ABSTRACT
PURPOSE: Motor evoked potential (MEP) amplitude and latency are acquired routinely during neuronavigated transcranial magnetic stimulation, a method of functional mapping of the motor cortex before epilepsy surgery. Although MEP amplitude is routinely used to generate a motor map, MEP latency in patients with focal epilepsy has not been studied systematically. Given that epilepsy may alter myelination, we tested whether intrinsic hand muscle MEPs obtained from the hemisphere containing a seizure focus differ in latency from MEPs collected from the opposite hemisphere. METHODS: Latencies of abductor pollicis brevis MEPs were obtained during routine motor mapping by neuronavigated transcranial magnetic stimulation in children with intractable, unihemispheric focal epilepsy. The primary motor cortex was stimulated bilaterally in all cases. Only data from patients without a lesion involving the corticospinal tract were included. We tested whether abductor pollicis brevis MEP latency varied as a function of seizure focus lateralization. RESULTS: In the 17 patients who met the inclusion criteria, the mean latency of MEPs with amplitudes in the top and bottom quartiles was shorter in the epileptic hemisphere. Interhemispheric latency difference was greater in patients with lesional epilepsy than in those with nonlesional epilepsy (0.7 ± 0.4 vs. 0.1 ± 0.6 milliseconds, P = 0.02). CONCLUSIONS: Motor evoked potential latency was shortened in the epileptic hemisphere of children with focal epilepsy.
ABSTRACT
BACKGROUND: Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by the absence of a functional UBE3A gene, which causes developmental, behavioral, and medical challenges. While currently untreatable, comprehensive data could help identify appropriate endpoints assessing meaningful improvements in clinical trials. Herein are reported the results from the FREESIAS study assessing the feasibility and utility of in-clinic and at-home measures of key AS symptoms. METHODS: Fifty-five individuals with AS (aged < 5 years: n = 16, 5-12 years: n = 27, ≥ 18 years: n = 12; deletion genotype: n = 40, nondeletion genotype: n = 15) and 20 typically developing children (aged 1-12 years) were enrolled across six USA sites. Several clinical outcome assessments and digital health technologies were tested, together with overnight 19-lead electroencephalography (EEG) and additional polysomnography (PSG) sensors. Participants were assessed at baseline (Clinic Visit 1), 12 months later (Clinic Visit 2), and during intermittent home visits. RESULTS: The participants achieved high completion rates for the clinical outcome assessments (adherence: 89-100% [Clinic Visit 1]; 76-91% [Clinic Visit 2]) and varied feasibility of and adherence to digital health technologies. The coronavirus disease 2019 (COVID-19) pandemic impacted participants' uptake of and/or adherence to some measures. It also potentially impacted the at-home PSG/EEG recordings, which were otherwise feasible. Participants achieved Bayley-III results comparable to the available natural history data, showing similar scores between individuals aged ≥ 18 and 5-12 years. Also, participants without a deletion generally scored higher on most clinical outcome assessments than participants with a deletion. Furthermore, the observed AS EEG phenotype of excess delta-band power was consistent with prior reports. CONCLUSIONS: Although feasible clinical outcome assessments and digital health technologies are reported herein, further improved assessments of meaningful AS change are needed. Despite the COVID-19 pandemic, remote assessments facilitated high adherence levels and the results suggested that at-home PSG/EEG might be a feasible alternative to the in-clinic EEG assessments. Taken altogether, the combination of in-clinic/at-home clinical outcome assessments, digital health technologies, and PSG/EEG may improve protocol adherence, reduce patient burden, and optimize study outcomes in AS and other rare disease populations.
