Electroencephalographic (EEG) Biomarkers in Genetic Neurodevelopmental Disorders

Alterations in aperiodic and periodic EEG activity in young children with Down syndrome

Down syndrome (DS) is the most common cause of intellectual disability, yet little is known about the neurobiological pathways leading to cognitive impairments. Electroencephalographic (EEG) measures are commonly used to study neurodevelopmental disorders, but few studies have focused on young children with DS. Here we assess resting state EEG data collected from toddlers/preschoolers with DS (n = 29, age 13-48 months old) and compare their aperiodic and periodic EEG features with both age-matched (n = 29) and developmental-matched (n = 58) comparison groups. DS participants exhibited significantly reduced aperiodic slope, increased periodic theta power, and decreased alpha peak amplitude. A majority of DS participants displayed a prominent peak in the theta range, whereas a theta peak was not present in age-matched participants. Overall, similar findings were also observed when comparing DS and developmental-matched groups, suggesting that EEG differences are not explained by delayed cognitive ability.

Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data

Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a revolutionary approach to investigate how the brain encodes information. By considering complex interactions among spatio-temporal features at the individual level, MVPA overcomes the limitations of univariate techniques, which often fail to account for the significant inter- and intra-individual neural variability. This is particularly relevant when studying clinical populations, and therefore MVPA of EEG data has recently started to be employed as a tool to study cognition in brain disorders. Here, we review the insights offered by this methodology in the study of anomalous patterns of neural activity in conditions such as autism, ADHD, schizophrenia, dyslexia, neurological and neurodegenerative disorders, within different cognitive domains (perception, attention, memory, consciousness). Despite potential drawbacks that should be attentively addressed, these studies reveal a peculiar sensitivity of MVPA in unveiling dysfunctional and compensatory neurocognitive dynamics of information processing, which often remain blind to traditional univariate approaches. Such higher sensitivity in characterizing individual neurocognitive profiles can provide unique opportunities to optimise assessment and promote personalised interventions.

Association of EEG characteristics with outcomes following pediatric ICU cardiac arrest: A secondary analysis of the ICU-RESUScitation trial

BACKGROUND AND OBJECTIVES

There are limited tools available following cardiac arrest to prognosticate neurologic outcomes. Prior retrospective and single center studies have demonstrated early EEG features are associated with neurologic outcome. This study aimed to evaluate the prognostic value of EEG for pediatric in-hospital cardiac arrest (IHCA) in a prospective, multicenter study.

METHODS

This cohort study is a secondary analysis of the ICU-Resuscitation trial, a multicenter randomized interventional trial conducted at 18 pediatric and pediatric cardiac ICUs in the United States. Patients who achieved return of circulation (ROC) and had post-ROC EEG monitoring were eligible for inclusion. Patients < 90 days old and those with pre-arrest Pediatric Cerebral Performance Category (PCPC) scores > 3 were excluded. EEG features of interest included EEG Background Category, and presence of focal abnormalities, sleep spindles, variability, reactivity, periodic and rhythmic patterns, and seizures. The primary outcome was survival to hospital discharge with favorable neurologic outcome. Associations between EEG features and outcomes were assessed with multivariable logistic regression. Prediction models with and without EEG Background Category were developed and receiver operator characteristic curves compared.

RESULTS

Of the 1129 patients with an index cardiac arrest who achieved ROC in the parent study, 261 had EEG within 24 h of ROC, of which 151 were evaluable. The cohort included 57% males with a median age of 1.1 years (IQR 0.4, 6.8). EEG features including EEG Background Category, sleep spindles, variability, and reactivity were associated with survival with favorable outcome and survival, (all p < 0.001). The addition of EEG Background Category to clinical models including age category, illness category, PRISM score, duration of CPR, first documented rhythm, highest early post-arrest arterial lactate improved the prediction accuracy achieving an AUROC of 0.84 (CI 0.77-0.92), compared to AUROC of 0.76 (CI 0.67-0.85) (p = 0.005) without EEG Background Category.

CONCLUSION

This multicenter study demonstrates the value of EEG, in the first 24 h following ROC, for predicting survival with favorable outcome after a pediatric IHCA.

