Evidence map›Paper›PMID 39583120›Full record

ReviewGlobal medical genetics2024

Mechanism of Genome Editing Tools and Their Application on Genetic Inheritance Disorders.

Dae Hwan Oh

Abstract readReview
In one paragraph

Review in Global medical genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Dae Hwan OhInstitute of Green Manufacturing Technology, Korea University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the fields of medicine and bioscience, gene editing is increasingly recognized as a promising therapeutic approach for treating pathogenic variants in humans and other living organisms. With advancements in technology and knowledge, it is now understood that most genetic defects are caused by single-base pair variants. The ability to substitute genes using genome editing tools enables scientists and doctors to cure genetic diseases and disorders. Starting with CRISPR (clustered regularly interspaced short palindromic repeats)/Cas, the technology has evolved to become more efficient and safer, leading to the development of base and prime editors. Furthermore, various approaches are used to treat genetic disorders such as hemophilia, cystic fibrosis, and Duchenne muscular dystrophy. As previously mentioned, most genetic defects leading to specific diseases are caused by single-base pair variants, which can occur at many locations in corresponding gene, potentially causing the same disease. This means that, even when using the same genome editing tool, results in terms of editing efficiency or treatment effectiveness may differ. Therefore, different approaches may need to be applied to different types of diseases. Prevalently, due to the safety of adeno-associated virus (AAV) vectors in gene therapy, most clinical trials of gene therapy are based on AAV delivery methods. However, despite their safety and nonintegration into the host genome, their limitations, such as confined capacity, dosage-dependent viral toxicity, and immunogenicity, necessitate the development of new approaches to enhance treatment effects. This review provides the structure and function of each CRISPR-based gene editing tool and focuses on introducing new approaches in gene therapy associated with improving treatment efficiency.

Indexed as

base editorCRISPRcystic fibrosisDuchenne muscular dystrophygene therapyhemophiliaprime editor

Identifiers

PMID39583120
PMCPMC11405120

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.