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  • Review Article
  • Published:

CRISPR-based functional genomics for neurological disease

Nature Reviews Neurology volume 16, pages 465–480 (2020)Cite this article

Subjects

Abstract

Neurodegenerative, neurodevelopmental and neuropsychiatric disorders are among the greatest public health challenges, as many lack disease-modifying treatments. A major reason for the absence of effective therapies is our limited understanding of the causative molecular and cellular mechanisms. Genome-wide association studies are providing a growing catalogue of disease-associated genetic variants, and the next challenge is to elucidate how these variants cause disease and to translate this understanding into therapies. This Review describes how new CRISPR-based functional genomics approaches can uncover disease mechanisms and therapeutic targets in neurological diseases. The bacterial CRISPR system can be used in experimental disease models to edit genomes and to control gene expression levels through CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa). These genetic perturbations can be implemented in massively parallel genetic screens to evaluate the functional consequences for human cells. CRISPR screens are particularly powerful in combination with induced pluripotent stem cell technology, which enables the derivation of differentiated cell types, such as neurons and glia, and brain organoids from cells obtained from patients. Modelling of disease-associated changes in gene expression via CRISPRi and CRISPRa can pinpoint causal changes. In addition, genetic modifier screens can be used to elucidate disease mechanisms and causal determinants of cell type-selective vulnerability and to identify therapeutic targets.

Key points

  • CRISPR technology enables editing of the human genome sequence, making it possible to model or correct disease-associated genetic variants.

  • CRISPR interference and CRISPR activation allow the expression levels of genes to be altered in human cells.

  • Perturbation of large numbers of genes in CRISPR-based genetic screens facilitates the identification of genes that are relevant for specific cellular functions.

  • Induced pluripotent stem cells (iPSCs) can be derived from patients and differentiated into neurons, glia and brain organoids to generate models of neurological disease.

  • CRISPR screens in iPSC-derived disease models can help us to elucidate disease mechanisms and identify potential therapeutic targets.

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Fig. 1: Key mechanistic questions in neurological disease.
Fig. 2: CRISPR-based approaches to alter or perturb genes.
Fig. 3: Types of genetic screens in human cells.
Fig. 4: Using iPSCs to study neurological disease.
Fig. 5: Modifier screens to study neurological disease.
Fig. 6: Modelling disease-associated changes in gene expression to pinpoint causal changes.
Fig. 7: Uncovering determinants of cell type-selective vulnerability.

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Acknowledgements

The author thanks members of the Kampmann laboratory and A. Pollen for discussions, X. Guo and S. See for feedback on the manuscript, and A. Bassett and the other, anonymous, reviewer(s) for their insightful comments. Research into neurodegenerative and neuropsychiatric diseases in the Kampmann laboratory is supported by a Ben Barres Early Career Acceleration Award from the Chan Zuckerberg Initiative, the Tau Consortium, an Allen Distinguished Investigator Award (Paul G. Allen Family Foundation), a Chan-Zuckerberg Biohub Investigator Award, an NIH Director’s New Innovator Award (NIH/NIGMS DP2 GM119139), NIH/National Institute on Ageing grants (R01 AG062359 and R56 AG057528), the National Institute of Neurological Disorders and Stroke (NINDS) Tau Center Without Walls (NIH/NINDS U54 NS100717), and the University of California, San Francisco/University of California, Berkeley Innovative Genomics Institute (IGI).

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  1. Institute for Neurodegenerative Diseases, University of California, San Francisco, CA, USA

    Martin Kampmann

  2. Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA

    Martin Kampmann

  3. Chan Zuckerberg Biohub, San Francisco, CA, USA

    Martin Kampmann

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Correspondence to Martin Kampmann.

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Competing interests

M.K. has filed a patent application related to CRISPRi and CRISPRa screening (PCT/US15/40449) and serves on the Scientific Advisory Boards of Engine Biosciences and Casma Therapeutics.

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Nature Reviews Neurology thanks A. Bassett and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

CRISPRbrain: https://www.crisprbrain.org/

Glossary

Isogenic

Sharing the same genetic background but differing in a genetic variant of interest to enable characterization of the variant.

Genome-wide association studies

(GWAS). Studies aiming to identify genetic variants associated with disease risk or other traits in human populations.

Pleiotropic

Affecting several traits.

Single-nucleus transcriptomics

Sequencing-based quantification of mRNA molecules in individual nuclei isolated from tissues to characterize gene expression programmes at single-cell resolution.

Spatial transcriptomics

Methods detecting abundance and localization of multiple RNA molecules of interest in the tissue context, based on hybridization or in situ sequencing approaches.

Multiplexed immunofluorescence

Methods detecting abundance and localization of multiple proteins and protein states of interest in the tissue context, based on parallel and sequential probing with antibodies.

Synthetic lethal

Two genetic variants or gene perturbations that are lethal to cells or organisms in combination but not individually.

Linkage disequilibrium

Co-occurrence of genetic variants at different loci within individuals in a population at frequencies different from those expected by chance.

Safe-harbour locus

A site in the genome considered suitable for the integration of transgenes, because it enables stable expression of the transgene without disrupting the function of endogenous genes.

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Kampmann, M. CRISPR-based functional genomics for neurological disease. Nat Rev Neurol 16, 465–480 (2020). https://doi.org/10.1038/s41582-020-0373-z

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