Subject(s)
Angelman Syndrome , COVID-19 , Humans , Angelman Syndrome/complications , Prospective Studies , Pandemics , ElectroencephalographyABSTRACT
Challenges in social communication is one of the core symptom domains in autism spectrum disorder (ASD). Novel therapies are under development to help individuals with these challenges, however the ability to show a benefit is dependent on a sensitive and reliable measure of treatment effect. Currently, measuring these deficits requires the use of time-consuming and subjective techniques. Objective measures extracted from natural conversations could be more ecologically relevant, and administered more frequently-perhaps giving them added sensitivity to change. While several studies have used automated analysis methods to study autistic speech, they require manual transcriptions. In order to bypass this time-consuming process, an automated speaker diarization algorithm must first be applied. In this paper, we are testing whether a speaker diarization algorithm can be applied to natural conversations between autistic individuals and their conversational partner in a natural setting at home over the course of a clinical trial. We calculated the average duration that a participant would speak for within their turn. We found a significant correlation between this feature and the Vineland Adaptive Behaviour Scales (VABS) expressive communication score (r = 0.51, p = 7 × 10-5). Our results show that natural conversations can be used to obtain measures of talkativeness, and that this measure can be derived automatically, thus showing the promise of objectively evaluating communication challenges in ASD.
Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Humans , Autistic Disorder/therapy , Autism Spectrum Disorder/therapy , Autism Spectrum Disorder/diagnosis , Communication , SpeechABSTRACT
Both, pharmacological and genome-wide association studies suggest N-methyl-D-aspartate receptor (NMDAR) dysfunction and excitatory/inhibitory (E/I)-imbalance as a major pathophysiological mechanism of schizophrenia. The identification of shared fMRI brain signatures of genetically and pharmacologically induced NMDAR dysfunction may help to define biomarkers for patient stratification. NMDAR-related genetic and pharmacological effects on functional connectivity were investigated by integrating three different datasets: (A) resting state fMRI data from 146 patients with schizophrenia genotyped for the disease-associated genetic variant rs7191183 of GRIN2A (encoding the NMDAR 2 A subunit) as well as 142 healthy controls. (B) Pharmacological effects of the NMDAR antagonist ketamine and the GABA-A receptor agonist midazolam were obtained from a double-blind, crossover pharmaco-fMRI study in 28 healthy participants. (C) Regional gene expression profiles were estimated using a postmortem whole-brain microarray dataset from six healthy donors. A strong resemblance was observed between the effect of the genetic variant in schizophrenia and the ketamine versus midazolam contrast of connectivity suggestive for an associated E/I-imbalance. This similarity became more pronounced for regions with high density of NMDARs, glutamatergic neurons, and parvalbumin-positive interneurons. From a functional perspective, increased connectivity emerged between striato-pallido-thalamic regions and cortical regions of the auditory-sensory-motor network, while decreased connectivity was observed between auditory (superior temporal gyrus) and visual processing regions (lateral occipital cortex, fusiform gyrus, cuneus). Importantly, these imaging phenotypes were associated with the genetic variant, the differential effect of ketamine versus midazolam and schizophrenia (as compared to healthy controls). Moreover, the genetic variant was associated with language-related negative symptomatology which correlated with disturbed connectivity between the left posterior superior temporal gyrus and the superior lateral occipital cortex. Shared genetic and pharmacological functional connectivity profiles were suggestive of E/I-imbalance and associated with schizophrenia. The identified brain signatures may help to stratify patients with a common molecular disease pathway providing a basis for personalized psychiatry.
