Journal of Neurodevelopmental Disorders

Published by Springer Nature
Online ISSN: 1866-1955
Print ISSN: 1866-1947
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Pathways of convergent validity estimates
Background Unusual responses to sensory stimuli are considered a diagnostic symptom of autism spectrum disorder with mounting research efforts put towards understanding, characterizing, and treating such symptoms. Methods This paper examines self and caregiver report tools used to measure sensory features in ASD through a systematic review of the psychometric evidence for their use. A total of 31 empirical papers were reviewed across 20 assessment tools. Substantial differences were identified in the specific sensory features defined across assessment tools. Sensory assessment questionnaires were evaluated against quality psychometric evidence criteria to provide a use recommendation. Results Five assessments were identified to be “appropriate with conditions,” while no sensory assessment tools were identified to have sufficient quality psychometric evidence to provide a recommendation of “Appropriate” for measuring sensory features in ASD. Conclusion Evidence from this review highlights potentially significant shortcomings among the current methods used to measure sensory features in ASD and suggests the need for more efforts in developing psychometrically sound sensory assessment tools for use in ASD populations.
 
Power when performance is operationalized as GSV versus V-scale. A The results for each impairment level in the younger age range conditions. B The results for each impairment level in the older age range conditions. Impairment level refers to SD below average, such that 5 corresponds to the most impaired condition. Power is the proportion of 5000 simulations where the t test of the group difference controlling for baseline score had a p value < .05. The dotted reference line is at 90%
Simulation design. PBO = placebo; TRT = active treatment; ANCOVA = analysis of covariance; GSV = growth scale value (ability score); range = age range condition (3–6 years or 12–16 years); imp = impairment condition (average V-scale for sample of 1, 2, 3, 4, or 5 SD below average); es = effect size condition (zero or large standardized effect). Baseline and follow-up scores were drawn from a bivariate normal distribution, where the within-subject correlation was fixed at r = 0.8 and the mean and standard deviation were defined based on the age range and impairment conditions. For the PBO condition, the mean at baseline and follow-up were identical. For the TRT condition, the baseline mean was identical to PBO, but the follow-up mean was shifted by a factor depending on the effect size condition. Baseline age of the simulated participants was drawn from a uniform distribution, and V-scale scores were obtained using a lookup table with age and the simulated GSV score. Finally, the effect of group on follow-up score was calculated based on ANCOVA, controlling for baseline score. This process was repeated 5000 times (large effect size) or 10,000 times (zero effect size) for each combination of conditions
Background For genetic conditions associated with neurodevelopmental disorder (GCAND), developmental domains such as motor ability, thinking and learning, social abilities, and communication are potential intervention targets. Performance on measures of developmental concepts can be expressed using several types of scores. Norm-referenced scores are intended for the diagnostic context, allowing for the identification of impairment relative to age-based expectations, and can exhibit dramatic floor effects when used in individuals with more significant limitations. Person ability scores, which are derived via Rasch analysis or item response theory, are available on many standardized tests and are intended to measure within-person change. However, they have not been used or evaluated as primary endpoints in GCAND clinical trials. In this study, we simulated a series of parallel-arm clinical trials under several chronological age and impairment conditions, to compare empirically the power and type I error rate of operationalizing test performance using ability scores rather than norm-referenced scores. Results Using the Vineland Adaptive Behavior Scales as the example, we demonstrated an advantage in statistical power of ability scores over norm-referenced scores at extreme levels of impairment. This advantage was at least partially driven by floor effects in norm-referenced scores. For simulated conditions where impairment was less severe, ability scores outperformed norm-referenced scores, but they were more similar. The type I error rate closely approximated the nominal type I error rate of 5% for both scores. Conclusion The results of this simulation demonstrate a substantial power and interpretative advantage of ability scores over norm-referenced scores for studies of GCAND that will enroll participants with high levels of impairment. These results are expected to generalize to studies of developmental concepts, regardless of the etiology or specific test. However, the relative advantage of ability scores is expected to be even greater for tests with a higher floor than the Vineland.
 
Longitudinal performance on cognitive measures. Spaghetti plots depicting cognitive performance over time on select cognitive measures. A Stanford-Binet Intelligence Scales Full Scale IQ. B Sanford-Binet Intelligence Scales Working Memory Index. C Wechsler Intelligence Scale for Children – Fifth Edition Processing Speed Index. D Expressive Vocabulary Test. Each gray line represents a single subject, while each colored line represents the group trend over time (blue: PTEN-no ASD; red: Macro-ASD; green: PTEN-ASD). Fragmented subject lines indicate the partial follow-up data
Background Individuals with PTEN hamartoma tumor syndrome (PHTS) demonstrate a distinct neurobehavioral profile suggesting primary disruption of frontal lobe symptoms, with more severe cognitive deficits in those with associated autism spectrum disorder (ASD) that extend to other areas of neurobehavioral function as well (e.g., adaptive behavior, sensory deficits). The current study sought to characterize longitudinal neurobehavioral profiles in individuals with PHTS who completed serial assessments (2–3 evaluations) over a 2-year time period. Methods Comprehensive neurobehavioral evaluations were conducted on 92 participants (age range 6–21) with PHTS and/or ASD. Spaghetti plots and linear mixed effects models were used to visualize the individual patient profiles and group trends and examine the group differences in cognitive/behavioral test scores over time. Practice-adjusted reliable change indices (RCIs) and standardized regression-based change scores (SRBs) were calculated for those measures in the battery with adequate sample sizes and test–retest reliabilities for future use in assessing neurobehavioral change in children and young adults with PHTS. Results Wide individual differences were observed at baseline across all measures. Encouragingly, baseline differences between patient groups persisted at the same magnitude over a 2-year time period with no differences in longitudinal neurobehavioral profiles within any one group. Test–retest reliabilities were generally high, ranging from 0.62 to 0.97, and group mean change from baseline to 12 months was small (range − 3.8 to 3.7). A Microsoft Excel calculator was created that clinicians and researchers can use to automatically calculate RCI and SRB thresholds at both 80% and 90% confidence intervals using test scores from a given child or young adult with PHTS. Conclusions Our results suggest that the neurobehavioral phenotypes observed in individuals with PHTS remain relatively stable over time, even in those with ASD. The RCIs and SRBs provided can be used in future research to examine patient outcomes at the individual level as well as to detect negative deviations from the expected trajectory that can be used to inform intervention strategies.
 
Endocannabinoid-mediated signaling in the CNS in the normal state. In a normal state with FMR1 protein present, (1) FMRP supports expression of DGKκ and traffics DAGL mRNA, which results in (2) normal production of 2-AG and release into the synaptic cleft, which (3) stimulates presynaptic CB1 receptors resulting in (4) retrograde inhibitory signaling and (5) optimal release of glutamate and activation of mGluR5 receptors and (6) modulation of GABAergic function. 2-AG, 2-arachidonoylglycerol; β-arr, β-arrestin; CB1, cannabinoid type 1 receptor; CNS, central nervous system; DAG, diacylglycerol; DAGL, diacylglycerol lipase; DGKκ, diacylglycerol kinase-κ; FMRP, FMR1 protein; G, G proteins; GABA, γ-aminobutyric acid; mGluR5, group I metabotropic glutamate receptor 5; mRNA, messenger RNA; PA, phosphatidic acid; PIP2, phosphatidylinositol-4,5-bisphosphate; PLC, phospholipase C
ECS dysfunction in FXS due to lack of FMRP. Lack of FMRP in FXS leads to (1) reduced expression of DGKκ and abnormal trafficking of DAGL mRNA, which results in (2) ectopic/abnormal production of 2-AG and release into the synaptic cleft, which causes (3) β-arrestin recruitment, internalization, and desensitization of CB1 receptors, resulting in (4) loss of the normal retrograde inhibitory signaling and (5) increased glutamate release and activation of mGluR5 receptors and (6) altered GABA release. 2-AG, 2-arachidonoylglycerol; β-arr, β-arrestin; CB1, cannabinoid type 1 receptor; CNS, central nervous system; DAG, diacylglycerol; DAGL, diacylglycerol lipase; DGKκ, diacylglycerol kinase-κ; ECS, endocannabinoid system; FMRP, FMR1 protein; FXS, fragile X syndrome; G, G proteins; GABA, γ-aminobutyric acid; mGluR5, group I metabotropic glutamate receptor 5; mRNA, messenger RNA; PA, phosphatidic acid; PIP2, phosphatidylinositol-4,5-bisphosphate; PLC, phospholipase C
Proposed mechanism(s) of action of cannabidiol on the ECS in FXS. Treatment of FXS with cannabidiol is proposed to lead to (1) cannabidiol’s acting as a negative allosteric modulator (NAM) at the CB1 receptors, resulting in (2) reduction of β-arrestin recruitment, along with prevention of internalization and desensitization of CB1 receptors in the presence of ectopic/abnormal 2-AG, which leads to (3) restoration of retrograde inhibitory signaling and (4) reduction in glutamate release and activation of mGluR5 receptors and (5) restoration of GABAergic function. 2-AG, 2-arachidonoylglycerol; β-arr, β-arrestin; CB1, cannabinoid type 1 receptor; CBD, cannabidiol; DAG, diacylglycerol; DAGL, diacylglycerol lipase; DGKκ, diacylglycerol kinase-κ; ECS, endocannabinoid system; FMRP, FMR1 protein; FXS, fragile X syndrome; G, G proteins; GABA, γ-aminobutyric acid; mGluR5, group I metabotropic glutamate receptor 5; PA, phosphatidic acid; PIP2, phosphatidylinositol-4,5-bisphosphate; PLC, phospholipase C
Multiple lines of evidence suggest a central role for the endocannabinoid system (ECS) in the neuronal development and cognitive function and in the pathogenesis of fragile X syndrome (FXS). This review describes the ECS, its role in the central nervous system, how it is dysregulated in FXS, and the potential role of cannabidiol as a treatment for FXS. FXS is caused by deficiency or absence of the fragile X messenger ribonucleoprotein 1 (FMR1) protein, FMRP, typically due to the presence of >200 cytosine, guanine, guanine sequence repeats leading to methylation of the FMR1 gene promoter. The absence of FMRP, following FMR1 gene-silencing, disrupts ECS signaling, which has been implicated in FXS pathogenesis. The ECS facilitates synaptic homeostasis and plasticity through the cannabinoid receptor 1, CB1, on presynaptic terminals, resulting in feedback inhibition of neuronal signaling. ECS-mediated feedback inhibition and synaptic plasticity are thought to be disrupted in FXS, leading to overstimulation, desensitization, and internalization of presynaptic CB1 receptors. Cannabidiol may help restore synaptic homeostasis by acting as a negative allosteric modulator of CB1, thereby attenuating the receptor overstimulation, desensitization, and internalization. Moreover, cannabidiol affects DNA methylation, serotonin 5HT1A signal transduction, gamma-aminobutyric acid receptor signaling, and dopamine D2 and D3 receptor signaling, which may contribute to beneficial effects in patients with FXS. Consistent with these proposed mechanisms of action of cannabidiol in FXS, in the CONNECT-FX trial the transdermal cannabidiol gel, ZYN002, was associated with improvements in measures of social avoidance, irritability, and social interaction, particularly in patients who are most affected, showing ≥90% methylation of the FMR1 gene.
 
CONSORT flow diagram for initial randomized clinical trials, 4-year follow-up study, and 7-year follow-up study
Axial view of eight corpus callosum tracts generated by tractography (anterior/top of figure to posterior/bottom of figure). Pink, rostrum; purple, genu; dark blue, body (prefrontal); light blue, body (premotor); green, body (central); yellow, body (parietal); orange, body (temporal); red, splenium
Scatterplots illustrating significant whole-group correlations (not corrected for multiple comparisons) between corpus callosum splenium ODI and executive function performance at follow-up evaluation. Lower ODI values are associated with better performance
Scatterplot illustrating a significant whole-group correlation between corpus callosum splenium ODI (imaged at follow-up evaluation) and number of dysmorphic facial features identified as baseline evaluation. Lower ODI values are associated with fewer dysmorphic features
Background Fetal alcohol spectrum disorder (FASD) is a lifelong condition. Early interventions targeting core neurocognitive deficits have the potential to confer long-term neurodevelopmental benefits. Time-targeted choline supplementation is one such intervention that has been shown to provide neurodevelopmental benefits that emerge with age during childhood. We present a long-term follow-up study evaluating the neurodevelopmental effects of early choline supplementation in children with FASD approximately 7 years on average after an initial efficacy trial. Methods The initial study was a randomized, double-blind, placebo-controlled trial of choline vs. placebo in 2.5 to 5 year olds with FASD. Participants in this long-term follow-up study include 18 children (9 placebo; 9 choline) seen 7 years on average following initial trial completion. The mean age at follow-up was 11.0 years old. Diagnoses were 28% fetal alcohol syndrome (FAS), 28% partial FAS, and 44% alcohol-related neurodevelopmental disorder. The follow-up included measures of executive functioning and an MRI scan. Results Children who received choline had better performance on several tasks of lower-order executive function (e.g., processing speed) and showed higher white matter microstructure organization (i.e., greater axon coherence) in the splenium of the corpus callosum compared to the placebo group. Conclusions These preliminary findings, although exploratory at this stage, highlight potential long-term benefits of choline as a neurodevelopmental intervention for FASD and suggest that choline may affect white matter development, representing a potential target of choline in this population. Trial registration Prior to enrollment, this trial was registered with clinicaltrials.gov ( NCT01149538 ) on June 23, 2010.
 
