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hiPSCs for predictive modelling of neurodegenerative diseases: dreaming the possible

Nature Reviews Neurology volume 17, pages 381–392 (2021)Cite this article

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Abstract

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.

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Fig. 1: Proposed approach to predictive HD modelling based on patient-derived hiPSCs.

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Acknowledgements

The work of the authors was funded by the CHDI Foundation (JSC A11103), a non-profit biomedical research organization exclusively dedicated to developing therapeutics that will substantially improve the life of individuals affected by HD; Novel Strategies for Cell based Neural Reconstruction 2020-23 (NSC-reconstruct), the European Union’s Horizon 2020 Research and Innovation Programme grant agreement no. 874758; Fondazione Telethon – Italy (Grant no. GGP17102); and Programmi di Ricerca Scientifica di rilevanza Nazionale, grant 2008JKSHKN_001 and Prot. 2015AY9AYB Ministero dell’Università e della Ricerca Scientifica.

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  1. These authors contributed equally: Pia Rivetti di Val Cervo, Dario Besusso.

Authors and Affiliations

  1. Department of Biosciences, University of Milan, Milan, Italy

    Pia Rivetti di Val Cervo, Dario Besusso, Paola Conforti & Elena Cattaneo

  2. Istituto Nazionale di Genetica Molecolare “Romeo ed Enrica Invernizzi”, Milan, Italy

    Pia Rivetti di Val Cervo, Dario Besusso, Paola Conforti & Elena Cattaneo

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  1. Pia Rivetti di Val Cervo
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Contributions

P.R.d.V.C., D.B. and P.C. researched data for the article. P.R.d.V.C., D.B. and E.C. made a substantial contribution to discussion of content, wrote the article, and reviewed and edited the manuscript before submission.

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Nature Reviews Neurology thanks V. Khurana, who co-reviewed with S. Srinivasan, P. De Sousa, C. Svendsen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

California Institute for Regenerative Medicine iPSC repository: https://www.cirm.ca.gov/researchers/ipsc-repository

ClinicalTrials.gov: www.clinicaltrials.gov

European Bank for induced Pluripotent Stem Cells: www.ebisc.org

Human Induced Pluripotent Stem Cell Initiative: www.hipsci.org

New York Stem Cell Foundation repository: https://nyscf.org/research-institute/repository-stem-cell-search/

RIKEN BRC Cell Bank: https://cell.brc.riken.jp/en/

WHO International Clinical Trials Registry Platform: https://www.who.int/clinical-trials-registry-platform

WiCell Research Institute: www.wicell.org/

Glossary

Non-integrative delivery systems

Systems that favour the transient expression of reprogramming factors without their genomic integration.

OncomiRs

Cancer-associated microRNAs.

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Rivetti di Val Cervo, P., Besusso, D., Conforti, P. et al. hiPSCs for predictive modelling of neurodegenerative diseases: dreaming the possible. Nat Rev Neurol 17, 381–392 (2021). https://doi.org/10.1038/s41582-021-00465-0

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