Evoked Potentials and EEG Analysis in Rett Syndrome and Related Developmental Encephalopathies: Towards a Biomarker for Translational Research

Saby, Joni N.; Peters, Sarika U.; Roberts, Timothy P. L.; Nelson, Charles A.; Marsh, Eric D.

doi:10.3389/fnint.2020.00030

Cited by 23 publications

(24 citation statements)

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“…These differential results might be caused by the differences in animal gender, recording location or animal strain background between the studies. Thus far, information about parallel studies on people with RTT is lacking ( Saby et al, 2020 ). Even though strong negative correlations between high gamma power and phenotypic severity were obtained, further evaluations looking at longitudinal progression in a variety of mouse models of RTT are needed to determine whether this feature could serve as a generalizable and translatable biomarker to guide preclinical or clinical studies.…”

Section: Discussionmentioning

confidence: 99%

Detection of neurophysiological features in female R255X MeCP2 mutation mice

Dong

Erickson

Lee

et al. 2020

Neurobiology of Disease

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Rett syndrome (RTT) is a severe neurodevelopmental disorder (NDD) that is nearly always caused by loss of function mutations in Methyl-CpG-binding Protein 2 ( MECP2 ) and shares many clinical features with other NDD. Genetic restoration of Mecp2 in symptomatic mice lacking MeCP2 expression can reverse symptoms, providing hope that disease modifying therapies can be identified for RTT. Effective and rapid clinical trial completion relies on well-defined clinical outcome measures and robust biomarkers of treatment responses. Studies on other NDD have found evidence of differences in neurophysiological measures that correlate with disease severity. However, currently there are no well-validated biomarkers in RTT to predict disease prognosis or treatment responses. To address this, we characterized neurophysiological features in a mouse model of RTT containing a knock-in nonsense mutation (p.R255X) in the Mecp2 locus. We found a variety of changes in heterozygous female Mecp2 R255X/X mice including age-related changes in sleep/wake architecture, alterations in baseline EEG power, increased incidence of spontaneous epileptiform discharges, and changes in auditory evoked potentials. Furthermore, we identified association of some neurophysiological features with disease severity. These findings provide a set of potential non-invasive and translatable biomarkers that can be utilized in preclinical therapy trials in animal models of RTT and eventually within the context of clinical trials.

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Section: Discussionmentioning

confidence: 99%

Detection of neurophysiological features in female R255X MeCP2 mutation mice

Dong

Erickson

Lee

et al. 2020

Neurobiology of Disease

View full text Add to dashboard Cite

show abstract

“…Recognition of the potential for EEG measures as biomarkers in RTT has grown recently [ 20 ] in light of the underlying disease physiology. Notably, a recent trial of IGF1 demonstrated alterations in spectral power measures within specific EEG bands at specific locations [ 22 ], particularly in frontal regions.…”

Section: Discussionmentioning

confidence: 99%

“…This procedure may have relaxed the patients, reducing anxiety-related biomarkers such as frontal asymmetry. These ambiguities further underline the importance of proper standardisation of biomarker methodologies and validation in large, multisite studies, as emphasised in Saby et al’s recent review [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

“…Further, network-based approaches have demonstrated promise in the development of diagnostic [ 18 ] and prognostic [ 19 ] biomarkers of neuropsychiatric disease. The potential utility of EEG-based measures in RTT and related disorders has recently gained attention [ 20 ], including evidence of abnormal spectral power profiles relative to typically developing controls [ 21 ] and deterioration in measures over time [ 22 ]. It has been demonstrated that RTT subtypes are associated with specific network profiles [ 23 ], suggesting that network-based approaches may facilitate the identification of further biomarkers for disease characterization and for improved design of intervention studies.…”

Section: Introductionmentioning

confidence: 99%

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Functional Network Mapping Reveals State-Dependent Response to IGF1 Treatment in Rett Syndrome

et al. 2020

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Rett Syndrome (RTT) is a neurodevelopmental disorder associated with mutations in the gene MeCP2, which is involved in the development and function of cortical networks. The clinical presentation of RTT is generally severe and includes developmental regression and marked neurologic impairment. Insulin-Like growth factor 1 (IGF1) ameliorates RTT-relevant phenotypes in animal models and improves some clinical manifestations in early human trials. However, it remains unclear whether IGF1 treatment has an impact on cortical electrophysiology in line with MeCP2’s role in network formation, and whether these electrophysiological changes are related to clinical response. We performed clinical assessments and resting-state electroencephalogram (EEG) recordings in eighteen patients with classic RTT, nine of whom were treated with IGF1. Among the treated patients, we distinguished those who showed improvements after treatment (responders) from those who did not show any changes (nonresponders). Clinical assessments were carried out for all individuals with RTT at baseline and 12 months after treatment. Network measures were derived using statistical modelling techniques based on interelectrode coherence measures. We found significant interaction between treatment groups and timepoints, indicating an effect of IGF1 on network measures. We also found a significant effect of responder status and timepoint, indicating that these changes in network measures are associated with clinical response to treatment. Further, we found baseline variability in network characteristics, and a machine learning model using these measures applied to pretreatment data predicted treatment response with 100% accuracy (100% sensitivity and 100% specificity) in this small patient group. These results highlight the importance of network pathology in RTT, as well as providing preliminary evidence for the potential of network measures as tools for the characterisation of disease subtypes and as biomarkers for clinical trials.

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“…Postdevelopmental loss of CDKL5 results in disruption of lowfrequency event-related neuronal oscillations. Auditory or visual event-related potentials (ERPs) have been increasingly leveraged as biomarkers for sensory information-processing deficits in both patients and animal models of various neurodevelopmental disorders (28). We previously reported that germline loss of CDKL5 required for the maintenance of neurological function after development.…”

Section: Introductionmentioning

confidence: 99%