Clinical Trial: Rare Diseases Clinical Research Network: Neurophysiological Correlates

Study Status: Recruiting
Recruit Status: Recruiting
Study Type: Observational

Official Title: Rett Syndrome, MECP2 Duplication, and Rett-Related Disorders Consortium, Rare Disease Clinical Research Network: Neurophysiologic Correlates

Brief Summary: The overall purpose of this project is to advance understanding of the neurophysiological features of Rett syndrome (RTT), MECP2 Duplication (MECP2 Dup) and RTT-related disorders (CDKL5, FOXG1) to gain insight into disease pathogenesis, with an emphasis on identifying biomarkers of disease evolution and severity. This specific study is intertwined to the core study Natural History of Rett Syndrome and Related Disorders (RTT5211), which characterizes range of clinical involvement and genotype-phenotype correlations and will provide phenotypical data for determining the clinical relevance of the neurophysiologic parameters; study subjects here are co- and primarily enrolled in RTT5211. The proposed studies will serve as basis of future translational investigations, including further refinement of biomarkers, development of outcome measures, and clinical trials per se.

Detailed Summary: Individuals with RTT, MECP2 Dup and RTT-related disorders have significant abnormalities on a number of neurophysiological measures such as EEG and Evoked Potentials (EP). Studies in representative animal models reproduce many of these abnormalities. Little is known about the relationship between these neurophysiological findings to disease evolution, severity and specific clinical features. Therefore, it is considered likely that detailed understanding of such neurophysiological features would provide additional insight into disease pathogenesis and will lead to biomarkers of disease state and severity of different features. Consequently, specialized neurophysiological assessments will be acquired, without sedation or any other type of pharmacological manipulation, on a subset of 170 subjects: 60 RTT, 18 MECP2 Dup, 32 RTT-related disorders, and 60 age-matched typically developing controls (30 females, 30 males). Primary evaluations will include auditory ERP (AEP) and visual ERP (VEP), as well as secondary analyses of specific rhythms/band activities obtained during the ERP acquisitions (gamma band changes and frontal alpha band asymmetry). Individuals will be recruited across the spectra of ages and severity. The main goal of the project is to identify potential biomarkers that can become measures for intervention and other translational studies and, at the same time, provide insight into abnormal synaptic activity and pathogenesis of RTT, MECP2 Dup, and RTT-related disorders. Therefore, the proposed assessments will be performed in all three groups of subjects enrolled in this consortium (RTT5211): RTT, MECP2 Dup, and RTT-related disorders. Findings in each set of disorders will be linked to the objectives of the the longitudinal clinical and neurobehavioral data (RTT5211) as well as to biological factors and genotyping that may be linked to clinical severity (RTT5213). The neurophysiological parameters for RTT, MECP2 Dup, and RTT-related disorders will not only b
Sponsor: University of Alabama at Birmingham

Current Primary Outcome:

  • Auditory Event-related potentials [ Time Frame: 3 years ]
    EEG will be filtered between 0.5 and 400Hz. The EEG will be segmented around each stimulus presentation. 200msec prior to 1000msec post each stimulus will be collected and averaged for each trial for each electrode. The electrodes with highest averaged N1 waveforms, predicted to be posterior temporal (T5/P3/T3) electrodes, will be used for subsequent analysis. The averaged waveforms will be analyzed for latency to N1 and P1 peak frm which the auditory event related potentials will be the main parameter for statistical analysis.
  • Visual Event-related potentials [ Time Frame: 3 years ]
    VEP analysis will be similar to the AEP analysis. EEG will be prepared using the same methodology but using occipital electrodes with Oz as the primary electrode of analysis. The EEG will be averaged from 200msec prior to 1000ms post stimulus. The N1, P1, and N2 components will be identified and will be averaged and the latency and amplitude of the peaks quantified. P1 latency and N1-P1 time will be the primary end point of the study. The latency will be used for the statistical parameter.
  • EEG [ Time Frame: 3 years ]
    For frequency based analysis, 10-20 ten-second epochs of noise free EEG without clear eye blinks during wakefulness and eyes open; 10 ten-second epochs of wakefulness and eyes closed (assessed by video); and 10-20 ten-second epochs of EEG during each stage of sleep will be analyzed. A prescreen of EEG using a template matching algorithm (EEGlab) can be used to reduce amount of data to be reviewed. For theta and gamma band activity, the EEG will be band passed filtered between 2-

    Original Primary Outcome:

    • Auditory Event-related potentials [ Time Frame: 3 years ]
      EEG will be filtered between 0.5 and 400Hz. The EEG will be segmented around each stimulus presentation. 200msec prior to 1000msec post each stimulus will be collected and averaged for each trial for each electrode. The electrodes with highest averaged N1 waveforms, predicted to be posterior temporal (T5/P3/T3) electrodes, will be used for subsequent analysis. The averaged waveforms will be analyzed for latency to N1 and P1 peak frm which the auditory event related potentials will be the main parameter for statistical analysis.
    • Visual Event-related potentials [ Time Frame: 3 years ]
      VEP analysis will be similar to the AEP analysis. EEG will be prepared using the same methodology but using occipital electrodes with Oz as the primary electrode of analysis. The EEG will be averaged from 200msec prior to 1000ms post stimulus. The N1, P1, and N2 components will be identified and will be averaged and the latency and amplitude of the peaks quantified. P1 latency and N1-P1 time will be the primary end point of the study. The latency will be used for the statistical parameter. Details are provided in reference #7.
    • EEG [ Time Frame: 3 years ]
      For frequency based analysis, 10-20 ten-second epochs of noise free EEG without clear eye blinks during wakefulness and eyes open; 10 ten-second epochs of wakefulness and eyes closed (assessed by video); and 10-20 ten-second epochs of EEG during each stage of sleep will be analyzed. A prescreen of EEG using a template matching algorithm (EEGlab) can be used to reduce amount of data to be reviewed. For theta and gamma band activity, the EEG w

      Current Secondary Outcome:

      Original Secondary Outcome:

      Information By: University of Alabama at Birmingham

      Dates:
      Date Received: March 1, 2017
      Date Started: January 2, 2017
      Date Completion: July 31, 2019
      Last Updated: May 18, 2017
      Last Verified: May 2017