🧠 Rethinking Early Aging: How ERM Fills a Critical Gap in Stress and Healthspan Science

Despite growing interest in longevity, most aging research still focuses on endpoints—decline, disease, disability. But what if we could detect the body’s slow derailment long before these milestones? What if early-stage biological strain—before weight loss, frailty, or abnormal labs—could be measured, staged, and reversed?

That’s exactly where Exposure-Related Malnutrition (ERM) enters the conversation.

ERM is a proposed condition that describes a reversible state of bioenergetic compromise resulting from chronic stress exposure. It’s not caused by insufficient calories or food insecurity. Instead, it arises from mismatch—between metabolic demand and resource availability—under conditions of sustained physiological strain. The hallmark isn’t weight loss but subtle patterns of substrate reallocation and functional decline across core systems: neuroendocrine, immune, muscular, mitochondrial, and cellular.

Our recent preprint and ongoing systematic review seek to formalize this concept—bringing structure to a pattern clinicians see, but rarely quantify.

🔍 Two Landmark Reviews That Set the Stage

In recent years, two important frameworks have emerged that independently identify the gap that ERM seeks to fill.

1. Fuellen et al. (2019): Health as Functional Deviation

This landmark review redefines aging not as a countdown to death, but as the accumulation of biological processes that reduce health or survival—collectively termed “illbeing.” In their model, health is scored across domains like physical, cognitive, immune, and metabolic function—not as binary disease/no disease, but as deviation from normative reference populations. Crucially, their model is threshold-free and staging-friendly—perfect for identifying patterns of subclinical stress-related decline.

2. Gaylord et al. (2023): Biomarkers of Aging Across the Life Course

This more recent review shifts the aging conversation to an even earlier timeline—highlighting that stress-related biological aging begins in utero and early childhood. It catalogs stress-imprinted biomarkers like:

Epigenetic clocks
Inflammation-related methylation scores (i-ePGS)
Glucocorticoid exposure scores (GES)
Mitochondrial DNA copy number (mtDNAcn)

These tools track how early adversity and chronic adaptation shape long-term health trajectories, but remain siloed in aging or developmental studies. Gaylord et al. call for integrative models to make sense of this complexity.

🧩 Where ERM Fits In

ERM builds the bridge between these frameworks:

From Fuellen, we inherit a scalable model of physiological function—defined by trade-offs, not thresholds.
From Gaylord, we gain tools to detect bioenergetic strain early, long before frailty or decline.
From clinical observation, we contribute the phenotype: patients who are "normal" on paper, but show chronic fatigue, immune dysregulation, anabolic resistance, or slowed recovery—despite normal weight and intake.

Together, ERM offers a stageable framework for early malnutrition that:

Recognizes stress-related metabolic compromise as an intermediate state.
Uses life-course biomarkers to identify energy-strained systems.
Supports precision prevention and resilience-informed recovery.

🚀 Why This Matters Now

Global health priorities are shifting. We can no longer wait for dysfunction to become disease. ERM gives us the language, structure, and biomarkers to identify chronic stress-related undernutrition early—when intervention is most likely to work.

Our systematic review aims to map the emerging evidence. We’re synthesizing studies on chronic stress, metabolic adaptation, and multi-system biomarker shifts—aligning them with this new clinical concept. The goal? To turn what was once a narrative into a stageable, reversible syndrome.

As the science of aging becomes the science of resilience, ERM may be the missing link—connecting the biology of stress with the future of healthspan.

📘 Fuellen et al. (2019)

Fuellen, G., Jansen, L., Cohen, A. A., Luyten, W., Gogol, M., Simm, A., Saul, N., Cirulli, F., Berry, A., Antal, P., Köhling, R., & Möller, S. (2019). Health and aging: Unifying concepts, scores, biomarkers and pathways. Aging and Disease, 10(4), 883–900. https://doi.org/10.14336/AD.2018.1030

📘 Gaylord et al. (2023)

Gaylord, A., Cohen, A. A., & Kupsco, A. (2023). Biomarkers of aging through the life course: A recent literature update. Current Opinion in Epidemiology and Public Health, 2(2), 7–17. https://doi.org/10.1097/PXH.0000000000000018

📘 Tippairote (2025)

Tippairote, T. (2025). Exposure-Related Malnutrition (ERM): A stageable model of bioenergetic trade-offs and stress-adapted undernutrition (Version 2) [Preprint]. Preprints.org. https://www.preprints.org/manuscript/202504.1142/v2