Evidence map›Paper›PMID 35955863›Full record

SynthesisInternational journal of molecular sciences2022

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG).

Sandra Brasil, Mariateresa Allocca, Salvador C M Magrinho, Inês Santos, Madalena Raposo, Rita Francisco, Carlota Pascoal, Tiago Martins, Paula A Videira, Florbela Pereira and 5 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 16 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

15 authors at 2 institutions in 3 countries.

Sandra BrasilUCIBIO-Applied Molecular Biosciences Unit, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.
Mariateresa AlloccaCDG & Allies PPAIN-Professionals and Patient Associations International Network, Department of Life Sciences, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0003-3693-2515
Salvador C M MagrinhoUCIBIO-Applied Molecular Biosciences Unit, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0002-8532-5271
Inês SantosCDG & Allies PPAIN-Professionals and Patient Associations International Network, Department of Life Sciences, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.
Madalena RaposoCDG & Allies PPAIN-Professionals and Patient Associations International Network, Department of Life Sciences, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0003-1796-1185
Rita FranciscoUCIBIO-Applied Molecular Biosciences Unit, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0002-4398-3401
Carlota PascoalUCIBIO-Applied Molecular Biosciences Unit, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0001-5049-0579
Tiago MartinsCDG & Allies PPAIN-Professionals and Patient Associations International Network, Department of Life Sciences, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.
Paula A VideiraUCIBIO-Applied Molecular Biosciences Unit, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0001-5987-2485
Florbela PereiraCDG & Allies PPAIN-Professionals and Patient Associations International Network, Department of Life Sciences, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.ORCID 0000-0003-4392-4644
Giuseppina AndreottiInstitute of Biomolecular Chemistry, National Research Council of Italy, 80078 Pozzuoli, Italy.ORCID 0000-0002-1594-0156
Jaak JaekenCDG & Allies PPAIN-Professionals and Patient Associations International Network, Department of Life Sciences, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.
Kristin A KantautasSappani Foundation, Brampton, ON L6Y 5T2, Canada.
Ethan O PerlsteinPerlara PBC, Berkeley, CA 94705, USA.
Vanessa Dos Reis FerreiraUCIBIO-Applied Molecular Biosciences Unit, School of Science and Technology, NOVA University of Lisbon, 2819-516 Caparica, Portugal.
University of Lisbon · PTNational Research Council · IT

Funding

Fundação para a Ciência e Tecnologia SFRH/BD/124326/2016Fundação para a Ciência e Tecnologia SFRH/BD/138647/2018
6 · The paper itself

Abstract

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders' views on AI for therapy discovery in CDG.

Indexed as

Congenital Disorders of GlycosylationArtificial IntelligenceBiomarkersDrug RepositioningHumansRare DiseasesBiomarkersAI in drug discoverybiomarkerscongenital disorders of glycosylationdisease modelsdrug repositioningorphan drugs

Identifiers

PMID35955863
PMCPMC9369176
OpenAlexW4290502018

What Socratic 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 Socratic graph.