Dysregulation of the causative genes for hereditary parkinsonism in the midbrain in Parkinson's disease

Kim, Yun Joong; Jeon, Junbeom; Shin, Jae-Moon; Kim, Nan Young; Hong, Jeong Hoon; Oh, Jae-Min; Hong, Sangkyoon; Kim, Yeo Jin; Kim, Young Eun; Kang, Suk Yun; Ma, Hyeo-Il; Lee, Unjoo; Yoon, Jeehee

doi:10.1002/mds.27019

Cited by 14 publications

(13 citation statements)

References 64 publications

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“…This suggests that regulatory subunits may play distinct roles at different stages of different diseases, and therefore, more attention should be focused on these subunits. Our data are also consistent with a prior work that showed a reduction in PPP2R2B mRNA expression in the midbrain of PD individuals ( Kim et al, 2017 ). Transcriptional regulation may also be involved in this process; this remains undetermined.…”

Section: Discussionsupporting

confidence: 93%

Leucine Carboxyl Methyltransferase Downregulation and Protein Phosphatase Methylesterase Upregulation Contribute Toward the Inhibition of Protein Phosphatase 2A by α-Synuclein

Tian

Liu

et al. 2018

Front. Aging Neurosci.

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The pathology of Parkinson’s disease (PD) is characterized by intracellular neurofibrillary tangles of phosphorylated α-synuclein (α-syn). Protein phosphatase 2A (PP2A) is responsible for α-syn dephosphorylation. Previous work has demonstrated that α-syn can regulate PP2A activity. However, the mechanisms underlying α-syn regulation of PP2A activity are not well understood. In this study, we found that α-syn overexpression induced increased α-syn phosphorylation at serine 129 (Ser129), and PP2A inhibition, in vitro and in vivo. α-syn overexpression resulted in PP2A demethylation. This demethylation was mediated via downregulated leucine carboxyl methyltransferase (LCMT-1) expression, and upregulated protein phosphatase methylesterase (PME-1) expression. Furthermore, LCMT-1 overexpression, or PME-1 inhibition, reversed α-syn-induced increases in α-syn phosphorylation and apoptosis. In addition to post-translational modifications of the catalytic subunit, regulatory subunits are involved in the regulation of PP2A activity. We found that the levels of regulatory subunits which belong to the PPP2R2 subfamily, not the PPP2R5 subfamily, were downregulated in the examined brain regions of transgenic mice. Our work identifies a novel mechanism to explain how α-syn regulates PP2A activity, and provides the optimization of PP2A methylation as a new target for PD treatment.

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Section: Discussionsupporting

confidence: 93%

Leucine Carboxyl Methyltransferase Downregulation and Protein Phosphatase Methylesterase Upregulation Contribute Toward the Inhibition of Protein Phosphatase 2A by α-Synuclein

Tian

Liu

et al. 2018

Front. Aging Neurosci.

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“…An alternative way to quantify miRNA expression would be to perform single‐cell experiments in cells of interest (eg, dopaminergic neurons). However, although a meta‐analysis has recently been published for mRNA‐based transcriptomics studies applying laser capturing for single‐cell analysis in the substantia nigra, equivalent data on miRNAs are currently too sparse.…”