Social Attention During Object Engagement (SADOE) is lower among children with versus without ASD. (A) Total time engaged with focal toys was not significantly different between groups (bars show mean ± 1 SE). (B) Proportions of time each group spent looking at social and nonsocial targets during engagement with the focal toys. (C) Non-ASD children made significantly more social looks per minute during engagement with the focal toys than children with ASD (p = .023; bars show mean ± 1 SE). non-ASD, without ASD; ASD, autism spectrum disorder; SE, standard error. N = 8 each for non-ASD and ASD groups
Social Attention During Object Engagement (SADOE) is greater among both high-likelihood (HL) and low-likelihood (LL) toddlers without ASD compared to toddlers with ASD. (A) Total time engaged with focal toys was not significantly different between groups (bars show mean ± 1 SE). B) Proportions of time each group spent looking at social and nonsocial targets during engagement with the focal toys. (C) HL- and LL- groups made more social looks per minute during play with the focal toys compared to the HL + group with ASD (LL- vs. HL + , p = .007; HL- vs. HL + , p < .001), with no significant difference in LL- versus HL- groups (p = .75; bars show mean ± 1 SE). Single asterisk indicates p < .01. Double asterisk indicates p < .001. (D) Number of social looks per minute by type for each group. Among social look types, the HL + group was lower than both the LL- and HL- groups specifically for spontaneous social looks (p’s ≤ .012). (E) Social look types as in (D) but expressed as a percentage of the total number of social looks. The HL + group displayed a lower percentage of spontaneous looks than the LL- and HL- groups (p’s ≤ .02). LL-, low-likelihood of ASD without a diagnosis (N = 19); HL-, high-likelihood of ASD without a diagnosis (N = 33); HL + , high-likelihood of ASD with a diagnosis (N = 15). ASD, autism spectrum disorder; SE, standard error
Social Attention During Object Engagement (SADOE) correlates with other measures of social behavior. (A) SADOE was negatively correlated with the ADOS CSS score (ρ = -.50, p < .001). (B) SADOE was positively correlated with CSBS social score (r = .49, p = .001). ASD, autism spectrum disorder; non-ASD, without ASD; ADOS, Autism Diagnostic Observation Schedule; CSS, calibrated severity score; CSBS, Communication and Symbolic Behavior Scales
Background A central challenge in preclinical research investigating the biology of autism spectrum disorder (ASD) is the translation of ASD-related social phenotypes across humans and animal models. Social orienting, an observable, evolutionarily conserved behavior, represents a promising cross-species ASD phenotype given that disrupted social orienting is an early-emerging ASD feature with evidence for predicting familial recurrence. Here, we adapt a competing-stimulus social orienting task from domesticated dogs to naturalistic play behavior in human toddlers and test whether this approach indexes decreased social orienting in ASD. Methods Play behavior was coded from the Autism Diagnostic Observation Schedule (ADOS) in two samples of toddlers, each with and without ASD. Sample 1 ( n = 16) consisted of community-ascertained research participants, while Sample 2 involved a prospective study of infants at a high or low familial liability for ASD ( n = 67). Coding quantified the child’s looks towards the experimenter and caregiver, a social stimulus, while playing with high-interest toys, a non-social stimulus. A competing-stimulus measure of “Social Attention During Object Engagement” (SADOE) was calculated by dividing the number of social looks by total time spent playing with toys. SADOE was compared based on ASD diagnosis and differing familial liability for ASD. Results In both samples, toddlers with ASD exhibited significantly lower SADOE compared to toddlers without ASD, with large effect sizes (Hedges’ g ≥ 0.92) driven by a lower frequency of child-initiated spontaneous looks. Among toddlers at high familial likelihood of ASD, toddlers with ASD showed lower SADOE than toddlers without ASD, while SADOE did not differ based on presence or absence of familial ASD risk alone. SADOE correlated negatively with ADOS social affect calibrated severity scores and positively with the Communication and Symbolic Behavior Scales social subscale. In a binary logistic regression model, SADOE alone correctly classified 74.1% of cases, which rose to 85.2% when combined with cognitive development. Conclusions This work suggests that a brief behavioral measure pitting a high-interest nonsocial stimulus against the innate draw of social partners can serve as a feasible cross-species measure of social orienting, with implications for genetically informative behavioral phenotyping of social deficits in ASD and other neurodevelopmental disorders.
 
FMRP level per sampled hair follicle by subject clustered by group and sex
Scatterplot of mean FMRP level across sampled hair follicles and PBMC FMRP level clustered by group and sex
Background Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability in males and the most common single gene cause of autism. This X-linked disorder is caused by an expansion of a trinucleotide CGG repeat (> 200 base pairs) on the promotor region of the fragile X messenger ribonucleoprotein 1 gene (FMR1) . This leads to the deficiency or absence of the encoded protein, fragile X messenger ribonucleoprotein 1 (FMRP). FMRP has a central role in the translation of mRNAs involved in synaptic connections and plasticity. Recent studies have demonstrated the benefit of therapeutics focused on reactivation of the FMR1 locus towards improving key clinical phenotypes via restoration of FMRP and ultimately disease modification. A key step in future studies directed towards this effort is the establishment of proof of concept (POC) for FMRP reactivation in individuals with FXS. For this, it is key to determine the feasibility of repeated collection of tissues or fluids to measure FMR1 mRNA and FMRP. Methods Individuals, ages 3 to 22 years of age, with FXS and those who were typically developing participated in this single-site pilot clinical biomarker study. The repeated collection of hair follicles was compared with the collection of blood and buccal swabs for detection of FMR1 mRNA and FMRP and related molecules. Results There were n = 15 participants, of whom 10 had a diagnosis of FXS (7.0 ± 3.56 years) and 5 were typically developing (8.2 ± 2.77 years). Absolute levels of FMRP and FMR1 mRNA were substantially higher in healthy participants compared to full mutation and mosaic FXS participants and lowest in the FXS boys. Measurement of FMR1 mRNA and FMRP levels by any method did not show any notable variation by collection location at home versus office across the various sample collection methodologies of hair follicle, blood sample, and buccal swab. Conclusion Findings demonstrated that repeated sampling of hair follicles in individuals with FXS, in both, home, and office settings, is feasible, repeatable, and can be used for measurement of FMR1 mRNA and FMRP in longitudinal studies.
 
Background Neurotypical individuals categorize items even during ultra-rapid presentations (20 ms; see Thorpe et al. Nature 381: 520, 1996). In cognitively able autistic adults, these semantic categorization processes may be impaired and/or may require additional time, specifically for the categorization of atypical compared to typical items. Here, we investigated how typicality structures influence ultra-rapid categorization in cognitively able autistic and neurotypical male adults. Methods Images representing typical or atypical exemplars of two different categories (food/animals) were presented for 23.5 vs. 82.3 ms (short/long). We analyzed detection rates, reaction times, and the event-related potential components dN150, N1, P2, N2, and P3 for each group. Results Behavioral results suggest slower and less correct responses to atypical compared to typical images. This typicality effect was larger for the category with less distinct boundaries (food) and observed in both groups. However, electrophysiological data indicate a different time course of typicality effects, suggesting that neurotypical adults categorize atypical images based on simple features (P2), whereas cognitively able autistic adults categorize later, based on arbitrary features of atypical images (P3). Conclusions We found evidence that all three factors under investigation — category, typicality, and presentation time — modulated specific aspects of semantic categorization. Additionally, we observed a qualitatively different pattern in the autistic adults, which suggests that they relied on different cognitive processes to complete the task.
 
Flow chart depicting estimation steps for the single-method and multimethod latent models. Model evaluation metrics are described in the circles, ordered from the most quantitative (top) to the most qualitative (bottom) in nature
Plots of means for unrestricted models with 2–4 classes. The two-class solution converged on a single mode, while the three- and four-class models converged on multiple modes. The two best modes (i.e., with the highest loglikelihoods) are depicted. Profile means (y-axis) are standardized within the sample. SSRT stop-signal reaction time, VRT go-reaction time variability, FSIQ full-scale IQ, Digit Span Fwd digit span forward, Digit Span Bkwd digit span backward. Note recurring features in the data, such as the shape of class 1 (“low average”) across models, the shape of class 3 (“low control/high memory”) in the top three- and four-class models, and the shape of class 4 (“high FSIQ”) in the two best four-class models
Plots of means and 95% confidence intervals for the unrestricted means (left) and fixed parameter (right) 5-class models. The fixed parameter model specifies a class with means of −0.5 (Low Average) and +0.5 (High Average). Numbers in parentheses are estimated proportions for each class (unrestricted/restricted). Note these values generally do not shift much, implying stability of the models. Profile means (y-axis) are standardized within the sample. SSRT stop-signal reaction time, VRT go-reaction time variability, FSIQ full-scale IQ, Digit Span Fwd digit span forward, Digit Span Bkwd digit span backward. Class proportions are depicted in parentheses (unrestricted model/restricted model)
EEG spectral power profiles by neuropsychological latent class. Y-axis values are log-transformed absolute spectral power
Background Heterogeneity in neurodevelopmental disorders, and attention deficit hyperactivity disorder (ADHD) in particular, is increasingly identified as a barrier to identifying biomarkers and developing standards for clinical care. Clustering analytic methods have previously been used across a variety of data types with the goal of identifying meaningful subgroups of individuals with ADHD. However, these analyses have often relied on algorithmic approaches which assume no error in group membership and have not made associations between patterns of behavioral, neurocognitive, and genetic indicators. More sophisticated latent classification models are often not utilized in neurodevelopmental research due to the difficulty of working with these models in small sample sizes. Methods In the current study, we propose a framework for evaluating mixture models in sample sizes typical of neurodevelopmental research. We describe a combination of qualitative and quantitative model fit evaluation procedures. We test our framework using latent profile analysis (LPA) in a case study of 120 children with and without ADHD, starting with well-understood neuropsychological indicators, and building toward integration of electroencephalogram (EEG) measures. Results We identified a stable five-class LPA model using seven neuropsychological indicators. Although we were not able to identify a stable multimethod indicator model, we did successfully extrapolate results of the neuropsychological model to identify distinct patterns of resting EEG power across five frequency bands. Conclusions Our approach, which emphasizes theoretical as well as empirical evaluation of mixture models, could make these models more accessible to clinical researchers and may be a useful approach to parsing heterogeneity in neurodevelopmental disorders.
 
Examples of photographs in the Static Faces paradigm: (1) happy face and (2) angry face (taken from KDEF; [25]). Screenshots of video clips in the Dynamic Social Information paradigm: (3) single face and (4) multiple faces
Affect recognition in SCT vs. TD group and age groups. SCT, sex chromosome trisomies; TD, typically developing. ηp², effect size; , standard deviation (only lower bar depicted)
Background About 1:650–1000 children are born with an extra X or Y chromosome (47,XXX; 47,XXY; 47,XYY), which results in a sex chromosome trisomy (SCT). This international cross-sectional study was designed to investigate gaze towards faces and affect recognition during early life of children with SCT, with the aim to find indicators for support and treatment. Methods A group of 101 children with SCT (aged 1–7 years old; Mage= 3.7 years) was included in this study, as well as a population-based sample of 98 children without SCT (Mage= 3.7). Eye gaze patterns to faces were measured using an eye tracking method that quantifies first fixations and fixation durations on eyes of static faces and fixation durations on eyes and faces in a dynamic paradigm (with two conditions: single face and multiple faces). Affect recognition was measured using the subtest Affect Recognition of the NEPSY-II neuropsychological test battery. Recruitment and assessment took place in the Netherlands and the USA. Results Eye tracking results reveal that children with SCT show lower proportion fixation duration on faces already from the age of 3 years, compared to children without SCT. Also, impairments in the clinical range for affect recognition were found (32.2% of the SCT group scored in the well below average range). Conclusions These results highlight the importance to further explore the development of social cognitive skills of children with SCT in a longitudinal design, the monitoring of affect recognition skills, and the implementation of (preventive) interventions aiming to support the development of attention to social important information and affect recognition.
 
Background It is unclear whether atypical patterns of facial expression production metrics in autism reflect the dynamic and nuanced nature of facial expressions across people or a true diagnostic difference. Furthermore, the heterogeneity observed across autism symptomatology suggests a need for more adaptive and personalized social skills programs. Towards this goal, it would be useful to have a more concrete and empirical understanding of the different expressiveness profiles within the autistic population and how they differ from neurotypicals. Methods We used automated facial coding and an unsupervised clustering approach to limit inter-individual variability in facial expression production that may have otherwise obscured group differences in previous studies, allowing an “apples-to-apples” comparison between autistic and neurotypical adults. Specifically, we applied k-means clustering to identify subtypes of facial expressiveness in an autism group (N = 27) and a neurotypical control group (N = 57) separately. The two most stable clusters from these analyses were then further characterized and compared based on their expressiveness and emotive congruence to emotionally charged stimuli. Results Our main finding was that a subset of autistic adults in our sample show heightened spontaneous facial expressions irrespective of image valence. We did not find evidence for greater incongruous (i.e., inappropriate) facial expressions in autism. Finally, we found a negative trend between expressiveness and emotion recognition within the autism group. Conclusion The results from our previous study on self-reported empathy and current expressivity findings point to a higher degree of facial expressions recruited for emotional resonance in autism that may not always be adaptive (e.g., experiencing similar emotional resonance regardless of valence). These findings also build on previous work indicating that facial expression intensity is not diminished in autism and suggest the need for intervention programs to focus on emotion recognition and social skills in the context of both negative and positive emotions.
 
Background Neurofibromatosis type 1 (NF1) is a genetic disorder often associated with cognitive dysfunctions, including a high occurrence of deficits in visuoperceptual skills. The neural underpinnings of these visuoperceptual deficits are not fully understood. We used steady-state visual evoked potentials (SSVEPs) to investigate possible alterations in the synchronization of neural activity in the occipital cortex of children with NF1. Methods SSVEPs were measured using electroencephalography and compared between children with NF1 ( n = 28) and neurotypical controls ( n = 28) aged between 4 and 13 years old. SSVEPs were recorded during visual stimulation with coloured icons flickering at three different frequencies (6 Hz, 10 Hz, and 15 Hz) and analyzed in terms of signal-to-noise ratios. A mixed design ANCOVA was performed to compare SSVEP responses between groups at the three stimulation frequencies. Pearson’s correlations with levels of intellectual functioning as well as with symptoms of ADHD, ASD and emotional/behavioral problems were performed. The impact of psychostimulant medication on the SSVEP responses was analyzed in a subset of the NF1 group ( n = 8) with paired t-tests. Results We observed reduced signal-to-noise ratios of the SSVEP responses in children with NF1. The SSVEP responses were negatively correlated with symptoms of inattention and with symptoms of emotional/behavioral problems in the NF1 group. The SSVEP response generated by the lowest stimulation frequency (i.e., 6 Hz) was rescued with the intake of psychostimulant medication. Conclusions Impaired processing of rhythmic visual stimulation was evidenced in children with NF1 through measures of SSVEP responses. Those responses seem to be more reduced in children with NF1 who exhibit more symptoms of inattention and emotional/behavioral problems in their daily life. SSVEPs are potentially sensitive electrophysiological markers that could be included in future studies investigating the impact of medication on brain activity and cognitive functioning in children with NF1.
 
