Modeling Type 1 Diabetes In Vitro Using Human Pluripotent Stem Cells
Nayara C. Leite,
Elad Sintov,
Torsten B. Meissner,
Michael A. Brehm,
Dale L. Greiner,
David M. Harlan,
Douglas A. Melton
Affiliations
Nayara C. Leite
Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
Elad Sintov
Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA; Corresponding author
Torsten B. Meissner
Department of Surgery, Beth Israel Deaconess Medical Center, Boston, 02215 MA, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
Michael A. Brehm
Program in Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA 01655, USA
Dale L. Greiner
Program in Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA 01655, USA
David M. Harlan
Department of Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA 01655, USA
Douglas A. Melton
Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Corresponding author
Summary: Understanding the root causes of autoimmune diseases is hampered by the inability to access relevant human tissues and identify the time of disease onset. To examine the interaction of immune cells and their cellular targets in type 1 diabetes, we differentiated human induced pluripotent stem cells into pancreatic endocrine cells, including β cells. Here, we describe an in vitro platform that models features of human type 1 diabetes using stress-induced patient-derived endocrine cells and autologous immune cells. We demonstrate a cell-type-specific response by autologous immune cells against induced pluripotent stem cell-derived β cells, along with a reduced effect on α cells. This approach represents a path to developing disease models that use patient-derived cells to predict the outcome of an autoimmune response.
