Decoding Parkinson's disease - iPSC-derived models in the OMICs era

Florian Krach; Marios-Evangelos Bogiongko; Beate Winner

doi:10.1016/j.mcn.2020.103501

Decoding Parkinson's disease - iPSC-derived models in the OMICs era

Mol Cell Neurosci. 2020 Jul:106:103501. doi: 10.1016/j.mcn.2020.103501. Epub 2020 May 18.

Authors

Florian Krach¹, Marios-Evangelos Bogiongko¹, Beate Winner²

Affiliations

¹ Department of Stem Cell Biology, University Hospital Erlangen, Friedrich-Alexander University of Erlangen-Nuernberg (FAU), Glückstraße 6, 91054 Erlangen, Germany.
² Department of Stem Cell Biology, University Hospital Erlangen, Friedrich-Alexander University of Erlangen-Nuernberg (FAU), Glückstraße 6, 91054 Erlangen, Germany. Electronic address: beate.winner@fau.de.

PMID: 32439399
DOI: 10.1016/j.mcn.2020.103501

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons in the midbrain. In recent years, researchers have started studying PD using induced pluripotent stem cell (iPSC) models of the disease. Surprisingly, few studies have combined iPSC-technology with the so-called powerful 'omics' approaches. Here, we review the current state of omics applications used in combination with iPSC-derived models to study PD. Our focus is on studies investigating transcriptional changes and publications using proteomics applications. Lastly, we discuss current caveats in the field and identify potential future directions to obtain novel insights into PD pathology.

Keywords: Disease modeling; Parkinson's disease; Proteomics; RNA-seq; Transcriptomics; iPSC.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Animals
Dopaminergic Neurons / metabolism
Dopaminergic Neurons / pathology*
Humans
Induced Pluripotent Stem Cells / metabolism
Induced Pluripotent Stem Cells / pathology*
Models, Biological*
Parkinson Disease / metabolism
Parkinson Disease / pathology*
Proteomics