At the present time, effective treatments for RTT, MECP2 Dup, or Rett-related disorders are lacking. Investigators have made substantial progress in RTT over the past eleven years such that this study represents a narrowing of focus to mutations or duplications of the MECP2 gene and related disorders, including those with phenotypic overlap. Understanding of RTT has advanced remarkably well through the Rett Syndrome Natural History Clinical Protocol (NHS) and correspondingly advancement in the basic science realm has moved forward with equivalent success. Thus, progress in clinical and basic science has led to the establishment of clinical trials and other translational studies that hold promise for additional clinical trials in future. In the process, however, investigators became aware of additional MECP2- and RTT-related disorders that were unknown at the time the original proposal was conceived and further were impressed by the substantial clinical variability in individuals with RTT that cannot be explained by differences in mutations alone. In fact, variability among individuals with identical mutations has led investigators to search for additional explanations. At the time of the initial application (2002), just three years after the identification of the gene, MECP2, as the molecular link to RTT, investigators were not aware of the variation in clinical disorders related to MECP2 mutations or to the related but quite different MECP2 Dup. Each disorder is characterized by significant neurodevelopmental features related either to alterations in the MECP2 gene or related to phenotypes closely resembling those seen in individuals with RTT. Further, the phenotypic overlap with RTT due to mutations in CDKL5 and FOXG1 was also unexplored. The investigators propose in this new study to build on the substantial progress made in understanding both classic and variant RTT and to add these related disorders, MECP2 Dup and the Rett-related disorders including CDKL5, FOXG1, and individuals with MECP2 mutations who do not have RTT. In conjunction with the longitudinal clinical assessment performed via the natural history component, investigators will systematically collect from all willing participant's blood and isolate plasma, DNA, and RNA. All participants in the Natural History Study will be asked to contribute samples at the initial visit, whereas samples will be collected repeatedly on a subset of participants in order to look for changes over time. In order to identify factors that distinguish between affected and unaffected individuals, as well as to have the potential to characterize the heritability and potential consequences of genetic changes in families, samples will be collected from unaffected family members. Additionally, on a subset of individuals chosen because of unique clinical features skin biopsies and/or hair follicles will be collected to establish cell lines. Investigators will ask all individuals providing samples to agree to potential future whole-genome sequencing in order to be able to potentially evaluate for genetic modifiers of these diseases.

These materials will be stored at a central repository (Greenwood Genetics Laboratory). The main purpose of these samples is to serve as durable materials for future analyses, however, a set of defined analyses will be performed on all samples. For the samples collected in the Rett syndrome cohort, investigators will perform X-chromosome inactivation studies and evaluate common polymorphisms in Brain derived neurotrophic factor (BDNF) and determine the contribution of these known factors to disease severity. For MECP2 Dup cohort investigators will characterize inflammatory markers in the plasma and correlate these with clinical features. Also for MECP2 Dup cohort investigators will perform detailed genomic breakpoint and gene content analysis and correlate this with disease severity. Similar analysis of genomic breakpoints and gene content will be performed on people with FOXG1 Duplications. Finally, in a pilot study, investigators will perform metabolic profiling on people from all disorders and evaluate for metabolic features correlated with disease severity, and metabolic features common or unique between these disorders. This work will provide a durable resource for future analysis, extend understanding of genotype/phenotype correlations, identify other biological factors contributing to disease severity, as well as provide the framework for the development of biomarkers of disease state and severity.