The Autism Biomarkers Consortium for Clinical Trials (ABC-CT): Scientific Context, Study Design, and Progress Toward Biomarker Qualification

Effects of non-invasive neurostimulation on autism spectrum disorder: A systematic review

Non-invasive neurostimulation techniques (NIBS) have shown benefits in psychiatric conditions. While in ASD patients, no guideline has so-far been recommended on these techniques due to a lack of high-quality synthetic evidence. Here, a comprehensive search from database inception onward was conducted in PubMed, EMBASE, and Cochrane library. Sham-controlled studies assessing the effects of NIBS in ASD patients were identified. After screening, twenty-two studies were included. A total of 552 patients were involved, and the sample size ranged from 5 to 78 patients. Although an iteration from exploratory attempts to more strictly designed trials has been seen to evaluate the efficacy of NIBS on ASD, further trials should also be needed to enable the clinicians and researchers to reach any consensus.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021292434], identifier [CRD42021292434].

Autism risk in neonatal intensive care unit patients associated with novel heart rate patterns

BACKGROUND

Neonatal intensive care unit (NICU) patients are at increased risk for autism spectrum disorder (ASD). Autonomic nervous system aberrancy has been described in children with ASD, and we aimed to identify heart rate (HR) patterns in NICU patients associated with eventual ASD diagnosis.

METHODS

This retrospective cohort study included NICU patients from 2009 to 2016 with archived HR data and follow-up beyond age 3 years. Medical records provided clinical variables and ASD diagnosis. HR data were compared in infants with and without ASD.

RESULTS

Of the 2371 patients, 88 had ASD, and 689,016 h of data were analyzed. HR skewness (HRskw) was significantly different between ASD and control infants. Preterm infants at early postmenstrual ages (PMAs) had negative HRskw reflecting decelerations, which increased with maturation. From 34 to 42 weeks PMA, positive HRskw toward accelerations was higher in males with ASD. In 931 males with at least 4 days of HR data, overall ASD prevalence was 5%, whereas 11% in the top 5th HRskw percentile had ASD.

CONCLUSION

High HRskw in NICU males, perhaps representing autonomic imbalance, was associated with increased ASD risk. Further study is needed to determine whether HR analysis identifies highest-risk infants who might benefit from earlier screening and therapies.

IMPACT

In a large retrospective single-center cohort of NICU patients, we found that high positive skewness of heart rate toward more accelerations was significantly associated with increased risk of eventual autism spectrum disorder diagnosis in male infants but not in females. Existing literature describes differences in heart rate characteristics in children, adolescents, and adults with autism spectrum disorders, but the finding from our study in NICU infants is novel. Heart rate analysis during the NICU stay might identify, among an inherently high-risk population, those infants with especially high risk of ASD who might benefit from earlier screening and therapies.

Looking Back at the Next 40 Years of ASD Neuroscience Research

During the last 40 years, neuroscience has become one of the most central and most productive approaches to investigating autism. In this commentary, we assemble a group of established investigators and trainees to review key advances and anticipated developments in neuroscience research across five modalities most commonly employed in autism research: magnetic resonance imaging, functional near infrared spectroscopy, positron emission tomography, electroencephalography, and transcranial magnetic stimulation. Broadly, neuroscience research has provided important insights into brain systems involved in autism but not yet mechanistic understanding. Methodological advancements are expected to proffer deeper understanding of neural circuitry associated with function and dysfunction during the next 40 years.

Can stratification biomarkers address the heterogeneity of autism spectrum disorder?

The search for biomarkers for autism spectrum disorder (henceforth autism) has received a lot of attention due to their potential clinical relevance. The clinical and aetiological heterogeneity of autism suggests the presence of subgroups. The lack of identification of a valid diagnostic biomarker for autism, and the inconsistencies seen in studies assessing differences between autism and typically developing control groups, may be partially explained by the vast heterogeneity observed in autism. The focus now is to better understand the clinical and biological heterogeneity and identify stratification biomarkers, which are measures that describe subgroups of individuals with shared biology. Using stratification approaches to assess treatment within pre-defined subgroups could clarify who may benefit from different treatments and therapies, and ultimately lead to more effective individualised treatment plans.