Subject(s)
Ketamine , Schizophrenia , Humans , Schizophrenia/diagnostic imaging , Schizophrenia/genetics , Schizophrenia/metabolism , Magnetic Resonance Imaging/methods , Ketamine/pharmacology , Receptors, N-Methyl-D-Aspartate/genetics , Genome-Wide Association Study , MidazolamABSTRACT
What is the common denominator of consciousness across divergent regimes of cortical dynamics? Does consciousness show itself in decibels or in bits? To address these questions, we introduce a testbed for evaluating electroencephalogram (EEG) biomarkers of consciousness using dissociations between neural oscillations and consciousness caused by rare genetic disorders. Children with Angelman syndrome (AS) exhibit sleep-like neural dynamics during wakefulness. Conversely, children with duplication 15q11.2-13.1 syndrome (Dup15q) exhibit wake-like neural dynamics during non-rapid eye movement (NREM) sleep. To identify highly generalizable biomarkers of consciousness, we trained regularized logistic regression classifiers on EEG data from wakefulness and NREM sleep in children with AS using both entropy measures of neural complexity and spectral (i.e., neural oscillatory) EEG features. For each set of features, we then validated these classifiers using EEG from neurotypical (NT) children and abnormal EEGs from children with Dup15q. Our results show that the classification performance of entropy-based EEG biomarkers of conscious state is not upper-bounded by that of spectral EEG features, which are outperformed by entropy features. Entropy-based biomarkers of consciousness may thus be highly adaptable and should be investigated further in situations where spectral EEG features have shown limited success, such as detecting covert consciousness or anesthesia awareness.
Subject(s)
Consciousness , Wakefulness , Child , Humans , Electroencephalography/methods , Sleep , EntropyABSTRACT
BACKGROUND: Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. METHODS: We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split). RESULTS: In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. LIMITATIONS: The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects. CONCLUSIONS: This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.
Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Adolescent , Adult , Autism Spectrum Disorder/diagnosis , Brain/diagnostic imaging , Brain Mapping/methods , Child , Cross-Sectional Studies , Electroencephalography/methods , Humans , Magnetic Resonance Imaging/methods , Reproducibility of ResultsABSTRACT
BACKGROUND: There are currently no pharmacological therapies to address the intellectual disability associated with Down syndrome. Excitatory/inhibitory imbalance has been hypothesized to contribute to impairments in cognitive functioning in Down syndrome. Negative modulation of the GABAA-α5 receptor is proposed as a mechanism to attenuate GABAergic function and restore the excitatory/inhibitory balance. METHODS: Basmisanil, a selective GABAA-α5 negative allosteric modulator, was evaluated at 120 mg or 240 mg BID (80 or 160 mg for 12-13 years) in a 6-month, randomized, double-blind, placebo-controlled phase II trial (Clematis) for efficacy and safety in adolescents and young adults with Down syndrome. The primary endpoint was based on a composite analysis of working memory (Repeatable Battery for the Assessment of Neuropsychological Scale [RBANS]) and independent functioning and adaptive behavior (Vineland Adaptive Behavior Scales [VABS-II] or the Clinical Global Impression-Improvement [CGI-I]). Secondary measures included the Behavior Rating Inventory of Executive Functioning-Preschool (BRIEF-P), Clinical Evaluation of Language Fundamentals (CELF-4), and Pediatric Quality of Life Inventory (Peds-QL). EEG was conducted for safety monitoring and quantitatively analyzed in adolescents. RESULTS: Basmisanil was safe and well-tolerated; the frequency and nature of adverse events were similar in basmisanil and placebo arms. EEG revealed treatment-related changes in spectral power (increase in low ~ 4-Hz and decrease in high ~ 20-Hz frequencies) providing evidence of functional target engagement. All treatment arms had a similar proportion of participants showing above-threshold improvement on the primary composite endpoint, evaluating concomitant responses in cognition and independent functioning (29% in placebo, 20% in low dose, and 25% in high dose). Further analysis of the individual measures contributing to the primary endpoint revealed no difference between placebo and basmisanil-treated groups in either adolescents or adults. There were also no differences across the secondary endpoints assessing changes in executive function, language, or quality of life. CONCLUSIONS: Basmisanil did not meet the primary efficacy objective of concomitant improvement on cognition and adaptive functioning after 6 months of treatment, despite evidence for target engagement. This study provides key learnings for future clinical trials in Down syndrome. TRIAL REGISTRATION: The study was registered on December 31, 2013, at clinicaltrials.gov as NCT02024789.
