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Embryonic and induced pluripotent stem cells are excellent models for disease research because of their ability to self-renew and differentiate into most cell types. Somatic cells from a patient are isolated and reprogrammed into induced pluripotent stem cells or iPSCs. These iPSCs are later differentiated into the desired cell type, which mirrors the diseased cell of the patient. In this way, disease models have been created for investigating diseases such as Down syndrome, type I diabetes,...
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Neurodegenerative disorders are progressive diseases that cause irreversible damage and loss to neurons in specific brain areas. Examples of these disorders include Parkinson's disease, Alzheimer's disease, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). These disorders share characteristics such as proteinopathies, selective neuronal vulnerability, and a complex interplay between genetic and environmental factors. The primary therapeutic goal for these conditions is...
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Neurodegenerative disorders, such as Parkinson's Disease (PD), involve the gradual and irreversible destruction of neurons in particular brain areas. These disorders exhibit standard features like proteinopathies, selective vulnerability of some neurons, and an interaction of intrinsic properties, genetics, and environmental influences in neural injury.
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Decoding Parkinson's disease - iPSC-derived models in the OMICs era.

Florian Krach1, Marios-Evangelos Bogiongko1, Beate Winner1

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Summary

Induced pluripotent stem cell (iPSC) models combined with

Keywords:
Disease modelingParkinson's diseaseProteomicsRNA-seqTranscriptomicsiPSC

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Area of Science:

  • Neuroscience
  • Stem Cell Biology
  • Genomics

Background:

  • Parkinson's disease (PD) involves the loss of specific brain cells.
  • Induced pluripotent stem cells (iPSCs) offer a novel model for studying PD.
  • Combining iPSC models with 'omics' approaches is underutilized in PD research.

Purpose of the Study:

  • To review the current applications of omics technologies in Parkinson's disease iPSC models.
  • To focus on transcriptional and proteomic studies in PD iPSC research.
  • To identify challenges and future directions for PD 'omics' research.

Main Methods:

  • Literature review of studies using iPSC-derived models for Parkinson's disease.
  • Analysis of publications focusing on transcriptional (gene expression) changes.
  • Inclusion of studies utilizing proteomic analyses in PD iPSC models.

Main Results:

  • Omics approaches, particularly transcriptomics and proteomics, are increasingly used with iPSC models for PD.
  • These combined methods provide insights into molecular changes in PD.
  • The integration of diverse omics data is still limited.

Conclusions:

  • Combining iPSC technology with omics approaches is a powerful strategy for Parkinson's disease research.
  • Further integration of transcriptional and proteomic data can deepen our understanding of PD pathology.
  • Addressing current limitations will pave the way for future discoveries in PD research.