Aging reframed as a shift from biological order to widening regulatory chaos

Aging may be less a story of accumulating damage and more a story of unraveling coordination. In a new perspective article published in Discover Aging, researchers propose that the earliest stages of aging reflect a large-scale reorganization of biological dynamics, in which the states of cells and organs become steadily more varied while the interactions that bind them together weaken. The framework, developed by Hamilton Ribeiro Correia, Tomás Balseiro, Lucas Caramujo and Sandra Balseiro, draws on single-cell biology, epigenomics, mitochondrial research, circadian science, resilience theory and network physiology to describe aging as a transition between two measurable dimensions: regulatory dispersion and systemic coherence.

Regulatory dispersion, in the authors’ formulation, captures the breadth of biological configurations an organism can occupy. It is quantified with entropy-based measures that describe how widely cells or subsystems are spread across possible states, rather than how far they deviate from an average. Systemic coherence, by contrast, describes the strength of statistical dependency, shared regulatory information and coordinated constraint among interacting subsystems. The authors are careful to distinguish coherence from mere synchrony: two organs can oscillate in time while exchanging little regulatory information, and strong coupling can exist without strict temporal alignment. Coherence, in their view, is about the informational content of interactions, not just their timing.

The empirical motivation comes from converging lines of evidence. Single-cell transcriptomic studies of human pancreatic tissue and aging mouse tissues show progressively divergent gene-expression programs within the same organs. Epigenetic work reveals age-related variability in DNA methylation patterns and trajectories. Mitochondrial dysfunction and altered bioenergetic states accompany aging as well. At the same time, cross-system coordination appears to deteriorate: circadian and metabolic rhythms fall out of alignment, inter-organ communication weakens, signaling fidelity declines, and the physiological coupling among cardiovascular, respiratory, neural and endocrine systems changes. Many of these shifts, the authors note, may emerge before overt functional decline, suggesting that aging involves early reorganization of biological dynamics rather than only late-stage damage accumulation.

To formalize these ideas, the team introduces a conceptual dynamical scaffold describing how dispersion at one biological scale can propagate to others. The equation treats regulatory dispersion at each scale as shaped by local destabilizing processes, damped by coherence-preserving constraints, and influenced by cross-scale propagation from neighboring levels of organization. The authors stress that this scaffold is deliberately abstract. It is not a mechanistic model, not intended for parameter inference or quantitative calibration of aging, and serves only to illustrate the principle that coherence-preserving constraints can limit the spread of regulatory dispersion across hierarchical, fractal and scale-free architectures. In such architectures, highly connected hubs can disproportionately disrupt network integration when they malfunction, amplifying dispersion and weakening coherence throughout the system.

Within this framework, the authors distinguish two kinds of dispersion that are often conflated. Intra-organism regulatory dispersion refers to heterogeneity across the cells, tissues and subsystems of a single individual, and it is the quantity that enters their dynamical equations. Inter-individual regulatory dispersion, a separate population-level measure, captures how people of the same chronological age diverge from one another in their internal dispersion trajectories. Keeping these apart, the authors argue, prevents confusion between within-organism regulatory dynamics and population-level heterogeneity, and clarifies how dispersion should be measured in empirical studies. In practice, intra-organism dispersion could be estimated from single-cell RNA sequencing by clustering cells into transcriptional states and computing entropy over the resulting distribution, from DNA methylation data by quantifying entropic variability across CpG sites, or from mitochondrial measurements by evaluating the heterogeneity of membrane potential or oxygen-consumption distributions across individual cells.

Systemic coherence, meanwhile, is given an illustrative information-theoretic formulation based on normalized mutual information between subsystem pairs. The authors acknowledge that estimating mutual information from real data is fraught with bias, particularly in high-dimensional or short time-series settings, and they outline practical remedies including k-nearest-neighbor estimators, permutation-based bias correction, dimensionality reduction before estimation, and transfer entropy or multivariate information measures when directional or higher-order interactions matter. Network physiology, they note, provides empirical grounding for such measures, including quantification of cardiorespiratory coupling and cross-organ communication. Dispersion and coherence, though conceptually distinct, are not independent: rising dispersion may destabilize interactions and erode coherence, while declining coherence may allow fluctuations to propagate more freely and widen dispersion further.