Subject(s)
Down Syndrome , Intellectual Disability , Adolescent , Child , Child, Preschool , Down Syndrome/complications , Down Syndrome/drug therapy , Humans , Intellectual Disability/complications , Intellectual Disability/drug therapy , Morpholines , Oxazoles , Pyridines , Quality of Life , Treatment Outcome , Young Adult , gamma-Aminobutyric Acid/therapeutic useABSTRACT
Electroencephalography (EEG), easily deployed at the bedside, is an attractive modality for deriving quantitative biomarkers of prognosis and differential diagnosis in severe brain injury and disorders of consciousness (DOC). Prior work by Schiff has identified four dynamic regimes of progressive recovery of consciousness defined by the presence or absence of thalamically-driven EEG oscillations. These four predefined categories (ABCD model) relate, on a theoretical level, to thalamocortical integrity and, on an empirical level, to behavioral outcome in patients with cardiac arrest coma etiologies. However, whether this theory-based stratification of patients might be useful as a diagnostic biomarker in DOC and measurably linked to thalamocortical dysfunction remains unknown. In this work, we relate the reemergence of thalamically-driven EEG oscillations to behavioral recovery from traumatic brain injury (TBI) in a cohort of N = 38 acute patients with moderate-to-severe TBI and an average of 1 week of EEG recorded per patient. We analyzed an average of 3.4 hr of EEG per patient, sampled to coincide with 30-min periods of maximal behavioral arousal. Our work tests and supports the ABCD model, showing that it outperforms a data-driven clustering approach and may perform equally well compared to a more parsimonious categorization. Additionally, in a subset of patients (N = 11), we correlated EEG findings with functional magnetic resonance imaging (fMRI) connectivity between nodes in the mesocircuit-which has been theoretically implicated by Schiff in DOC-and report a trend-level relationship that warrants further investigation in larger studies.
Subject(s)
Brain Injuries, Traumatic , Brain Injuries , Brain Injuries, Traumatic/complications , Brain Injuries, Traumatic/diagnostic imaging , Consciousness , Consciousness Disorders/diagnostic imaging , Consciousness Disorders/etiology , Electroencephalography/methods , HumansABSTRACT
BACKGROUND: Angelman syndrome (AS) is a rare neurodevelopmental disorder caused by the absence of functional UBE3A in neurons. Excess low-frequency oscillations as measured with electroencephalography (EEG) have been identified as a characteristic finding, but the relationship of this EEG finding to the symptomatology of AS and its significance in the pathophysiology of AS remain unknown. METHODS: We used correlations and machine learning to investigate the cross-sectional and longitudinal relationship between EEG spectral power and motor, cognitive, and language skills (Bayley Scales of Infant and Toddler Development, Third Edition); adaptive behavior (Vineland Adaptive Behavior Scales, Second Edition); AS-specific symptoms (AS Clinical Severity Scale); and the age of epilepsy onset in a large sample of children (age: 1-18 years) with AS due to a chromosomal deletion of 15q11-q13 (45 individuals with 72 visits). RESULTS: We found that after accounting for age differences, participants with stronger EEG delta-band abnormality had earlier onset of epilepsy and lower performance scores across symptom domains including cognitive, motor, and communication. Combing spatial and spectral information beyond the delta frequency band increased the cross-sectional association with clinical severity on average by approximately 45%. Furthermore, we found evidence for longitudinal correlations of EEG delta-band power within several performance domains, including the mean across Bayley Scales of Infant and Toddler Development, Third Edition, scores. CONCLUSIONS: Our results show an association between EEG abnormalities and symptom severity in AS, underlining the significance of the former in the pathophysiology of AS. Furthermore, our work strengthens the rationale for using EEG as a biomarker in the development of treatments for AS, a concept that may apply more generally to neurodevelopmental disorders.
