1. Clinical variability and relationship with genotype in Rett syndrome:insights from AussieRett and InterRett Telethon Institute for Child Health Research Chicago June 2008

2. Introduction to the Australian Rett Syndrome Database Clinical variability in Rett syndrome though the use of video Introduction to InterRett Relationship between genotype and phenotype using data from the Australian Rett Syndrome Database and InterRett Overview

3. Western Australia

4. Perth, Western Australia

5. Subiaco, Perth Telethon Institute for Child Health Research

6. Aims of Australian Rett syndrome research Original aims of the study were: to estimate the incidence and prevalence of juvenile Rett syndrome in Australia establish a database for future research Aims of the research today include: describing and investigating the variability of severity and its determinants, both genetic and environmental providing longitudinal data to identify changes in phenotype over time describing patterns of health service usage and morbidity and mortality in Rett syndrome investigating the impact of Rett syndrome on family life (resources, time, holiday/respite options) comparing the burden for families with Rett syndrome with that of families with Down syndrome

7. Cumulative number of cases by calendar year in Australia

8. MECP2 gene & distribution of mutations in Australia R133C P152R T158M R168X R255X R270X R294X R106W NLS region R306H Methyl-binding domain R306C Inter-Domain Transcription repression domain Courtesy of Lyn Colvin

10. Western Australia: PERTH

11. Follow-up study 1999-2002 Funding obtained in 1999: Financial Markets Foundation for Children Basis of study was to obtain ongoing information about medical, functioning, educational aspects which would provide more information about natural history and phenotypic classification Parental questionnaire –Information related to phenotype information Calendar data –Parental completion of calendar Jan-Dec 2000 –Returned on monthly basis

12. Use of data from follow-up & calendar studies Formation of tool to measure level of functioning Phenotype score Natural history of disorder Life expectancy Use of health services Medication use Comparison with non-affected children and young adults

13. Genotype phenotype correlations Discovery of gene and multiple mutations led to the need for a phenotypic scoring system. Several systems derived: –Kerr (2001) - Glasgow –Percy (2001) - USA –Pineda (2001) - Spain –WeeFIM (1994)-Msall Describing the phenotype in Rett syndrome using a population database. Colvin et al. Archives of Diseases in Children 2003;88:38-43

14. Clinical Severity Score from Percy et al. (2000) 1:Age at onset of regression 2:Head growth 3:Motor function 4:Crawling and creeping 5:Ambulation 6:Nonverbal communication 7:Language 8:Respiratory dysfunction 9:Epilepsy and seizures 10:Hand use 11:Feeding 12:Onset of stereotypies 13:Somatic growth 14:Autonomic dysfunction 15:Scoliosis

15. 1. Increase the clinical understanding of Rett syndrome 2. Provide a large sample of cases for analysis 3. Encourage collaboration among researchers around the world 4. Provide an innovative and efficient mechanism to disseminate information Project aims InterRett is now a unique resource with considerable potential

16. Cases from 36 different countries n=1588 (June 2008)-includes ~300 Australian cases USA Spain Australia France China Canada UK Distribution of cases by country of birth

17. Distribution of cases by genetic status All Cases - 637 Tested – 544 (85.4%)Not Tested – 93 (14.6%) No Mutation – 197 Positive Mutation – 346 Common Mutation – 244 Early Truncating - 18 C-terminal Deletions - 32 Large Deletions - 6 All other Mutations - 46 Bebbington et al. Investigating genotype-phenotype relationships in Rett syndrome using an international dataset. Neurology. 2008;70:868-875.

18. Common mutation frequency  276 cases with a common mutation  Most frequent mutation is R255X (20%)  AussieRett found T158M most common  T158M second most common (18%)  R168X (15%) Bebbington et al. Investigating genotype-phenotype relationships in Rett syndrome using an international dataset. Neurology. 2008;70:868-875.

