Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks.

Area of Science:

• Neuroscience
• Biochemistry
• Systems Biology

Background:

• Proteinopathy, including misfolded alpha-synuclein forming Lewy bodies, is central to Parkinson's disease (PD) pathogenesis.
• These pathological inclusions appear early, potentially preceding clinical symptoms.
• Understanding early disease mechanisms in PD is crucial for timely intervention.

Purpose of the Study:

• To investigate the early pathophysiology of Parkinson's disease (PD) using an in vitro model.
• To assess changes in neural network function and criticality following induced alpha-synucleinopathy.
• To determine if network criticality can serve as an early biomarker for PD.

Main Methods:

• Utilized engineered human neural networks in a physiologically relevant in vitro setup.
• Induced Parkinson's disease (PD)-related alpha-synuclein inclusions.
• Monitored neural network activity using multielectrode arrays (MEAs) for 3 weeks.
• Analyzed network function with a focus on self-organized criticality measurements.

Main Results:

• Early-onset alpha-synucleinopathy was successfully induced in engineered neural networks.
• While standard network function measurements showed minimal changes, network criticality was altered.
• Differences in network criticality states were discernible even with developing pathology.

Conclusions:

• Network criticality serves as a sensitive indicator of early Parkinson's disease (PD) pathophysiology.
• Changes in self-organized criticality may precede overt functional deficits in neurodegenerative diseases.
• This study highlights the potential of network criticality analysis for early PD detection in vitro.