Unraveling the Mechanisms Underlying Irregularities in Inspiratory Rhythm Generation in a Mouse Model of Parkinson's Disease

揭示帕金森病小鼠模型中吸气节律异常的潜在机制

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作者:Luiz M Oliveira, Nathan A Baertsch, Thiago S Moreira, Jan-Marino Ramirez, Ana C Takakura

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder anatomically characterized by a progressive loss of dopaminergic neurons in the substantia nigra compacta (SNpc). Much less known, yet clinically very important, are the detrimental effects on breathing associated with this disease. Consistent with the human pathophysiology, the 6-hydroxydopamine hydrochloride (6-OHDA) rodent model of PD shows reduced respiratory frequency (fR) and NK1r-immunoreactivity in the pre-Bötzinger complex (preBötC) and PHOX2B+ neurons in the retrotrapezoid nucleus (RTN). To unravel mechanisms that underlie bradypnea in PD, we employed a transgenic approach to label or stimulate specific neuron populations in various respiratory-related brainstem regions. PD mice were characterized by a pronounced decreased number of putatively rhythmically active excitatory neurons in the preBötC and adjacent ventral respiratory column (VRC). Specifically, the number of Dbx1 and Vglut2 neurons was reduced by 47.6% and 17.3%, respectively. By contrast, inhibitory Vgat+ neurons in the VRC, as well as neurons in other respiratory-related brainstem regions, showed relatively minimal or no signs of neuronal loss. Consistent with these anatomic observations, optogenetic experiments identified deficits in respiratory function that were specific to manipulations of excitatory (Dbx1/Vglut2) neurons in the preBötC. We conclude that the decreased number of this critical population of respiratory neurons is an important contributor to the development of irregularities in inspiratory rhythm generation in this mouse model of PD.SIGNIFICANCE STATEMENT We found a decreased number of a specific population of medullary neurons which contributes to breathing abnormalities in a mouse model of Parkinson's disease (PD).

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