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hiPSCs for predictive modelling of neurodegenerative diseases: dreaming the possible.

Pia Rivetti di Val CervoDario BesussoPaola ConfortiElena Cattaneo
Published in: Nature reviews. Neurology (2021)
Human induced pluripotent stem cells (hiPSCs) were first generated in 2007, but the full translational potential of this valuable tool has yet to be realized. The potential applications of hiPSCs are especially relevant to neurology, as brain cells from patients are rarely available for research. hiPSCs from individuals with neuropsychiatric or neurodegenerative diseases have facilitated biological and multi-omics studies as well as large-scale screening of chemical libraries. However, researchers are struggling to improve the scalability, reproducibility and quality of this descriptive disease modelling. Addressing these limitations will be the first step towards a new era in hiPSC research - that of predictive disease modelling - involving the correlation and integration of in vitro experimental data with longitudinal clinical data. This approach is a key element of the emerging precision medicine paradigm, in which hiPSCs could become a powerful diagnostic and prognostic tool. Here, we consider the steps necessary to achieve predictive modelling of neurodegenerative disease with hiPSCs, using Huntington disease as an example.
Keyphrases
  • induced pluripotent stem cells
  • cross sectional
  • newly diagnosed
  • endothelial cells
  • big data
  • prognostic factors
  • ejection fraction
  • risk assessment
  • resting state
  • functional connectivity