The Vineland Adaptive Behavior Scale (VABS) is a standardized assessment of adaptive behavior skills across four domains: Communication, Motor, Daily Living Skills, and Socialization. The chronological age at the time of evaluation (years) is plotted against the estimated age-equivalent of the following subdomains: expressive language skills, personal daily living skills, interpersonal relationship skills, and fine motor skills. The motor domains of the VABS have a ceiling of approximately 8 years. The gray lines represent the cross-section of the chronological age and age-equivalent at 5 years for expressive language skills, personal daily living skills, and interpersonal relationship skills, and 4 years for fine motor skills
Background SLC6A1-related disorder is a recently identified, rare, genetic neurodevelopmental disorder that is associated with loss-of-function variants in SLC6A1. This gene encodes GABA transporter type I that is responsible for re-uptake of GABA from the synapse into the pre-synaptic terminal or circulating neuroglia. Based upon retrospective review of published cases and available research databases including Epi25 collective and SLC6A1 Connect patient database, the phenotypic spectrum is broad and includes developmental delay, epilepsy, and autism or autistic traits. SLC6A1 is one of the genes included in the Simons Searchlight registry, which includes standardized data collection across genetically identified neurodevelopmental conditions. Methods In this study, we compare parent-report measures of phenotypic features in the Simons Searchlight registry to previously published, provider-reported cases to assess if parent-report measures are consistent with what has been reported in the literature. Results There were 116 participants in the provider-reported dataset compared to 43 individuals in the caregiver-reported dataset. Carriers in Searchlight had 83 unique pathogenic or likely pathogenic variants in SLC6A1, which were predominantly missense or nonsense variants. There was no significant difference between groups for the prevalence of developmental delay, ASD, or ADHD. Caregivers more often reported hypotonia, while epilepsy was slightly more frequently reported by providers. Conclusions We propose that standardized parent-report data collection methods are consistent with provider reports on many core features of SLC6A1-related disorder. The availability of patient registries and standardized natural history studies may fill an important need in clinical trial readiness programs, with larger sample sizes than smaller published case series.
 
Evidence of any dysfunction in pleiotropy network biological processes in individuals with ASD. Plotted are the proportion of individuals with autism spectrum disorder (ASD) with evidence of dysfunction (DBP > 0) versus no evidence of dysfunction (DBP = 0) in biological processes with overrepresentation of ASD and/or sleep duration (SD) genes in the ASD-SD protein–protein interaction network
Genetic risk scores reflecting the level of dysfunction in pleiotropy network biological processes in individuals with ASD. Shown are the distributions of raw scores, across individuals with autism spectrum disorder (ASD), for each process with significantly more PDV-containing genes encoding proteins in the ASD-sleep duration protein–protein interaction network. No scores were normally distributed (p ≤ 8.46 × 10–48)
Network of proteins encoded by autism spectrum disorder (ASD) and sleep duration (SD) genes implicated in cerebral cortex development. Shown is the protein–protein interaction network predicted for the products of genes with predicted damaging variants identified in individuals with ASD that are assigned to the Gene Ontology biological process of “GO:0,021,987: cerebral cortex development”. Proteins are colored according to the associated condition as follows: blue = ASD-related protein, yellow = SD-related protein, green = both ASD, and SD-related protein
Association between dysfunctional cerebral cortex development scores and sleep duration. Plotted is the linear prediction for the relationship between dysfunctional biological process (DBP) scores for cerebral cortex development (GO:0,021,987) and reported sleep duration in minutes. 95% confidence intervals around fitted lines are indicated in gray; Beta coefficients (β) and the corresponding p value are provided
Background Numerous genes are implicated in autism spectrum disorder (ASD). ASD encompasses a wide-range and severity of symptoms and co-occurring conditions; however, the details of how genetic variation contributes to phenotypic differences are unclear. This creates a challenge for translating genetic evidence into clinically useful knowledge. Sleep disturbances are particularly prevalent co-occurring conditions in ASD, and genetics may inform treatment. Identifying convergent mechanisms with evidence for dysfunction that connect ASD and sleep biology could help identify better treatments for sleep disturbances in these individuals. Methods To identify mechanisms that influence risk for ASD and co-occurring sleep disturbances, we analyzed whole exome sequence data from individuals in the Simons Simplex Collection ( n = 2380). We predicted protein damaging variants (PDVs) in genes currently implicated in either ASD or sleep duration in typically developing children. We predicted a network of ASD-related proteins with direct evidence for interaction with sleep duration-related proteins encoded by genes with PDVs. Overrepresentation analyses of Gene Ontology-defined biological processes were conducted on the resulting gene set. We calculated the likelihood of dysfunction in the top overrepresented biological process. We then tested if scores reflecting genetic dysfunction in the process were associated with parent-reported sleep duration. Results There were 29 genes with PDVs in the ASD dataset where variation was reported in the literature to be associated with both ASD and sleep duration. A network of 108 proteins encoded by ASD and sleep duration candidate genes with PDVs was identified. The mechanism overrepresented in PDV-containing genes that encode proteins in the interaction network with the most evidence for dysfunction was cerebral cortex development (GO:0,021,987). Scores reflecting dysfunction in this process were associated with sleep durations; the largest effects were observed in adolescents ( p = 4.65 × 10 –3 ). Conclusions Our bioinformatic-driven approach detected a biological process enriched for genes encoding a protein–protein interaction network linking ASD gene products with sleep duration gene products where accumulation of potentially damaging variants in individuals with ASD was associated with sleep duration as reported by the parents. Specifically, genetic dysfunction impacting development of the cerebral cortex may affect sleep by disrupting sleep homeostasis which is evidenced to be regulated by this brain region. Future functional assessments and objective measurements of sleep in adolescents with ASD could provide the basis for more informed treatment of sleep problems in these individuals.
 
Flowchart of study design, N = 62. Notes: ASD, autism spectrum disorders; CLDS-R, Child Language Disorder Scale-Revised; MCDI-T, Mandarin-Chinese version of the MacArthur-Bates Communicative Developmental Inventories Toddler; M-CHAT, Modified Checklist for Autism in Toddlers
Background Late talking (LT) in toddlers is a risk factor for language weakness that may interfere with the development of using language to regulate behavior and emotion and contribute to the development of behavior problems from early childhood. This study examined the temporal stability of parent-reported behavior problems among Mandarin-speaking LT toddlers from ages 2 to 4 in Taiwan. Methods Thirty-one LT and 31 typical language development (TLD) toddlers were assessed for their vocabulary production at age 2 with the Words and Sentences Forms of the MacArthur-Bates Communicative Developmental Inventories Toddler Form (Taiwan version). Additionally, participants’ receptive and expressive language abilities were assessed using the receptive and expressive language subscales of the Bayley Scales of Infant and Toddler Development, Third Edition. At age 4, the Child Language Disorder Scale-Revised was applied and included the two core subtests for auditory comprehension and expressive communication. At ages 2 and 4 years, behavior problems were assessed with the Child Behavior Checklist. Results There was a higher percentage of participants with persistent behavior problems among LT toddlers than among TLD toddlers. Moreover, toddlers with larger vocabularies were less likely to develop withdrawal behaviors by preschool age. Conclusions This study supported the temporal stability of parent-reported behavior problems among LT toddlers across early childhood. Early identification of and intervention for behavior problems associated with LT in toddlerhood is essential to alleviate their behavior problems later in preschool years.
 
Taxonomy of Speech Disorders (adapted from https://www.asha.org/practice-portal/clinical-topics/articulation-and-phonology/). Note: “Motor Speech Disorders-Not Otherwise Specified” does not appear on this diagram
Cortical and subcortical areas related to spoken language. Underlined regions express FOXP2. Regions in italics are structurally or functionally abnormal in KE family members
Illustration of the DIVA model and its neural correlates
Background Speech is the most common modality through which language is communicated, and delayed, disordered, or absent speech production is a hallmark of many neurodevelopmental and genetic disorders. Yet, speech is not often carefully phenotyped in neurodevelopmental disorders. In this paper, we argue that such deep phenotyping, defined as phenotyping that is specific to speech production and not conflated with language or cognitive ability, is vital if we are to understand how genetic variations affect the brain regions that are associated with spoken language. Speech is distinct from language, though the two are related behaviorally and share neural substrates. We present a brief taxonomy of developmental speech production disorders, with particular emphasis on the motor speech disorders childhood apraxia of speech (a disorder of motor planning) and childhood dysarthria (a set of disorders of motor execution). We review the history of discoveries concerning the KE family, in whom a hereditary form of communication impairment was identified as childhood apraxia of speech and linked to dysfunction in the FOXP2 gene. The story demonstrates how instrumental deep phenotyping of speech production was in this seminal discovery in the genetics of speech and language. There is considerable overlap between the neural substrates associated with speech production and with FOXP2 expression, suggesting that further genes associated with speech dysfunction will also be expressed in similar brain regions. We then show how a biologically accurate computational model of speech production, in combination with detailed information about speech production in children with developmental disorders, can generate testable hypotheses about the nature, genetics, and neurology of speech disorders. Conclusions Though speech and language are distinct, specific types of developmental speech disorder are associated with far-reaching effects on verbal communication in children with neurodevelopmental disorders. Therefore, detailed speech phenotyping, in collaboration with experts on pediatric speech development and disorders, can lead us to a new generation of discoveries about how speech development is affected in genetic disorders.
 
Concept overview of ADHD with comorbidities algorithm. Details for cases and controls are outlined in methods and supplementary tables
ADHD with all comorbidities. Number of ADHD cases in isolation and with comorbidities
Background In over half of pediatric cases, ADHD presents with comorbidities, and often, it is unclear whether the symptoms causing impairment are due to the comorbidity or the underlying ADHD. Comorbid conditions increase the likelihood for a more severe and persistent course and complicate treatment decisions. Therefore, it is highly important to establish an algorithm that identifies ADHD and comorbidities in order to improve research on ADHD using biorepository and other electronic record data. Methods It is feasible to accurately distinguish between ADHD in isolation from ADHD with comorbidities using an electronic algorithm designed to include other psychiatric disorders. We sought to develop an EHR phenotype algorithm to discriminate cases with ADHD in isolation from cases with ADHD with comorbidities more effectively for efficient future searches in large biorepositories. We developed a multi-source algorithm allowing for a more complete view of the patient’s EHR, leveraging the biobank of the Center for Applied Genomics (CAG) at Children’s Hospital of Philadelphia (CHOP). We mined EHRs from 2009 to 2016 using International Statistical Classification of Diseases and Related Health Problems (ICD) codes, medication history and keywords specific to ADHD, and comorbid psychiatric disorders to facilitate genotype-phenotype correlation efforts. Chart abstractions and behavioral surveys added evidence in support of the psychiatric diagnoses. Most notably, the algorithm did not exclude other psychiatric disorders, as is the case in many previous algorithms. Controls lacked psychiatric and other neurological disorders. Participants enrolled in various CAG studies at CHOP and completed a broad informed consent, including consent for prospective analyses of EHRs. We created and validated an EHR-based algorithm to classify ADHD and comorbid psychiatric status in a pediatric healthcare network to be used in future genetic analyses and discovery-based studies. Results In this retrospective case-control study that included data from 51,293 subjects, 5840 ADHD cases were discovered of which 46.1% had ADHD alone and 53.9% had ADHD with psychiatric comorbidities. Our primary study outcome was to examine whether the algorithm could identify and distinguish ADHD exclusive cases from ADHD comorbid cases. The results indicate ICD codes coupled with medication searches revealed the most cases. We discovered ADHD-related keywords did not increase yield. However, we found including ADHD-specific medications increased our number of cases by 21%. Positive predictive values (PPVs) were 95% for ADHD cases and 93% for controls. Conclusion We established a new algorithm and demonstrated the feasibility of the electronic algorithm approach to accurately diagnose ADHD and comorbid conditions, verifying the efficiency of our large biorepository for further genetic discovery-based analyses. Trial registration ClinicalTrials.gov, NCT02286817. First posted on 10 November 2014. ClinicalTrials.gov, NCT02777931. First posted on 19 May 2016. ClinicalTrials.gov, NCT03006367. First posted on 30 December 2016. ClinicalTrials.gov, NCT02895906. First posted on 12 September 2016.
 
Histogram of symptom onset by age
Number of patients with neurodiagnostic study abnormalities (n). None: n = 43 (60%)
Axial T2 FLAIR sequence demonstrating T2 signal prolongation along the gray, white junction bilaterally
Axial GRE sequence demonstrating symmetric hypodensities in the bilateral deep gray nuclei consistent with calcification
Background Down syndrome regression disorder is a symptom cluster consisting of neuropsychiatric regression without cause. This study evaluated the incidence of neurodiagnostic abnormalities in individuals with Down syndrome regression disorder and determined if abnormalities are indicative of responses to therapeutic intervention. Methods A retrospective, multi-center, case-control study was performed. Patients were required to have subacute onset and the presence of four of five symptom groups present (cognitive decline, expressive language, sleep derangement, loss of ability to perform activities of daily living, and/or a new movement disorder) and no other explanation for symptoms. Results Individuals with Down syndrome regression disorder were comparable to a cohort of individuals with only Down syndrome although had higher rates of autoimmune disease ( p = 0.02, 95%CI 1.04–1.75). Neurodiagnostic abnormalities were found on EEG ( n = 19, 26%), neuroimaging ( n = 16, 22%), and CSF ( n = 9, 17%). Pleocytosis was appreciated in five cases, elevated total protein in nine, elevated IgG index in seven, and oligoclonal bands in two. Testing within 2 years of symptom onset was more likely to have neurodiagnostic abnormalities ( p = 0.01, 95%CI 1.64–37.06). In individuals with neurodiagnostic abnormalities, immunotherapy was nearly four times more likely to have a therapeutic effect than in those without neurodiagnostic abnormalities (OR 4.11, 95%CI 1.88–9.02). In those with normal neurodiagnostic studies ( n = 43), IVIg was effective in 14 of 17 (82%) patients as well although other immunotherapies were uniformly ineffective. Conclusions This study reports the novel presence of neurodiagnostic testing abnormalities in individuals with Down syndrome regression disorder, providing credence to this symptom cluster potentially being of neurologic and/or neuroimmunologic etiology.
 