Neural Correlates of Infant Face Processing and Later Emerging Autism Symptoms in Fragile X Syndrome

Fragile X syndrome (FXS) is the leading known genetic cause of autism spectrum disorder (ASD) with 60-74% of males with FXS meeting diagnostic criteria for ASD. Infants with FXS have demonstrated atypical neural responses during face processing that are unique from both typically developing, low-risk infants and infants at high familial risk for ASD (i.e., infants siblings of children with ASD). In the current study, event-related potential (ERP) responses during face processing measured at 12 months of age were examined in relation to ASD symptoms measured at ~48 months of age in participants with FXS, as well as siblings of children with ASD and low-risk control participants. Results revealed that greater amplitude N290 responses in infancy were associated with more severe ASD symptoms in childhood in FXS and in siblings of children with ASD. This pattern of results was not observed for low-risk control participants. Reduced Nc amplitude was associated with more severe ASD symptoms in participants with FXS but was not observed in the other groups. This is the first study to examine ASD symptoms in childhood in relation to infant ERP responses in FXS. Results indicate that infant ERP responses may be predictive of later symptoms of ASD in FXS and the presence of both common and unique pathways to ASD in etiologically-distinct high-risk groups is supported (i.e., syndromic risk vs. familial risk).

Investigating Changes in Reward-Related Neural Correlates After PEERS Intervention in Adolescents With ASD: Preliminary Evidence of a "Precision Medicine" Approach

Background: The Social Motivation Hypothesis proposes that individuals with autism spectrum disorder (ASD) experience social interactions as less rewarding than their neurotypical (TD) peers, which may lead to reduced social initiation. Existing studies of the brain's reward system in individuals with ASD report varied findings for anticipation of and response to social rewards. Given discrepant findings, the anticipation of and response to social rewards should be further evaluated, particularly in the context of intervention outcome. We hypothesized that individual characteristics may help predict neural changes from pre- to post-intervention. Methods: Thirteen adolescents with ASD received the Program for the Education and Enrichment of Relational Skills (PEERS) intervention for 16 weeks; reward-related EEG was collected before and after intervention. Fourteen TD adolescents were tested at two timepoints but did not receive intervention. Event-related potentials were calculated to measure anticipation of (stimulus-preceding negativity; SPN) and response to (reward-related positivity; RewP) social and non-social rewards. Additionally, measures of social responsiveness, social skills, and intervention-engagement were collected. Group differences were analyzed as well as individual differences using prediction models. Result: Parent-reported social responsiveness and social skills improved in adolescents with ASD after participation in PEERS. ASD adolescents displayed marginally decreased anticipation of social rewards at post-intervention compared to pre-intervention. Regression models demonstrated that older adolescents and those with lower parent-reported social motivation prior to participation in PEERS displayed marginally increased social reward anticipation (more robust SPN) from pre- to post-intervention. Participants who displayed more parent-reported social motivation before intervention and were more actively engaged in the PEERS intervention evidenced increased social reward processing (more robust RewP) from pre- to post-intervention. Conclusion: Findings suggest that there may be differences in saliency between wanting/anticipating social rewards vs. liking/responding to social rewards in individuals with ASD. Our findings support the hypothesis that identification of individual differences may predict which adolescents are poised to benefit the most from particular interventions. As such, reported findings set the stage for the advancement of "precision medicine." This investigation is a critical step forward in our ability to understand and predict individual response to interventions in individuals with ASD.

EEG/ERP as a pragmatic method to expand the reach of infant-toddler neuroimaging in HBCD: Promises and challenges

Though electrophysiological measures (EEG and ERP) offer complementary information to MRI and a variety of advantages for studying infants and young children, these measures have not yet been included in large cohort studies of neurodevelopment. This review summarizes the types of EEG and ERP measures that could be used in the HEALthy Brain and Cognitive Development (HBCD) study, and the promises and challenges in doing so. First, we provide brief overview of the use of EEG/ERP for studying the developing brain and discuss exemplar findings, using resting or baseline EEG measures as well as the ERP mismatch negativity (MMN) as exemplars. We then discuss the promises of EEG/ERP such as feasibility, while balancing challenges such as ensuring good signal quality in diverse children with different hair types. We then describe an ongoing multi-site EEG data harmonization from our groups. We discuss the process of alignment and provide preliminary usability data for both resting state EEG data and auditory ERP MMN in diverse samples including over 300 infants and toddlers. Finally, we provide recommendations and considerations for the HBCD study and other studies of neurodevelopment.

