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

Alexey N KolodkinRaju Prasad SharmaAnna Maria ColangeloAndrew IgnatenkoFrancesca MartoranaDanyel JennenJacco J BriedéNathan BradyMatteo BarberisThierry D G A MondeelMichele PapaVikas KumarBernhard PetersAlexander SkupinLilia AlberghinaRudi BallingHans V Westerhoff
Published in: NPJ systems biology and applications (2020)
How the network around ROS protects against oxidative stress and Parkinson's disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only five simpler subnetworks each delivering one type of robustness. The comprehensive dynamic model described in vitro data sets from two independent laboratories. Notwithstanding its five-fold robustness, it exhibited a relatively sudden breakdown, after some 80 years of virtually steady performance: it predicted aging. PD-related conditions such as lack of DJ-1 protein or increased α-synuclein accelerated the collapse, while antioxidants or caffeine retarded it. Introducing a new concept (aging-time-control coefficient), we found that as many as 25 out of 57 molecular processes controlled aging. We identified new targets for "life-extending interventions": mitochondrial synthesis, KEAP1 degradation, and p62 metabolism.
Keyphrases
  • oxidative stress
  • dna damage
  • cell death
  • physical activity
  • magnetic resonance imaging
  • machine learning
  • computed tomography
  • artificial intelligence
  • single molecule
  • small molecule
  • induced apoptosis
  • data analysis