Themes and sub-themes of the behavioural phenotype of SYNGAP1-related ID
Themes and sub-themes of the sensory profile of SYNGAP1-related ID
Background SYNGAP1-related intellectual disability (ID) is a recently described neurodevelopmental disorder that is caused by pathogenic variation in the SYNGAP1 gene. To date, the behavioural characteristics of this disorder have mainly been highlighted via the prevalence of existing diagnoses in case series. We set out to detail the behavioural features of this disorder by undertaking interviews with those who have a child with SYNGAP1-related ID to allow them to describe their child’s behaviour. Methods We conducted 27 semi-structured interviews with parents and caregivers which covered basic information (e.g., age, gender), family history, perinatal history, past medical history, developmental history, epilepsy, behavioural history, and a general description of their child’s behaviour. Results Using a mixed quantitative and qualitative approach, the responses from the parents indicated that those with SYNGAP1-related ID showed high rates of autism spectrum disorder (52%), difficulties with fine and gross motor skills, delays in language development, and a high prevalence of epilepsy (70%). A qualitative analysis highlighted their general behaviour affected the themes of daily living skills, distress-related behaviours, emotional regulation, difficulties with change, a lack of danger awareness, and sensory differences. Sensory features described involved auditory, visual, tactile, gustatory, and proprioceptive themes. Conclusions Our findings and behavioural descriptions provide important insights as well as implications for the diagnosis and care of those with SYNGAP1-related ID.
 
Background Regulator of calcineurin 1 ( RCAN1 ) is overexpressed in Down syndrome (DS), but RCAN1 levels are also increased in Alzheimer’s disease (AD) and normal aging. AD is highly comorbid among individuals with DS and is characterized in part by progressive neurodegeneration that resembles accelerated aging. Importantly, abnormal RCAN1 levels have been demonstrated to promote memory deficits and pathophysiology that appear symptomatic of DS, AD, and aging. Anomalous diurnal rest-activity patterns and circadian rhythm disruptions are also common in DS, AD, and aging and have been implicated in facilitating age-related cognitive decline and AD progression. However, no prior studies have assessed whether RCAN1 dysregulation may also promote the age-associated alteration of rest-activity profiles and circadian rhythms, which could in turn contribute to neurodegeneration in DS, AD, and aging. Methods The present study examined the impacts of RCAN1 deficiency and overexpression on the photic entrainment, circadian periodicity, intensity and distribution, diurnal patterning, and circadian rhythmicity of wheel running in young (3–6 months old) and aged (9–14 months old) mice of both sexes. Results We found that daily RCAN1 levels in the hippocampus and suprachiasmatic nucleus (SCN) of light-entrained young mice are generally constant and that balanced RCAN1 expression is necessary for normal circadian locomotor activity rhythms. While the light-entrained diurnal period was unaltered, RCAN1-null and RCAN1-overexpressing mice displayed lengthened endogenous (free-running) circadian periods like mouse models of AD and aging. In light-entrained young mice, RCAN1 deficiency and overexpression also recapitulated the general hypoactivity, diurnal rest-wake pattern fragmentation, and attenuated amplitudes of circadian activity rhythms reported in DS, preclinical and clinical AD, healthily aging individuals, and rodent models thereof. Under constant darkness, RCAN1-null and RCAN1-overexpressing mice displayed altered locomotor behavior indicating circadian clock dysfunction. Using the Dp(16)1Yey/+ ( Dp16 ) mouse model for DS, which expresses three copies of Rcan1 , we found reduced wheel running activity and rhythmicity in both light-entrained and free-running young Dp16 mice like young RCAN1-overexpressing mice. Critically, these diurnal and circadian deficits were rescued in part or entirely by restoring Rcan1 to two copies in Dp16 mice. We also found that RCAN1 deficiency but not RCAN1 overexpression altered protein levels of the clock gene Bmal1 in the SCN. Conclusions Collectively, this study’s findings suggest that both loss and aberrant gain of RCAN1 precipitate anomalous light-entrained diurnal and circadian activity patterns emblematic of DS, AD, and possibly aging.
 
Workflow of ASD phenotype ontology development
Gender and age distribution in ASD patient cohort. Some patients were diagnosed at very early age, which may represent an artifact of retrospective assignment of ICD codes in EHRs
Comparison of t-SNE clustering analysis for top 2000 ASD patients and 2000 psychiatric (non-ASD) patients using our terminology set (a) and using Lingren’s terminology set (b). Since not all the patients contain the ASD vocabulary developed by Lingren et al., we only analyzed patients containing these terms. Results showed that our terminology set separates ASD patients from general psychiatric (non-ASD) patients much better than Lingren’s list. From the t-SNE plot, we can see ASD patients can be further divided into 4 subgroups; however, one group of ASD patients (cluster 4) is mixed with non-ASD psychiatric patients
Mapping subgroup of ASD patients to DSM-5 guideline. a The percentage of subgroups of ASD patients in each cluster that maps to DSM-5 individual criteria. b As an illustrative example, we quantified individual patient’s ASD characteristics to DSM-5 guideline for patients in cluster 1 and cluster 4
Five levels of ASD phenotype ontology developed in our study. A Example of ASD phenotype ontology. B Examples of our ASD phenotype ontology displayed in the Protégé software for ontology analysis
Background Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients’ clinical narratives. Methods To address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method. Results Through a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders. Conclusion Our ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making.
 
Rett syndrome natural history study (RNHS) participants selected for analysis (n = 1380). Both = subjects participating in both the first and second iterations; cohort 1 = subjects only participating in the first iteration; cohort 2 = subjects only participating in the second iteration
Responses to: How often is your child anxious or nervous? From 662 participants in the second iteration of the RNHS. First iteration = subjects enrolled 2006–2015; second iteration = subjects enrolled 2015–2019
Frequency of anxious/nervous behavior based on direct report of anxiolytic treatment. Frequency values: 0 = “never”, 1 = “occasionally”, 2 = “frequently”, 3 = “very frequently”, 4 = “constantly”
Frequency of anxiolytic use reported in medication logs by age group. First iteration = subjects enrolled 2006–2015; second iteration = subjects enrolled 2015–2019
Frequency of anxiolytic use reported in medication logs by MECP2 pathogenic variant. MECP2 variant percent in parentheses indicates overall frequency of the variant in the entire study population. †Severe variant = R106W, R168X, R255X, R270X, early truncations, large deletions, and splice site. First iteration = subjects enrolled 2006–2015; second iteration = subjects enrolled 2015–2019
Background Rett syndrome (RTT) is a neurodevelopmental disorder most often related to a pathogenic variant in the X-linked MECP2 gene. Internalizing behaviors appear to be common, but standard methods of diagnosing anxiety are not readily applied in this population which typically has cognitive impairment and limited expressive language. This study aims to describe the frequency of anxiety-like behavior and anxiolytic treatments along with associated clinical features in individuals with RTT. Methods Parental reports and medication logs provided data from 1380 females with RTT participating in two iterations of the multicenter U.S. RTT Natural History Study (RNHS) from 2006 to 2019. Results Most participants with RTT (77.5%) had at least occasional anxious or nervous behavior. Anxiety was reported to be the most troublesome concern for 2.6%, and within the top 3 concerns for 10.0%, of participants in the second iteration. Parents directly reported treatment for anxious or nervous behavior in 16.6% of participants in the second iteration with most reporting good control of the behavior (71.6%). In the medication logs of both RNHS iterations, the indication of anxiety was listed for a similar number of participants (15% and 14.5%, respectively). Increased use of anxiolytics and selective serotonin reuptake inhibitors (SSRIs) was related to more frequent anxiety-like behaviors (P < 0.001), older age (P < 0.001), and mild MECP2 variants (P = 0.002). Conclusion Anxiety-like behavior is frequent at all ages and is a significant parental concern in RTT. Older individuals and those with mild MECP2 variants are more likely to be treated with medications. Better diagnosis and treatment of anxiety in RTT should be a goal of both future studies and clinical care. Trial registration NCT00299312 and NCT02738281
 
Age and genetic diagnosis of study participants
Diagnostic journey timeline for patients receiving developmental diagnosis before genetic diagnosis
Diagnostic journey timeline for patients receiving genetic diagnosis before developmental diagnosis
Background The development of advanced genetic technologies has resulted in rapid identification of genetic etiologies of neurodevelopmental disorders (NDDs) and has transformed the classification and diagnosis of various NDDs. However, diagnostic genetics has far outpaced our ability to provide timely medical counseling, guidance, and care for patients with genetically defined NDDs. These patients and their caregivers present with an unmet need for care coordination across multiple domains including medical, developmental, and psychiatric care and for educational resources and guidance from care professionals. After a genetic diagnosis is made, families also face several barriers in access to informed diagnostic evaluations and medical support. Methods As part of Care and Research in Neurogenetics (CARING), a multidisciplinary clinical program for children and adults with neurogenetic disorders, we conducted qualitative clinical interviews about the diagnostic journey of families. This included the overall timeline to receiving diagnoses, experiences before and after diagnosis, barriers to care, and resources that helped them to navigate the diagnostic process. Results A total of 37 interviews were conducted with parents of children ages 16 months to 33 years. Several key themes were identified: (1) delays between initial caregiver observations and formal developmental or genetic diagnoses; (2) practical barriers to clinical evaluation and care, including long wait times for an appointment, lack of insurance coverage, availability of local evaluations, transportation difficulties, and native language differences; (3) the importance of being part of a patient advocacy group to help navigate the diagnostic journey; and (4) unique challenges faced by adults (18 years or older). Conclusions Families of children with complex neurodevelopmental and genetic disabilities face numerous challenges in finding adequate medical care and services for their child. They experience considerable delays in receiving timely diagnoses and face significant barriers that further delay the process of receiving access to services needed for the child’s continued care. The gaps indicated in this study speak to the need for more comprehensive coordination of care for patients with intellectual and developmental disabilities, as well as the development of systematic, disorder-specific resources both for providers and families in order to improve patient outcomes.
 
An overview of the ML process and potential applications to IDDs. Various types of data (e.g., clinical, behavior, neuroimaging, and multi-omics) are usually recorded in IDD cohorts. These data sets are first individually processed and cleaned to remove noise and extract relevant biological signals (feature extraction). Then, an AI/ML algorithm is trained to find rules and patterns in the integrated dataset. The choice of the algorithm usually depends on the formulation of the biological problem and other data-set specific factors (discussed in Machine learning methods and applications to IDDs section of the main text). Typically, the model can be tested objectively with independent datasets or prior knowledge. A correctly evaluated and validated model is often generalizable, and such models have a variety of clinical and laboratory applications in IDDs
A typical machine learning workflow. While there are generally four main broad steps to develop a ML strategy (shaded boxes here and discussed comprehensively in the main text), a user is often left with multiple choices to select from a variety of tools/algorithms available for each step. The choice mainly depends on the dataset-specific factors and desired outcomes from the model. The workflow presented here can possibly guide decisions when choosing algorithms for developing and testing a data analysis strategy
Applications of ML/AI-driven research. Some of the key studies we discussed in Machine learning methods and applications to IDDs section of this review are summarized. It is clear that the application of AI/ML (colored edges with references) to multimodal data types (depicted in the middle layer) has the potential to be useful in enhancing clinical decision-making (top layer) as well as developing a mechanistic understanding of IDDs (bottom layer)
Intellectual and Developmental Disabilities (IDDs), such as Down syndrome, Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth or early childhood. IDDs are characterized by significant impairment in intellectual and adaptive functioning, and both genetic and environmental factors underpin IDD biology. Molecular and genetic stratification of IDDs remain challenging mainly due to overlapping factors and comorbidity. Advances in high throughput sequencing, imaging, and tools to record behavioral data at scale have greatly enhanced our understanding of the molecular, cellular, structural, and environmental basis of some IDDs. Fueled by the “big data” revolution, artificial intelligence (AI) and machine learning (ML) technologies have brought a whole new paradigm shift in computational biology. Evidently, the ML-driven approach to clinical diagnoses has the potential to augment classical methods that use symptoms and external observations, hoping to push the personalized treatment plan forward. Therefore, integrative analyses and applications of ML technology have a direct bearing on discoveries in IDDs. The application of ML to IDDs can potentially improve screening and early diagnosis, advance our understanding of the complexity of comorbidity, and accelerate the identification of biomarkers for clinical research and drug development. For more than five decades, the IDDRC network has supported a nexus of investigators at centers across the USA, all striving to understand the interplay between various factors underlying IDDs. In this review, we introduced fast-increasing multi-modal data types, highlighted example studies that employed ML technologies to illuminate factors and biological mechanisms underlying IDDs, as well as recent advances in ML technologies and their applications to IDDs and other neurological diseases. We discussed various molecular, clinical, and environmental data collection modes, including genetic, imaging, phenotypical, and behavioral data types, along with multiple repositories that store and share such data. Furthermore, we outlined some fundamental concepts of machine learning algorithms and presented our opinion on specific gaps that will need to be filled to accomplish, for example, reliable implementation of ML-based diagnosis technology in IDD clinics. We anticipate that this review will guide researchers to formulate AI and ML-based approaches to investigate IDDs and related conditions.
 
