EEG as a translational biomarker and outcome measure in fragile X syndrome

Clinically-probed mechanisms of action in Fragile-X Syndrome fail to normalize translational EEG phenotypes in Fmr1 knockout mice

Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by Fragile X Messenger Ribonucleoprotein (FMRP) deficiency. Electroencephalogram (EEG) changes in FXS include alterations of oscillatory activity and responses to sensory stimuli, some of which have been back-translated into rodent models by knocking-out the Fragile X messenger ribonucleoprotein 1 gene (Fmr1-KO). However, the validity of these EEG phenotypes as objective biomarkers requires further investigation. Potential pharmacotherapies such as mGluR5 inhibitors (e.g. CTEP; 2-chloro-4-((2,5-dimethyl-1-(4-(trifluoromethoxy)phenyl)-1H-imidazol-4-yl)ethynyl)pyridine), GABABR agonists (e.g. arbaclofen) and δ-containing GABAAR agonists (e.g. gaboxadol) have not translated into clinical success despite rescuing many phenotypes in the Fmr1-KO model. Yet none of these treatments have been assessed on EEG phenotypes in the Fmr1-KO model. Therefore, we set out to discover new EEG phenotypes in Fmr1-KO mice, using "task-free" and auditory-evoked (AEPs) and visually-evoked potential (VEP) paradigms, and probe their modulation by CTEP, arbaclofen and gaboxadol, using within-subjects designs. First, we report Fmr1-KO-associated EEG abnormalities that closely resemble those observed in FXS, including elevated gamma-band power, reduced alpha/beta-band coherence, increased AEPs and delayed VEPs. Secondly, we found that pharmacological treatment, at best, only partially normalized EEG phenotypes. CTEP restored alpha/beta-band coherence and AEP amplitudes but failed to normalize gamma power and VEP latencies. Conversely, arbaclofen reduced gamma power but did not restore coherence or AEP amplitudes and further delayed VEPs. Gaboxadol did not normalize any EEG phenotypes. We conclude that these compounds have limited ability to normalize these EEG phenotypes.

Validating brain activity measures as reliable indicators of individual diagnostic group and genetically mediated sub-group membership Fragile X Syndrome

Recent failures translating preclinical behavioral treatment effects to positive clinical trial results in humans with Fragile X Syndrome (FXS) support refocusing attention on biological pathways and associated measures, such as electroencephalography (EEG), with strong translational potential and small molecule target engagement. This study utilized guided machine learning to test promising translational EEG measures (resting power and auditory chirp oscillatory variables) in a large heterogeneous sample of individuals with FXS to identify best performing EEG variables for reliably separating individuals with FXS, and genetically-mediated subgroups within FXS, from typically developing controls. Best performing variables included resting relative frontal theta power, all combined posterior-head resting power bands, posterior peak alpha frequency (PAF), combined PAF across all measured regions, combined theta, alpha, and gamma power during the chirp, and all combined chirp oscillatory variables. Sub-group analyses for resting EEG best discriminated non-mosaic FXS males via frontal theta resting relative power (AUC = 0.8759), even with data reduced to a 20-channel clinical montage (AUC = 0.9062). In the chirp task, FXS females and non-mosaic males were nearly perfectly discriminated by combined theta, alpha, and gamma power (AUC = 0.9444) and a combination of all variables (AUC = 0.9610), respectively. Results support use of resting and auditory oscillatory tasks to reliably identify neural deficit in FXS, and to identify specific translational targets for genetically-mediated sub-groups, supporting potential points for stratification.

Adult Inception of Ketogenic Diet Therapy Increases Sleep during the Dark Cycle in C57BL/6J Wild Type and Fragile X Mice

