The Role of Protein Quantity Control in Polyglutamine Spinocerebellar Ataxias.

Cerebellum

State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Department of Neurology, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, 361005, Fujian, China.

Published: December 2024

AI Article Synopsis

  • Polyglutamine spinocerebellar ataxias (polyQ SCAs) are the most common type of SCAs, caused mainly by the toxic effects of polyQ proteins.
  • The protein quality control (PQC) system, which includes molecular chaperones and the ubiquitin-proteasome system (UPS), is crucial for managing protein levels and preventing toxic buildup.
  • Strategies to enhance PQC system function through genetic or drug interventions may help reduce polyQ protein toxicity and alleviate symptoms in models of the disease.

Article Abstract

Polyglutamine spinocerebellar ataxias (polyQ SCAs) represent the most prevalent subtype of SCAs. The primary pathogenic mechanism is believed to be the gain-of-function neurotoxicity of polyQ proteins. Strategies such as enhancing the degradation or inhibiting the accumulation of these mutant proteins are pivotal for reducing their toxicity and slowing disease progression. The protein quality control (PQC) system, comprising primarily molecular chaperones and the ubiquitin‒proteasome system (UPS), is essential for maintaining protein homeostasis by regulating protein folding, trafficking, and degradation. Notably, polyQ proteins can disrupt the PQC system by sequestering its critical components and impairing its proteasomal functions. Therefore, restoring the PQC system through genetic or pharmacological interventions could potentially offer beneficial effects and alleviate the symptoms of the disease. Here, we will provide a review on the distribution, expression, and genetic or pharmacological intervention of protein quality control system in cellular or animal models of PolyQ SCAs.

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Source
http://dx.doi.org/10.1007/s12311-024-01722-wDOI Listing

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