4.6 Article

Neurodegeneration in SCA14 is associated with increased PKC gamma kinase activity, mislocalization and aggregation

期刊

出版社

BMC
DOI: 10.1186/s40478-018-0600-7

关键词

Ataxia; Stem cells; Purkinje cells; Neurodegeneration; Cerebellum; Protein kinase C gamma

资金

  1. Royal Society
  2. Ataxia UK
  3. European Union's Horizon 2020 research and innovation program (Marie Sklodowska-Curie grant) [699978]
  4. John Fell OUP Fund
  5. Monument Trust Discovery Award from Parkinson's UK
  6. Oxford NIHR Biomedical Research Centre
  7. Wellcome Trust [WTISSF121302]
  8. Oxford Martin School [LC0910-004]
  9. MRC [MC_UP_1502/3] Funding Source: UKRI

向作者/读者索取更多资源

Spinocerebellar ataxia type 14 (SCA14) is a subtype of the autosomal dominant cerebellar ataxias that is characterized by slowly progressive cerebellar dysfunction and neurodegeneration. SCA14 is caused by mutations in the PRKCG gene, encoding protein kinase C gamma (PKC gamma). Despite the identification of 40 distinct disease-causing mutations in PRKCG, the pathological mechanisms underlying SCA14 remain poorly understood. Here we report the molecular neuropathology of SCA14 in post-mortem cerebellum and in human patient-derived induced pluripotent stem cells (iPSCs) carrying two distinct SCA14 mutations in the C1 domain of PKC gamma, H36R and H101Q. We show that endogenous expression of these mutations results in the cytoplasmic mislocalization and aggregation of PKC gamma in both patient iPSCs and cerebellum. PKC gamma aggregates were not efficiently targeted for degradation. Moreover, mutant PKC gamma was found to be hyper-activated, resulting in increased substrate phosphorylation. Together, our findings demonstrate that a combination of both, loss-of-function and gain-of-function mechanisms are likely to underlie the pathogenesis of SCA14, caused by mutations in the C1 domain of PKC gamma. Importantly, SCA14 patient iPSCs were found to accurately recapitulate pathological features observed in post-mortem SCA14 cerebellum, underscoring their potential as relevant disease models and their promise as future drug discovery tools.

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