Evidence map›Paper›PMID 25816009›Full record

ArticlePloS one2015

In silico screening based on predictive algorithms as a design tool for exon skipping oligonucleotides in Duchenne muscular dystrophy.

Yusuke Echigoya, Vincent Mouly, Luis Garcia, Toshifumi Yokota, William Duddy

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

45 citing papers in PubMed, 60 citations in OpenAlex.

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  20. Development of DG9 peptide-conjugated single- and multi-exon skipping therapies for the treatment of Duchenne muscular dystrophy.Proceedings of the National Academy of Sciences of the United States of America · 2022
    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

5 authors at 3 institutions in 2 countries.

Yusuke EchigoyaUniversity of Alberta, Faculty of Medicine and Dentistry, Department of Medical Genetics, Edmonton, Alberta, Canada.
Vincent MoulyUPMC-Sorbonne Universités-Univ. Paris 6, UPMC/INSERM UMRS974, CNRS FRE 3617, Center of Research in Myology, Paris, 75651 cedex 13, France.
Luis GarciaUFR des Sciences de la Santé, Université de Versailles Saint-Quentin-en-Yvelines, 78180 Montigny-le-Bretonneux, France.
Toshifumi YokotaUniversity of Alberta, Faculty of Medicine and Dentistry, Department of Medical Genetics, Edmonton, Alberta, Canada; Muscular Dystrophy Canada Research Chair, University of Alberta, Edmonton, Alberta, Canada.
William DuddyUPMC-Sorbonne Universités-Univ. Paris 6, UPMC/INSERM UMRS974, CNRS FRE 3617, Center of Research in Myology, Paris, 75651 cedex 13, France.
Centre de Recherche en MyologieUniversité de Versailles Saint-Quentin-en-Yvelines · FRUniversity of Alberta · CA

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

The use of antisense 'splice-switching' oligonucleotides to induce exon skipping represents a potential therapeutic approach to various human genetic diseases. It has achieved greatest maturity in exon skipping of the dystrophin transcript in Duchenne muscular dystrophy (DMD), for which several clinical trials are completed or ongoing, and a large body of data exists describing tested oligonucleotides and their efficacy. The rational design of an exon skipping oligonucleotide involves the choice of an antisense sequence, usually between 15 and 32 nucleotides, targeting the exon that is to be skipped. Although parameters describing the target site can be computationally estimated and several have been identified to correlate with efficacy, methods to predict efficacy are limited. Here, an in silico pre-screening approach is proposed, based on predictive statistical modelling. Previous DMD data were compiled together and, for each oligonucleotide, some 60 descriptors were considered. Statistical modelling approaches were applied to derive algorithms that predict exon skipping for a given target site. We confirmed (1) the binding energetics of the oligonucleotide to the RNA, and (2) the distance in bases of the target site from the splice acceptor site, as the two most predictive parameters, and we included these and several other parameters (while discounting many) into an in silico screening process, based on their capacity to predict high or low efficacy in either phosphorodiamidate morpholino oligomers (89% correctly predicted) and/or 2'O Methyl RNA oligonucleotides (76% correctly predicted). Predictions correlated strongly with in vitro testing for sixteen de novo PMO sequences targeting various positions on DMD exons 44 (R² 0.89) and 53 (R² 0.89), one of which represents a potential novel candidate for clinical trials. We provide these algorithms together with a computational tool that facilitates screening to predict exon skipping efficacy at each position of a target exon.

Indexed as

AlgorithmsComputer SimulationHigh-Throughput Screening AssaysDystrophinExonsHumansModels, StatisticalMorpholinosMuscular Dystrophy, DuchenneOligonucleotidesOligonucleotides, AntisenseRNA SplicingDystrophinMorpholinosOligonucleotidesOligonucleotides, Antisense

Identifiers

PMID25816009
PMCPMC4376395
OpenAlexW2024664316

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.