The recent National Institute of Health (NIH) INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) initiative has bolstered capacity for the current increase in clinical trials involving individuals with Down syndrome (DS). This new NIH funding mechanism offers new opportunities to expand and develop novel approaches in engaging and effectively enrolling a broader representation of clinical trials participants addressing current medical issues faced by individuals with DS. To address this opportunity, the NIH assembled leading clinicians, scientists, and representatives of advocacy groups to review existing methods and to identify those areas where new approaches are needed to engage and prepare DS populations for participation in clinical trial research. This paper summarizes the results of the Clinical Trial Readiness Working Group that was part of the INCLUDE Project Workshop: Planning a Virtual Down Syndrome Cohort Across the Lifespan Workshop held virtually September 23 and 24, 2019.
 
Background Computational phenotypes are most often combinations of patient billing codes that are highly predictive of disease using electronic health records (EHR). In the case of rare diseases that can only be diagnosed by genetic testing, computational phenotypes identify patient cohorts for genetic testing and possible diagnosis. This article details the validation of a computational phenotype for PTEN hamartoma tumor syndrome (PHTS) against the EHR of patients at three collaborating clinical research centers: Boston Children's Hospital, Children's National Hospital, and the University of Washington. Methods A combination of billing codes from the International Classification of Diseases versions 9 and 10 (ICD-9 and ICD-10) for diagnostic criteria postulated by a research team at Cleveland Clinic was used to identify patient cohorts for genetic testing from the clinical data warehouses at the three research centers. Subsequently, the EHR—including billing codes, clinical notes, and genetic reports—of these patients were reviewed by clinical experts to identify patients with PHTS. Results The PTEN genetic testing yield of the computational phenotype, the number of patients who needed to be genetically tested for incidence of pathogenic PTEN gene variants, ranged from 82 to 94% at the three centers. Conclusions Computational phenotypes have the potential to enable the timely and accurate diagnosis of rare genetic diseases such as PHTS by identifying patient cohorts for genetic sequencing and testing.
 
Frequency of individual adaptive skill patterns based on significant differences between Vineland Adaptive Behavior Scales, third edition domain standard scores. C communication domain, DL daily living skills domain, S socialization domain, “=”, difference not statistically significant, “<” or “>”, difference is statistically significant. *Group level-pattern: S > DL > C
Background There is substantial variability in adaptive skills among individuals with Down syndrome. Few studies, however, have focused on the early developmental period or on the potential sources of variability in adaptive skills. This study characterizes adaptive skills in young children with Down syndrome and investigates child characteristics associated with adaptive skills. Methods Participants were 44 children with Down syndrome ranging in age from 2.50 to 7.99 years ( M = 4.66 years, SD = 1.46). The Vineland Adaptive Behavior Scales-3 (VABS-3) Comprehensive Interview Form was used to assess adaptive behavior in the three core domains: socialization, daily living, and communication skills. Caregivers also reported on motor skills and autism spectrum disorder symptoms. Child cognitive abilities were assessed. Results Analyses comparing mean standard score performance across the three VABS-3 core domains demonstrated significant differences between all pairs of domains, resulting in a group-level pattern of socialization > daily living > communication skills. At the individual level, 10 different patterns of relative strength and weakness were identified, with only 18% of participants evidencing significant differences between adaptive skill domain standard scores corresponding to the group-level pattern of significant differences. Child characteristics (cognitive abilities, motor skills, and autism spectrum disorder symptoms) were significantly associated with VABS-3 adaptive domain standard scores. Conclusion These findings underscore the importance of individualizing intervention programs focused on improving the adaptive skills of young children with Down syndrome based on consideration of the child’s relative adaptive strengths and weaknesses.
 
Serial reaction time performances in neurofibromatosis type 1 (NF1) and typically developing children (TD). Vertical bars represent interindividual variability (standard errors)
Areas showing significant positive connectivity with the striatal seeds in the somatomotor network (in blue) and in the parietofrontal network (in orange) (p < 0.001, family-wise error-corrected, cluster size > 100)
Cerebral regions of the cortico-striatal functional circuits that expressed any difference between NF1 and typically developing children. The right angular gyrus (AG) is significantly more connected with the somatomotor striatal seed “striatum 2” of Choi’s functional atlas in NF1 children than in typically developing children. Age, sex, and GCOR are used as covariables; voxel threshold p < 0.001 p-uncorrected and cluster threshold p < 0.05
Correlation between the M-ABC score and the average connectivity values within a significant cluster between the NF1 and TD groups
Introduction Neurofibromatosis type 1 (NF1) is considered a model of neurodevelopmental disorder because of the high frequency of learning deficits, especially developmental coordination disorder. In neurodevelopmental disorder, Nicolson and Fawcett formulated the hypothesis of an impaired procedural learning system that has its origins in cortico-subcortical circuits. Our aim was to investigate the relationship between cortico-striatal connectivity and procedural perceptual-motor learning performance and motor skills in NF1 children. Methods Seventeen NF1 and 18 typically developing children aged between 8 and 12 years old participated in the study. All were right-handed and did not present intellectual or attention deficits. In all children, procedural perceptual-motor learning was assessed using a bimanual visuo-spatial serial reaction time task (SRTT) and motor skills using the Movement Assessment Battery for Children (M-ABC). All participants underwent a resting-state functional MRI session. We used a seed-based approach to explore cortico-striatal connectivity in somatomotor and frontoparietal networks. A comparison between the groups’ striato-cortical connectivity and correlations between connectivity and learning (SRTT) and motor skills (M-ABC) were performed. Results At the behavioral level, SRTT scores are not significantly different in NF1 children compared to controls. However, M-ABC scores are significantly impaired within 9 patients (scores below the 15th percentile). At the cerebral level, NF1 children present a higher connectivity in the cortico-striatal regions mapping onto the right angular gyrus compared to controls. We found that the higher the connectivity values between these regions, differentiating NF1 and controls, the lower the M-ABC scores in the whole sample. No correlation was found for the SRTT scores. Conclusion NF1 children present atypical hyperconnectivity in cortico-striatal connections. The relationship with motor skills could suggest a sensorimotor dysfunction already found in children with developmental coordination disorder. These abnormalities are not linked to procedural perceptual-motor learning assessed by SRTT.
 
Subcortical volume differences between 47,XXX women and healthy controls. Effect sizes for significant differences in volumes of subcortical brain regions between 47,XXX subjects and healthy controls. Negative effect sizes indicate lower subcortical brain volume in 47,XXX subjects compared to healthy controls
Cortical surface area differences between 47,XXX women and healthy controls. Effect sizes for significant differences in surface area of cortical brain regions between 47,XXX subjects and healthy controls. Negative effect sizes indicate lower cortical surface area in 47,XXX subjects compared to healthy controls
Correlation between cortical thickness regions and social cognition in 47,XXX. Correlations for significant relationships between cortical thickness regions and ERT scores in 47,XXX subjects
Summary of ERT and SRS-A T-scores
Background Triple X syndrome (47,XXX) is a relatively common sex chromosomal aneuploidy characterized by the presence of a supernumerary X chromosome in females and has been associated with a variable cognitive, behavioural and psychiatric phenotype. 47,XXX may serve as a suitable model for studying the effect of genetic architecture on brain morphology. Previous studies have shown alterations in brain structure in 47,XXX particularly in childhood and adolescence. In this study, we examined subcortical and cortical brain morphology in adult women with 47,XXX using ultra-high field 7T MRI. Given previous evidence of impaired social functioning and emotion recognition in adults with 47,XXX, we also investigated the relationship of these functions with brain morphology. Methods Twenty-one adult women with 47,XXX and 22 age- and sex-matched healthy controls were included. Structural T1-weighted images were acquired using a 7-Tesla magnetic resonance scanner. Measures of subcortical brain volumes, cortical surface area and thickness, and cortical folding were obtained and compared between the groups using general linear models. Additionally, we examined potential relationships between brain outcome measures and social functioning and social cognition in 47,XXX using correlation analyses. Results Adults with 47,XXX showed lower volumes of the thalamus, caudate, putamen, hippocampus, nucleus accumbens and pallidum, and larger lateral ventricle volumes. Lower surface area was found in the superior frontal gyrus and superior temporal gyrus in 47,XXX participants compared to healthy controls. Altered cortical thickness and cortical folding were not present in 47,XXX. Cortical thickness was associated with social cognition in 47,XXX. Conclusions Results suggest that a supernumerary X chromosome in females affects subcortical and lateral ventricle volumes, and cortical surface area in adulthood. 47,XXX may serve as a suitable model for studying genetic influences on structural brain morphology across developmental stages in order to understand neurobiological mechanisms underlying cognitive and behavioural impairments.
 
LiCl treatment restores normal synapse numbers in Tbr1layer5 mutant mice. Immunofluorescence (IF) was used to detect excitatory (A, C) and inhibitory (B, D) synapses onto dendrites from mPFCx of Tbr1wildtype (Rbp4-cre::tdTomatof/+; green), Tbr1layer5 CKOs (Tbr1f/f::Rbp4-cre::tdTomatof/+; orange) (n = 10 dendrites). Synapses were measured (i) 24 h and (ii) 4 weeks after injection with saline or LiCl at P180. Excitatory synapses were analyzed by VGlut1⁺ boutons and PSD95⁺ clusters co-localizing onto the dendrites from layer 5 neurons of mPFCx of Tbr1wildtype (green) and Tbr1layer5CKO (orange) mice 24 h (at P181; A, A’) and 4 weeks (P208; C, C’) after saline and/or LiCl was administered. Mann-Whitney ****p < 0.0001, ns = not significant. Inhibitory synaptic density was measured by VGat⁺ boutons and Gephyrin⁺ clusters co-localizing onto dendrites of mPFCx of Tbr1wildtype (green) and Tbr1layer5CKO (orange) 24 h (at P181; B, B’) and 4 weeks (P208; D, D’) after saline and/or LiCl was administered. Mann-Whitney ****p < 0.0001, ns = not significant. The Fiji ImageJ software was used to process confocal images for quantification. Two-tailed T-test with Mann-Whitney’s correction was used for pairwise comparisons
LiCl rescues dendritic spine density deficit in mPFCx of Tbr1layer5 CKOs at P180. Rbp4-cre::tdTomatof/+ allele was used to label the dendrites of layer 5 neurons (A–D). The monochrome tdTomato signal (white) is shown from apical dendrites of saline-injected (A, B) and LiCl injected (C, D) Tbr1 CKOs at P181, 24 h after treatment. The Imaris software (v9.2.1) was used to analyze the dendritic spine density on apical dendrites of Tbr1layer5 wildtype and Tbr1layer5CKO neurons located within layers 2-4 of mPFCx (A–D). E Quantification of dendritic spine density on apical dendrites of Tbr1layer5 wildtype (green) and Tbr1layer5CKO neurons (orange) at P181. Spine density was improved 24 h after LiCl treatment (D), compared to the saline-injected control animals (B). Two-tailed T-test with Tukey correction was used for pairwise comparisons. Mann-Whitney ****p < 0.0001 (n = 10 dendrites), ns = not significant. Scale bar = 2 μm
A single LiCl treatment restores excitatory synapse function in Tbr1layer5 CKOs. A Representative traces of miniature excitatory postsynaptic currents (mEPSCs) from saline treated (4 ml/kg) P65-106 Tbr1wildtype (black) and Tbr1layer5CKO (cyan) layer 5 thick-tufted pyramidal neurons in the medial prefrontal cortex (mPFCx). Scale bars: 20 pA, 100 ms. B Left: quantification of mEPSC frequency. Mann-Whitney ***p = 0.0001 (Tbr1wildtype+saline: 6.71 ± 0.6 Hz, n = 18, Tbr1layer5CKO+saline 3.627 ± 0.7 Hz, n = 20). Right: cumulative probability distribution of mEPSC inter-event intervals. Kolmogorov-Smirnov **p = 0.002. C Left: quantification of mEPSC amplitude. Mann-Whitney p = 0.32 (Tbr1wildtype: 6.03 ± 0.4 pA, n = 18, Tbr1layer5CKO 5.15 ± 0.4 pA, n = 20). Right: cumulative probability distribution of mEPSC amplitude. Kolmogorov-Smirnov p = 1.0. D Representative traces of mEPSCs from layer 5 neurons of P95-104 Tbr1wildtype (green) and Tbr1layer5CKO (purple) treated with 400 mg/kg LiCl at P30. Scale bars: 20 pA, 100 ms. E Left: quantification of mEPSC frequency. Mann-Whitney p = 0.31 (Tbr1wildtype+ LiCl: 4.43 ± 0.5 Hz, n = 16, Tbr1layer5CKO+ LiCl: 5.69 ± 0.9 Hz, n = 13). Right: cumulative probability distribution of mEPSC inter-event intervals. Kolmogorov-Smirnov p > 0.99. F Left: quantification of mEPSC amplitude. Mann-Whitney p = 0.09 (Tbr1wildtype+ LiCl: 8.41 ± 0.5 pA, n = 16, Tbr1layer5CKO+ LiCl 9.63 ± 0.6 pA, n = 13). Right: cumulative probability distribution of mEPSC inter-event intervals. Kolmogorov-Smirnov p > 0.99. Boxplots are min to max show all points
LiCl rescues inhibitory synapse deficits in mPFCx of Tbr1layer5 CKOs. A Representative traces of miniature inhibitory postsynaptic currents (mIPSCs) from layer 5 mPFCx neurons of P65-106 Tbr1wildtype (black) and Tbr1layer5CKO (cyan) mice following saline administration (4 ml/kg) at P30. Scale bars: 20 pA, 100 ms. B Left: quantification of mIPSC frequency. Mann-Whitney ***p = 0.0005 (Tbr1wildtype+saline: 15.6 ± 1.0 Hz, n = 18, Tbr1layer5CKO+saline 9.4 ± 1.2 Hz, n = 19). Right: cumulative probability distribution of mIPSC inter-event intervals. Kolmogorov-Smirnov ****p < 0.0001. C Left: quantification of mIPSC amplitude. Mann-Whitney p = 0.32 (Tbr1wildtype+saline: 9.24 ± 0.6 pA, n = 18, Tbr1layer5CKO+saline: 9.08 ± 0.5 pA, n = 19). Right: cumulative probability distribution of mIPSC amplitude. Kolmogorov-Smirnov *p = 0.04. D Representative traces of mIPSCs from layer 5 neurons of LiCl (400 mg/kg) treated P95-104 Tbr1wildtype (green) and Tbr1layer5CKO (purple) mice. Scale bars: 20 pA, 100 ms. E Left: quantification of mIPSC frequency. Mann-Whitney p = 0.77 (Tbr1wildtype+ LiCl: 15.84 ± 1.7 Hz, n = 14, Tbr1layer5CKO+ LiCl: 18.73 ± 2.7 Hz, n = 11). Right: cumulative probability distribution of mIPSC inter-event intervals. Kolmogorov-Smirnov p = 0.47. F Left: quantification of mIPSC amplitude. Mann-Whitney p = 0.57 (Tbr1wildtype+ LiCl: 8.6 ± 0.4 pA, n = 14, Tbr1layer5CKO+ LiCl 9.1 ± 0.8 pA, n = 11). Right: cumulative probability distribution of mIPSC inter-event intervals. Kolmogorov-Smirnov p = 0.86. Boxplots are min to max show all points
Background Tbr1 encodes a T-box transcription factor and is considered a high confidence autism spectrum disorder (ASD) gene. Tbr1 is expressed in the postmitotic excitatory neurons of the deep neocortical layers 5 and 6. Postnatally and neonatally, Tbr1 conditional mutants (CKOs) have immature dendritic spines and reduced synaptic density. However, an understanding of Tbr1 ’s function in the adult mouse brain remains elusive. Methods We used conditional mutagenesis to interrogate Tbr1 ’s function in cortical layers 5 and 6 of the adult mouse cortex. Results Adult Tbr1 CKO mutants have dendritic spine and synaptic deficits as well as reduced frequency of mEPSCs and mIPSCs. LiCl, a WNT signaling agonist, robustly rescues the dendritic spine maturation, synaptic defects, and excitatory and inhibitory synaptic transmission deficits. Conclusions LiCl treatment could be used as a therapeutic approach for some cases of ASD with deficits in synaptic transmission.
 
