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Published in: Journal of Neurodevelopmental Disorders 1/2019

Open Access 01-12-2019 | Rett Syndrome | Research

Electroencephalographic spectral power as a marker of cortical function and disease severity in girls with Rett syndrome

Authors: Katherine J. Roche, Jocelyn J. LeBlanc, April R. Levin, Heather M. O’Leary, Lauren M. Baczewski, Charles A. Nelson

Published in: Journal of Neurodevelopmental Disorders | Issue 1/2019

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Abstract

Background

Rett syndrome is a neurodevelopmental disorder caused by a mutation in the X-linked MECP2 gene. Individuals with Rett syndrome typically develop normally until around 18 months of age before undergoing a developmental regression, and the disorder can lead to cognitive, motor, sensory, and autonomic dysfunction. Understanding the mechanism of developmental regression represents a unique challenge when viewed through a neuroscience lens. Are circuits that were previously established erased, and are new ones built to supplant old ones? One way to examine circuit-level changes is with the use of electroencephalography (EEG). Previous studies of the EEG in individuals with Rett syndrome have focused on morphological characteristics, but few have explored spectral power, including power as an index of brain function or disease severity. This study sought to determine if EEG power differs in girls with Rett syndrome and typically developing girls and among girls with Rett syndrome based on various clinical characteristics in order to better understand neural connectivity and cortical organization in individuals with this disorder.

Methods

Resting state EEG data were acquired from girls with Rett syndrome (n = 57) and typically developing children without Rett syndrome (n = 37). Clinical data were also collected for girls with Rett syndrome. EEG power across several brain regions in numerous frequency bands was then compared between girls with Rett syndrome and typically developing children and power in girls with Rett syndrome was compared based on these clinical measures. 1/ƒ slope was also compared between groups.

Results

Girls with Rett syndrome demonstrate significantly lower power in the middle frequency bands across multiple brain regions. Additionally, girls with Rett syndrome that are postregression demonstrate significantly higher power in the lower frequency delta and theta bands and a significantly more negative slope of the power spectrum. Increased power in these bands, as well as a more negative 1/ƒ slope, trended with lower cognitive assessment scores.