Section: Discussionmentioning

confidence: 99%

Meta‐analyses identify differentially expressed microRNAs in Parkinson's disease

Schulz

Takousis

Wohlers

et al. 2019

Annals of Neurology

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Objective: MicroRNA (miRNA)-mediated (dys)regulation of gene expression has been implicated in Parkinson's disease (PD), although results of miRNA expression studies remain inconclusive. We aimed to identify miRNAs that show consistent differential expression across all published expression studies in PD. Methods: We performed a systematic literature search on miRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen, we performed meta-analyses across miRNAs assessed in three or more independent data sets. Meta-analyses were performed using effect-size-and p-value-based methods, as applicable. Results: After screening 599 publications, we identified 47 data sets eligible for meta-analysis. On these, we performed 160 meta-analyses on miRNAs quantified in brain (n = 125), blood (n = 31), or CSF (n = 4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α = 3.13 × 10 -4 ) differentially expressed miRNAs in brain (n = 3) and blood (n = 10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p = 6.37 × 10 -5 ), hsa-miR-497-5p (p = 1.35 × 10 -4 ), and hsa-miR-133b (p = 1.90 × 10 -4 ) in brain and with hsa-miR-221-3p (p = 4.49 × 10 -35 ), hsa-miR-214-3p (p = 2.00 × 10 -34 ), and hsa-miR-29c-3p (p = 3.00 × 10 -12 ) in blood. No significant signals were found in CSF. Analyses of genome-wide association study data for target genes of brain miRNAs showed significant association (α = 9.40 × 10 -5 ) of genetic variants in nine loci. Interpretation: We identified several miRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood miRNAs as biomarkers for diagnosis, progression, or prediction of PD. ANN NEUROL 2019;85:835-851 P arkinson's disease (PD) is the second-most common neurodegenerative disease affecting 1% of people over the age of 60. The increasing incidence of PD in industrialized, aging populations constitutes a growing socioeconomic burden. 1 Idiopathic PD results from a combination of multiple genetic 2-4 and environmental/lifestyle factors. 5,6 However, the currently known risk factors only explain a small fraction of the phenotypic variance of PD. Likewise, PD View this article online at wileyonlinelibrary.com.

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“…dopaminergic neurons. However, while a meta-analysis has recently been published for mRNA-based transcriptomics studies applying laser capturing for single cell analysis in the substantia nigra (28), equivalent data on miRNAs are currently too sparse.…”

Section: Discussionmentioning

confidence: 99%

Meta-analyses identify differentially expressed microRNAs in Parkinson’s disease

Takousis

Wohlers

Itua

et al. 2018

Preprint

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ObjectiveMicroRNA-mediated (dys)regulation of gene expression has been implicated in Parkinson’s disease (PD), although results of microRNA expression studies remain inconclusive. We aimed to identify microRNAs that show consistent differential expression across all published expression studies in PD.MethodsWe performed a systematic literature search on microRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen we performed meta-analyses across microRNAs assessed in three or more independent datasets. Meta-analyses were performed using effect-size and p-value based methods, as applicable.ResultsAfter screening 599 publications we identified 47 datasets eligible for meta-analysis. On these, we performed 160 meta-analyses on microRNAs quantified in brain (n=125), blood (n=31), or CSF samples (n=4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α=3.13×10-4) differentially expressed microRNAs in brain (n=3) and blood (n=10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p=6.37×10-5), hsa-miR-497-5p (p=1.35×10-4), and hsa-miR-133b (p=1.90×10-4) in brain, and with hsa-miR-221-3p (p=4.49×10-35), hsa-miR-214-3p (p=2.00×10-34), and hsa-miR-29c-3p (p=3.00×10-12) in blood. No significant signals were found in CSF. Analyses of GWAS data for target genes of brain microRNAs showed significant association (α=9.40×10-5) of genetic variants in nine loci.InterpretationWe identified several microRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood microRNAs as biomarkers for diagnosis, progression or prediction of PD.

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Dysregulation of the causative genes for hereditary parkinsonism in the midbrain in Parkinson's disease

Cited by 14 publications

References 64 publications

Leucine Carboxyl Methyltransferase Downregulation and Protein Phosphatase Methylesterase Upregulation Contribute Toward the Inhibition of Protein Phosphatase 2A by α-Synuclein

Leucine Carboxyl Methyltransferase Downregulation and Protein Phosphatase Methylesterase Upregulation Contribute Toward the Inhibition of Protein Phosphatase 2A by α-Synuclein

Meta‐analyses identify differentially expressed microRNAs in Parkinson's disease

Meta-analyses identify differentially expressed microRNAs in Parkinson’s disease

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