Induced Pluripotent Stem Cells, A Slippery Slope for Neurodegenerative Disease Modelling?
Kuldip S. Sidhu*
Identifiers and Pagination:Year: 2011
First Page: 46
Last Page: 51
Publisher Id: TOSCJ-3-46
Article History:Received Date: 12/08/2010
Revision Received Date: 22/09/2010
Acceptance Date: 22/09/2010
Electronic publication date: 17/3/2011
Collection year: 2011
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The recent breakthrough in reprogramming somatic cells has invigorated the prospect that disease mechanisms that underpin various human diseases particularly the neurodegenerative disorders could be unravelled by using the disease-specific pluripotent stem cells. A number of studies have demonstrated that such disease-specific induced pluripotent stem cell (iPSC) could be generated relatively easy. Some recent studies have substantiated the utility of this technology in describing the initial characterization of neurodegenerative patient-derived iPSC as a proof of concept. However, as it is becoming evident now that the cell type of origin influences the molecular and functional properties of derived iPSC. The indications that reprogramming may erase the cell memory also raises the question if the disease phenotype may not be correctly represented or also erased in iPSC unless coaxed by further perturbation in vitro culture conditions. Other associated difficulties in iPSC research such as culture variability, selective adaptation of such cultures and the lack of robust protocols to generate homogeneous population of desired cell type may have compounding affects in the use of these cells in disease modelling. Unless these issues are addressed properly the prospects of iPSC in disease modelling may remain a slippery slop.