Conclusions

Increased power in lower frequency bands is consistent with previous studies demonstrating a “slowing” of the background EEG in Rett syndrome. This increase, particularly in the delta band, could represent abnormal cortical inhibition due to dysfunctional GABAergic signaling and could potentially be used as a marker of severity due to associations with more severe Rett syndrome phenotypes.
Literature
1.
go back to reference Amir RE, Van den Veyver IB, Wan M, et al. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nat Genet. 1999;23:185–8.CrossRef Amir RE, Van den Veyver IB, Wan M, et al. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2. Nat Genet. 1999;23:185–8.CrossRef
2.
go back to reference Rett A. On a unusual brain atrophy syndrome in hyperammonemia in childhood. Wien Med Wochenschr. 1966;116:723–6.PubMed Rett A. On a unusual brain atrophy syndrome in hyperammonemia in childhood. Wien Med Wochenschr. 1966;116:723–6.PubMed
3.
go back to reference Hagberg B, Witt-Engerström I. Rett syndrome: a suggested staging system for describing impairment profile with increasing age towards adolescence. Am J Med Genet. 1986;24:47–59.CrossRef Hagberg B, Witt-Engerström I. Rett syndrome: a suggested staging system for describing impairment profile with increasing age towards adolescence. Am J Med Genet. 1986;24:47–59.CrossRef
4.
go back to reference Neul JL, Kaufmann WE, Glaze DG, et al. Rett syndrome: revised diagnostic criteria and nomenclature. Ann Neurol. 2010;68:944–50.CrossRef Neul JL, Kaufmann WE, Glaze DG, et al. Rett syndrome: revised diagnostic criteria and nomenclature. Ann Neurol. 2010;68:944–50.CrossRef
5.
go back to reference Pohodich AE, Zoghbi HY. Rett syndrome: disruption of epigenetic control of postnatal neurological functions. Hum Mol Genet. 2015;24:R10–6.CrossRef Pohodich AE, Zoghbi HY. Rett syndrome: disruption of epigenetic control of postnatal neurological functions. Hum Mol Genet. 2015;24:R10–6.CrossRef
6.
go back to reference Dani VS, Chang Q, Maffei A, et al. Reduced cortical activity due to a shift in the balance between excitation and inhibition in a mouse model of Rett syndrome. Proc Natl Acad Sci U S A. 2005;102:12560–5.CrossRef Dani VS, Chang Q, Maffei A, et al. Reduced cortical activity due to a shift in the balance between excitation and inhibition in a mouse model of Rett syndrome. Proc Natl Acad Sci U S A. 2005;102:12560–5.CrossRef
7.
go back to reference Zhang W, Peterson M, Beyer B, et al. Loss of MeCP2 from forebrain excitatory neurons leads to cortical hyperexcitation and seizures. J Neurosci. 2014;34:2754–63.CrossRef Zhang W, Peterson M, Beyer B, et al. Loss of MeCP2 from forebrain excitatory neurons leads to cortical hyperexcitation and seizures. J Neurosci. 2014;34:2754–63.CrossRef
8.
go back to reference Zhou Z, Hong EJ, Cohen S, et al. Brain-specific phosphorylation of MeCP2 regulates activity-dependent Bdnf transcription, dendritic growth, and spine maturation. Neuron. 2006;52:255–69.CrossRef Zhou Z, Hong EJ, Cohen S, et al. Brain-specific phosphorylation of MeCP2 regulates activity-dependent Bdnf transcription, dendritic growth, and spine maturation. Neuron. 2006;52:255–69.CrossRef
9.
go back to reference McLeod F, Ganley R, Williams L, et al. Reduced seizure threshold and altered network oscillatory properties in a mouse model of Rett syndrome. Neuroscience. 2013;231:195–205.CrossRef McLeod F, Ganley R, Williams L, et al. Reduced seizure threshold and altered network oscillatory properties in a mouse model of Rett syndrome. Neuroscience. 2013;231:195–205.CrossRef
10.
go back to reference Kron M, Howell CJ, Adams IT, et al. Brain activity mapping in Mecp2 mutant mice reveals functional deficits in forebrain circuits, including key nodes in the default mode network, that are reversed with ketamine treatment. J Neurosci. 2012;32:13860–72.CrossRef Kron M, Howell CJ, Adams IT, et al. Brain activity mapping in Mecp2 mutant mice reveals functional deficits in forebrain circuits, including key nodes in the default mode network, that are reversed with ketamine treatment. J Neurosci. 2012;32:13860–72.CrossRef
