Evidence map›Paper›PMID 29399048›Full record

ReviewTherapeutic advances in neurological disorders2018

The prospects of CRISPR-based genome engineering in the treatment of neurodegenerative disorders.

Jun Wan Shin, Jong-Min Lee

Abstract readReview
In one paragraph

Review in Therapeutic advances in neurological disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Translational Geroscience Strategies for Delaying Multimorbidity.ACS pharmacology & translational science · 2026
    Review
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  6. 3 Biotech · 2020
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jun Wan ShinMolecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Medical and Population Genetics Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Jong-Min LeeMolecular Neurogenetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA Department of Neurology, Harvard Medical School, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past few decades, as gene discovery methods and sequencing technologies have evolved, many genetic variations that significantly increase the risk of or cause neurodegenerative diseases have been identified. However, knowledge of those pathogenic mutations and subsequent mechanism-focused studies has rarely yielded effective treatments, warranting alternative strategies for refining rational therapeutic targets. Nevertheless, with the evolution of gene targeting methods, it has been increasingly recognized that the disease-causing gene itself is the best therapeutic target even when we do not have a full understanding of its biological functions. Considering this, CRISPR/Cas gene editing technology offers the promise of permanently silencing or correcting the disease-causing mutations, potentially overcoming key limitations of RNA-targeting approaches. The versatile CRISPR/Cas-based strategies have the potential to become treatment options for challenging disorders such as neurodegenerative diseases. Here, we summarize recent reports of preclinical applications of CRISPR/Cas in models of neurodegenerative disorders to provide perspectives on therapeutic gene editing for diseases of the nervous system.

Indexed as

allele-specificCRISPR/CasgRNAneurodegenerative diseasePAMprecision medicine

Identifiers

PMID29399048
PMCPMC5784517

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.