Dysregulated biodynamics in metabolic attractor systems precede the emergence of amyotrophic lateral sclerosis

Evolutionarily conserved mechanisms maintain homeostasis of essential elements, and are believed to be highly time-variant. However, current approaches measure elemental biomarkers at a few discrete time-points, ignoring complex higher-order dynamical features. To study dynamical properties of elemental homeostasis, we apply laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) to tooth samples to generate 500 temporally sequential measurements of elemental concentrations from birth to 10 years. We applied dynamical system and Information Theory-based analyses to reveal the longest-known attractor system in mammalian biology underlying the metabolism of nutrient elements, and identify distinct and consistent transitions between stable and unstable states throughout development. Extending these dynamical features to disease prediction, we find that attractor topography of nutrient metabolism is altered in amyotrophic lateral sclerosis (ALS), as early as childhood, suggesting these pathways are involved in disease risk. Mechanistic analysis was undertaken in a transgenic mouse model of ALS, where we find similar marked disruptions in elemental attractor systems as in humans. Our results demonstrate the application of a phenomological analysis of dynamical systems underlying elemental metabolism, and emphasize the utility of these measures in characterizing risk of disease.
Author summary The metabolism of essential elements in early life is essential to healthy growth and development. Elemental homeostasis is typically studied by characterizing distributions of elemental concentrations at the level of the population. Here, we introduce a new method of characterizing elemental metabolism at the level of the individual. Using tooth-based biomarkers, we tracked the longitudinal trajectory of essential elements throughout childhood at weekly temporal resolution from birth through approximately 10 years of life. We analyzed these trajectories to identify the formation of stable dynamic states (attractors) and transitions between these states throughout development. We found that metabolic dynamics were specific to discrete elemental pathways; copper metabolism typically involved the formation of multiple discrete states throughout childhood, whereas other elements, such as zinc, tended to persist in a single stable dynamic throughout development. Next, we compared elemental biodynamics in neurologically healthy cases and subjects that were later diagnosed with amyotrophic lateral sclerosis (ALS). We found these patterns were dysregulated in ALS, and also found similar results in a mouse model of ALS. Overall, our results provide a novel approach to characterize elemental biodynamics throughout development, and emphasize that the dysregulation of these processes may be predictive of later onset of disease.