Rare Diseases Clinical Research Network: Neurophysiological Correlates

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

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.

Study Overview

• Status: Completed
• Conditions: Rett Syndrome, Preserved Speech Variant; Mecp2 Duplication Syndrome; Rett-related Disorders
• Intervention / Treatment: Procedure: Auditory and Visual Event-related Potentials and EEG

Detailed Description

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 be correlated with each other but also to disease staging, overall clinical severity scores and through exploratory analyses with specific clinical features; these will be repeated up to 3 times (i.e., annual [every 10-14 month] evaluations, in the context of visits for the RTT5211 protocol) during the course of study. For this purpose, linear regression and linear mixed models will be used. Preliminary and published data indicate that RTT and MECP2 Dup have distinct patterns of cortical processing on AEP, VEP demonstrates disorder and age/disease-stage dependent changes. Phenotypic severity may be related to specific ERP parameters, as some modest effects of (severity) category of mutations were observed. In addition, the secondary analyses of specific EEG rhythms/band activities will expand our preliminary studies demonstrating alpha band asymmetry as a marker of an anxiety-like response in RTT.

• Study Type: Observational
• Enrollment (Actual): 185

Contacts and Locations

Study Locations

• United States
  • Colorado
    • Denver, Colorado, United States, 80045-2571
      • University of Colorado Denver
  • Massachusetts
    • Boston, Massachusetts, United States, 02115-5724
      • Boston Children's Hospital
  • Ohio
    • Cincinnati, Ohio, United States, 45229
      • Cincinnati Children's Hospital
  • Pennsylvania
    • Philadelphia, Pennsylvania, United States, 19104-4318
      • Children's Hospital of Philadelphia
  • Tennessee
    • Nashville, Tennessee, United States, 37212
      • Vanderbilt University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 2 years to 65 years (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Individuals with RTT, MECP2 Dup, and RTT-related disorders (mutations or deletions in CDKL5 and FOXG1 genes) who are also enrolled in the RTT5211 Protocol, which collects longitudinal clinical and neurobehavioral data in the above mentioned disorders. Participants will be linked to the RTT5211 Protocol by their RDCRN identification numbers. All participants will be tested for MECP2, CDKL5, and/or FOXG1 mutations; those with RTT phenotype will be assessed in terms of diagnostic criteria for classic or atypical RTT. No phenotypic selection will be performed; the cohort will be representative of each disorder.

60 typically developing girls and boys (30 each) will be enrolled to serve as controls for all three cohorts with age matching to the RTT/CDKL5 girls and MECP2 Dup/FOXG1 boy cohorts.

Description

Inclusion Criteria: Individuals with RTT, MECP2 Dup, and RTT-related disorders (mutations or deletions in CDKL5 and FOXG1 genes) who are also enrolled in the RTT5211 Protocol, which collects longitudinal clinical and neurobehavioral data will be linked to the RTT5211 Protocol by their RDCRN identification numbers. No phenotypical selection of subjects will be performed; we expect the cohort will be representative of each disorder.

A cohort of 60 typically developing girls and boys (30 each) will be enrolled to serve as controls. Typical development in the control group will be confirmed by normal intelligence quotient scores or equivalent scores on developmental tests using standardized measures and negative psychiatric diagnoses on a standardized diagnostic interview administered to their mothers, fathers or guardians (Diagnostic Interview for Children and Adolescents, Revised: Parents' Version). All control subjects must have a negative history of neurologic impairment or neuropsychiatric conditions and show no clinical evidence of a genetic disorder.

Exclusion Criteria: Individuals who do not meet the above criteria will be excluded.

