• Open Access

Investigating the utility of human embryonic stem cell-derived neurons to model ageing and neurodegenerative disease using whole-genome gene expression and splicing analysis


Address correspondence and reprint requests to Siddharthan Chandran, Anne McLaren Laboratory for Regenerative Medicine, University of Cambridge, Forvie Site, Robinson Way, Cambridge CB2 0SZ, UK. E-mail: siddharthan.chandran@ed.ac.uk or Mina Ryten, Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London WC1N 3BG UK. E-mail: mina.ryten@ucl.ac.uk.


J. Neurochem. (2012) 122, 738–751.


A major goal in regenerative medicine is the predictable manipulation of human embryonic stem cells (hESCs) to defined cell fates that faithfully represent their somatic counterparts. Directed differentiation of hESCs into neuronal populations has galvanized much interest into their potential application in modelling neurodegenerative disease. However, neurodegenerative diseases are age-related, and therefore establishing the maturational comparability of hESC-derived neural derivatives is critical to generating accurate in vitro model systems. We address this issue by comparing genome-wide, exon-specific expression analyses of pluripotent hESCs, multipotent neural precursor cells and a terminally differentiated enriched neuronal population to expression data from post-mortem foetal and adult human brain samples. We show that hESC-derived neuronal cultures (using a midbrain differentiation protocol as a prototypic example of lineage restriction), while successful in generating physiologically functional neurons, are closer to foetal than adult human brain in terms of molecular maturation. These findings suggest that developmental stage has a more dominant influence on the cellular transcriptome than regional identity. In addition, we demonstrate that developmentally regulated gene splicing is common, and potentially a more sensitive measure of maturational state than gene expression profiling alone. In summary, this study highlights the value of genomic indices in refining and validating optimal cell populations appropriate for modelling ageing and neurodegeneration.