Analysis of the Phenotypes in the Rett Networked Database.

Rett spectrum disorder is a progressive neurological disease and the most common genetic cause of intellectual disability in females. MECP2 is the major causative gene. In addition, CDKL5 and FOXG1 mutations have been reported in Rett patients, especially with the atypical presentation. Each gene and different mutations within each gene contribute to variability in clinical presentation, and several groups worldwide performed genotype-phenotype correlation studies using cohorts of patients with classic and atypical forms of Rett spectrum disorder. The Rett Networked Database is a unified registry of clinical and molecular data of Rett patients, and it is currently one of the largest Rett registries worldwide with several hundred records provided by Rett expert clinicians from 13 countries. Collected data revealed that the majority of MECP2-mutated patients present with the classic form, the majority of CDKL5-mutated patients with the early-onset seizure variant, and the majority of FOXG1-mutated patients with the congenital form. A computation of severity scores further revealed significant differences between groups of patients and correlation with mutation types. The highly detailed phenotypic information contained in the Rett Networked Database allows the grouping of patients presenting specific clinical and genetic characteristics for studies by the Rett community and beyond. These data will also serve for the development of clinical trials involving homogeneous groups of patients.

Revealing the complexity of a monogenic disease: rett syndrome exome sequencing.

Rett syndrome (OMIM#312750) is a monogenic disorder that may manifest as a large variety of phenotypes ranging from very severe to mild disease. Since there is a weak correlation between the mutation type in the Xq28 disease-gene MECP2/X-inactivation status and phenotypic variability, we used this disease as a model to unveil the complex nature of a monogenic disorder. Whole exome sequencing was used to analyze the functional portion of the genome of two pairs of sisters with Rett syndrome. Although each pair of sisters had the same MECP2 (OMIM*300005) mutation and balanced X-inactivation, one individual from each pair could not speak or walk, and had a profound intellectual deficit (classical Rett syndrome), while the other individual could speak and walk, and had a moderate intellectual disability (Zappella variant). In addition to the MECP2 mutation, each patient has a group of variants predicted to impair protein function. The classical Rett girls, but not their milder affected sisters, have an enrichment of variants in genes related to oxidative stress, muscle impairment and intellectual disability and/or autism. On the other hand, a subgroup of variants related to modulation of immune system, exclusive to the Zappella Rett patients are driving toward a milder phenotype. We demonstrate that genome analysis has the potential to identify genetic modifiers of Rett syndrome, providing insight into disease pathophysiology. Combinations of mutations that affect speaking, walking and intellectual capabilities may represent targets for new therapeutic approaches. Most importantly, we demonstrated that monogenic diseases may be more complex than previously thought.

Rett networked database: an integrated clinical and genetic network of Rett syndrome databases.

Rett syndrome (RTT) is a neurodevelopmental disorder with one principal phenotype and several distinct, atypical variants (Zappella, early seizure onset and congenital variants). Mutations in MECP2 are found in most cases of classic RTT but at least two additional genes, CDKL5 and FOXG1, can underlie some (usually variant) cases. There is only limited correlation between genotype and phenotype. The Rett Networked Database (http://www.rettdatabasenetwork.org/) has been established to share clinical and genetic information. Through an "adaptor" process of data harmonization, a set of 293 clinical items and 16 genetic items was generated; 62 clinical and 7 genetic items constitute the core dataset; 23 clinical items contain longitudinal information. The database contains information on 1838 patients from 11 countries (December 2011), with or without mutations in known genes. These numbers can expand indefinitely. Data are entered by a clinician in each center who supervises accuracy. This network was constructed to make available pooled international data for the study of RTT natural history and genotype-phenotype correlation and to indicate the proportion of patients with specific clinical features and mutations. We expect that the network will serve for the recruitment of patients into clinical trials and for developing quality measures to drive up standards of medical management.

Investigation of modifier genes within copy number variations in Rett syndrome.

MECP2 mutations are responsible for two different phenotypes in females, classical Rett syndrome and the milder Zappella variant (Z-RTT). We investigated whether copy number variants (CNVs) may modulate the phenotype by comparison of array-CGH data from two discordant pairs of sisters and four additional discordant pairs of unrelated girls matched by mutation type. We also searched for potential MeCP2 targets within CNVs by chromatin immunopreceipitation microarray (ChIP-chip) analysis. We did not identify one major common gene/region, suggesting that modifiers may be complex and variable between cases. However, we detected CNVs correlating with disease severity that contain candidate modifiers. CROCC (1p36.13) is a potential MeCP2 target, in which a duplication in a Z-RTT and a deletion in a classic patient were observed. CROCC encodes a structural component of ciliary motility that is required for correct brain development. CFHR1 and CFHR3, on 1q31.3, may be involved in the regulation of complement during synapse elimination, and were found to be deleted in a Z-RTT but duplicated in two classic patients. The duplication of 10q11.22, present in two Z-RTT patients, includes GPRIN2, a regulator of neurite outgrowth and PPYR1, involved in energy homeostasis. Functional analyses are necessary to confirm candidates and to define targets for future therapies.

NF1 microdeletions in neurofibromatosis type 1: from genotype to phenotype.

In 5-10% of patients, neurofibromatosis type 1 (NF1) results from microdeletions that encompass the entire NF1 gene and a variable number of flanking genes. Two recurrent microdeletion types are found in most cases, with microdeletion breakpoints located in paralogous regions flanking NF1 (proximal NF1-REP-a and distal NF1-REP-c for the 1.4 Mb type-1 microdeletion, and SUZ12 and SUZ12P for the 1.2 Mb type-2 microdeletion). A more severe phenotype is usually associated with NF1 microdeletion patients than in those with intragenic mutations. We characterized NF1 microdeletions in 70 unrelated NF1 microdeleted patients using a high-resolution NF1 custom array comparative genomic hybridization (CGH). Genotype-phenotype correlations were studied in 58 of these microdeletion patients and compared to 389 patients with intragenic truncating NF1 mutations and phenotyped in the same standardized way. Our results confirmed in an unbiased manner the existence of a contiguous gene syndrome with a significantly higher incidence of learning disabilities and facial dysmorphism in microdeleted patients compared to patients with intragenic NF1 mutations. Microdeleted NF1 patients also showed a trend toward significance for childhood overgrowth. High-resolution array-CGH identified a new recurrent approximately 1.0 Mb microdeletion type, designated as type-3, with breakpoints in the paralogous regions middle NF1-REP-b and distal NF1-REP-c.