ArticlebioRxiv : the preprint server for biology2025
Parkinson's Paradox: Alpha-synuclein's Selective Strike on SNc Dopamine Neurons over VTA.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
In synucleinopathies, including Parkinson's disease (PD), dopamine neurons in the substantia nigra pars compacta (SNc) exhibit greater vulnerability to degeneration than those in the ventral tegmental area (VTA). While α-synuclein (αSyn) pathology is implicated in nigral dopamine neuron loss, the mechanisms by which αSyn affects neuronal activity and midbrain dopamine network connectivity prior to cell death remain unclear. This study tested the hypothesis that elevated αSyn expression induces pathophysiological changes in firing activity and disrupts network connectivity dynamics of dopamine neurons before neuronal loss. We employed two mouse models of synucleinopathy: preformed αSyn fibril (PFF) injection and AAV-mediated expression of human αSyn (hαSyn) under the control of the tyrosine hydroxylase (TH) promoter, both targeting the VTA and SNc. Four weeks post-injection, brain sections underwent histological, electrophysiological, and network analyses. Immunohistochemistry for TH, hαSyn, and phospho-Ser129 αSyn assessed αSyn expression and dopaminergic neuron alterations. Neuronal viability was evaluated using two complementary approaches: quantification of TH Significance Statement: A central question in Parkinson's disease research is why dopamine neurons in the substantia nigra pars compacta (SNc) are more vulnerable than those in the ventral tegmental area (VTA). This study reveals that alpha-synuclein (αSyn) pathology differentially impacts dopamine neuronal activity and network connectivity, causing changes in the SNc before neuronal loss occurs, but not in the VTA. These findings provide a mechanism to explain the differential resilience of these neighboring dopamine neuron populations and provide insights into Parkinson's disease progression. The methodologies developed in this study establish a foundation for investigating network topology in deep brain structures and its role in neurodegenerative disorders.
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