Background: Megalencephalic leukoencephalopathy with subcortical cysts (MLC), a rare and progressive neurodegenerative disorder involving the white matter, is not adequately recapitulated by current disease models. Somatic cell reprogramming, along with advancements in genome engineering, may allow the establishment of in-vitro human models of MLC for disease modeling and drug screening. In this study, we utilized cellular reprogramming and gene-editing techniques to develop induced pluripotent stem cell (iPSC) models of MLC to recapitulate the cellular context of the classical MLC-impacted nervous system.
Methods: Somatic cell reprogramming of peripheral patient-derived blood mononuclear cells (PBMCs) was used to develop iPSC models of MLC. CRISPR-Cas9 system-based genome engineering was also utilized to create the MLC1 knockout model of the disease. Directed differentiation of iPSCs to neural stem cells (NSCs) and astrocytes was performed in a 2D cell culture format, followed by various cellular and molecular biology approaches, to characterize the disease model.
Results: MLC iPSCs established by somatic cell reprogramming and genome engineering were well characterized for pluripotency. iPSCs were subsequently differentiated to disease-relevant cell types: neural stem cells (NSCs) and astrocytes. RNA sequencing profiling of MLC NSCs revealed a set of differentially expressed genes related to neurological disorders and epilepsy, a common clinical finding within MLC disease. This gene set can serve as a target for drug screening for the development of a potential therapeutic for this disease. Upon differentiation to the more disease relevant cell type-astrocytes, MLC-characteristic vacuoles were clearly observed, which were distinctly absent from controls. This emergence recapitulated a distinguishing phenotypic marker of the disease.
Conclusion: Through the creation and analyses of iPSC models of MLC, our work addresses a critical need for relevant cellular models of MLC for use in both disease modeling and drug screening assays. Further investigation can utilize MLC iPSC models, as well as generated transcriptomic data sets and analyses, to identify potential therapeutic interventions for this debilitating disease.