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Cell Stem Cell
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Cell Stem Cell
Article . 2013
License: Elsevier Non-Commercial
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Cell Stem Cell
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Human iPSC-Based Modeling of Late-Onset Disease via Progerin-Induced Aging

Authors: Miller, Justine D.; Ganat, Yosif M.; Kishinevsky, Sarah; Bowman, Robert L.; Liu, Becky; Tu, Edmund Y.; Mandal, Pankaj K.; +10 Authors

Human iPSC-Based Modeling of Late-Onset Disease via Progerin-Induced Aging

Abstract

Reprogramming somatic cells to induced pluripotent stem cells (iPSCs) resets their identity back to an embryonic age and, thus, presents a significant hurdle for modeling late-onset disorders. In this study, we describe a strategy for inducing aging-related features in human iPSC-derived lineages and apply it to the modeling of Parkinson's disease (PD). Our approach involves expression of progerin, a truncated form of lamin A associated with premature aging. We found that expression of progerin in iPSC-derived fibroblasts and neurons induces multiple aging-related markers and characteristics, including dopamine-specific phenotypes such as neuromelanin accumulation. Induced aging in PD iPSC-derived dopamine neurons revealed disease phenotypes that require both aging and genetic susceptibility, such as pronounced dendrite degeneration, progressive loss of tyrosine hydroxylase (TH) expression, and enlarged mitochondria or Lewy-body-precursor inclusions. Thus, our study suggests that progerin-induced aging can be used to reveal late-onset age-related disease features in hiPSC-based disease models.

Keywords

Adult, Aging, Induced Pluripotent Stem Cells, Models, Biological, Mice, Mesencephalon, Genetics, Animals, Humans, Age of Onset, Child, Cellular Senescence, Aged, Aged, 80 and over, Dopaminergic Neurons, Cell Differentiation, Cell Biology, Fibroblasts, Middle Aged, Cellular Reprogramming, Lamin Type A, Molecular Medicine, Biomarkers

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    685
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
685
Top 0.1%
Top 1%
Top 0.1%
hybrid