Looking for consistency in an uncertain world: test-retest reliability of neurophysiological and behavioral readouts in autism

BACKGROUND

Autism spectrum disorders (ASD) are associated with altered sensory processing and perception. Scalp recordings of electrical brain activity time-locked to sensory events (event-related potentials; ERPs) provide precise information on the time-course of related altered neural activity, and can be used to model the cortical loci of the underlying neural networks. Establishing the test-retest reliability of these sensory brain responses in ASD is critical to their use as biomarkers of neural dysfunction in this population.

METHODS

EEG and behavioral data were acquired from 33 children diagnosed with ASD aged 6-9.4 years old, while they performed a child-friendly task at two different time-points, separated by an average of 5.2 months. In two blocked conditions, participants responded to the occurrence of an auditory target that was either preceded or not by repeating visual stimuli. Intraclass correlation coefficients (ICCs) were used to assess test-retest reliability of measures of sensory (auditory and visual) ERPs and performance, for the two experimental conditions. To assess the degree of reliability of the variability of responses within individuals, this analysis was performed on the variance of the measurements, in addition to their means. This yielded a total of 24 measures for which ICCs were calculated.

RESULTS

The data yielded significant good ICC values for 10 of the 24 measurements. These spanned across behavioral and ERPs data, experimental conditions, and mean as well as variance measures. Measures of the visual evoked responses accounted for a disproportionately large number of the significant ICCs; follow-up analyses suggested that the contribution of a greater number of trials to the visual compared to the auditory ERP partially accounted for this.

CONCLUSIONS

This analysis reveals that sensory ERPs and related behavior can be highly reliable across multiple measurement time-points in ASD. The data further suggest that the inter-trial and inter-participant variability reported in the ASD literature likely represents replicable individual participant neural processing differences. The stability of these neuronal readouts supports their use as biomarkers in clinical and translational studies on ASD. Given the minimum interval between test/retest sessions across our cohort, we also conclude that for the tested age-range of ~ 6 to 9.4 years, these reliability measures are valid for at least a 3-month interval. Limitations related to EEG task demands and study length in the context of a clinical trial are considered.

Resting state EEG in youth with ASD: age, sex, and relation to phenotype

BACKGROUND

Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy.

METHODS

We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations.

RESULTS

Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD.

CONCLUSIONS

Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

Potential Novel Therapies for Neurodevelopmental Diseases Targeting Oxidative Stress

Neurodevelopmental disorders are a category of diseases that is not yet fully understood. Due to their common traits and pathways, often it is difficult to differentiate between them based on their symptoms only. A series of hypotheses are trying to define their etiology, such as neuroinflammation, neurodegeneration, and immunology, but none have managed to explain their multifactorial manifestation. One feature that may link all theories is that of oxidative stress, with a redox imbalance as well as several other markers of oxidative damage (on lipids, proteins, and nucleic acids) being observed in both postmortem samples of the brain of patients with schizophrenia and autism spectrum disorders. However, the implication of oxidative stress in pathology is still distrustfully looked upon. For this purpose, in the current paper, we were interested in reviewing the implications of oxidative stress in these disorders as well as the impact of N-acetylcysteine on the oxidative status with a focus on the glutathione level and N-methyl-D-aspartate receptor. We were also interested in finding papers targeting the use of antioxidant properties of different plant extracts.

