Heart rate mean and variability as a biomarker for phenotypic variation in preschoolers with autism spectrum disorder

Bazelmans, Tessel; Jones, Emily J. H.; Ghods, Sheila; Corrigan, Sarah; Toth, Karen; Charman, Tony; Webb, Sara Jane

doi:10.1002/aur.1982

Cited by 28 publications

(26 citation statements)

References 59 publications

(78 reference statements)

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“…This study aimed to obtain reference values in healthy children for candidate digital endpoints related to physical activity in the form of 90% prediction intervals. While these graphically presented prediction intervals could be used as a screening tool for pediatric patients, individual predictions that take weather condition, wear time and city of residence into account may be more appropriate and can be calculated using the model coefficients in S2 Table. HR has been proposed as a candidate biomarker in, among others, pediatric pulmonology, intensive care and psychiatry [25][26][27], and remote non-invasive HR monitoring could extend this measurement to the home-setting. In the past, Pelizzo et al have shown that HR measured via PPG technology can be reliable in children [28].…”

Section: Plos Onementioning

confidence: 99%

Towards remote monitoring in pediatric care and clinical trials—Tolerability, repeatability and reference values of candidate digital endpoints derived from physical activity, heart rate and sleep in healthy children

et al. 2021

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Background Digital devices and wearables allow for the measurement of a wide range of health-related parameters in a non-invasive manner, which may be particularly valuable in pediatrics. Incorporation of such parameters in clinical trials or care as digital endpoint could reduce the burden for children and their parents but requires clinical validation in the target population. This study aims to determine the tolerability, repeatability, and reference values of novel digital endpoints in healthy children. Methods Apparently healthy children (n = 175, 46% male) aged 2–16 were included. Subjects were monitored for 21 days using a home-monitoring platform with several devices (smartwatch, spirometer, thermometer, blood pressure monitor, scales). Endpoints were analyzed with a mixed effects model, assessing variables that explained within- and between-subject variability. Endpoints based on physical activity, heart rate, and sleep-related parameters were included in the analysis. For physical-activity-related endpoints, a sample size needed to detect a 15% increase was calculated. Findings Median compliance was 94%. Variability in each physical activity-related candidate endpoint was explained by age, sex, watch wear time, rain duration per day, average ambient temperature, and population density of the city of residence. Estimated sample sizes for candidate endpoints ranged from 33–110 per group. Daytime heart rate, nocturnal heart rate and sleep duration decreased as a function of age and were comparable to reference values published in the literature. Conclusions Wearable- and portable devices are tolerable for pediatric subjects. The raw data, models and reference values presented here can be used to guide further validation and, in the future, clinical trial designs involving the included measures.

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Section: Plos Onementioning

confidence: 99%

Towards remote monitoring in pediatric care and clinical trials—Tolerability, repeatability and reference values of candidate digital endpoints derived from physical activity, heart rate and sleep in healthy children

et al. 2021

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“…Finally, as suggested above, recent large scale trials (Bazelmans et al, 2018), and systematic reviews (Klusek et al, 2015; Lydon et al, 2016) of the literature on physiological reactivity to sensory, social, and emotional stimuli indicate that differences in cardiovascular arousal exist for many individuals with ASD.…”

Section: Introductionmentioning

confidence: 81%

An Observational Study With the Janssen Autism Knowledge Engine (JAKE®) in Individuals With Autism Spectrum Disorder