ABSTRACT
BACKGROUND: Epilepsy is highly prevalent in children with Angelman syndrome (AS), and its detailed characterization and relationship to the genotype (deletion vs nondeletion) is important both for medical practice and for clinical trial design. METHODS AND MATERIALS: We retrospectively analyzed the main clinical features of epilepsy in 265 children with AS who were enrolled in the AS Natural History Study, a multicenter, observational study conducted at six centers in the United States. Participants were prospectively followed up and classified by genotype. RESULTS: Epilepsy was reported in a greater proportion of individuals with a deletion than a nondeletion genotype (171 of 187 [91%] vs. 48 of 78 [61%], P < 0.001). Compared with participants with a nondeletion genotype, those with deletions were younger at the time of the first seizure (age: median [95% confidence interval]: 24 [21-24] months vs. 57 [36-85] months, P < 0.001) and had a higher prevalence of generalized motor seizures. Hospitalization following a seizure was reported in more children with a deletion than a nondeletion genotype (92 of 171 [54%] vs. 17 of 48 [36%], P = 0.04). The overall prevalence of absence seizures was not significantly different between genotype groups. Forty-six percent (102/219) of the individuals reporting epilepsy were diagnosed with AS concurrently or after their first seizure. CONCLUSIONS: Significant differences exist in the clinical expression of epilepsy in AS according to the underlying genotype, with earlier age of onset and more severe epilepsy in individuals with AS due to a chromosome 15 deletion.
Subject(s)
Angelman Syndrome/genetics , Angelman Syndrome/physiopathology , Epilepsy/physiopathology , Adolescent , Angelman Syndrome/complications , Child , Child, Preschool , Epilepsy/etiology , Female , Follow-Up Studies , Genotype , Humans , Infant , Infant, Newborn , Male , Retrospective StudiesABSTRACT
In this work, we propose a Bluetooth low energy (BLE) beacon-based algorithm to enable remote measurement of the social behavior of the participants of an observational Autism Spectrum Disorder (ASD) clinical trial (NCT03611075). We have developed a mobile application for a smartphone and a smartwatch to collect beacon signals from BLE beacon sensors as well as to store information about the participants' household rooms. Our goal is to collect beacon information about the time the participants spent in different rooms of their household to infer sociability information. We applied the same technology and setup in an internal experiment with healthy volunteers to evaluate the accuracy of the proposed algorithm in 10 different home setups, and we observed an average accuracy of 97.2%. Moreover, we show that it is feasible for the clinical study participants/caregivers to set up the BLE beacon sensors in their homes without any technical help, with 96% of them setting up the technology on the first day of data collection. Next, we present results from one-week location data from study participants collected through the proposed technology. Finally, we provide a list of good practice guidelines for optimally applying beacon technology for indoor location monitoring. The proposed algorithm enables us to estimate time spent in different rooms of a household that can pave the development of objective sociability features and eventually support decisions regarding drug efficacy in ASD.
Subject(s)
Autism Spectrum Disorder , Mobile Applications , Autism Spectrum Disorder/diagnosis , Feasibility Studies , Humans , Smartphone , Social BehaviorABSTRACT
GABAA-α5 subunit-containing receptors have been shown to play a key modulatory role in cognition and represent a promising drug target for cognitive dysfunction, as well as other disorders. Here we report on the preclinical and early clinical profile of a novel GABAA-α5 selective negative allosteric modulator (NAM), basmisanil, which progressed into Phase II trials for intellectual disability in Down syndrome and cognitive impairment associated with schizophrenia. Preclinical pharmacology studies showed that basmisanil is the most selective GABAA-α5 receptor NAM described so far. Basmisanil bound to recombinant human GABAA-α5 receptors with 5 nM affinity and more than 90-fold selectivity versus α1, α2, and α3 subunit-containing receptors. Moreover, basmisanil inhibited GABA-induced currents at GABAA-α5 yet had little or no effect at the other receptor subtypes. An in vivo occupancy study in rats showed dose-dependent target engagement and was utilized to establish the plasma exposure to receptor occupancy relationship. At estimated receptor occupancies between 30 and 65% basmisanil attenuated diazepam-induced spatial learning impairment in rats (Morris water maze), improved executive function in non-human primates (object retrieval), without showing anxiogenic or proconvulsant effects in rats. During the Phase I open-label studies, basmisanil showed good safety and tolerability in healthy volunteers at maximum GABAA-α5 receptor occupancy as confirmed by PET analysis with the tracer [11C]-Ro 15-4513. An exploratory EEG study provided evidence for functional activity of basmisanil in human brain. Therefore, these preclinical and early clinical studies show that basmisanil has an ideal profile to investigate potential clinical benefits of GABAA-α5 receptor negative modulation.
