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Published on: August 24, 2013
InterRett, a model for international data collection in a rare genetic disorder
Sandra Louise1, Sue Fyfe2, Ami Bebbington1
1Telethon Institute for Child Health Research, Centre for Child Health Research, University of Western Australia, Perth, Western Australia.
The InterRett database, an international resource for Rett syndrome (RTT), is comparable to Australia's Rett syndrome database. This validates InterRett for studying RTT's genetic and clinical variations.
Area of Science:
- Genetics
- Neurology
- Rare Diseases
Background:
- Rett syndrome (RTT) is a rare neurodevelopmental disorder within the autistic spectrum.
- Existing RTT databases vary in scope and representativeness.
- The InterRett database is a significant international resource for RTT research.
Purpose of the Study:
- To compare the socio-demographic, clinical, and genetic characteristics of the InterRett database with the Australian Rett syndrome database (ARSD).
- To evaluate the strengths and limitations of InterRett against other Rett syndrome studies.
- To assess the suitability of InterRett for investigating genotype-phenotype associations in RTT.
Main Methods:
- Comparative analysis of questionnaire data from InterRett and ARSD.
- Literature review of RTT population-based and case-based studies investigating genotype-phenotype relationships.
- Verification of case status and comparability between the two databases.
Main Results:
- A total of 935 verified RTT cases from InterRett (born after 1976) were compared with 295 ARSD cases.
- InterRett families reported higher education and occupation levels; their children exhibited marginally less severe symptoms.
- The distribution of *MECP2* mutation types was similar across both databases.
Conclusions:
- The InterRett database demonstrates comparability with population-based registries like ARSD.
- InterRett can be confidently utilized for investigating genotype-phenotype associations and clinical variations in Rett syndrome.
- InterRett serves as an exemplary international model for rare disease data collection and research.
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