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Rett Syndrome; Auditory and Visual event-related potentials (ERP) and EEG in 60 individuals with Rett syndrome.	Procedure: Auditory and Visual Event-related Potentials and EEG; Specifically, through up to three standardized sessions (i.e., annual [every 10-14 months]), we will assess AEP and VEP. ERP recordings will also provide data for specific rhythms/band (gamma and alpha) pattern analyses as secondary measures as well as technical control data, which will help to exclude those with co-current seizures.
MECP2 Duplication Syndrome; Auditory and Visual event-related potentials (ERP) and EEG in 18 individuals with MECP2 Duplication syndrome.	Procedure: Auditory and Visual Event-related Potentials and EEG; Specifically, through up to three standardized sessions (i.e., annual [every 10-14 months]), we will assess AEP and VEP. ERP recordings will also provide data for specific rhythms/band (gamma and alpha) pattern analyses as secondary measures as well as technical control data, which will help to exclude those with co-current seizures.
Rett-related disorders; Auditory and Visual event-related potentials (ERP) and EEG in 18 individuals with CDKL5 syndrome and 14 individuals with FOXG1 syndrome.	Procedure: Auditory and Visual Event-related Potentials and EEG; Specifically, through up to three standardized sessions (i.e., annual [every 10-14 months]), we will assess AEP and VEP. ERP recordings will also provide data for specific rhythms/band (gamma and alpha) pattern analyses as secondary measures as well as technical control data, which will help to exclude those with co-current seizures.
Controls; Auditory and Visual event-related potentials (ERP) and EEG in 60 Control individuals (30 males and 30 females).	Procedure: Auditory and Visual Event-related Potentials and EEG; Specifically, through up to three standardized sessions (i.e., annual [every 10-14 months]), we will assess AEP and VEP. ERP recordings will also provide data for specific rhythms/band (gamma and alpha) pattern analyses as secondary measures as well as technical control data, which will help to exclude those with co-current seizures.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Auditory Event-related potentials	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.	3 years
Visual Event-related potentials	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.	3 years
EEG	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 2-10 and 25-70Hz, respectively, and a FFT performed on the filtered data. Spike location, frequency, and activity (change with sleep, eye closure, stimulation) will be calculated.	3 years

Collaborators and Investigators

• Sponsor: University of Alabama at Birmingham
• Collaborators: University of Colorado, Denver; Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD); Children's Hospital of Philadelphia; University of South Florida; Boston Children's Hospital; Vanderbilt University; International Rett Syndrome Foundation Rettsyndrome.org
• Investigators: Principal Investigator: Eric Marsh, MD, PhD, Children's Hospital of Philadelphia