Subject(s)
GABA-A Receptor Agonists/pharmacology , Receptors, GABA-A/drug effects , Allosteric Regulation , Animals , Brain/diagnostic imaging , Brain/drug effects , Brain/metabolism , Female , HEK293 Cells , Healthy Volunteers , Humans , Learning/drug effects , Macaca fascicularis , Positron-Emission Tomography , Radioligand Assay , Rats , Rats, Sprague-Dawley , Receptors, GABA-A/chemistry , Receptors, GABA-A/metabolism , Xenopus laevisABSTRACT
Synchronized neuronal population activity in the gamma-frequency range (>30 Hz) correlates with the bottom-up drive of various visual features. It has been hypothesized that gamma-band synchronization enhances the gain of neuronal representations, yet evidence remains sparse. We tested a critical prediction of the gain hypothesis, which is that features that drive synchronized gamma-band activity interact super-linearly. To test this prediction, we employed whole-head magnetencephalography in human subjects and investigated if the strength of visual motion (motion coherence) and luminance contrast interact in driving gamma-band activity in visual cortex. We found that gamma-band activity (64-128 Hz) monotonically increased with coherence and contrast, while lower frequency activity (8-32 Hz) decreased with both features. Furthermore, as predicted for a gain mechanism, we found a multiplicative interaction between motion coherence and contrast in their joint drive of gamma-band activity. The lower frequency activity did not show such an interaction. Our findings provide evidence that gamma-band activity acts as a cortical gain mechanism that nonlinearly combines the bottom-up drive of different visual features.
Subject(s)
Contrast Sensitivity/physiology , Motion Perception/physiology , Visual Cortex/physiology , Adult , Female , Humans , Magnetoencephalography , Male , Photic StimulationABSTRACT
Angelman Syndrome (AS) is a severe neurodevelopmental disorder due to impaired expression of UBE3A in neurons. There are several genetic mechanisms that impair UBE3A expression, but they differ in how neighboring genes on chromosome 15 at 15q11-q13 are affected. There is evidence that different genetic subtypes present with different clinical severity, but a systematic quantitative investigation is lacking. Here we analyze natural history data on a large sample of individuals with AS (n = 250, 848 assessments), including clinical scales that quantify development of motor, cognitive, and language skills (Bayley Scales of Infant Development, Third Edition; Preschool Language Scale, Fourth Edition), adaptive behavior (Vineland Adaptive Behavioral Scales, Second Edition), and AS-specific symptoms (AS Clinical Severity Scale). We found that clinical severity, as captured by these scales, differs between genetic subtypes: individuals with UBE3A pathogenic variants and imprinting defects (IPD) are less affected than individuals with uniparental paternal disomy (UPD); of those with UBE3A pathogenic variants, individuals with truncating mutations are more impaired than those with missense mutations. Individuals with a deletion that encompasses UBE3A and other genes are most impaired, but in contrast to previous work, we found little evidence for an influence of deletion length (class I vs. II) on severity of manifestations. The results of this systematic analysis highlight the relevance of genomic regions beyond UBE3A as contributing factors in the AS phenotype, and provide important information for the development of new therapies for AS. More generally, this work exemplifies how increasing genetic irregularities are reflected in clinical severity.
