ROS networks: designs, aging, Parkinson's disease and precision therapies.

Area of Science:

• Biochemistry
• Systems Biology
• Aging Research

Background:

• The role of reactive oxygen species (ROS) in oxidative stress, Parkinson's disease (PD), and aging is complex and not fully understood.
• The timescale of molecular processes and their long-term impact on disease and aging remains enigmatic.

Purpose of the Study:

• To challenge the perceived complexity of the ROS network by developing a simplified, comprehensive dynamic model.
• To investigate the mechanisms underlying aging and PD onset within this ROS network.
• To identify novel targets for interventions aimed at extending lifespan and preventing age-related diseases.

Main Methods:

• Construction of a comprehensive dynamic model of the ROS network, simplified into five robust subnetworks.
• Validation of the model against in vitro datasets from two independent laboratories.
• Introduction of the 'aging-time-control coefficient' to quantify the influence of molecular processes on aging.

Main Results:

• The model, despite its robustness, predicted a sudden breakdown after approximately 80 years, simulating aging.
• Parkinson's disease conditions (e.g., DJ-1 deficiency, alpha-synuclein increase) accelerated the model's collapse.
• Antioxidants and caffeine were found to retard the aging process in the model.
• A significant number of molecular processes (25 out of 57) were identified as controlling aging via the aging-time-control coefficient.

Conclusions:

• A simplified ROS network model can effectively simulate aging and PD onset.
• Specific molecular pathways, including mitochondrial synthesis, KEAP1 degradation, and p62 metabolism, are critical targets for life-extending interventions.
• Understanding the dynamics of the ROS network offers new insights into aging and neurodegenerative diseases.