et al. 2019

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Objective: The Janssen Autism Knowledge Engine (JAKE®) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components. Methods: An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States. Feedback on JAKE usability was obtained from caregivers. JAKE Sense included electroencephalography, eye tracking, electrocardiography, electrodermal activity, facial affect analysis, and actigraphy. Caregivers of individuals with ASD reported behaviors using My JAKE. Results from My JAKE and JAKE Sense were compared to traditional ASD symptom measures. Results: Individuals with ASD ( N = 144) and a cohort of typically developing (TD) individuals ( N = 41) participated in JAKE Sense. Most caregivers reported that overall use and utility of My JAKE was “easy” (69%, 74/108) or “very easy” (74%, 80/108). My JAKE could detect differences in ASD symptoms as measured by traditional methods. The majority of biosensors included in JAKE Sense captured sizable amounts of quality data (i.e., 93–100% of eye tracker, facial affect analysis, and electrocardiogram data was of good quality), demonstrated differences between TD and ASD individuals, and correlated with ASD symptom scales. No significant safety events were reported. Conclusions: My JAKE was viewed as easy or very easy to use by caregivers participating in research outside of a clinical study. My JAKE sensitively measured a broad range of ASD symptoms. JAKE Sense biosensors were well-tolerated. JAKE functioned well when used at clinical sites previously inexperienced with some of the technologies. Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions. Additionally, because biosensors were able to detect features differentiating TD and ASD individuals, and also were correlated with standardized symptom scales, these measures could be explored as potential biomarkers for ASD and as endpoints in future clinical studies. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02668991 identifier: NCT02668991

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“…For both the baseline and experimental task recording, four participants from the 52 who completed the direct assessments had no usable ECG data due to electrode refusal (n=2) and corrupted data les (n=2). For the baseline recording, ECG segments with more than three consecutive missing peaks or 10% of data missing were excluded (as in previous studies of autistic populations) (37), and participants with ≥ 50% missing task data overall were excluded (n=4), leaving a nal sample of n=44 for the baseline HR data. For the experimental task, ECG task segments with more than one peak missing were excluded, and as before, participants with ≥ 50% missing task data were excluded (n=1), leaving a nal sample of n=47 for the frustration task HR data.…”

Section: Physiological Data Extraction and Processingmentioning

confidence: 99%

Behavioural and Physiological Response to Frustration in Autistic Youth: Associations with Irritability

Leno

Forth

Chandler

et al. 2020

Preprint

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Background: Irritability is a common and impairing occurrence in autistic youth, yet the underlying mechanisms are not well known. In typically developing populations, differences in frustration response have been suggested as important driver of the behavioural symptoms of irritability. Research exploring the role of frustration response as a risk factor for irritability in autistic populations is limited and often uses on parent report or observer ratings; objective measures of frustration response appropriate for use in autistic populations are required to advance the field. Methods: In the current study, fifty-two autistic adolescents aged 13-17 years from a population-based longitudinal study completed an experimental task designed to induce frustration through exposure to periods of unexpected delay. Behavioural (number of button presses) and physiological (heart rate; HR) metrics were collected during delay periods. Irritability was measured using the parent-rated Affective Reactivity Index (ARI). Analyses used mixed-level models to test whether irritability was associated with different slopes of behavioural and physiological response in response to experimentally induced frustration. Age and baseline HR (for the physiological data only) were included as covariates. Results: Analyses showed a marginal association between irritability and the slope of behavioural response (incident rate ratio=.98, p=.06), and a significant association with the slope of physiological response (b=-.10, p=.04); higher levels of irritability were associated with a dampened behavioural and physiological response, as indicated by flatter slopes of change over the course of the task. This pattern of results remained when adjusting for IQ, autism symptom severity and medication use (association between irritability and slope of behavioural response: incident rate ratio=.98, p=.02; slope of HR response; b=-.10, p=.04). Conclusions: Results suggest that the current experimental task may be a useful objective measure of frustration response for use with autistic populations, and that a non-adaptive response to frustration may be one biological mechanism underpinning irritability in autistic youth. This may represent an important target for future intervention studies.

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Heart rate mean and variability as a biomarker for phenotypic variation in preschoolers with autism spectrum disorder

Cited by 28 publications

References 59 publications

Towards remote monitoring in pediatric care and clinical trials—Tolerability, repeatability and reference values of candidate digital endpoints derived from physical activity, heart rate and sleep in healthy children

Towards remote monitoring in pediatric care and clinical trials—Tolerability, repeatability and reference values of candidate digital endpoints derived from physical activity, heart rate and sleep in healthy children

An Observational Study With the Janssen Autism Knowledge Engine (JAKE®) in Individuals With Autism Spectrum Disorder

Behavioural and Physiological Response to Frustration in Autistic Youth: Associations with Irritability

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