Evidence map›Paper›PMID 33452270›Full record

ArticleScientific data2021

A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration.

Friederike Ehrhart, Annika Jacobsen, Maria Rigau, Mattia Bosio, Rajaram Kaliyaperumal, Jeroen F J Laros, Egon L Willighagen, Alfonso Valencia, Marco Roos, Salvador Capella-Gutierrez and 2 more

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
4.5field-weighted citation impact, top 5% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. An updated catalog ofFrontiers in molecular neuroscience · 2023
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  4. Modulating alternative splicing ofScience translational medicine · 2026
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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

12 authors at 5 institutions in 2 countries.

Friederike EhrhartDepartment of Bioinformatics - BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, MHeNS School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands. friederike.ehrhart@maastrichtuniversity.nl.ORCID 0000-0002-7770-620X
Annika JacobsenDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0003-4818-2360
Maria RigauBarcelona Supercomputing Centre (BSC), Barcelona, Spain.ORCID 0000-0002-6501-7212
Mattia BosioBarcelona Supercomputing Centre (BSC), Barcelona, Spain.
Rajaram KaliyaperumalDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Jeroen F J LarosDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Egon L WillighagenDepartment of Bioinformatics - BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, MHeNS School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0001-7542-0286
Alfonso ValenciaBarcelona Supercomputing Centre (BSC), Barcelona, Spain.ORCID 0000-0002-8937-6789
Marco RoosDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0002-8691-772X
Salvador Capella-GutierrezBarcelona Supercomputing Centre (BSC), Barcelona, Spain.ORCID 0000-0002-0309-604X
Leopold M G CurfsGKC - Rett Expertise Centre, Maastricht University Medical Center, Maastricht, The Netherlands.ORCID 0000-0001-9154-1395
Chris T EveloDepartment of Bioinformatics - BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, MHeNS School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-5301-3142
Leiden University Medical Center · NLBarcelona Supercomputing Center · ESMaastricht University · NLInstitució Catalana de Recerca i Estudis Avançats · ESMaastricht University Medical Centre · NL

Funding

EC | EC Seventh Framework Programm | FP7 Coordination of Non-Community Research Programmes (FP7-GA - Coordination of Non-Community Research Programmes) RD-connect 305444EC | EC Seventh Framework Programm | FP7 Coordination of Non-Community Research Programmes (FP7-GA - Coordination of Non-Community Research Programmes) RD Connect 305444EC | EU Framework Programme for Research and Innovation H2020 | H2020 Euratom (H2020 Euratom Research and Training Programme 2014-2018) EJP-RD 825575EC | EU Framework Programme for Research and Innovation H2020 | H2020 Euratom (H2020 Euratom Research and Training Programme 2014-2018) EXCELERATE 676559EC | EU Framework Programme for Research and Innovation H2020 | H2020 European Institute of Innovation and Technology (H2020 The European Institute of Innovation and Technology) 676559 EXCELERATEEC | EU Framework Programme for Research and Innovation H2020 | H2020 European Institute of Innovation and Technology (H2020 The European Institute of Innovation and Technology) EJP-RD 825575EC | EU Framework Programme for Research and Innovation H2020 | H2020 European Institute of Innovation and Technology (H2020 The European Institute of Innovation and Technology) EXCELERATE 676559
6 · The paper itself

Abstract

Rett syndrome (RTT) is a rare neurological disorder mostly caused by a genetic variation in MECP2. Making new MECP2 variants and the related phenotypes available provides data for better understanding of disease mechanisms and faster identification of variants for diagnosis. This is, however, currently hampered by the lack of interoperability between genotype-phenotype databases. Here, we demonstrate on the example of MECP2 in RTT that by making the genotype-phenotype data more Findable, Accessible, Interoperable, and Reusable (FAIR), we can facilitate prioritization and analysis of variants. In total, 10,968 MECP2 variants were successfully integrated. Among these variants 863 unique confirmed RTT causing and 209 unique confirmed benign variants were found. This dataset was used for comparison of pathogenicity predicting tools, protein consequences, and identification of ambiguous variants. Prediction tools generally recognised the RTT causing and benign variants, however, there was a broad range of overlap Nineteen variants were identified that were annotated as both disease-causing and benign, suggesting that there are additional factors in these cases contributing to disease development.

Indexed as

MutationData AnalysisDNA Mutational AnalysisHumansMethyl-CpG-Binding Protein 2Rett SyndromeMethyl-CpG-Binding Protein 2

Identifiers

PMID33452270
PMCPMC7810705
OpenAlexW3125637088

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.