Every adaptive response requires energy: immune activation, inflammation resolution, mitochondrial turnover, proteostasis, tissue repair, anabolic rebuilding, detoxification, neuroendocrine regulation, and recovery from stress all depend on ATP availability, redox flexibility, substrate handling, nutrient reserve, and mitochondrial oxidative capacity.

From the ERM perspective, the body does not simply “lose resilience.”

It spends resilience.

Repeated stress exposure creates a continuous demand for maintenance and repair.

When energy supply, nutrient reserve, mitochondrial throughput, and recovery time remain sufficient, adaptation resolves.

When exposure load repeatedly exceeds bioenergetic capacity, adaptation becomes prolonged, costly, and eventually maladaptive.

This adds a mechanistic layer to precision geromedicine.

Precision geromedicine asks:

Which aging trajectory, in whom, and when?

ERM and the throughput-limit framework ask:

What energetic constraint is driving that trajectory, and why is recovery failing to complete?

The image shows mitochondrial dysfunction, chronic inflammation, and proteostasis failure as separate examples of failing pathways. Clinically, this is useful. But biologically, these pathways may not be independent. They may be interlocking expressions of unresolved bioenergetic stress.

Mitochondrial throughput limitation can reduce ATP availability, increase redox pressure, impair proteostasis, sustain inflammatory signaling, alter substrate handling, and weaken repair capacity.

Chronic inflammation increases energetic demand and can further impair mitochondrial function.

Proteostasis failure increases the burden of damaged proteins and organelles, requiring even more energy for repair and clearance.

These processes can reinforce one another until adaptation no longer resolves.

In this sense, ERM provides a bridge between the pathways in the figure. It asks whether the organism still has enough energetic execution capacity to complete the biological work required for recovery.

The review also emphasizes the need for dynamic biomarkers that capture stress responsiveness and system-level resilience, not only static biological-age scores.

This is another area where ERM can contribute.

A dynamic biomarker does not always need to be a new molecule. It may be a changing relationship among existing markers across time, stress exposure, and recovery.

For example, the clinically meaningful signal may not be “CRP is high” or “glucose is abnormal” in isolation.

The more important question is whether inflammation resolves, whether glucose and lipid flux remain metabolically flexible, whether muscle maintenance resumes, whether nutritional reserves are preserved, and whether functional recovery occurs after perturbation.

This is the basis of biomarker trade-off pattern recognition.

Under chronic stress adaptation, the body reallocates resources. Energy may be redirected from long-term maintenance toward short-term survival. Repair may be delayed. Muscle anabolism may be suppressed. Lipid storage may increase when oxidative throughput is constrained. Inflammation may persist when resolution becomes energetically unaffordable. Insulin resistance may partly act as an inflow throttle when substrate supply exceeds mitochondrial processing capacity.

These patterns are not random abnormalities. They may represent adaptive trade-offs that become harmful when they fail to resolve.

This helps fill one of the major gaps in current geromedicine.

The field increasingly recognizes that aging biomarkers must be interpreted longitudinally and dynamically. But it still needs a framework for interpreting what coordinated biomarker changes mean.

ERM offers one: biomarkers can be read as signatures of allocation, compensation, and unresolved adaptation.

A metabolic-dominant trajectory may reflect substrate overload, impaired metabolic flexibility, and mitochondrial throughput limitation.

An inflammatory-dominant trajectory may reflect persistent immune activation, unresolved repair signaling, and increasing energetic cost of defense.

A frailty-dominant trajectory may reflect declining ATP reserve, impaired anabolic maintenance, reduced muscle energetics, and failure of recovery after stress.

A high-resilience trajectory may reflect preserved mitochondrial flexibility, adequate nutrient reserve, efficient repair, and rapid resolution after perturbation.

This does not replace precision geromedicine.

It strengthens it.

The review’s proposal becomes more actionable when resilience is grounded in bioenergetics.

Instead of only identifying that a person is on a metabolic, inflammatory, or frailty trajectory, clinicians and researchers can ask whether the underlying bottleneck is substrate inflow, oxidative throughput, redox balance, ATP availability, mitochondrial quality control, nutrient reserve, or recovery time.

This also changes how we think about intervention.

If mitochondrial throughput is constrained, simply pushing more anabolic, metabolic, or immune-stimulating signals may fail. The cell may receive the command to repair, rebuild, or adapt, but lack the energetic execution capacity to complete the work. In that situation, the priority is not only to stimulate repair, but to restore the conditions that make repair biologically affordable: mitochondrial efficiency, redox balance, nutrient adequacy, sleep, recovery, physical conditioning, and appropriate substrate matching.

This is why the bioenergetic perspective is not pessimistic. It is more precise and more compassionate. It explains why people can feel stuck despite good intentions, good signals, or even good interventions. The body may not be broken; it may be overloaded, under-resourced, and unable to complete recovery.

Precision geromedicine is moving the field in the right direction by asking us to target trajectories rather than endpoints.

ERM, stress-adaptation biology, and the throughput-limit framework can help explain why those trajectories emerge in the first place.

The next step may be to place bioenergetics at the center of resilience science.

Because stress exposure is unavoidable.

But recovery is conditional.

Reference

Ferrucci, L., Donega, S., Maier, A. B., & Kroemer, G. (2026). Encouraging a move toward precision geromedicine. Geromedicine, 2, Article 202611. https://doi.org/10.70401/Geromedicine.2026.0020