A systematic review and embryological perspective of pluripotent stem cell-derived autonomic postganglionic neuron differentiation for human disease modelling
Abstract
Human autonomic neuronal cell models are emerging as tools for modelling diseases such as cardiac arrhythmias. In this systematic review, we compared thirty-three articles applying fourteen different protocols to generate sympathetic neurons and three different procedures to produce parasympathetic neurons. All methods involved the differentiation of human pluripotent stem cells, and none employed permanent or reversible cell immortalization. Almost all protocols were reproduced in multiple pluripotent stem cell lines, and over half show evidence of neural firing capacity. Common limitations in the field are a lack of three-dimensional models and models including multiple cell types. Sympathetic neuron differentiation protocols largely mirrored embryonic development, with the notable absence of migration, axon extension, and target-specificity cues. Parasympathetic neuron differentiation protocols may be improved by including several embryonic cues promoting cell survival, cell maturation, or ion channel expression. Moreover, additional markers to define parasympathetic neurons in vitro may support the validity of these protocols. Nonetheless, four sympathetic neuron differentiation protocols and one parasympathetic neuron differentiation protocol reported more than two thirds of cells expressing autonomic neuron markers. Altogether, these protocols promise to open new research avenues of human autonomic neuron development and disease modelling.
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All supporting data is provided in the tables, figures and supplementary files.
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Funding
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (91719346)
- Monique RM Jongbloed
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2025, Bos et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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