USING FAMILIAL ALZHEIMER'S DISEASE AND ISOGENIC CONTROL IPSC-DERIVED BASAL FOREBRAIN NEURONS TO MODEL AD

The lack of effective treatments for Alzheimer's disease (AD) underscores the importance of developing better human-specific models of AD to further understand disease mechanism and provide better platforms for therapeutic screening. We recently published a study in which we created a familial Alzheimer's disease (FAD) induced pluripotent stem cell (iPSC) model analyzing neural progenitors (NPCs). In order to reduce inherent variability between iPSCs derived from different patients, we are developing an allelic series, in which heterozygous and homozygous presenilin-1 (PSEN1) mutations can be introduced into an unaffected control line via TALEN-mediated gene editing. In addition, we are studying FAD phenotypes in the context of a more specific disease-relevant cell type, namely basal forebrain cholinergic neurons (BFCNs). A FAD4 family control fibroblast line used in our previous study was reprogrammed in an integration-free manner. TALEN constructs targeting exon 5 of PSEN1 were screened for target site cutting efficacy, and the best pair was used in combination with a DNA oligo donor were used to introduce the M146L mutation.We have developed a method of isolating an iPSC-derived BFCN neural progenitor by FACS, which can then be propagated as a neuronal embryoid body (NEB). NEBs can be subsequently dissociated into a monolayer for subsequent terminal differentiation and phenotypic analysis. We successfully knocked in heterozygous and homozygous M46L mutations into a control background. We have improved the efficacy of BFCN directed differentiation protocol to allow a greater > 90% yield of Nkx2.1+ NPCs, which propagated as NEBs maintain a ventral forebrain identity for at least 100 days of culture. We are currently testing forced overexpression of Lhx8 to improve BFCN patterning, the role of NGF for improving terminal differentiation, and translating our differentiation protocol to an automated platform. We are developing an isogenic FAD model of BFCN neurons. Furthermore, automated BFCN differentiation will allow investigation of a large cohort of late-onset AD iPSCs, which is critical for understanding and further dissecting the far more common sporadic forms of the disease. Recent phenotypic analysis of FAD BFCNs will be presented at the meeting.