Journal
MOLECULAR PSYCHIATRY
Volume 21, Issue 11, Pages 1573-1588Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/mp.2016.158
Keywords
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Funding
- Ipsen Pharma
- Leona M. and Harry B. Helmsley Charitable Trust [2012-PG-MED002]
- JPB Foundation
- G Harold and Leila Y. Mathers Foundation
- NIH [MH095741, NS075449, HG004659, HG007005]
- Brain Research Foundation
- NSF
- George E. Hewitt Foundation for Medical Research
- EMBO Long-term fellowship
- Bettencourt Schueller Foundation
- Philippe Foundation
- FP7 Marie Curie International Outgoing Fellowship for Career Development
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Human neural progenitors derived from pluripotent stem cells develop into electrophysiologically active neurons at heterogeneous rates, which can confound disease-relevant discoveries in neurology and psychiatry. By combining patch clamping, morphological and transcriptome analysis on single-human neurons in vitro, we defined a continuum of poor to highly functional electrophysiological states of differentiated neurons. The strong correlations between action potentials, synaptic activity, dendritic complexity and gene expression highlight the importance of methods for isolating functionally comparable neurons for in vitro investigations of brain disorders. Although whole-cell electrophysiology is the gold standard for functional evaluation, it often lacks the scalability required for disease modeling studies. Here, we demonstrate a multimodal machine-learning strategy to identify new molecular features that predict the physiological states of single neurons, independently of the time spent in vitro. As further proof of concept, we selected one of the potential neurophysiological biomarkers identified in this study-GDAP1L1-to isolate highly functional live human neurons in vitro.
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