Epilepsy, EEG and chromosomal rearrangements

Chromosomal abnormalities are associated with a broad spectrum of clinical manifestations, one of the more commonly observed of which is epilepsy. The frequency, severity, and type of epileptic seizures vary according to the macro- and microrearrangements present. Even within a single chromosomal anomaly, we most often deal with a phenotypic spectrum. The aim of the study was to look for chromosomal rearrangements with a characteristic electroencephalographic pattern. Only a few disorders have peculiar electroclinical abnormalities: 1p36, 4p16, 6q terminal or trisomy 12p, Angelman syndrome, inv dup 15, 15q13.3 deletions, ring 20, Down syndrome, or Xp11.22-11.23 duplication. We also reviewed studies on epileptic seizures and typical electroencephalographic patterns described in certain chromosomal rearrangements, focusing on the quest for potential electroclinical biomarkers. The comprehensive review concludes with clinical presentations of the most common micro and macro chromosomal rearrangements, such as 17q21.31 microdeletion, 6q terminal deletion, 15q inv dup syndrome, 2q24.4 deletion, Xp11.22-11.23 duplication, 15q13.3 microdeletion, 1p36 terminal deletion, 5q14.3 microdeletion, and Xq28 duplication. The papers reviewed did not identify any specific interictal electroencephalographic patterns that were unique and significant biomarkers for a given chromosomal microrearrangement. The types of seizures described varied, with both generalized and focal seizures of various morphologies being reported. Patients with chromosomal anomalies may also meet the criteria for specific epileptic syndromes such as Infantile Epilepsy Spasms Syndrome (IESS, West syndrome): 16p13.11, 15q13.3 and 17q21.31 microdeletions, 5q inv dup. syndrome; Dravet syndrome (2q24.4 deletion), Lennox-Gastaut syndrome (15q11 duplication. 1q13.3, 5q inv dup.); or Self-Limited Epilepsy with Autonomic Features (SeLEAS, Panayiotopoulos syndrome: terminal deletion of 6q.n), Self-Limited Epilepsy with Centrotemporal Spikes (SeLECT): fragile X syndrome. It is essential to better characterize groups of patients to more accurately define patterns of epilepsy and EEG abnormalities. This could lead to new treatment strategies. Future research is required to better understand epileptic syndromes and chromosomal rearrangements. PLAIN LANGUAGE SUMMARY: This paper presents EEG recording abnormalities in patients with various gene abnormalities that can cause epilepsy. The authors summarize these EEG variations based on a literature review to see if they occur frequently enough in other chromosomal abnormalities (in addition to those already known) to be a clue for further diagnosis.

Alterations in aperiodic and periodic EEG activity in young children with Down syndrome

Down syndrome is the most common cause of intellectual disability, yet little is known about the neurobiological pathways leading to cognitive impairments. Electroencephalographic (EEG) measures are commonly used to study neurodevelopmental disorders, but few studies have focused on young children with DS. Here we assess resting state EEG data collected from toddlers/preschoolers with DS (n=29, age 13-48 months old) and compare their aperiodic and periodic EEG features with both age-matched (n=29) and cognitive-matched (n=58) comparison groups. DS participants exhibited significantly reduced aperiodic slope, increased periodic theta power, and decreased alpha peak amplitude. A majority of DS participants displayed a prominent peak in the theta range, whereas a theta peak was not present in age-matched participants. Overall, similar findings were also observed when comparing DS and cognitive-matched groups, suggesting that EEG differences are not explained by delayed cognitive ability.