EcoSupermarketX task design, considering the different types of cues. The task blocks included an instruction that consisted in the grocery list the participants had to pick. The grocery list (3 items) was presented as an instruction individually in a trial-by-trial basis: “Find strawberry cake” followed by “Find sausages” and “Find Olive Oil”, for example (each item image and name appeared for 3 s). The groceries were replaced randomly in the shelves on a trial-by-trial basis. Participants were instructed to collect all items in the sequence they appeared in the list, and as fast and accurately as possible. Additionally, there were three different conditions related to cues: no cue, non-social cue (wooden arrow) and social cue (avatar gazing to the grocery). The task blocks were divided into three runs with an interval between each run
Performance across time and distance in social cue condition in ASD and TD groups. A Total time for ASD and TD groups for the social cue condition. B Total distance for ASD and TD groups for the social cue condition. Boxplots: central mark—median; edges of box—25th and 75th percentiles; whiskers—most extreme data points (minimum and maximum). Note. ASD, autism spectrum disorder, TD, typical neurodevelopment.
RFX ANOVA group effects for EcoSupermarketX task. Statistical maps from group analysis overlaid on sagittal, coronal, and transversal slices of a representative subject. Red clusters depict regions where BOLD activity was higher for individuals with ASD than TD. Blue clusters depict regions where BOLD activity was lower for individuals with ASD than TD. Slice locations are given in MNI coordinates. NOTE. ASD, autism spectrum disorder group, TD, typical neurodevelopment group, TPJ, temporal-parietal junction, PFC, prefrontal cortex, pgACC, pregenual anterior cingulate cortex; OFC, orbitofrontal cortex, SMA, supplementary motor area, A, anterior; P, posterior, R, right, L, left; SAG, sagittal plane; COR, coronal plane; TRA, transversal plane; MNI, Montreal Neurological Institute
Background The concomitant role of the Central Executive, the Saliency and the Social Cognition networks in autism spectrum disorder (ASD) in demanding ecological tasks remains unanswered. We addressed this question using a novel task-based fMRI virtual-reality task mimicking a challenging daily-life chore that may present some difficulties to individuals with ASD: the EcoSupermarketX. Methods Participants included 29 adolescents: 15 with ASD and 15 with typical neurodevelopment (TD). They performed the EcoSupermarketX (a shopping simulation with three goal-oriented sub-tasks including “no cue”, “non-social” or “social” cues), during neuroimaging and eye-tracking. Results ASD differed from TD only in total time and distance to complete the “social cue” sub-task with matched eye-tracking measures. Neuroimaging revealed simultaneous hyperactivation across social, executive, and saliency circuits in ASD. In contrast, ASD showed reduced activation in the parahippocampal gyrus, involved in scene recognition. Conclusions When performing a virtual shopping task matching the performance of controls, ASD adolescents hyperactivate three core networks: executive, saliency and social cognition. Parahippocampal hypoactivation is consistent with effortless eidetic scene processing, in line with the notion of peaks and valleys of neural recruitment in individuals with ASD. These hyperactivation/hypoactivation patterns in daily life tasks provide a circuit-level signature of neural diversity in ASD, a possible intervention target.
 
Background Social communication is a key area of difficulty in fragile X syndrome (FXS) and there are not yet adequate outcome measurement tools. Appropriate outcome measures for FXS have been identified as a key area of research interest in order to evaluate future therapeutic trials. The Brief Observation of Social Communication Change-Minimally Verbal (BOSCC-MV), an outcome measure with strong psychometrics developed for autism spectrum disorder, has promise as an outcome measure to assess social communication change with FXS participants. Methods We examined the BOSCC-MV via central coders in this multi-site-trial to assess its appropriateness for FXS. Eighteen minimally verbal males ages 3–12 years were enrolled and assessed on two consecutive days and 7 participants completed a third visit 6 months later. We examined test-retest reliability, inter-rater reliability, and both convergent and divergent validity with standard clinical measures including the Autism Diagnostic and Observation Schedule-2, Vineland 3, Social Responsiveness Scale, and the Aberrant Behavior Checklist. Results The BOSCC-MV in FXS demonstrated strong inter-rater and test-retest reliability, comparable to previous trials in idiopathic ASD. Strong convergent validity was found with Autism Diagnostic Observation Schedule-2 and Vineland-3. Divergent validity was demonstrated between BOSCC-MV and unrelated measures. Conclusions The BOSCC-MV shows promise as a FXS social communication outcome measure, warranting further large-scale evaluation.
 
Background: Differences in face processing in individuals with ASD is hypothesized to impact the development of social communication skills. This study aimed to characterize the neural correlates of face processing in 12-month-old infants at familial risk of developing ASD by (1) comparing face-sensitive event-related potentials (ERP) (Nc, N290, P400) between high-familial-risk infants who develop ASD (HR-ASD), high-familial-risk infants without ASD (HR-NoASD), and low-familial-risk infants (LR), and (2) evaluating how face-sensitive ERP components are associated with development of social communication skills. Methods: 12-month-old infants participated in a study in which they were presented with alternating images of their mother's face and the face of a stranger (LR = 45, HR-NoASD = 41, HR-ASD = 24) as EEG data were collected. Parent-reported and laboratory-observed social communication measures were obtained at 12 and 18 months. Group differences in ERP responses were evaluated using ANOVA, and multiple linear regressions were conducted with maternal education and outcome groups as covariates to assess relationships between ERP and behavioral measures. Results: For each of the ERP components (Nc [negative-central], N290, and P400), the amplitude difference between mother and stranger (Mother-Stranger) trials was not statistically different between the three outcome groups (Nc p = 0.72, N290 p = 0.88, P400 p = 0.91). Marginal effects analyses found that within the LR group, a greater Nc Mother-Stranger response was associated with better expressive language skills on the Mullen Scales of Early Learning, controlling for maternal education and outcome group effects (marginal effects dy/dx = 1.15; p < 0.01). No significant associations were observed between the Nc and language or social measures in HR-NoASD or HR-ASD groups. In contrast, specific to the HR-ASD group, amplitude difference between the Mother versus Stranger P400 response was positively associated with expressive (dy/dx = 2.1, p < 0.001) and receptive language skills at 12 months (dy/dx = 1.68, p < 0.005), and negatively associated with social affect scores on the Autism Diagnostic Observation Schedule (dy/dx = - 1.22, p < 0.001) at 18 months. Conclusions: In 12-month-old infant siblings with subsequent ASD, increased P400 response to Mother over Stranger faces is positively associated with concurrent language and future social skills.
 
Background Imitation skills play a crucial role in social cognitive development from early childhood. Many studies have shown a deficit in imitation skills in children with autism spectrum disorders (ASD). Little is known about the development of imitation behaviors in children with ASD. This study aims to measure the trajectories of early imitation skills in preschoolers with ASD and how these skills impact other areas of early development. Methods For this purpose, we assessed imitation, language, and cognition skills in 177 children with ASD and 43 typically developing children (TD) aged 2 to 5 years old, 126 of which were followed longitudinally, yielding a total of 396 time points. Results Our results confirmed the presence of an early imitation deficit in toddlers with ASD compared to TD children. The study of the trajectories showed that these difficulties were marked at the age of 2 years and gradually decreased until the age of 5 years old. Imitation skills were strongly linked with cognitive and language skills and level of symptoms in our ASD group at baseline. Moreover, the imitation skills at baseline were predictive of the language gains a year later in our ASD group. Using a data-driven clustering method, we delineated different developmental trajectories of imitation skills within the ASD group. Conclusions The clinical implications of the findings are discussed, particularly the impact of an early imitation deficit on other areas of competence of the young child.
 
Background This implementation feasibility study was conducted to determine whether an evidence-based parent-implemented distance-learning intervention model for young children at high likelihood of having ASD could be implemented at fidelity by Part C community providers and by parents in low-resource communities. Methods The study used a community-academic partnership model to adapt an evidence-based intervention tested in the current pilot trial involving randomization by agency in four states and enrollment of 35 coaches and 34 parent-family dyads. After baseline data were gathered, providers in the experimental group received 12–15 h of training while control providers received six webinars on early development. Providers delivered 6 months of intervention with children-families, concluding with data collection. Regression analyses were used to model outcomes of the coach behaviors, the parent fidelity ratings, and child outcomes. Results A block design model-building approach was used to test the null model followed by the inclusion of group as a predictor, and finally the inclusion of the planned covariates. Model fit was examined using changes in R ² and F -statistic. As hypothesized, results demonstrated significant gains in (1) experimental provider fidelity of coaching implementation compared to the control group; and (2) experimental parent fidelity of implementation compared to the control group. There were no significant differences between groups on child developmental scores. Conclusions Even though the experimental parent group averaged less than 30 min of intervention weekly with providers in the 6 months, both providers and parents demonstrated statistically significant gains on the fidelity of implementation scores with moderate effect sizes compared to control groups. Since child changes in parent-mediated models are dependent upon the parents’ ability to deliver the intervention, and since parent delivery is dependent upon providers who are coaching the parents, these results demonstrated that two of these three links of the chain were positively affected by the experimental implementation model. However, a lack of significant differences in child group gains suggests that further work is needed on this model. Factors to consider include the amount of contact with the provider, the amount of practice children experience, the amount of contact both providers and parents spend on training materials, and motivational strategies for parents, among others. Trial registration Registry of Efficacy and Effectiveness Studies: #4360, registered 1xx, October, 2020 – Retrospectively registered, https://sreereg.icpsr.umich.edu/sreereg/
 
Background P hosphatase and ten sin homologue ( PTEN ) is a cancer suppressor gene. Constitutional mutations affecting this gene are associated with several conditions, collectively termed PTEN hamartoma tumour syndromes (PHTS). In addition to hamartomas, PTEN aberrations have been associated with a range of non-tumoural phenotypes such as macrocephaly, and research indicates possibly increased rates of developmental delay and autism spectrum disorder (ASD) for people with germline mutations affecting PTEN . Method A systematic review of literature reporting behavioural and psychological variables for people with constitutional PTEN mutations/PHTS was conducted using four databases. Following in-depth screening, 25 articles met the inclusion criteria and were used in the review. Fourteen papers reported the proportion of people with PTEN mutations/PTHS meeting criteria for or having characteristics of ASD and were thus used in a pooled prevalence meta-analysis. Results Meta-analysis using a random effects model estimated pooled prevalence of ASD characteristics at 25% (95% CI 16–33%), although this should be interpreted cautiously due to possible biases in existing literature. Intellectual disability and developmental delay (global, motor and speech and language) were also reported frequently. Emotional difficulties and impaired cognitive functioning in specific domains were noted but assessed/reported less frequently. Methods of assessment of psychological/behavioural factors varied widely (with retrospective examination of medical records common). Conclusions Existing research suggests approximately 25% of people with constitutional PTEN mutations may meet criteria for or have characteristics of ASD. Studies have also begun to establish a range of possible cognitive impairments in affected individuals, especially when ASD is also reported. However, further large-scale studies are needed to elucidate psychological/behavioural corollaries of this mutation, and how they may relate to physiological/physical characteristics.
 