Subject(s)
Angelman Syndrome , Angelman Syndrome/genetics , Chromosomes, Human, Pair 15 , Genomic Imprinting/genetics , Genotype , Humans , Phenotype , Ubiquitin-Protein Ligases/geneticsABSTRACT
[This corrects the article DOI: 10.1093/nc/niaa005.][This corrects the article DOI: 10.1093/nc/niaa005.].
ABSTRACT
Heart rate variability (HRV) measures the regularity between consecutive heartbeats driven by the balance between the sympathetic and parasympathetic branches of the autonomous nervous system. Wearable devices embedding photoplethysmogram (PPG) technology can be used to derive HRV, creating many opportunities for remote monitoring of this physiological parameter. However, uncontrolled conditions met in daily life pose several challenges related to disturbances that can deteriorate the PPG signal, making the calculation of HRV metrics untrustworthy and not reliable. In this work, we propose a HRV quality metric that is directly related to the HRV accuracy and can be used to distinguish between accurate and inaccurate HRV values. A parametric supervised approach estimates HRV accuracy using a model whose inputs are features extracted from the PPG signal and the output is the HRV error between HRV metrics obtained from the PPG and the ECG collected during an experimental protocol involving several activities. The estimated HRV accuracy of the model is used as an indication of the HRV quality.
Subject(s)
Photoplethysmography , Wearable Electronic Devices , Data Collection , Electrocardiography , Heart Rate , HumansABSTRACT
BACKGROUND: Duplications of 15q11.2-q13.1 (Dup15q syndrome) are highly penetrant for autism, intellectual disability, hypotonia, and epilepsy. The 15q region harbors genes critical for brain development, particularly UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We recently described an electrophysiological biomarker of the syndrome, characterized by excessive beta oscillations (12-30 Hz), resembling electroencephalogram (EEG) changes induced by allosteric modulation of GABAARs. In this follow-up study, we tested a larger cohort of children with Dup15q syndrome to comprehensively examine properties of this EEG biomarker that would inform its use in future clinical trials, specifically, its (1) relation to basic clinical features, such as age, duplication type, and epilepsy; (2) relation to behavioral characteristics, such as cognition and adaptive function; (3) stability over time; and (4) reproducibility of the signal in clinical EEG recordings. METHODS: We computed EEG power and beta peak frequency (BPF) in a cohort of children with Dup15q syndrome (N = 41, age range 9-189 months). To relate EEG parameters to clinical (study 1) and behavioral features (study 2), we examined age, duplication type, epilepsy, cognition, and daily living skills (DLS) as predictors of beta power and BPF. To evaluate stability over time (study 3), we derived the intraclass correlation coefficients (ICC) from beta power and BPF computed from children with multiple EEG recordings (N = 10, age range 18-161 months). To evaluate reproducibility in a clinical setting (study 4), we derived ICCs from beta power computed from children (N = 8, age range 19-96 months), who had undergone both research EEG and clinical EEG. RESULTS: The most promising relationships between EEG and clinical traits were found using BPF. BPF was predicted both by epilepsy status (R2 = 0.11, p = 0.038) and the DLS component of the Vineland Adaptive Behavior Scale (R2 = 0.17, p = 0.01). Beta power and peak frequency showed high stability across repeated visits (beta power ICC = 0.93, BPF ICC = 0.92). A reproducibility analysis revealed that beta power estimates are comparable between research and clinical EEG (ICC = 0.94). CONCLUSIONS: In this era of precision health, with pharmacological and neuromodulatory therapies being developed and tested for specific genetic etiologies of neurodevelopmental disorders, quantification and examination of mechanistic biomarkers can greatly improve clinical trials. To this end, the robust beta oscillations evident in Dup15q syndrome are clinically reproducible and stable over time. With future preclinical and computational studies that will help disentangle the underlying mechanism, it is possible that this biomarker could serve as a robust measure of drug target engagement or a proximal outcome measure in future disease modifying intervention trials.