Informant (Dis)Agreement on Ratings of Challenging Behaviors and Social Communication in Preschool Children With Autism Spectrum Disorder

Purpose Cross-informant ratings are considered best practice for assessing children with autism spectrum disorder (ASD). However, informant disagreement often occurs, which can pose significant challenges to various aspects of clinical services. This study explored the degree of parent and speech-language pathologist (SLP) agreement on ratings of challenging behaviors and social communication skills in preschool children with ASD. Method Fifty-eight informant ratings of challenging behaviors and social communication skills were collected from parents and SLPs on the same 29 preschool children with ASD (M = 49.93 months, SD = 11.67 months) using the Pervasive Developmental Disorder Behavior Inventory. Parent versus SLP group rating comparisons were assessed with paired t tests and Cohen's d effect sizes. Intraclass correlation coefficients were calculated to examine interrater reliability between individual parent and SLP ratings. Bland-Altman plots were generated to evaluate informant agreement across the entire range of Pervasive Developmental Disorder Behavior Inventory composite scores. Results Group comparisons indicated that parents rated arousal regulation problems as more severe than SLPs, with no other group differences observed. Parents and SLPs exhibited poor agreement on ratings of challenging behaviors; however, moderate to good agreement was observed for social communication ratings. Conclusions These results highlight the importance of including parents in the assessment and treatment planning process for preschool children with ASD, as parents may report key behavioral concerns that clinicians may not otherwise observe. Understanding behaviors that may be more prone to informant disagreement has implications for promoting a shared understanding of behavioral concerns and treatment targets between parents and clinicians.

Refining biomarker evaluation in ASD

This commentary reflects on reasonable biomarker expectations in ASD by addressing three key questions: What is a biomarker? What is required for a biomarker in ASD? How can biomarkers be useful in ASD? In addressing these queries, a path forward emerges based on clear definition of the objective for any given ASD biomarker and evaluation of each biomarker relative to current best practices.

Brief Report: Preliminary Evidence of the N170 as a Biomarker of Response to Treatment in Autism Spectrum Disorder

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by primary difficulties in social function. Individuals with ASD display slowed neural processing of faces, as indexed by the latency of the N170, a face-sensitive event-related potential. Currently, there are no objective biomarkers of ASD useful in clinical care or research. Efficacy of behavioral treatment is currently evaluated through subjective clinical impressions. To explore whether the N170 might have utility as an objective index of treatment response, we examined N170 before and after receipt of an empirically validated behavioral treatment in children with ASD. Method: Electroencephalography (EEG) data were obtained on a preliminary cohort of preschool-aged children with ASD before and after a 16-week course of PRT and in a subset of participants in waitlist control (16-weeks before the start of PRT) and follow-up (16-weeks after the end of PRT). EEG was recorded while participants viewed computer-generated faces with neutral and fearful affect. Results: Significant reductions in N170 latency to faces were observed following 16 weeks of PRT intervention. Change in N170 latency was not observed in the waitlist-control condition. Conclusions: This exploratory study offers suggestive evidence that N170 latency may index response to behavioral treatment. Future, more rigorous, studies in larger samples are indicated to evaluate whether the N170 may be useful as a biomarker of treatment response.

Sensory processing and P300 event-related potential correlates of stimulant response in children with attention-deficit/hyperactivity disorder: A critical review

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder associated with considerable impairment in psychiatric and functional domains. Although stimulant medication can reduce core symptoms of inattention, hyperactivity, and impulsivity, a subgroup of patients does not respond to this intervention. A precision medicine approach has been proposed, whereby biomarkers are used to identify an effective treatment approach for a given individual. This review synthesizes the existing literature on event-related potential (ERP) correlates of stimulant response in children diagnosed with ADHD, with the goal of evaluating the potential for ERP to inform precision medicine care in this population. Forty-three articles were examined and results tentatively suggest that stimulant medications normalize the amplitude of the P300 component, and this is also associated with behavioral improvement. In contrast, results generally indicate that stimulants do not significantly alter early processing components, although there are some exceptions to this finding. Implications for research, theory, and clinical work are considered and concrete recommendations for future directions are provided. While recognizing limitations of existing literature (e.g., homogenous samples, variable methodologies), we conclude that ERP methods represent a promising approach for precision medicine care of patients with ADHD.