11.
go back to reference Rubin DI. In: Rubin DI, Daube JR, editors. editors Clinical neurophysiology. 4th ed. New York: Oxford University Press; 2015. p. 2015. Rubin DI. In: Rubin DI, Daube JR, editors. editors Clinical neurophysiology. 4th ed. New York: Oxford University Press; 2015. p. 2015.
12.
go back to reference Schnitzler A, Gross J. Normal and pathological oscillatory communication in the brain. Nat Rev Neurosci. 2005;6:285–96.CrossRef Schnitzler A, Gross J. Normal and pathological oscillatory communication in the brain. Nat Rev Neurosci. 2005;6:285–96.CrossRef
13.
go back to reference Benz N, Hatz F, Bousleiman H, et al. Slowing of EEG background activity in Parkinson’s and Alzheimer’s disease with early cognitive dysfunction. Front Aging Neurosci. 2014;6:314.CrossRef Benz N, Hatz F, Bousleiman H, et al. Slowing of EEG background activity in Parkinson’s and Alzheimer’s disease with early cognitive dysfunction. Front Aging Neurosci. 2014;6:314.CrossRef
14.
go back to reference Tierney AL, Gabard-Durnam L, Vogel-Farley V, et al. Developmental trajectories of resting EEG power: an endophenotype of autism spectrum disorder. PLoS One. 2012;7:e39127.CrossRef Tierney AL, Gabard-Durnam L, Vogel-Farley V, et al. Developmental trajectories of resting EEG power: an endophenotype of autism spectrum disorder. PLoS One. 2012;7:e39127.CrossRef
15.
go back to reference Uhlhaas PJ. The role of oscillations and synchrony in cortical networks and their putative relevance for the pathophysiology of schizophrenia. Schizophr Bull. 2008;34:927–43.CrossRef Uhlhaas PJ. The role of oscillations and synchrony in cortical networks and their putative relevance for the pathophysiology of schizophrenia. Schizophr Bull. 2008;34:927–43.CrossRef
16.
go back to reference Glaze DG. Neurophysiology of Rett syndrome. J Child Neurol. 2005;20:740–6.CrossRef Glaze DG. Neurophysiology of Rett syndrome. J Child Neurol. 2005;20:740–6.CrossRef
17.
go back to reference O’Leary H, Kaufmann WE, Barnes KV, et al. Placebo-controlled crossover assessment of mecasermin for the treatment of Rett syndrome. Ann Clin Transl Neurol. 2018;5:323–32.CrossRef O’Leary H, Kaufmann WE, Barnes KV, et al. Placebo-controlled crossover assessment of mecasermin for the treatment of Rett syndrome. Ann Clin Transl Neurol. 2018;5:323–32.CrossRef
18.
go back to reference Khwaja OS, Ho E, Barnes KV, et al. 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. 2011;11:4596–601. Khwaja OS, Ho E, Barnes KV, et al. 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. 2011;11:4596–601.
19.
go back to reference Cuddapah VA, Pillai RB, Shekar KV, et al. Methyl-CpG-binding protein 2 (MECP2) mutation type is associated with disease severity in Rett syndrome. J Med Genet. 2014;51:152–8.CrossRef Cuddapah VA, Pillai RB, Shekar KV, et al. Methyl-CpG-binding protein 2 (MECP2) mutation type is associated with disease severity in Rett syndrome. J Med Genet. 2014;51:152–8.CrossRef
20.
go back to reference Barnes KV, Coughlin FR, O'Leary HM, et al. Anxiety-like behavior in Rett syndrome: characteristics and assessment by anxiety scales. J Neurodev Disord. 2015;7:30.CrossRef Barnes KV, Coughlin FR, O'Leary HM, et al. Anxiety-like behavior in Rett syndrome: characteristics and assessment by anxiety scales. J Neurodev Disord. 2015;7:30.CrossRef
21.
go back to reference Mullen EM. Mullen scales of early learning: AGS edition. Circle Pines: American Guidance Service; 1995. Mullen EM. Mullen scales of early learning: AGS edition. Circle Pines: American Guidance Service; 1995.
22.
go back to reference Zhan Y, Guo S, Kendrick KM, Feng J. Filtering noise for synchronised activity in multi-trial electrophysiology data using Wiener and Kalman filters. BioSystems. 2009;96:1–13.CrossRef Zhan Y, Guo S, Kendrick KM, Feng J. Filtering noise for synchronised activity in multi-trial electrophysiology data using Wiener and Kalman filters. BioSystems. 2009;96:1–13.CrossRef