Publications and helpful links

General Publications

• Gandal MJ, Edgar JC, Ehrlichman RS, Mehta M, Roberts TP, Siegel SJ. Validating gamma oscillations and delayed auditory responses as translational biomarkers of autism. Biol Psychiatry. 2010 Dec 15;68(12):1100-6. doi: 10.1016/j.biopsych.2010.09.031.
• Peters SU, Gordon RL, Key AP. Induced gamma oscillations differentiate familiar and novel voices in children with MECP2 duplication and Rett syndromes. J Child Neurol. 2015 Feb;30(2):145-52. doi: 10.1177/0883073814530503. Epub 2014 Apr 27.
• Deregnier RA, Nelson CA, Thomas KM, Wewerka S, Georgieff MK. Neurophysiologic evaluation of auditory recognition memory in healthy newborn infants and infants of diabetic mothers. J Pediatr. 2000 Dec;137(6):777-84. doi: 10.1067/mpd.2000.109149.
• Rojas DC, Teale PD, Maharajh K, Kronberg E, Youngpeter K, Wilson LB, Wallace A, Hepburn S. Transient and steady-state auditory gamma-band responses in first-degree relatives of people with autism spectrum disorder. Mol Autism. 2011 Jul 5;2:11. doi: 10.1186/2040-2392-2-11.
• Liao W, Gandal MJ, Ehrlichman RS, Siegel SJ, Carlson GC. MeCP2+/- mouse model of RTT reproduces auditory phenotypes associated with Rett syndrome and replicate select EEG endophenotypes of autism spectrum disorder. Neurobiol Dis. 2012 Apr;46(1):88-92. doi: 10.1016/j.nbd.2011.12.048. Epub 2012 Jan 9.
• LeBlanc JJ, DeGregorio G, Centofante E, Vogel-Farley VK, Barnes K, Kaufmann WE, Fagiolini M, Nelson CA. Visual evoked potentials detect cortical processing deficits in Rett syndrome. Ann Neurol. 2015 Nov;78(5):775-86. doi: 10.1002/ana.24513. Epub 2015 Sep 18.
• Khwaja OS, Ho E, Barnes KV, O'Leary HM, Pereira LM, Finkelstein Y, Nelson CA 3rd, Vogel-Farley V, DeGregorio G, Holm IA, Khatwa U, Kapur K, Alexander ME, Finnegan DM, Cantwell NG, Walco AC, Rappaport L, Gregas M, Fichorova RN, Shannon MW, Sur M, Kaufmann WE. Safety, pharmacokinetics, and preliminary assessment of efficacy of mecasermin (recombinant human IGF-1) for the treatment of Rett syndrome. Proc Natl Acad Sci U S A. 2014 Mar 25;111(12):4596-601. doi: 10.1073/pnas.1311141111. Epub 2014 Mar 12.
• Larimore JL, Chapleau CA, Kudo S, Theibert A, Percy AK, Pozzo-Miller L. Bdnf overexpression in hippocampal neurons prevents dendritic atrophy caused by Rett-associated MECP2 mutations. Neurobiol Dis. 2009 May;34(2):199-211. doi: 10.1016/j.nbd.2008.12.011. Epub 2009 Jan 3.
• Blackman MP, Djukic B, Nelson SB, Turrigiano GG. A critical and cell-autonomous role for MeCP2 in synaptic scaling up. J Neurosci. 2012 Sep 26;32(39):13529-36. doi: 10.1523/JNEUROSCI.3077-12.2012.
• Stuss DP, Boyd JD, Levin DB, Delaney KR. MeCP2 mutation results in compartment-specific reductions in dendritic branching and spine density in layer 5 motor cortical neurons of YFP-H mice. PLoS One. 2012;7(3):e31896. doi: 10.1371/journal.pone.0031896. Epub 2012 Mar 7.
• Kaufmann WE, Johnston MV, Blue ME. MeCP2 expression and function during brain development: implications for Rett syndrome's pathogenesis and clinical evolution. Brain Dev. 2005 Nov;27 Suppl 1:S77-S87. doi: 10.1016/j.braindev.2004.10.008. Epub 2005 Sep 22.
• Na ES, Nelson ED, Adachi M, Autry AE, Mahgoub MA, Kavalali ET, Monteggia LM. A mouse model for MeCP2 duplication syndrome: MeCP2 overexpression impairs learning and memory and synaptic transmission. J Neurosci. 2012 Feb 29;32(9):3109-17. doi: 10.1523/JNEUROSCI.6000-11.2012.
• Wang IT, Allen M, Goffin D, Zhu X, Fairless AH, Brodkin ES, Siegel SJ, Marsh ED, Blendy JA, Zhou Z. Loss of CDKL5 disrupts kinome profile and event-related potentials leading to autistic-like phenotypes in mice. Proc Natl Acad Sci U S A. 2012 Dec 26;109(52):21516-21. doi: 10.1073/pnas.1216988110. Epub 2012 Dec 10.
• Na ES, Nelson ED, Kavalali ET, Monteggia LM. The impact of MeCP2 loss- or gain-of-function on synaptic plasticity. Neuropsychopharmacology. 2013 Jan;38(1):212-9. doi: 10.1038/npp.2012.116. Epub 2012 Jul 11.