Background Fragile X syndrome (FXS) is associated with dysregulated endocannabinoid signaling and may therefore respond to cannabidiol therapy. Design CONNECT-FX was a double-blind, randomized phase 3 trial assessing efficacy and safety of ZYN002, transdermal cannabidiol gel, for the treatment of behavioral symptoms in children and adolescents with FXS. Methods Patients were randomized to 12 weeks of ZYN002 (250 mg or 500 mg daily [weight-based]) or placebo, as add-on to standard of care. The primary endpoint assessed change in social avoidance (SA) measured by the Aberrant Behavior Checklist–Community Edition FXS (ABC-C FXS ) SA subscale in a full cohort of patients with a FXS full mutation, regardless of the FMR1 methylation status. Ad hoc analyses assessed efficacy in patients with ≥ 90% and 100% methylation of the promoter region of the FMR1 gene, in whom FMR1 gene silencing is most likely. Results A total of 212 patients, mean age 9.7 years, 75% males, were enrolled. A total of 169 (79.7%) patients presented with ≥ 90% methylation of the FMR1 promoter and full mutation of FMR1 . Although statistical significance for the primary endpoint was not achieved in the full cohort, significant improvement was demonstrated in patients with ≥ 90% methylation of FMR1 (nominal P = 0.020). This group also achieved statistically significant improvements in Caregiver Global Impression‐Change in SA and isolation, irritable and disruptive behaviors, and social interactions (nominal P -values: P = 0.038, P = 0.028, and P = 0.002). Similar results were seen in patients with 100% methylation of FMR1 . ZYN002 was safe and well tolerated. All treatment-emergent adverse events (TEAEs) were mild or moderate. The most common treatment-related TEAE was application site pain (ZYN002: 6.4%; placebo: 1.0%). Conclusions In CONNECT-FX, ZYN002 was well tolerated in patients with FXS and demonstrated evidence of efficacy with a favorable benefit risk relationship in patients with ≥ 90% methylation of the FMR1 gene, in whom gene silencing is most likely, and the impact of FXS is typically most severe. Trial registration The CONNECT-FX trial is registered on Clinicaltrials.gov (NCT03614663).
 
Background Anxiety symptomatology is common in individuals with intellectual disability (ID). Symptomatology includes both traditional Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) anxiety disorders and autism spectrum disorder (ASD)-related anxiety traits. Some genetic disorders such as Cornelia de Lange (CdLS) and fragile X syndromes (FXS) are at very high risk of anxiety and afford the opportunity to examine prevalence, profiles and associated person characteristics. However, prevalence and associated characteristics of anxiety in these high-risk groups remain poorly described and understood. The aim of the current study was to examine the prevalence and profile of DSM-5 and ASD-related anxiety symptomatology in individuals with CdLS and FXS and associated behavioural and cognitive characteristics. Methods Questionnaires and interviews assessing DSM-5 and ASD-related anxiety were conducted with caregivers of individuals with CdLS ( n = 49) and FXS ( n = 36). Results DSM-5 anxiety symptomatology was present in both groups with high co-morbidity across anxiety diagnoses. ASD-related anxiety was also prevalent with specific difficulties related to intolerance of uncertainty identified in both groups. Symptomatology was persistent over the lifespan for both groups. Anxiety type was partially associated with repetitive behaviour but not measures of overall ASD phenomenology in CdLS. Conclusions DSM-5 and ASD-related anxiety are common in these high-risk syndromes associated with ID. Prospective syndrome specific presentations and associations, which may implicate specific underlying mechanisms, are discussed. Clinicians should be aware of the risk and difficulties involved in assessment of anxiety in individuals with ID, including atypical types, to ensure these individuals do not “miss” diagnoses and support in general clinical practice.
 
Trajectory of scores obtained at baseline and follow-up on each subscale of the Aberrant Behavior Checklist–Community (ABC-C) plotted by age for boys in each group
Trajectory of scores obtained at baseline and follow-up on each subscale of the Parenting Stress Index-4th Edition (PSI-4) plotted by age for boys in each group
Background A significant proportion of boys with fragile X syndrome (FXS), the most common known genetic cause of intellectual disability, exhibit challenging behaviors such as aggression and self-injury that can cause significant distress to families. Recent evidence suggests that coaching caregivers to implement functional communication training (FCT) with their child via telehealth can help to ameliorate these behaviors in FXS. In the present study, we followed families who had participated in our previous randomized controlled trial of FCT to evaluate the longer-term effects of FCT on challenging behaviors in this population. Methods In study 1, follow-up emails, phone calls, text messages, and letters were sent to caregivers of 48 boys with FXS who had completed our previous study conducted between 2016 and 2019. The main outcome measures administered at follow-up were the Aberrant Behavior Checklist–Community (ABC-C) and the Parenting Stress Index, 4th Edition (PSI-4). In study 2, families who had received FCT treatment but whose child exhibited challenging behaviors daily at follow-up received a 1-h parent training booster session to determine whether the intervention effect could be recovered. Results Sixteen (66.7%) of 24 families who had received FCT treatment and 18 (75.0%) of 24 families who had received treatment as usual were traced and consented between March and August 2021. The mean follow-up time was 3.1 years (range, 1.4 to 4.2 years). Longitudinal mixed effects analyses indicated that boys who had received FCT were more likely to show improvements on the irritability and lethargy/social withdrawal subscales of the ABC-C over the follow-up interval compared to boys who had continued with treatment as usual. Four of the six boys who had received the booster parent training session via telehealth were reported to exhibit fewer forms of challenging behavior at a 4-week follow-up. Conclusions Empowering parents to implement behavior analytic treatments with their child in their own home can have durable effects on maintaining low levels of challenging behaviors in boys with FXS. These data further support the need to implement parent-mediated interventions for challenging behaviors in this population at an early age. Trial registration ClinicalTrials.gov, NCT03510156. Registered 27 April 2018
 
Background Fragile X syndrome (FXS) is the most common inherited form of neurodevelopmental disability. It is often characterized, especially in males, by intellectual disability, anxiety, repetitive behavior, social communication deficits, delayed language development, and abnormal sensory processing. Recently, we identified electroencephalographic (EEG) biomarkers that are conserved between the mouse model of FXS (Fmr1 KO mice) and humans with FXS. Methods In this report, we evaluate small molecule target engagement utilizing multielectrode array electrophysiology in the Fmr1 KO mouse and in humans with FXS. Neurophysiologic target engagement was evaluated using single doses of the GABAB selective agonist racemic baclofen (RBAC). Results In Fmr1 KO mice and in humans with FXS, baclofen use was associated with suppression of elevated gamma power and increase in low-frequency power at rest. In the Fmr1 KO mice, a baclofen-associated improvement in auditory chirp synchronization was also noted. Conclusions Overall, we noted synchronized target engagement of RBAC on resting state electrophysiology, in particular the reduction of aberrant high frequency gamma activity, across species in FXS. This finding holds promise for translational medicine approaches to drug development for FXS, synchronizing treatment study across species using well-established EEG biological markers in this field. Trial registration The human experiments are registered under NCT02998151.
 
Depictions of results from analyses of regional volumes from the fronto-parietal network (FPN) and default mode network (DMN) networks using multivariate distance matrix regression (MDMR) and effect size analysis. Ordination plots depict the significant MDMR differences between longitudinal IQ trajectory groups in the a FPN and b DMN. These plots were produced using distance-based redundancy analysis (dbRDA) to facilitate visualization of high-dimensional data. The black dots depict median centroid locations of the changers, persistent-low, and persistent-high groups on the first two dbRDA axes. The ellipsoids indicate the standard error of the locations of each group centroid on those two axes. Results of effect-size analyses of the c FPN and d DMN are depicted for the pair-wise differences between the changers, persistent low, and persistent high groups
Background Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism). Yet, a major unresolved neurobiological question is what differentiates autistic individuals with and without intellectual disability. Intelligence quotients (IQs) are highly variable during childhood. We previously identified three subgroups of autistic children with different trajectories of intellectual development from early (2–3½ years) to middle childhood (9–12 years): (a) persistently high: individuals whose IQs remained in the normal range; (b) persistently low: individuals whose IQs remained in the range of intellectual disability (IQ < 70); and (c) changers: individuals whose IQs began in the range of intellectual disability but increased to the normal IQ range. The frontoparietal (FPN) and default mode (DMN) networks have established links to intellectual functioning. Here, we tested whether brain regions within the FPN and DMN differed volumetrically between these IQ trajectory groups in early childhood. Methods We conducted multivariate distance matrix regression to examine the brain regions within the FPN (11 regions x 2 hemispheres) and the DMN (12 regions x 2 hemispheres) in 48 persistently high (18 female), 108 persistently low (32 female), and 109 changers (39 female) using structural MRI acquired at baseline. FPN and DMN regions were defined using networks identified in Smith et al. (Proc Natl Acad Sci U S A 106:13040–5, 2009). IQ trajectory groups were defined by IQ measurements from up to three time points spanning early to middle childhood (mean age time 1: 3.2 years; time 2: 5.4 years; time 3: 11.3 years). Results The changers group exhibited volumetric differences in the DMN compared to both the persistently low and persistently high groups at time 1. However, the persistently high group did not differ from the persistently low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory. In contrast, the persistently high group exhibited differences in the FPN compared to both the persistently low and changers groups, suggesting differences related more to concurrent IQ and the absence of intellectual disability. Conclusions Within autism, volumetric differences of brain regions within the DMN in early childhood may differentiate individuals with persistently low IQ from those with low IQ that improves through childhood. Structural differences in brain networks between these three IQ-based subgroups highlight distinct neural underpinnings of these autism sub-phenotypes.
 
Use of MPRA to identify causal variants at a GWAS locus containing many SNPs in high LD. A The schematic cartoon plots show GWAS and MPRA SNPs and their corresponding significance at a single locus. LD structure confounds identification of the causal variant in the GWAS, but the MPRA tests regulatory effects of each SNP independently so it can identify a specific causal variant. B. Top, SNP association statistics at a genome-wide significant locus from an ASD GWAS [19]. The index SNP, rs60527016, reached genome-wide significance. SNPs are colored by binned LD (r²) relative to the MPRA-validated variant (rs7001340). The existence of SNPs that are in high LD with rs7001340 highlights the difficulties in defining which SNPs are functional or causal based on GWAS alone. Bottom, MPRA identified a causal variant within this locus (rs7001340) that shows strong allelic regulatory activity. Image adapted from [19]
Luciferase assay vs cis-regulatory MPRA. A Luciferase assay measures light emitted by a reporter gene, luciferase, driven by a regulatory element. B In a canonical cis-regulatory MPRA, the regulatory element drives the RNA expression of the unique barcodes. Transcriptional activity is quantified as barcode transcription (via RNA-seq of the barcodes) normalized to initial input of barcodes (via DNA-seq of the barcodes). Thousands of cis-regulatory elements (CREs) can be tested in the same experiment
MPRA designs for studying gene regulation. MPRA modifies the design of canonical cis-regulatory MPRA (described in Fig. 2B) that contains a cis-regulatory element (CRE), a promoter, a reporter gene, and a unique barcode (BC). Elements of this construct can be replaced or rearranged to test different types of CREs. The red vertical line indicates where a variant can be located. A Promoter MPRA contains a promoter harboring a variant, a reporter gene (e.g., GFP), and a unique BC. Image adapted from [40]. B Enhancer MPRA contains a regulatory element harboring a variant, a (minimal) promoter, a reporter gene, and a unique BC. C Transcription factor binding MPRA (TransMPRA) can be broken down into two components: (1) a promoter with a guide RNA (gRNA) that targets a transcription factor (TF) of interest and (2) a promoter, a test enhancer sequence harboring a variant, and a unique BC. The gRNA brings catalytically dead Cas9 protein with an attached Krüppel-associated box (dCas9-KRAB) which silences the expression of the TF gene. If the silenced TF interacts with the test enhancer, the downstream barcode expression is decreased. Image adapted from preprint [41]. D Silencer MPRA (in a STARR-seq style) contains a (strong) promoter and a test silencer harboring a variant. The silencer sequence can prevent self-transcription by silencing the promoter. Image adapted from [42]. E Splicing MPRA has minigene constructs that are inserted between a split-GFP reporter (GFP-N terminus and GFP-C terminus) and a peptide 2A (P2A) upstream of an mCherry reporter. Variants can be located in the variable intron sections on either side of the exon or within the exon. Inclusion of the middle exon disrupts GFP fluorescence, and cells can be FACS sorted into bins based on GFP:mCherry ratios. The GFP with or without the exon are quantified for exon inclusion or skipping via DNA-seq of the plasmid in each sorted bin. Image adapted from [43]. F RNA modification MPRA contains a promoter, an arbitrary coding sequence (CDS), a putative pseudouridine (Ψ) sequence as 3′ untranslated region (UTR), and a unique barcode. Once the library is introduced, cells are treated with N-cyclohexyl-N′-β-(4-methylmorpholinium) ethylcarbodiimide (CMC) which binds to Ψ and prevents reverse transcription (RT). High-throughput sequencing of cDNA allows prediction of the exact base pair location of the Ψ RNA modification. Variants can be inserted anywhere in the CDS. Image adapted from [44]. G 3′ UTR MPRA consists of a promoter, a reporter gene, a 3′ UTR harboring a variant, and a BC. BC RNA counts reflect transcriptional stability modulated by 3′ UTRs. H RNA localization MPRA consists of a promoter, a mutated Sox2 gene that localizes in the cytoplasm (fsSox2), a lncRNA harboring a variant, and a unique barcode. Barcode expression from subcellular fractions is used to interrogate subcellular localization of lncRNA. Image adapted from [45]
An example of how cell types influence variant function. A In cell type A, TF is expressed and binds to the A allele in both the host genome and the MPRA construct. In the host genome with allele A, the gene is expressed. In the MPRA construct with allele A, the barcoded (BC) reporter gene is expressed. TF does not bind to the C allele, so the gene and BC associated with that allele are not expressed. B In cell type B, TF is not expressed, so the allele is not associated with BC expression
A cartoon example of a response MPRA. A In traditional MPRA, MPRA constructs introduced to the cells are not expressed because TF2 that acts on the element of interest is not translocated to the nucleus. Barcode expression of these alleles is displayed in a box plot. B In response MPRA, cells are treated with a drug X that activates downstream pathways to translocate response-dependent TF2 to the nucleus. Allele C disrupts the TF2 binding motif, and its unique barcode is not expressed, while allele A matches the TF2 motif leading to expression of its unique barcode. The barcode expression of each allele is displayed in an accompanied box plot. Therefore, this variant displays allelic regulatory activity only in response to drug X treatment
A growing number of variants associated with risk for neurodevelopmental disorders have been identified by genome-wide association and whole genome sequencing studies. As common risk variants often fall within large haplotype blocks covering long stretches of the noncoding genome, the causal variants within an associated locus are often unknown. Similarly, the effect of rare noncoding risk variants identified by whole genome sequencing on molecular traits is seldom known without functional assays. A massively parallel reporter assay (MPRA) is an assay that can functionally validate thousands of regulatory elements simultaneously using high-throughput sequencing and barcode technology. MPRA has been adapted to various experimental designs that measure gene regulatory effects of genetic variants within cis- and trans-regulatory elements as well as posttranscriptional processes. This review discusses different MPRA designs that have been or could be used in the future to experimentally validate genetic variants associated with neurodevelopmental disorders. Though MPRA has limitations such as it does not model genomic context, this assay can help narrow down the underlying genetic causes of neurodevelopmental disorders by screening thousands of sequences in one experiment. We conclude by describing future directions of this technique such as applications of MPRA for gene-by-environment interactions and pharmacogenetics.
 