Developmental outcome of electroencephalographic findings in SYNGAP1 encephalopathy

SYNGAP1 haploinsufficiency results in a developmental and epileptic encephalopathy (DEE) causing generalized epilepsies accompanied by a spectrum of neurodevelopmental symptoms. Concerning interictal epileptiform discharges (IEDs) in electroencephalograms (EEG), potential biomarkers have been postulated, including changes in background activity, fixation-off sensitivity (FOS) or eye closure sensitivity (ECS). In this study we clinically evaluate a new cohort of 36 SYNGAP1-DEE individuals. Standardized questionnaires were employed to collect clinical, electroencephalographic and genetic data. We investigated electroencephalographic findings, focusing on the cortical distribution of interictal abnormalities and their changes with age. Among the 36 SYNGAP1-DEE cases 18 presented variants in the SYNGAP1 gene that had never been previously reported. The mean age of diagnosis was 8 years and 8 months, ranging from 2 to 17 years, with 55.9% being male. All subjects had global neurodevelopmental/language delay and behavioral abnormalities; 83.3% had moderate to profound intellectual disability (ID), 91.7% displayed autistic traits, 73% experienced sleep disorders and 86.1% suffered from epileptic seizures, mainly eyelid myoclonia with absences (55.3%). A total of 63 VEEGs were revised, observing a worsening of certain EEG findings with increasing age. A disorganized background was observed in all age ranges, yet this was more common among older cases. The main IEDs were bilateral synchronous and asynchronous posterior discharges, accounting for ≥50% in all age ranges. Generalized alterations with maximum amplitude in the anterior region showed as the second most frequent IED (≥15% in all age ranges) and were also more common with increasing age. Finally, diffuse fast activity was much more prevalent in cases with 6 years or older. To the best of our knowledge, this is the first study to analyze EEG features across different age groups, revealing an increase in interictal abnormalities over infancy and adolescence. Our findings suggest that SYNGAP1 haploinsufficiency has complex effects in human brain development, some of which might unravel at different developmental stages. Furthermore, they highlight the potential of baseline EEG to identify candidate biomarkers and the importance of natural history studies to develop specialized therapies and clinical trials.

Challenges in developing therapies in fragile X syndrome: how the FXLEARN trial can guide research

Fragile X syndrome (FXS), the most common inherited cause of intellectual disability and the single-gene cause of autism, is caused by decreased expression of the fragile X messenger ribonucleoprotein protein (FMRP), a ribosomal-associated RNA-binding protein involved in translational repression. Extensive preclinical work in several FXS animal models supported the therapeutic potential of decreasing metabotropic glutamate receptor (mGluR) signaling to correct translation of proteins related to synaptic plasticity; however, multiple clinical trials failed to show conclusive evidence of efficacy. In this issue of the JCI, Berry-Kravis and colleagues conducted the FXLEARN clinical trial to address experimental design concerns from previous trials. Unfortunately, despite treatment of young children with combined pharmacological and learning interventions for a prolonged period, no efficacy of blocking mGluR activity was observed. Future systematic evaluation of potential therapeutic approaches should evaluate consistency between human and animal pathophysiological mechanisms, utilize innovative clinical trial design from FXLEARN, and incorporate translatable biomarkers.

Beyond Diagnosis: Preliminary Study of Impact on Children and Parents in Neurodevelopmental Disorders and Juvenile Idiopathic Arthritis-Associated Uveitis

Chronic diseases are a growing problem for global health due to the large number of people they involve, the repercussions they have on the mental and physical well-being of those affected, and the costs to society. Particularly, chronic illnesses of childhood have important psychological implications, not only for affected children but also for their parents. Among these pathologies, neurodevelopmental disorders (NDDs) and uveitis associated with juvenile idiopathic arthritis (JIA-U) may affect mental and physical health, emotions, memory, learning, and socializing. This study evaluates the psychological and behavioral/emotional impact of NDDs and JIA-U on children and parents. Specifically, 30 children with active JIA-U and 30 children with NDDs and their parents completed the Child Behavior Checklist (CBCL) and Parent Stress Index-Short Form (PSI) questionnaires. Children with NDDs have statistically significant differences in all the emotional and behavioral variables compared to JIA-U children, and parents of children with NDDs experience an increased stress load compared to parents of children with JIA-U. This study emphasizes the wide range of emotional and behavioral challenges that parents face with NDDs. This study emphasizes that parents of children with NDDs not only experience higher levels of stress compared to parents of normally developing children but also experience higher levels of stress compared to parents of children with potentially debilitating chronic diseases such as JIA-U.