Sleep problems are a significant phenotype in children with fragile X syndrome. Our prior work assessed sleep-wake cycles in Fmr1KO male mice and wild type (WT) littermate controls in response to ketogenic diet therapy where mice were treated from weaning (postnatal day 18) through study completion (5-6 months of age). A potentially confounding issue with commencing treatment during an active period of growth is the significant reduction in weight gain in response to the ketogenic diet. The aim here was to employ sleep electroencephalography (EEG) to assess sleep-wake cycles in mice in response to the Fmr1 genotype and a ketogenic diet, with treatment starting at postnatal day 95. EEG results were compared with prior sleep outcomes to determine if the later intervention was efficacious, as well as with published rest-activity patterns to determine if actigraphy is a viable surrogate for sleep EEG. The data replicated findings that Fmr1KO mice exhibit sleep-wake patterns similar to wild type littermates during the dark cycle when maintained on a control purified-ingredient diet but revealed a genotype-specific difference during hours 4-6 of the light cycle of the increased wake (decreased sleep and NREM) state in Fmr1KO mice. Treatment with a high-fat, low-carbohydrate ketogenic diet increased the percentage of NREM sleep in both wild type and Fmr1KO mice during the dark cycle. Differences in sleep microstructure (length of wake bouts) supported the altered sleep states in response to ketogenic diet. Commencing ketogenic diet treatment in adulthood resulted in a 15% (WT) and 8.6% (Fmr1KO) decrease in body weight after 28 days of treatment, but not the severe reduction in body weight associated with starting treatment at weaning. We conclude that the lack of evidence for improved sleep during the light cycle (mouse sleep time) in Fmr1KO mice in response to ketogenic diet therapy in two studies suggests that ketogenic diet may not be beneficial in treating sleep problems associated with fragile X and that actigraphy is not a reliable surrogate for sleep EEG in mice.

Phenotypic analysis of multielectrode array EEG biomarkers in developing and adult male Fmr1 KO mice

Fragile X Syndrome (FXS) is a leading known genetic cause of intellectual disability with symptoms that include increased anxiety and social and sensory processing deficits. Recent electroencephalographic (EEG) studies in humans with FXS have identified neural oscillation deficits that include increased resting state gamma power, increased amplitude of auditory evoked potentials, and reduced phase locking of sound-evoked gamma oscillations. Similar EEG phenotypes are present in mouse models of FXS, but very little is known about the development of such abnormal responses. In the current study, we employed a 30-channel mouse multielectrode array (MEA) system to record and analyze resting and stimulus-evoked EEG signals in male P21 and P91 WT and Fmr1 KO mice. This led to several novel findings. First, P91, but not P21, Fmr1 KO mice have significantly increased resting EEG power in the low- and high-gamma frequency bands. Second, both P21 and P91 Fmr1 KO mice have markedly attenuated inter-trial phase coherence (ITPC) to spectrotemporally dynamic auditory stimuli as well as to 40 Hz and 80 Hz auditory steady-state response (ASSR) stimuli. This suggests abnormal temporal processing from early development that may lead to abnormal speech and language function in FXS. Third, we found hemispheric asymmetry of fast temporal processing in the mouse auditory cortex in WT but not Fmr1 KO mice. Together, these findings define a set of EEG phenotypes in young and adult mice that can serve as translational targets for genetic and pharmacological manipulation in phenotypic rescue studies.

Rodents' visual gamma as a biomarker of pathological neural conditions

Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.

Validating brain activity measures as reliable indicators of individual diagnostic group and genetically mediated sub-group membership Fragile X Syndrome

Recent failures translating preclinical behavioral treatment effects to positive clinical trial results in humans with Fragile X Syndrome (FXS) support refocusing attention on biological pathways and associated measures, such as electroencephalography (EEG), with strong translational potential and small molecule target engagement. This study utilized guided machine learning to test promising translational EEG measures (resting power and auditory chirp oscillatory variables) in a large heterogeneous sample of individuals with FXS to identify best performing EEG variables for reliably separating individuals with FXS, and genetically-mediated subgroups within FXS, from typically developing controls. Best performing variables included resting relative frontal theta power, all combined whole-head resting power bands, posterior peak alpha frequency (PAF), combined PAF across all measured regions, combined theta, alpha, and gamma power during the chirp, and all combined chirp oscillatory variables. Sub-group analyses best discriminated non-mosaic FXS males via whole-head resting relative power (AUC = .9250), even with data reduced to a 20-channel clinical montage. FXS females were nearly perfectly discriminated by combined theta, alpha, and gamma power during the chirp (AUC = .9522). Results support use of resting and auditory oscillatory tasks to reliably identify neural deficit in FXS, and to identify specific translational targets for genetically-mediated sub-groups, supporting potential points for stratification.

