Dataset Information

Rett Syndrome: Crossing the Threshold to Clinical Translation.

ABSTRACT: Lying at the intersection between neurobiology and epigenetics, Rett syndrome (RTT) has garnered intense interest in recent years, not only from a broad range of academic scientists, but also from the pharmaceutical and biotechnology industries. In addition to the critical need for treatments for this devastating disorder, optimism for developing RTT treatments derives from a unique convergence of factors, including a known monogenic cause, reversibility of symptoms in preclinical models, a strong clinical research infrastructure highlighted by an NIH-funded natural history study and well-established clinics with significant patient populations. Here, we review recent advances in understanding the biology of RTT, particularly promising preclinical findings, lessons from past clinical trials, and critical elements of trial design for rare disorders.

SUBMITTER: Katz DM

PROVIDER: S-EPMC4924590 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Rett Syndrome: Crossing the Threshold to Clinical Translation.

Katz David M DM Bird Adrian A Coenraads Monica M Gray Steven J SJ Menon Debashish U DU Philpot Benjamin D BD Tarquinio Daniel C DC

Trends in neurosciences 20160201 2

Lying at the intersection between neurobiology and epigenetics, Rett syndrome (RTT) has garnered intense interest in recent years, not only from a broad range of academic scientists, but also from the pharmaceutical and biotechnology industries. In addition to the critical need for treatments for this devastating disorder, optimism for developing RTT treatments derives from a unique convergence of factors, including a known monogenic cause, reversibility of symptoms in preclinical models, a stro ...[more]

PMID: 26830113

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Project description:BACKGROUND:Rett Syndrome (RTT) is a complex neurodevelopmental disorder, frequently associated with epilepsy. Despite increasing recognition of the clinical heterogeneity of RTT and its variants (e.g Classical, Hanefeld and PSV(Preserved Speech Variant)), the link between causative mutations and observed clinical phenotypes remains unclear. Quantitative analysis of electroencephalogram (EEG) recordings may further elucidate important differences between the different clinical and genetic forms of RTT. METHODS:Using a large cohort (n?=?42) of RTT patients, we analysed the electrophysiological profiles of RTT variants (genetic and clinical) in addition to epilepsy status (no epilepsy/treatment-responsive epilepsy/treatment-resistant epilepsy). The distribution of spectral power and inter-electrode coherence measures were derived from continuous resting-state EEG recordings. RESULTS:RTT genetic variants (MeCP2/CDLK5) were characterised by significant differences in network architecture on comparing first principal components of inter-electrode coherence across all frequency bands (p?<?0.0001). Greater coherence in occipital and temporal pairs were seen in MeCP2 vs CDLK5 variants, the main drivers in between group differences. Similarly, clinical phenotypes (Classical RTT/Hanefeld/PSV) demonstrated significant differences in network architecture (p?<?0.0001). Right tempero-parietal connectivity was found to differ between groups (p?=?0.04), with greatest coherence in the Classical RTT phenotype. PSV demonstrated a significant difference in left-sided parieto-occipital coherence (p?=?0.026). Whilst overall power decreased over time, there were no difference in asymmetry and inter-electrode coherence profiles over time. There was a significant difference in asymmetry in the overall power spectra between epilepsy groups (p?=?0.04) in addition to occipital asymmetry across all frequency bands. Significant differences in network architecture were also seen across epilepsy groups (p?=?0.044). CONCLUSIONS:Genetic and clinical variants of RTT are characterised by discrete patterns of inter-electrode coherence and network architecture which remain stable over time. Further, hemispheric distribution of spectral power and measures of network dysfunction are associated with epilepsy status and treatment responsiveness. These findings support the role of discrete EEG profiles as non-invasive biomarkers in RTT and its genetic/clinical variants.

Dataset Information

Rett Syndrome: Crossing the Threshold to Clinical Translation.

Publications

Rett Syndrome: Crossing the Threshold to Clinical Translation.

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