Evidence map›Paper›PMID 33823301›Full record

ReviewMolecular therapy : the journal of the American Society of Gene Therapy2021

CRISPR technologies for the treatment of Duchenne muscular dystrophy.

Eunyoung Choi, Taeyoung Koo

Open access · bronzeAbstract readReview
In one paragraph

Review in Molecular therapy : the journal of the American Society of Gene Therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.3field-weighted citation impact, top 6% of its field
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

32 citing papers in PubMed, 52 citations in OpenAlex.

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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 at 1 institution in 1 country.

Eunyoung ChoiDepartment of Life and Nanopharmaceutical Sciences, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Taeyoung KooDepartment of Life and Nanopharmaceutical Sciences, Graduate School, Kyung Hee University, Seoul, Republic of Korea; Department of Biomedical and Pharmaceutical Sciences, Graduate School, Kyung Hee University, Seoul, Republic of Korea; Department of Pharmaceutical Science, College of Pharmacy, Kyung Hee University, Seoul 02447, Republic of Korea. Electronic address: taeyoungkoo@khu.ac.kr.
Kyung Hee University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emerging clustered regularly interspaced short palindromic repeats (CRISPR)-mediated genome editing technologies have progressed remarkably in recent years, opening up the potential of precise genome editing as a therapeutic approach to treat various diseases. The CRISPR-CRISPR-associated (Cas) system is an attractive platform for the treatment of Duchenne muscular dystrophy (DMD), which is a neuromuscular disease caused by mutations in the DMD gene. CRISPR-Cas can be used to permanently repair the mutated DMD gene, leading to the expression of the encoded protein, dystrophin, in systems ranging from cells derived from DMD patients to animal models of DMD. However, the development of more efficient therapeutic approaches and delivery methods remains a great challenge for DMD. Here, we review various therapeutic strategies that use CRISPR-Cas to correct or bypass DMD mutations and discuss their therapeutic potential, as well as obstacles that lie ahead.

Indexed as

CRISPR-Cas SystemsAnimalsClinical Studies as TopicDisease ManagementDisease Models, AnimalDystrophinExonsGene EditingGenetic TherapyHumansMuscular Dystrophy, DuchenneMutationTreatment OutcomeDMD protein, humanDystrophinCasCRISPRDuchenne muscular dystrophygenome editingneuromuscular disorder

Identifiers

PMID33823301
PMCPMC8571109
OpenAlexW3144275831

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.