23.
go back to reference Levin AR, Mendez Leal AS, Gabard-Durnam LJ, O’Leary HM. BEAPP: the batch electroecephalography automated processing platform. Front Neurosci. 2018;12:513.CrossRef Levin AR, Mendez Leal AS, Gabard-Durnam LJ, O’Leary HM. BEAPP: the batch electroecephalography automated processing platform. Front Neurosci. 2018;12:513.CrossRef
24.
go back to reference Cornilessen L, Kim SE, Purdon PL, Brown EN, Berde CB. Age-dependent encephalogram (EEG) patterns during sevoflurane general anesthesia in infants. Elife. 2015;4:e06513.CrossRef Cornilessen L, Kim SE, Purdon PL, Brown EN, Berde CB. Age-dependent encephalogram (EEG) patterns during sevoflurane general anesthesia in infants. Elife. 2015;4:e06513.CrossRef
25.
go back to reference Levin AR, Varcin KJ, O'Leary HM, et al. EEG power at 3 months in infants at high familial risk for autism. J Neurodev Disord. 2017;9:34.CrossRef Levin AR, Varcin KJ, O'Leary HM, et al. EEG power at 3 months in infants at high familial risk for autism. J Neurodev Disord. 2017;9:34.CrossRef
26.
go back to reference Voytek B, Kramer MA, Case J, Lepage KQ, et al. Age-related changes in 1/ƒ neural elecreophysiological noise. J Neurosci. 2015;35:12257–3265.CrossRef Voytek B, Kramer MA, Case J, Lepage KQ, et al. Age-related changes in 1/ƒ neural elecreophysiological noise. J Neurosci. 2015;35:12257–3265.CrossRef
27.
go back to reference Gabard-Durnam L, Tierney AL, Vogel-Farley V, et al. Alpha asymmetry in infants at risk for autism spectrum disorders. J Autism Dev Disord. 2015;45:473–80.CrossRef Gabard-Durnam L, Tierney AL, Vogel-Farley V, et al. Alpha asymmetry in infants at risk for autism spectrum disorders. J Autism Dev Disord. 2015;45:473–80.CrossRef
28.
go back to reference Niedermeyer E, Rett A, Renner H, et al. Rett syndrome and the electroencephalogram. Am J Med Genet. 1986;24:195–9.CrossRef Niedermeyer E, Rett A, Renner H, et al. Rett syndrome and the electroencephalogram. Am J Med Genet. 1986;24:195–9.CrossRef
29.
go back to reference Robertson R, Langill L, Wong PK, Ho HH. Rett syndrome: EEG presentation. Electroencephalogr Clin Neurophysiol. 1988;70:388–95.CrossRef Robertson R, Langill L, Wong PK, Ho HH. Rett syndrome: EEG presentation. Electroencephalogr Clin Neurophysiol. 1988;70:388–95.CrossRef
30.
go back to reference Garofalo EA, Drury I, Goldstein GW. EEG abnormalities aid diagnosis of Rett syndrome. Pediatr Neurol. 1988;4:350–3.CrossRef Garofalo EA, Drury I, Goldstein GW. EEG abnormalities aid diagnosis of Rett syndrome. Pediatr Neurol. 1988;4:350–3.CrossRef
31.
go back to reference LeBlanc JL, DeGregorio G, Centofante E, et al. Visual evoked potentials detect cortical processing deficits in Rett syndrome. Ann Neurol. 2015;78:775–86.CrossRef LeBlanc JL, DeGregorio G, Centofante E, et al. Visual evoked potentials detect cortical processing deficits in Rett syndrome. Ann Neurol. 2015;78:775–86.CrossRef
32.
go back to reference Foxe JJ, Burke KM, Andrade GN, et al. Automatic cortical representation of auditory pitch changes in Rett syndrome. J Neurodev Disord. 2016;8:34.CrossRef Foxe JJ, Burke KM, Andrade GN, et al. Automatic cortical representation of auditory pitch changes in Rett syndrome. J Neurodev Disord. 2016;8:34.CrossRef
33.
go back to reference Smith SM. EEG in neurological conditions other than epilepsy: when does it help, what does it add? J Neurol Neurosurg Psychiatry. 2005;76:ii8–ii12.CrossRef Smith SM. EEG in neurological conditions other than epilepsy: when does it help, what does it add? J Neurol Neurosurg Psychiatry. 2005;76:ii8–ii12.CrossRef
34.
go back to reference Kilavik E, Zaepffel M, Brovelli A, et al. The ups and downs of beta oscillations in sensorimotor cortex. Exp Neurol. 2013;245:15–26.CrossRef Kilavik E, Zaepffel M, Brovelli A, et al. The ups and downs of beta oscillations in sensorimotor cortex. Exp Neurol. 2013;245:15–26.CrossRef
35.
