MECP2 variation in Rett syndrome—An overview of current coverage of genetic and phenotype data within existing databases |
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Authors: | Friederike Ehrhart Henk J. van Kranen Mark Wilkinson Annika Jacobsen Marco Roos Egon L. Willighagen David van Enckevort Chris T. Evelo Leopold M. G. Curfs |
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Affiliation: | 1. Rett Expertise Centre Netherlands ‐ GKC, Maastricht University Medical Center, Maastricht, The Netherlands;2. Department of Bioinformatics ‐ BiGCaT, NUTRIM, Maastricht University, Maastricht, The NetherlandsGillian S. Townend and Friederike Ehrhart share first authorship.;3. Institute for Public Health Genomics, Maastricht University, Maastricht, The Netherlands;4. Center for Plant Biotechnology and Genomics, Universidad Politécnica de Madrid, Madrid, Spain;5. Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands;6. Department of Bioinformatics ‐ BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands;7. Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands |
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Abstract: | Rett syndrome (RTT) is a monogenic rare disorder that causes severe neurological problems. In most cases, it results from a loss‐of‐function mutation in the gene encoding methyl‐CPG‐binding protein 2 (MECP2). Currently, about 900 unique MECP2 variations (benign and pathogenic) have been identified and it is suspected that the different mutations contribute to different levels of disease severity. For researchers and clinicians, it is important that genotype–phenotype information is available to identify disease‐causing mutations for diagnosis, to aid in clinical management of the disorder, and to provide counseling for parents. In this study, 13 genotype–phenotype databases were surveyed for their general functionality and availability of RTT‐specific MECP2 variation data. For each database, we investigated findability and interoperability alongside practical user functionality, and type and amount of genetic and phenotype data. The main conclusions are that, as well as being challenging to find these databases and specific MECP2 variants held within, interoperability is as yet poorly developed and requires effort to search across databases. Nevertheless, we found several thousand online database entries for MECP2 variations and their associated phenotypes, diagnosis, or predicted variant effects, which is a good starting point for researchers and clinicians who want to provide, annotate, and use the data. |
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Keywords: | databases FAIR data genetic variation MECP2 phenotype Rett syndrome |
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