• Chao HT, Zoghbi HY, Rosenmund C. MeCP2 controls excitatory synaptic strength by regulating glutamatergic synapse number. Neuron. 2007 Oct 4;56(1):58-65. doi: 10.1016/j.neuron.2007.08.018.
• 17. Wechsler DL (1991). The Wechsler Intelligence Scale for Children -III. San Antonio: The Psychological Corporation.
• 18. Reich MJ, Shayka T, Taibleson C (1991) The Diagnostic Interview for Children and Adolescents-Revised. St Louis: Washington University Press.
• Neul JL, Fang P, Barrish J, Lane J, Caeg EB, Smith EO, Zoghbi H, Percy A, Glaze DG. Specific mutations in methyl-CpG-binding protein 2 confer different severity in Rett syndrome. Neurology. 2008 Apr 15;70(16):1313-21. doi: 10.1212/01.wnl.0000291011.54508.aa. Epub 2008 Mar 12.
• Bebbington A, Anderson A, Ravine D, Fyfe S, Pineda M, de Klerk N, Ben-Zeev B, Yatawara N, Percy A, Kaufmann WE, Leonard H. Investigating genotype-phenotype relationships in Rett syndrome using an international data set. Neurology. 2008 Mar 11;70(11):868-75. doi: 10.1212/01.wnl.0000304752.50773.ec.
• Cuddapah VA, Pillai RB, Shekar KV, Lane JB, Motil KJ, Skinner SA, Tarquinio DC, Glaze DG, McGwin G, Kaufmann WE, Percy AK, Neul JL, Olsen ML. Methyl-CpG-binding protein 2 (MECP2) mutation type is associated with disease severity in Rett syndrome. J Med Genet. 2014 Mar;51(3):152-8. doi: 10.1136/jmedgenet-2013-102113. Epub 2014 Jan 7.
• Goffin D, Allen M, Zhang L, Amorim M, Wang IT, Reyes AR, Mercado-Berton A, Ong C, Cohen S, Hu L, Blendy JA, Carlson GC, Siegel SJ, Greenberg ME, Zhou Z. Rett syndrome mutation MeCP2 T158A disrupts DNA binding, protein stability and ERP responses. Nat Neurosci. 2011 Nov 27;15(2):274-83. doi: 10.1038/nn.2997.
• McLeod F, Ganley R, Williams L, Selfridge J, Bird A, Cobb SR. Reduced seizure threshold and altered network oscillatory properties in a mouse model of Rett syndrome. Neuroscience. 2013 Feb 12;231:195-205. doi: 10.1016/j.neuroscience.2012.11.058. Epub 2012 Dec 10.
• Pillion JP, Naidu S. Auditory brainstem response findings in Rett syndrome: stability over time. J Pediatr. 2000 Sep;137(3):393-6. doi: 10.1067/mpd.2000.107952.
• D'Cruz JA, Wu C, Zahid T, El-Hayek Y, Zhang L, Eubanks JH. Alterations of cortical and hippocampal EEG activity in MeCP2-deficient mice. Neurobiol Dis. 2010 Apr;38(1):8-16. doi: 10.1016/j.nbd.2009.12.018. Epub 2010 Jan 4.
• Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004 Mar 15;134(1):9-21. doi: 10.1016/j.jneumeth.2003.10.009.
• Brown MW 3rd, Porter BE, Dlugos DJ, Keating J, Gardner AB, Storm PB Jr, Marsh ED. Comparison of novel computer detectors and human performance for spike detection in intracranial EEG. Clin Neurophysiol. 2007 Aug;118(8):1744-52. doi: 10.1016/j.clinph.2007.04.017. Epub 2007 Jun 1.

Study record dates

Study Major Dates

• Study Start (Actual): January 2, 2017
• Primary Completion (Actual): July 31, 2021
• Study Completion (Actual): July 31, 2021

Study Registration Dates

• First Submitted: March 1, 2017
• First Submitted That Met QC Criteria: March 6, 2017
• First Posted (Actual): March 10, 2017

Study Record Updates

• Last Update Posted (Actual): August 5, 2021
• Last Update Submitted That Met QC Criteria: August 3, 2021
• Last Verified: August 1, 2021

More Information

Terms related to this study

• Keywords: Auditory ERP, Visual ERP, EEG
• Additional Relevant MeSH Terms: Pathologic Processes; Nervous System Diseases; Neurologic Manifestations; Neurobehavioral Manifestations; Disease Attributes; Disease; Genetic Diseases, Inborn; Genetic Diseases, X-Linked; Mental Retardation, X-Linked; Intellectual Disability; Heredodegenerative Disorders, Nervous System; Syndrome; Rett Syndrome; Rare Diseases
• Other Study ID Numbers: RDCRN 5212

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: Yes
• IPD Plan Description: Data will be submitted to NDAR/dbGAP.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No