Evidence map›Paper›PMID 36829465›Full record

ReviewBiology2023

AAV Engineering for Improving Tropism to the Central Nervous System.

Muhammad S Ghauri, Li Ou

Open access · goldAbstract readReview
In one paragraph

Review in Biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
16.3field-weighted citation impact, top 1% 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

38 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
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  19. Identification of a robust promoter in mouse and human hepatocytes by in vivo biopanning of a barcoded AAV library.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Article
  20. Review
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.

Muhammad S GhauriSchool of Medicine, California University of Science and Medicine, Colton, CA 92324, USA.ORCID 0000-0001-6387-589X
Li OuGenemagic Biosciences, Media, PA 19086, USA.
University of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adeno-associated virus (AAV) is a non-pathogenic virus that mainly infects primates with the help of adenoviruses. AAV is being widely used as a delivery vector for in vivo gene therapy, as evidenced by five currently approved drugs and more than 255 clinical trials across the world. Due to its relatively low immunogenicity and toxicity, sustained efficacy, and broad tropism, AAV holds great promise for treating many indications, including central nervous system (CNS), ocular, muscular, and liver diseases. However, low delivery efficiency, especially for the CNS due to the blood-brain barrier (BBB), remains a significant challenge for more clinical application of AAV gene therapy. Thus, there is an urgent need for utilizing AAV engineering to discover next-generation capsids with improved properties, e.g., enhanced BBB penetrance, lower immunogenicity, and higher packaging efficiency. AAV engineering methods, including directed evolution, rational design, and in silico design, have been developed, resulting in the discovery of novel capsids (e.g., PhP.B, B10, PAL1A/B/C). In this review, we discuss key studies that identified engineered CNS capsids and/or established methodological improvements. Further, we also discussed important issues that need to be addressed, including cross-species translatability, cell specificity, and modular engineering to improve multiple properties simultaneously.

Indexed as

AAVblood-brain-barriercapsid engineeringCNSdirected evolutionin silico

Identifiers

PMID36829465
PMCPMC9953251
OpenAlexW4318206221

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.