Rescue of sharp wave-ripples and prevention of network hyperexcitability in the ventral but not the dorsal hippocampus of a rat model of fragile X syndrome

Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder characterized by intellectual disability and is related to autism. FXS is caused by mutations of the fragile X messenger ribonucleoprotein 1 gene (Fmr1) and is associated with alterations in neuronal network excitability in several brain areas including hippocampus. The loss of fragile X protein affects brain oscillations, however, the effects of FXS on hippocampal sharp wave-ripples (SWRs), an endogenous hippocampal pattern contributing to memory consolidation have not been sufficiently clarified. In addition, it is still not known whether dorsal and ventral hippocampus are similarly affected by FXS. We used a Fmr1 knock-out (KO) rat model of FXS and electrophysiological recordings from the CA1 area of adult rat hippocampal slices to assess spontaneous and evoked neural activity. We find that SWRs and associated multiunit activity are affected in the dorsal but not the ventral KO hippocampus, while complex spike bursts remain normal in both segments of the KO hippocampus. Local network excitability increases in the dorsal KO hippocampus. Furthermore, specifically in the ventral hippocampus of KO rats we found an increased effectiveness of inhibition in suppressing excitation and an upregulation of α1GABAA receptor subtype. These changes in the ventral KO hippocampus are accompanied by a striking reduction in its susceptibility to induced epileptiform activity. We propose that the neuronal network specifically in the ventral segment of the hippocampus is reorganized in adult Fmr1-KO rats by means of balanced changes between excitability and inhibition to ensure normal generation of SWRs and preventing at the same time derailment of the neural activity toward hyperexcitability.

Association of Intrinsic Functional Brain Network and Longitudinal Development of Cognitive Behavioral Symptoms in Young Girls With Fragile X Syndrome

BACKGROUND

Fragile X syndrome (FXS) is an X chromosome-linked genetic disorder characterized by increased risk for behavioral, social, and neurocognitive deficits. Because males express a more severe phenotype than females, research has focused largely on identifying neural abnormalities in all-male or both-sex populations with FXS. Therefore, very little is known about the neural alterations that contribute to cognitive behavioral symptoms in females with FXS. This cross-sectional study aimed to elucidate the large-scale resting-state brain networks associated with the multidomain cognitive behavioral phenotype in girls with FXS.

METHODS

We recruited 38 girls with full-mutation FXS (11.58 ± 3.15 years) and 32 girls without FXS (11.66 ± 2.27 years). Both groups were matched on age, verbal IQ, and multidomain cognitive behavioral symptoms. Resting-state functional magnetic resonance imaging data were collected.

RESULTS

Compared with the control group, girls with FXS showed significantly greater resting-state functional connectivity of the default mode network, lower nodal strength at the right middle temporal gyrus, stronger nodal strength at the left caudate, and higher global efficiency of the default mode network. These aberrant brain network characteristics map directly onto the cognitive behavioral symptoms commonly observed in girls with FXS. An exploratory analysis suggested that brain network patterns at a prior time point (time 1) were predictive of the longitudinal development of participants' multidomain cognitive behavioral symptoms.

CONCLUSIONS

These findings represent the first examination of large-scale brain network alterations in a large sample of girls with FXS, expanding our knowledge of potential neural mechanisms underlying the development of cognitive behavioral symptoms in girls with FXS.

Ketogenic Diet Affects Sleep Architecture in C57BL/6J Wild Type and Fragile X Mice

Nearly half of children with fragile X syndrome experience sleep problems including trouble falling asleep and frequent nighttime awakenings. The goals here were to assess sleep-wake cycles in mice in response to Fmr1 genotype and a dietary intervention that reduces hyperactivity. Electroencephalography (EEG) results were compared with published rest-activity patterns to determine if actigraphy is a viable surrogate for sleep EEG. Specifically, sleep-wake patterns in adult wild type and Fmr1KO littermate mice were recorded after EEG electrode implantation and the recordings manually scored for vigilance states. The data indicated that Fmr1KO mice exhibited sleep-wake patterns similar to wild type littermates when maintained on a control purified ingredient diet. Treatment with a high-fat, low-carbohydrate ketogenic diet increased the percentage of non-rapid eye movement (NREM) sleep in both wild type and Fmr1KO mice during the dark cycle, which corresponded to decreased activity levels. Treatment with a ketogenic diet flattened diurnal sleep periodicity in both wild type and Fmr1KO mice. Differences in several sleep microstructure outcomes (number and length of sleep and wake bouts) supported the altered sleep states in response to a ketogenic diet and were correlated with altered rest-activity cycles. While actigraphy may be a less expensive, reduced labor surrogate for sleep EEG during the dark cycle, daytime resting in mice did not correlate with EEG sleep states.