The N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD

Atypical neural response to faces is thought to contribute to social deficits in autism spectrum disorder (ASD). Compared to typically developing (TD) controls, individuals with ASD exhibit delayed brain responses to upright faces at a face-sensitive event-related potential (ERP), the N170. Given observed differences in patterns of visual attention to faces, it is not known whether slowed neural processing may simply reflect atypical looking to faces. The present study manipulated visual attention to facial features to examine whether directed attention to the eyes normalizes N170 latency in ASD. ERPs were recorded in 30 children and adolescents with ASD as well as 26 TD children and adolescents. Results replicated prior findings of shorter N170 latency to the eye region of the face in TD individuals. In contrast, those with ASD did not demonstrate modulation of N170 latency by point of regard to the face. Group differences in latency were most pronounced when attention was directed to the eyes. Results suggest that well-replicated findings of N170 delays in ASD do not simply reflect atypical patterns of visual engagement with experimental stimuli. These findings add to a body of evidence indicating that N170 delays are a promising marker of atypical neural response to social information in ASD. LAY SUMMARY: This study looks at how children's and adolescents' brains respond when looking at different parts of a face. Typically developing children and adolescents processed eyes faster than other parts of the face, whereas this pattern was not seen in ASD. Children and adolescents with ASD processed eyes more slowly than typically developing children. These findings suggest that observed inefficiencies in face processing in ASD are not simply reflective of failure to attend to the eyes.

Leveraging large genomic datasets to illuminate the pathobiology of autism spectrum disorders

"Big data" approaches in the form of large-scale human genomic studies have led to striking advances in autism spectrum disorder (ASD) genetics. Similar to many other psychiatric syndromes, advances in genotyping technology, allowing for inexpensive genome-wide assays, has confirmed the contribution of polygenic inheritance involving common alleles of small effect, a handful of which have now been definitively identified. However, the past decade of gene discovery in ASD has been most notable for the application, in large family-based cohorts, of high-density microarray studies of submicroscopic chromosomal structure as well as high-throughput DNA sequencing-leading to the identification of an increasingly long list of risk regions and genes disrupted by rare, de novo germline mutations of large effect. This genomic architecture offers particular advantages for the illumination of biological mechanisms but also presents distinctive challenges. While the tremendous locus heterogeneity and functional pleiotropy associated with the more than 100 identified ASD-risk genes and regions is daunting, a growing armamentarium of comprehensive, large, foundational -omics databases, across species and capturing developmental trajectories, are increasingly contributing to a deeper understanding of ASD pathology.

Identifying Subgroups of Patients With Autism by Gene Expression Profiles Using Machine Learning Algorithms

Objectives: The identification of subgroups of autism spectrum disorder (ASD) may partially remedy the problems of clinical heterogeneity to facilitate the improvement of clinical management. The current study aims to use machine learning algorithms to analyze microarray data to identify clusters with relatively homogeneous clinical features. Methods: The whole-genome gene expression microarray data were used to predict communication quotient (SCQ) scores against all probes to select differential expression regions (DERs). Gene set enrichment analysis was performed for DERs with a fold-change >2 to identify hub pathways that play a role in the severity of social communication deficits inherent to ASD. We then used two machine learning methods, random forest classification (RF) and support vector machine (SVM), to identify two clusters using DERs. Finally, we evaluated how accurately the clusters predicted language impairment. Results: A total of 191 DERs were initially identified, and 54 of them with a fold-change >2 were selected for the pathway analysis. Cholesterol biosynthesis and metabolisms pathways appear to act as hubs that connect other trait-associated pathways to influence the severity of social communication deficits inherent to ASD. Both RF and SVM algorithms can yield a classification accuracy level >90% when all 191 DERs were analyzed. The ASD subtypes defined by the presence of language impairment, a strong indicator for prognosis, can be predicted by transcriptomic profiles associated with social communication deficits and cholesterol biosynthesis and metabolism. Conclusion: The results suggest that both RF and SVM are acceptable options for machine learning algorithms to identify AD subgroups characterized by clinical homogeneity related to prognosis.

Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development

Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individual's EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.