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Stem cell-based multi-tissue platforms to model human autoimmune diabetes
- Source :
- Molecular Metabolism, Vol 66, Iss , Pp 101610- (2022)
- Publication Year :
- 2022
- Publisher :
- Elsevier, 2022.
-
Abstract
- Background: Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic insulin-producing β cells are specifically destroyed by the immune system. Understanding the initiation and progression of human T1D has been hampered by the lack of appropriate models that can reproduce the complexity and heterogeneity of the disease. The development of platforms combining multiple human pluripotent stem cell (hPSC) derived tissues to model distinct aspects of T1D has the potential to provide critical novel insights into the etiology and pathogenesis of the human disease. Scope of review: In this review, we summarize the state of hPSC differentiation approaches to generate cell types and tissues relevant to T1D, with a particular focus on pancreatic islet cells, T cells, and thymic epithelium. We present current applications as well as limitations of using these hPSC-derived cells for disease modeling and discuss efforts to optimize platforms combining multiple cell types to model human T1D. Finally, we outline remaining challenges and emphasize future improvements needed to accelerate progress in this emerging field of research. Major conclusions: Recent advances in reprogramming approaches to create patient-specific induced pluripotent stem cell lines (iPSCs), genome engineering technologies to efficiently modify DNA of hPSCs, and protocols to direct their differentiation into mature cell types have empowered the use of stem cell derivatives to accurately model human disease. While challenges remain before complex interactions occurring in human T1D can be modeled with these derivatives, experiments combining hPSC-derived β cells and immune cells are already providing exciting insight into how these cells interact in the context of T1D, supporting the viability of this approach.
Details
- Language :
- English
- ISSN :
- 22128778
- Volume :
- 66
- Issue :
- 101610-
- Database :
- Directory of Open Access Journals
- Journal :
- Molecular Metabolism
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.56bcad7a7f4a40dda6f7d215d879fca9
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.molmet.2022.101610