Evidence map›Paper›PMID 39707712›Full record

ReviewNanomedicine (London, England)2025

Non-viral gene therapy for Leber's congenital amaurosis: progress and possibilities.

Latifat Abdulsalam, James Mordecai, Irshad Ahmad

Abstract readReview
In one paragraph

Review in Nanomedicine (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

3 authors.

Latifat AbdulsalamDepartment of Bioengineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.ORCID 0009-0004-4264-950X
James MordecaiDepartment of Bioengineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.
Irshad AhmadDepartment of Bioengineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.ORCID 0000-0001-8914-282X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Leber's congenital amaurosis (LCA) represents a set of rare and pervasive hereditary conditions of the retina that cause severe vision loss starting in early childhood. Targeted treatment intervention has become possible thanks to recent advances in understanding LCA genetic basis. While viral vectors have shown efficacy in gene delivery, they present challenges related to safety, low cargo capacity, and the potential for random genomic integration. Non-viral gene therapy is a safer and more flexible alternative to treating the underlying genetic mutation causing LCA. Non-viral gene delivery methods, such as inorganic nanoparticles, polymer-based delivery systems, and lipid-based nanoparticles, bypass the risks of immunogenicity and genomic integration, potentially offering a more versatile and personalized treatment for patients. This review explores the genetic background of LCA, emphasizing the mutations involved, and explores diverse non-viral gene delivery methods being developed. It also highlights recent studies on non-viral gene therapy for LCA in animal models and clinical trials. It presents future perspectives for gene therapy, including integrating emerging technologies like CRISPR-Cas9, interdisciplinary collaborations, personalized medicine, and ethical considerations.

Indexed as

Genetic TherapyGene Transfer TechniquesLeber Congenital AmaurosisAnimalsCRISPR-Cas SystemsHumansMutationNanoparticlesPrecision MedicinedegenerationDNA nanoparticlegene therapygeneticsLeber’s congenital amaurosisnon-viral vectorsocular gene therapy

Identifiers

PMID39707712
PMCPMC11792828

What OpenQuestion holds

Textmetadata
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.