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.

Highlights

  • Rett syndrome (RTT; MIM# 312750) is one of 5,000–8,000 known rare diseases that together have been identified as affecting 6%–8% of the world's population

  • We analyzed (a) the FAIR status, (b) the upload and download possibilities, (c) form of phenotype and genotype information, (d) the total number of entries relating to the methyl-CPG-binding protein 2 (MECP2) gene or RTT, and (e) the coverage for the chosen MECP2 mutations

  • The genetic variation or location databases were easier to find than the RTT-specific ones

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Summary

Introduction

Rett syndrome (RTT; MIM# 312750) is one of 5,000–8,000 known rare diseases that together have been identified as affecting 6%–8% of the world's population. 80% of these diseases have a genetic origin (Council Recommendation on an action in the field of rare diseases (2009/C 151/02), Recital 5) Most of these diseases are caused by pathological variants in one single, disease-specific gene. To help distinguish between pathological and neutral genetic variants (Hunter et al, 2016), scientists and clinicians collect genetic data and corresponding phenotypic information and make this information available in databases, which can be used for research and prognostic purposes. In this respect, RTT serves as an example for any monogenic rare disease where, due to the limited number of individuals, a better

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