The framework’s central claim is that aging can be read as a progressive shift in a two-dimensional phase space. Young biological systems, in this picture, occupy constrained and dynamically stable regions of configuration space, where stochastic molecular fluctuations and environmental perturbations are continuously generated but effectively buffered by coordinated interactions. With advancing age, the balance tips: dispersion rises as biological states diversify, and coherence falls as coupling weakens. The authors emphasize that these trajectories need not be strictly monotonic. Adaptive responses, environmental modification or effective interventions may temporarily restore coherence or reduce dispersion, and candidate approaches such as circadian reinforcement, structured exercise, metabolic coupling restoration and anti-inflammatory modulation should be evaluated empirically rather than assumed to work.

To test whether the proposed feedback structure can even generate such a trajectory, the team built a dimensionless illustrative simulation, explicitly not fitted to biological data. Under slowly increasing destabilizing pressure, the simulated dispersion variable rose from 0.10 to approximately 0.67 while the coherence variable declined from 0.90 to approximately 0.49. A transient coherence-reducing perturbation, applied between two points in the simulated timeline, produced a subsequent increase in dispersion relative to the unperturbed trajectory, with a maximum separation of roughly 0.017 in normalized units. The authors interpret this as a demonstration of mathematical feasibility only, consistent with the proposed direction of influence but not evidence that living systems follow these numerical rates, and not an establishment of causality in organisms.

The framework is positioned as a complement to, not a replacement for, the hallmarks of aging. Genomic instability, epigenetic alterations and mitochondrial dysfunction may contribute to rising dispersion by broadening the distribution of accessible biological states, while loss of proteostasis, cellular senescence, chronic inflammation and altered intercellular communication may weaken the constraints that preserve coherence. The authors also situate their proposal relative to earlier complexity-based theories, including the loss-of-complexity hypothesis of Lipsitz and Goldberger, arguing that the two-axis formulation extends that tradition by separately tracking the breadth of accessible states and the strength of cross-scale interactions.

What sets the work apart is its set of falsifiable predictions. The framework anticipates early-warning signals across molecular, cellular and physiological time series, including rising autocorrelation and slowing recovery dynamics, grounded in established critical-transition theory. It hypothesizes a specific temporal ordering, with dispersion increasing earlier and coherence declining more pronouncedly later in adulthood, a signature the authors explicitly flag as untested. It predicts that individuals of similar chronological age should diverge in their inter-individual dispersion, producing measurable heterogeneity in biological-aging trajectories. It proposes that a perturbation designed to directly reduce coherence, such as controlled disruption of circadian organization, should be followed by an increase in within-organism dispersion if the proposed feedback direction holds. And it suggests that composite biomarkers combining entropy-based dispersion with information-theoretic coherence metrics may outperform single-level measures in predicting resilience loss and intervention responsiveness. The authors are candid about limitations: standardized measurement protocols remain to be established, trajectories are unlikely to be uniform across tissues or environments, and causal relationships among dispersion, coherence and resilience remain incompletely understood. Whether the framework delivers predictive and translational value beyond current aging models, they conclude, is an empirical question that longitudinal omics, multimodal cohort studies, controlled perturbation experiments and wearable-derived physiological time series will need to answer.

Subject of Research: A theoretical framework describing aging as a multiscale transition of rising regulatory dispersion and declining systemic coherence

Article Title: Aging as a multiscale transition of regulatory dispersion and systemic coherence

Article References: Correia, H. R., Balseiro, T., Caramujo, L., & Balseiro, S. (2026). Aging as a multiscale transition of regulatory dispersion and systemic coherence. Discover Aging, 1(1), Article 14. https://doi.org/10.1007/s44518-026-00015-0

Image Credits: AI Generated

DOI: 10.1007/s44518-026-00015-0

Keywords: aging, regulatory dispersion, systemic coherence, single-cell biology, network physiology, resilience, epigenetics, circadian regulation, biological age, entropy, hallmarks of aging, critical transitions