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Introduction Amyotrophic Lateral Sclerosis (ALS) is a paralyzing, multifactorial neurodegenerative disease with limited therapeutics and no known cure. The study goal was to determine which pathophysiological treatment targets appear most beneficial. Methods A big data approach was used to analyze high copy SOD1 G93A experimental data. The secondary data set comprised 227 published studies and 4,296 data points. Treatments were classified by pathophysiological target: apoptosis, axonal transport, cellular chemistry, energetics, neuron excitability, inflammation, oxidative stress, proteomics, or systemic function. Outcome assessment modalities included onset delay, health status (rotarod performance, body weight, grip strength), and survival duration. Pairwise statistical analysis (two-tailed t -test with Bonferroni correction) of normalized fold change (treatment/control) assessed significant differences in treatment efficacy. Cohen’s d quantified pathophysiological treatment category effect size compared to “all” (e.g., all pathophysiological treatment categories combined). Results Inflammation treatments were best at delaying onset ( d = 0.42, p > 0.05). Oxidative stress treatments were significantly better for prolonging survival duration ( d = 0.18, p < 0.05). Excitability treatments were significantly better for prolonging overall health status ( d = 0.22, p < 0.05). However, the absolute best pathophysiological treatment category for prolonging health status varied with disease progression: oxidative stress was best for pre-onset health ( d = 0.18, p > 0.05); excitability was best for prolonging function near onset ( d = 0.34, p < 0.05); inflammation was best for prolonging post-onset function ( d = 0.24, p > 0.05); and apoptosis was best for prolonging end-stage function ( d = 0.49, p > 0.05). Finally, combination treatments simultaneously targeting multiple pathophysiological categories (e.g., polytherapy) performed significantly ( p < 0.05) better than monotherapies at end-stage. Discussion In summary, the most effective pathophysiological treatments change as function of assessment modality and disease progression. Shifting pathophysiological treatment category efficacy with disease progression supports the homeostatic instability theory of ALS disease progression.
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This content will become publicly available on February 1, 2026
Restoring Homeostasis: Treating Amyotrophic Lateral Sclerosis by Resolving Dynamic Regulatory Instability
Amyotrophic lateral sclerosis (ALS) has an interactive, multifactorial etiology that makes treatment success elusive. This study evaluates how regulatory dynamics impact disease progression and treatment. Computational models of wild-type (WT) and transgenic SOD1-G93A mouse physiology dynamics were built using the first-principles-based first-order feedback framework of dynamic meta-analysis with parameter optimization. Two in silico models were developed: a WT mouse model to simulate normal homeostasis and a SOD1-G93A ALS model to simulate ALS pathology dynamics and their response to in silico treatments. The model simulates functional molecular mechanisms for apoptosis, metal chelation, energetics, excitotoxicity, inflammation, oxidative stress, and proteomics using curated data from published SOD1-G93A mouse experiments. Temporal disease progression measures (rotarod, grip strength, body weight) were used for validation. Results illustrate that untreated SOD1-G93A ALS dynamics cannot maintain homeostasis due to a mathematical oscillating instability as determined by eigenvalue analysis. The onset and magnitude of homeostatic instability corresponded to disease onset and progression. Oscillations were associated with high feedback gain due to hypervigilant regulation. Multiple combination treatments stabilized the SOD1-G93A ALS mouse dynamics to near-normal WT homeostasis. However, treatment timing and effect size were critical to stabilization corresponding to therapeutic success. The dynamics-based approach redefines therapeutic strategies by emphasizing the restoration of homeostasis through precisely timed and stabilizing combination therapies, presenting a promising framework for application to other multifactorial neurodegenerative diseases.
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- Award ID(s):
- 1944247
- PAR ID:
- 10615489
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- International Journal of Molecular Sciences
- Volume:
- 26
- Issue:
- 3
- ISSN:
- 1422-0067
- Page Range / eLocation ID:
- 872
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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