19. Age at regression by mutation

20. Language development by mutation

21. Ambulation history by mutation

22. Hand use by mutation

23. Rottnest Island The Pinnacles Gascoyne Region The Kimberleys

24. Clinical Scores Colvin et al. Refining the phenotype of common mutations in Rett syndrome. Journal of Medical Genetics 2003;41(1):25-30.

25. Kerr severity by common mutations

26. Pineda severity by common mutations Bebbington et al. Investigating genotype-phenotype relationships in Rett syndrome using an international dataset. Neurology. 2008;70:868-875.

27. Percy severity by common mutations Bebbington et al. Investigating genotype-phenotype relationships in Rett syndrome using an international dataset. Neurology. 2008;70:868-875.

28. Individual and composite scores relating to early development by six common mutations Genotype and Early Development in Rett Syndrome: the Value of International Data. Leonard et al Brain & Development 2005; 27 Suppl 1, S59-68.

29. Summary of results R133C P152R T158M R168X R255X R270X R294X R106W NLS region R306H Methyl-binding domain R306C significantly more severe region most severe mutation milder Inter-Domain Transcription repression domain Courtesy of Lyn Colvin C-terminal Deletions Also milder Early Truncating mutations up to here

30. Risk of onset of scoliosis for common major mutations compared with T158M. Ager et al. Predictors of scoliosis in Rett syndrome. Journal of Child Neurology, 2006, 21 (9): 809-813.

31. Median age at onset of seizures Jian et al. Predictors of seizure onset in Rett syndrome. Journal of Pediatrics, 2006, 149 (4): 542-47.

32. Association of seizure rate with mutation type in Rett syndrome cases with epilepsy Jian et al. Seizures in Rett syndrome: an overview from a one-year calendar study. European Journal of Paediatric Neurology 2007 ; 11 (5): 310-317.

33. Fracture Incidence 84 (ex 236) fractured at least once 32 had more than one fracture (maximum 9) 151 fracture episodes Fracture Incidence Rates 43.3/1000 py - Rett 11.4/1000 py - General Population (females <20yrs – Cooley & Jones)

34. Association of fracture rate with mutation type in Rett syndrome Downs et al. Fractures in Rett syndrome. Pediatrics 2008 ; 121: 540-546.

35. Skewed X-Inactivation Mechanism by which mammals achieve gene- dosage compensation ie. males have one X- chromosome and females have two X-chromosomes Females are mosaic -. comprising mixtures of cell lines in which the paternal X is inactivated and cell lines where the maternally inherited X is inactivated Preferential silencing of one allele, leading to skewed X-inactivation Could either be favourable or detrimental

36. Modulation of severity by X inactivation status Archer et al. Correlation between clinical severity in Rett syndrome patients with a p.R168X or p.T158M MECP2 mutation and the direction and proportion of X chromosome inactivation Journal of Medical Genetics 2006, 44 (2): 148-152.

37. Survival with p.R270X mutation compared with other mutations Jian et al. The p.R270X MECP2 mutation and mortality in Rett syndrome. European Journal of Human Genetics 2005; 13(11), 1235-1238.

38. Co-investigators & Contributors

39. Thanks go to... Financial Markets Foundation for Children Rett Syndrome Association Research Fund International Rett Syndrome Association APSU National Institutes of Health NHMRC Janelle Lillis and family Bill Callaghan and the Rett Syndrome Association of Australia The families and clinicians who support the research so well Current funding NIH 1 R01 HD043100-01A1 & NHMRC #303189

40. Thanks go to...  International Rett Syndrome Association  All the families and clinicians who support the research so well InterRett - IRSA Rett Phenotype Database Telethon Institute for Child Health Research PO Box 855 West Perth WA AUSTRALIA 6872 Ph: +61 8 9489 7790 Mob/Cell: +61 419 956 946 Email: rett@ichr.uwa.edu.aurett@ichr.uwa.edu.au URL: www.ichr.uwa.edu.au/rett/irsa