go back to reference Banerjee A, Rikhye RV, Breton-Provencher V, et al. Jointly reduced inhibition and excitation underlies circuit-wide changes in cortical processing in Rett syndrome. Proc Natl Acad Sci U S A. 2016;113:E7287–96.CrossRef Banerjee A, Rikhye RV, Breton-Provencher V, et al. Jointly reduced inhibition and excitation underlies circuit-wide changes in cortical processing in Rett syndrome. Proc Natl Acad Sci U S A. 2016;113:E7287–96.CrossRef
36.
go back to reference Sidorov MS, Deck GM, Dolatshahi M, et al. Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis. J Neurodev Disord. 2017;9:17.CrossRef Sidorov MS, Deck GM, Dolatshahi M, et al. Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis. J Neurodev Disord. 2017;9:17.CrossRef
37.
go back to reference Kim S, Chahrour M, Ben-Chacha S, Lim J. Ube3a/E6AP is involved in a subset of MeCP2 functions. Biochem Biophys Res Commun. 2013;437:67–73.CrossRef Kim S, Chahrour M, Ben-Chacha S, Lim J. Ube3a/E6AP is involved in a subset of MeCP2 functions. Biochem Biophys Res Commun. 2013;437:67–73.CrossRef
38.
go back to reference Marshall PJ, Bar-Haim Y, Fox NA. Development of the EEG from 5 months to 4 years of age. Clin Neurophysiol. 2002;113:1199–208.CrossRef Marshall PJ, Bar-Haim Y, Fox NA. Development of the EEG from 5 months to 4 years of age. Clin Neurophysiol. 2002;113:1199–208.CrossRef
39.
go back to reference Vuga M, Fox NA, Cohn JF, et al. Long-term stability of electroencephalographic asymmetry and power in 3 to 9 year old children. Int J Psychophsiol. 2008;67:70–7.CrossRef Vuga M, Fox NA, Cohn JF, et al. Long-term stability of electroencephalographic asymmetry and power in 3 to 9 year old children. Int J Psychophsiol. 2008;67:70–7.CrossRef
40.
go back to reference Wang J, Barstein J, Ethridge LE, et al. Resting state EEG abnormalities in autism spectrum disorders. J Neurodev Disord. 2013;5:24.CrossRef Wang J, Barstein J, Ethridge LE, et al. Resting state EEG abnormalities in autism spectrum disorders. J Neurodev Disord. 2013;5:24.CrossRef
41.
go back to reference Bader GG, Witt-Enderstrom I, Hagberg B. Neurophysiological findings in the Rett syndrome, I: EMG, conduction velocity, EEG and somatosensory-evoked potential studies. Brain and Development. 1989;11:102–9.CrossRef Bader GG, Witt-Enderstrom I, Hagberg B. Neurophysiological findings in the Rett syndrome, I: EMG, conduction velocity, EEG and somatosensory-evoked potential studies. Brain and Development. 1989;11:102–9.CrossRef
42.
go back to reference Goffin D, Brodkin ES, Blendy JA, et al. Cellular origins of auditory event-related potential deficits in Rett syndrome. Nat Neurosci. 2014;17:804–6.CrossRef Goffin D, Brodkin ES, Blendy JA, et al. Cellular origins of auditory event-related potential deficits in Rett syndrome. Nat Neurosci. 2014;17:804–6.CrossRef
43.
go back to reference Yamanouchi H, Kaga M, Arima M. Abnormal cortical excitability in Rett syndrome. Pediatr Neurol. 1993;9:202–6.CrossRef Yamanouchi H, Kaga M, Arima M. Abnormal cortical excitability in Rett syndrome. Pediatr Neurol. 1993;9:202–6.CrossRef
44.
go back to reference Yizhar O, Fenno LE, Prigge M, et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature. 2011;477:171–8.CrossRef Yizhar O, Fenno LE, Prigge M, et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature. 2011;477:171–8.CrossRef
45.
go back to reference Voytek B, Knight RT. Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease. Biol Psychiatry. 2016;77:1089–97.CrossRef Voytek B, Knight RT. Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease. Biol Psychiatry. 2016;77:1089–97.CrossRef
Metadata
Title
Electroencephalographic spectral power as a marker of cortical function and disease severity in girls with Rett syndrome
Authors
Katherine J. Roche
Jocelyn J. LeBlanc
April R. Levin
Heather M. O’Leary
Lauren M. Baczewski
Charles A. Nelson
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Journal of Neurodevelopmental Disorders / Issue 1/2019
Print ISSN: 1866-1947
Electronic ISSN: 1866-1955
DOI
https://doi.org/10.1186/s11689-019-9275-z

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