Electroencephalographic (EEG) Biomarkers in Genetic Neurodevelopmental Disorders

Collectively, neurodevelopmental disorders are highly prevalent, but more than a third of neurodevelopmental disorders have an identifiable genetic etiology, each of which is individually rare. The genes associated with neurodevelopmental disorders are often involved in early brain development, neuronal signaling, or synaptic plasticity. Novel treatments for many genetic neurodevelopmental disorders are being developed, but disease-relevant clinical outcome assessments and biomarkers are limited. Electroencephalography (EEG) is a promising noninvasive potential biomarker of brain function. It has been used extensively in epileptic disorders, but its application in neurodevelopmental disorders needs further investigation. In this review, we explore the use of EEG in 3 of the most prevalent genetic neurodevelopmental disorders-Angelman syndrome, Rett syndrome, and fragile X syndrome. Quantitative analyses of EEGs, such as power spectral analysis or measures of connectivity, can quantify EEG signatures seen on qualitative review and potentially correlate with phenotypes. In both Angelman syndrome and Rett syndrome, increased delta power on spectral analysis has correlated with clinical markers of disease severity including developmental disability and seizure burden, whereas spectral power analysis on EEG in fragile X syndrome tends to demonstrate abnormalities in gamma power. Further studies are needed to establish reliable relationships between quantitative EEG biomarkers and clinical phenotypes in rare genetic neurodevelopmental disorders.

Sex-Related Changes in the Clinical, Genetic, Electrophysiological, Connectivity, and Molecular Presentations of ASD: A Comparison between Human and Animal Models of ASD with Reference to Our Data

The etiology of autism spectrum disorder (ASD) is genetic, environmental, and epigenetic. In addition to sex differences in the prevalence of ASD, which is 3-4 times more common in males, there are also distinct clinical, molecular, electrophysiological, and pathophysiological differences between sexes. In human, males with ASD have more externalizing problems (i.e., attention-deficit hyperactivity disorder), more severe communication and social problems, as well as repetitive movements. Females with ASD generally exhibit fewer severe communication problems, less repetitive and stereotyped behavior, but more internalizing problems, such as depression and anxiety. Females need a higher load of genetic changes related to ASD compared to males. There are also sex differences in brain structure, connectivity, and electrophysiology. Genetic or non-genetic experimental animal models of ASD-like behavior, when studied for sex differences, showed some neurobehavioral and electrophysiological differences between male and female animals depending on the specific model. We previously carried out studies on behavioral and molecular differences between male and female mice treated with valproic acid, either prenatally or early postnatally, that exhibited ASD-like behavior and found distinct differences between the sexes, the female mice performing better on tests measuring social interaction and undergoing changes in the expression of more genes in the brain compared to males. Interestingly, co-administration of S-adenosylmethionine alleviated the ASD-like behavioral symptoms and the gene-expression changes to the same extent in both sexes. The mechanisms underlying the sex differences are not yet fully understood.

Neural response to repeated auditory stimuli and its association with early language ability in male children with Fragile X syndrome

Background

Fragile X syndrome (FXS) is the most prevalent form of inherited intellectual disability and is commonly associated with autism. Previous studies have linked the structural and functional alterations in FXS with impaired sensory processing and sensory hypersensitivity, which may hinder the early development of cognitive functions such as language comprehension. In this study, we compared the P1 response of the auditory evoked potential and its habituation to repeated auditory stimuli in male children (2-7 years old) with and without FXS, and examined their association with clinical measures in these two groups.

Methods

We collected high-density electroencephalography (EEG) data in an auditory oddball paradigm from 12 male children with FXS and 11 age- and sex-matched typically developing (TD) children. After standardized EEG pre-processing, we conducted a spatial principal component (PC) analysis and identified two major PCs-a frontal PC and a temporal PC. Within each PC, we compared the P1 amplitude and inter-trial phase coherence (ITPC) between the two groups, and performed a series of linear regression analysis to study the association between these EEG measures and several clinical measures, including assessment scores for language abilities, non-verbal skills, and sensory hypersensitivity.

Results

At the temporal PC, both early and late standard stimuli evoked a larger P1 response in FXS compared to TD participants. For temporal ITPC, the TD group showed greater habituation than the FXS group. However, neither group showed significant habituation of the frontal or temporal P1 response. Despite lack of habituation, exploratory analysis of brain-behavior associations observed that within the FXS group, reduced frontal P1 response to late standard stimuli, and increased frontal P1 habituation were both associated with better language scores.

Conclusion

We identified P1 amplitude and ITPC in the temporal region as a contrasting EEG phenotype between the FXS and the TD groups. However, only frontal P1 response and habituation were associated with language measures. Larger longitudinal studies are required to determine whether these EEG measures could be used as biomarkers for language development in patients with FXS.