Restricción energética celular como principio unificador del envejecimiento: marco ISHEA Δ±1

This manuscript proposes the ISHEA Δ±1 Coherence Framework as a theoretical perspective on aging, in which cellular biological state is approximated by a Coherence Index (CI = K / R+T), defined as the ratio between energetic availability (ATP production and NAD⁺ bioavailability) and repair–detoxification demand (oxidative stress burden, autophagic load, and proteostatic pressure). We propose that aging emerges as a phase transition across three stability regimes: a coherent state (Δ+1), a transitional regime (Δ0), and an entropic collapse state (Δ−1).
The CI is introduced as a latent systems-level variable, not a validated biomarker, approximating the balance between energy supply and maintenance demand. The framework generates 10 falsifiable predictions across cellular, neural, social, and intervention domains, and is positioned as complementary to established aging frameworks including the Hallmarks of Aging (López-Otín et al., 2023) and the Information Theory of Aging (Sinclair, 2019).
Empirical grounding is drawn from published biomarker data (Massudi 2012; Short 2005; Cawthon 2003; Wyss-Coray 2019) and from independent observations presented at the Brain Aging and Neurodegeneration Conference (Nature Korea, 2025), including astrocytic metabolic support (T variable), APOE4 as a constraint sensitivity modifier, and MAO-B/GABA as a predicted feedback brake in the Δ0→Δ−1 transition.
This work is a theoretical perspective intended for empirical testing. No clinical recommendations are made or implied.
Keywords:
bioenergetics; aging; NAD⁺; ATP; coherence; constraint; phase transition; ISHEA; falsifiable hypothesis; systems biology; neurodegeneration; telomeres; proteostasis

🧬 ISHEA Δ±1 Coherence Framework — OSF Project Wiki

Overview

The ISHEA Δ±1 Coherence Framework proposes a unifying systems-level model of aging based on cellular energetic constraints. Rather than treating aging as a collection of independent processes, this framework integrates metabolic, redox, and informational dynamics into a single measurable construct: the Coherence Index (CI).

The CI is defined as:

CI = K / (R + T)

Where:

K = Energetic supply and coherence (Level I: redox regulation; Level II: ATP execution)

R = Repair, detoxification, and systemic demand

T = Entropic and environmental stressors

This formulation captures aging as a balance between energetic capacity and biological demand, rather than a unidirectional decline.

Conceptual Framework

Two-Level Bioenergetic Hierarchy

Level I (K1): Redox and informational coherence (NAD⁺, ROS signaling, metabolic regulation)

Level II (K2): Energetic execution capacity (ATP production and mitochondrial output)

The model predicts that:

Aging is redox-limited, not ATP-limited

This prediction is supported by global sensitivity analysis showing Level I dominance over Level II (~154×).

Phase Dynamics (Δ±1 Model)

Aging is represented as a phase transition across three regimes:

Regime CI State Interpretation

Δ+1 CI > 0 High coherence, adaptive capacity
Δ0 CI ≈ 0 Transition point, maximum plasticity
Δ−1 CI < 0 Systemic decline, high demand burden

The model predicts a critical transition around ~40 years, where system variability peaks and intervention potential is maximized.

Empirical Cross-Validation

The framework has been evaluated using published data from the UK Biobank (n≈250,000 participants).

Key Findings

26/26 biomarkers (100%) correctly classified by hazard ratio direction

Pro-aging biomarkers (HR>1) → mapped to R (demand)

Anti-aging biomarkers (HR<1) → mapped to K (coherence)

GlycA (HR=1.25), the strongest mortality predictor, maps to R (r≈−0.957 with CI)

CI extended vs. original: r≈0.99 convergence

These results support the structural validity of the framework.

Computational Validation

Sensitivity Analysis (Sobol)

Level I / Level II ratio ≈ 154×

Indicates dominance of redox coherence over ATP capacity

Monte Carlo Simulation

Maximum uncertainty observed at Δ0 (~age 40)

Consistent with phase transition theory

Intervention Insights (In Silico)

Simulation scenarios suggest:

NAD⁺ restoration (Level I) → strongest impact near Δ0

ATP enhancement alone (Level II) → limited effect

Chronic stress → accelerates transition to Δ−1

This supports a hierarchical intervention strategy, prioritizing coherence restoration over isolated energy boosting.

Scope and Limitations

The CI is currently a theoretical composite variable

No prospective cohort has yet measured CI directly

Validation is structural and predictive, not causal

Biomarker classification, while pre-defined, may require independent external validation

Future Work

Planned validation pathway includes:

1. Cross-sectional calibration of CI components in a single cohort

2. Longitudinal validation of CI vs. aging outcomes

3. Intervention trials targeting Level I vs. Level II mechanisms

4. External blinded classification of biomarkers

Reproducibility and Data

All computational analyses are available in this repository, including:

CI calculation scripts (Python)

Sobol sensitivity analysis

Monte Carlo simulations

UK Biobank cross-validation tables

Citation

Pérez Pulido, C.J. (2025).
ISHEA Δ±1 Coherence Framework: A Systems-Level Model of Cellular Energetic Constraint in Aging.
DOI: https://doi.org/10.17605/OSF.IO/RMAFU

Contact

Carlos J. Pérez Pulido
ISHEA Institute