Background: CHARGE syndrome (OMIM #214800) is a phenotypically complex genetic condition characterised by multi-system, multi-sensory impairments. Behavioural, psychological, cognitive and sleep difficulties are not well delineated and are likely associated with biopsychosocial factors. Methods: This meta-analysis investigated the prevalence of clinical features, physical characteristics and conditions, behavioural, psychological, cognitive and sleep characteristics in CHARGE syndrome, and statistically evaluated directional associations between these characteristics. Pooled prevalence estimates were calculated using reliable, prespecified quality weighting criteria, and meta-regression was conducted to identify associations between characteristics. Results: Of the 42 eligible studies, data could be extracted for 1675 participants. Prevalence estimates were highest for developmental delay (84%), intellectual disability (64%), aggressive behaviour (48%), self-injurious behaviour (44%) and sleep difficulties (45%). Meta-regression indicated significant associations between intellectual disability and choanal atresia, intellectual disability and inner ear anomalies, sleep difficulties and growth deficiency, and sleep difficulties and gross motor difficulties. Conclusions: Our comprehensive review of clinical features, behavioural, psychological, cognitive and physical characteristics, conditions and comorbidities in CHARGE syndrome provides an empirically based foundation to further research and practice. Keywords: CHARGE syndrome, Sensory impairment, Behavioural phenotype, Aggressive behaviour, Self-injurious behaviour, Sleep, Intellectual disability
 
Key structures in the auditory processing pathway in the human and mouse brain. Auditory information enters the central nervous system at the cochlear nuclei and is then processed at the level of the superior olivary complex, lateral lemniscus, inferior colliculus, auditory thalamus (medial geniculate nucleus and thalamic reticular nucleus), auditory cortex, and prefrontal cortex. Scale bars are approximate. Images generated with brainrender [18]
A Search strategy for systematic review. Records were found from searches in two databases. After removing duplicated entries, 234 abstracts were screened for inclusion in the review. Of these, 88 were primary research articles investigating the structure and function of the auditory processing pathway in mouse or rat models of autism. B Publication year of the records which were included in the review. Almost all records were published in the last 10 years
Measures of function in along the auditory pathway. A Example human auditory brainstem response (ABR) trace. The first peak represents activity in the auditory nerve, and the second correlates to the cochlear nucleus. Peak III represents the superior olivary complex, and peaks IV and V represent the lateral lemniscus and the inferior colliculus, respectively. B Example cortical auditory event-related potential (ERP) trace. The ERP is made up of 5 peaks, representing activation in different areas. P1 is produced by activity in the auditory thalamus (MGN) and the primary auditory cortex, N1 is produced by the auditory cortex. P2 is produced by the association cortex. N2 and P3 peaks (associated with the frontal cortex) are observed in humans, but less commonly in rodents. C Exemplar EEG frequency activity. Raw EEG traces (as may be recorded from the auditory or prefrontal cortices) are composite waves, from which activity in several frequency ranges can be extracted. The power in each of these frequency bands indicates the extent to which activity at that frequency contributes to the overall recorded activity
The ascending auditory processing pathway with presumed changes in autism based on results from studies in rodent models. Excitatory (red) and inhibitory (blue) connections between structures along the pathway are illustrated along with the changes to these connections and the activity within areas in rodent models of autism. Connections are primarily ipsilateral unless otherwise stated. There is increased activity in structures such as the lateral superior olive (LSO), the medial geniculate nucleus of the thalamus (MGN), thalamic reticular nucleus (TRN), the auditory cortex (specifically in layers 2/3), and the prefrontal cortex. Activity is consistently decreased in the dorsal and ventral lateral lemniscus (DNLL and VNLL) and the anterior auditory field (AAF) of the rat auditory cortex. Activity in other areas is either unchanged or results are conflicted. The connection from the ventral cochlear nucleus (VCN) to the LSO is increased in strength, while the strength of the connection from the anterior VCN (AVCN) to the medial nucleus of the trapezoid body (MNTB) is decreased. Signals from the VCN take longer to reach the SPON and from the MGN take longer to reach the auditory cortex in rodent models of autism. The speed of other connections is either unchanged or disputed between studies. The strength of connections between contralateral auditory cortices and between the auditory and prefrontal cortex is decreased, as is the feedback connection from the prefrontal cortex to the TRN
Autism is a complex condition with many traits, including differences in auditory sensitivity. Studies in human autism are plagued by the difficulty of controlling for aetiology, whereas studies in individual rodent models cannot represent the full spectrum of human autism. This systematic review compares results in auditory studies across a wide range of established rodent models of autism to mimic the wide range of aetiologies in the human population. A search was conducted in the PubMed and Web of Science databases to find primary research articles in mouse or rat models of autism which investigate central auditory processing. A total of 88 studies were included. These used non-invasive measures of auditory function, such as auditory brainstem response recordings, cortical event-related potentials, electroencephalography, and behavioural tests, which are translatable to human studies. They also included invasive measures, such as electrophysiology and histology, which shed insight on the origins of the phenotypes found in the non-invasive studies. The most consistent results across these studies were increased latency of the N1 peak of event-related potentials, decreased power and coherence of gamma activity in the auditory cortex, and increased auditory startle responses to high sound levels. Invasive studies indicated loss of subcortical inhibitory neurons, hyperactivity in the lateral superior olive and auditory thalamus, and reduced specificity of responses in the auditory cortex. This review compares the auditory phenotypes across rodent models and highlights those that mimic findings in human studies, providing a framework and avenues for future studies to inform understanding of the auditory system in autism.
 
Source localization differences between ASD and TD groups in the alpha frequency band. Blue areas represent the spatial extent of voxels with a significantly reduced current source density between ASD and TD groups (p < 0.05 corrected for multiple testing, t < −3.426). L left, R right, A anterior, P posterior, S superior, I inferior
and summary
Connectogram of significant differences in within-RSN connectivity in the ASD group relative to the TD group. Lines indicate significantly decreased lagged phase synchronization for the ASD group relative to the TD group within SMN, DAN, and DMN (thin line p < 0.05, thick line p < 0.01). L left, R right
Connectogram of significant differences in between-RSN connectivity in the ASD group relative to the TD group. Lines indicate significantly decreased lagged phase synchronization for the ASD group relative to the TD group between SMN and DAN, between SMN and DMN, and between DAN and DMN (thin line p < 0.05). L left, R right
of decreased connectivity within and between RSN in the ASD group relative to TD. Lines indicate significant decreased lagged phase synchronization for the ASD group relative to the TD group. Green lines represent decreased connectivity within RSNs, and blue lines represent decreased connectivity between RSNs. Thin line p < 0.05, thick line p < 0.01. L, left, R right
Background Autism spectrum disorder (ASD) is associated with atypical neural activity in resting state. Most of the studies have focused on abnormalities in alpha frequency as a marker of ASD dysfunctions. However, few have explored alpha synchronization within a specific interest in resting-state networks, namely the default mode network (DMN), the sensorimotor network (SMN), and the dorsal attention network (DAN). These functional connectivity analyses provide relevant insight into the neurophysiological correlates of multimodal integration in ASD. Methods Using high temporal resolution EEG, the present study investigates the functional connectivity in the alpha band within and between the DMN, SMN, and the DAN. We examined eyes-closed EEG alpha lagged phase synchronization, using standardized low-resolution brain electromagnetic tomography (sLORETA) in 29 participants with ASD and 38 developing (TD) controls (age, sex, and IQ matched). Results We observed reduced functional connectivity in the ASD group relative to TD controls, within and between the DMN, the SMN, and the DAN. We identified three hubs of dysconnectivity in ASD: the posterior cingulate cortex, the precuneus, and the medial frontal gyrus. These three regions also presented decreased current source density in the alpha band. Conclusion These results shed light on possible multimodal integration impairments affecting the communication between bottom-up and top-down information. The observed hypoconnectivity between the DMN, SMN, and DAN could also be related to difficulties in switching between externally oriented attention and internally oriented thoughts.
 
Quantitative measure of sleep disturbance across groups. Sleep disturbance, assessed via the SIPS, is significantly worse in CNV carriers compared to controls cross-sectionally (q<0.001) and longitudinally (q<0.001). However, there is no significant difference in sleep quality between CNV groups (q>0.940). Large dots represent the group mean and 95% confidence interval at each timepoint
Clinical measures in good and poor sleepers at each timepoint within 22q11.2 CNV groups. In both cross-sectional and longitudinal analyses across CNV groups, poor sleepers score higher (i.e., more pathological) on positive symptoms (cross-sectional: q=<0.001, longitudinal: q<0.001), total repetitive behaviors (cross-sectional: q= 0.005, longitudinal: q=0.018), and social responsiveness (cross-sectional: q= 0.026, longitudinal: q=0.015 ). The effect of sleep on BRIEF global composite score failed to survive FDR correction (cross-sectional: p= 0.0, longitudinal: p=0.0). Large dots represent the group mean and 95% confidence interval for good and poor sleepers at each timepoint
Baseline CNV group-by-sleep interactions. There were significant group-by-sleep interactions at baseline for positive psychosis-risk symptoms (q=0.041), and CBCL-measured withdrawn/depressed (q=0.020), somatic complaints (q=0.007), social problems (q=0.017), thought problems (q=0.012), attention problems (q=0.009), rule-breaking (q=0.006), and aggressive behaviors subscales (q=0.004). Large dots represent the group mean and 95% confidence interval for good and poor sleepers in each subject group
CBCL subdomain scores in good and poor sleepers at each timepoint within 22q11.2 CNV groups. At baseline, there was a significant main effect of sleep category on all CBCL subdomains (q<0.017). Across timepoints, there was a significant main effect of sleep category on anxious/depressed (q=0.005), somatic complaints (q=0.038), thought problems (q<0.001), and aggressive behavior (q=0.002) subscales. There was a trend towards a significant effect of sleep category on attention problems (q=0.061). Large dots represent the group mean and 95% confidence interval for good and poor sleepers at each timepoint
Results of cross-sectional models
Background Sleep disturbance is common, impairing, and may affect symptomatology in developmental neuropsychiatric disorders. Here, we take a genetics-first approach to study the complex role of sleep in psychopathology. Specifically, we examine severity of sleep disturbance in individuals with a reciprocal copy number variant (CNV) at the 22q11.2 locus and determine sleep’s effect on psychiatric symptoms. CNVs (deletion or duplication) at this locus confer some of the greatest known risks of neuropsychiatric disorders; recent studies suggest the 22q11.2 deletion negatively impacts sleep, but sleep disruption associated with 22q11.2 duplication has not been investigated. Methods We compared subjective sleep disturbance and its relationship to psychiatric symptoms cross-sectionally and longitudinally over 1 year in 107 22q11.2 deletion (22qDel) carriers (14.56±8.0 years; 50% male), 42 22q11.2 duplication (22qDup) carriers (16.26±13.1 years; 54.8% male), and 88 age- and sex-matched controls (14.65±7.4 years; 47.1% male). Linear mixed models were used to compare sleep disturbance, assessed via the Structured Interview for Psychosis-Risk Syndromes (SIPS), across groups. Next, CNV carriers were categorized as good or poor sleepers to investigate sleep effects on multiple neurobehavioral traits: psychosis-risk symptoms (SIPS), autism-related behaviors (Repetitive Behavior Scale (RBS) and Social Responsiveness Scale (SRS)), real-world executive function (Behavior Rating Inventory of Executive Function (BRIEF)), and emotional/behavioral problems (Child Behavior Checklist (CBCL)). Linear mixed models tested the effect of sleep category and a group-by-sleep interaction on each measure, cross-sectionally and longitudinally. Results 22qDel and 22qDup carriers both reported poorer sleep than controls, but did not differ from each other. Cross-sectionally and longitudinally, poor sleepers scored higher on positive symptoms, anxious/depressed, somatic complaints, thought problems, and aggressive behavior, as well as RBS and SRS total scores. There were significant group-by-sleep interactions for positive symptoms and the majority of CBCL subdomains, in which the difference between good and poor sleepers was larger in 22qDel compared to 22qDup. Conclusions Our findings indicate that CNVs at the 22q11.2 locus impact sleep which, in turn, influences psychopathology. Sleep disturbances can differentially impact psychopathology, depending on 22q11.2 gene dosage. Our findings serve as a starting point for exploring a genetic basis for sleep disturbance in developmental neuropsychiatric disorders.
 
Background Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood neurodevelopmental disorder. It shares some genetic risk with Autism Spectrum Disorder (ASD), and the conditions often occur together. Both are potentially associated with abnormal glutamate and GABA neurotransmission, which can be modelled by measuring the synaptic activity in the retina with an electroretinogram (ERG). Reduction of retinal responses in ASD has been reported, but little is known about retinal activity in ADHD. In this study, we compared the light-adapted ERGs of individuals with ADHD, ASD and controls to investigate whether retinal responses differ between these neurodevelopmental conditions. Methods Full field light-adapted ERGs were recorded from 15 ADHD, 57 ASD (without ADHD) and 59 control participants, aged from 5.4 to 27.3 years old. A Troland protocol was used with a random series of nine flash strengths from −0.367 to 1.204 log photopic cd.s.m ⁻² . The time-to-peak and amplitude of the a- and b-waves and the parameters of the Photopic Negative Response (PhNR) were compared amongst the three groups of participants, using generalised estimating equations. Results Statistically significant elevations of the ERG b-wave amplitudes, PhNR responses and faster timings of the b-wave time-to-peak were found in those with ADHD compared with both the control and ASD groups. The greatest elevation in the b-wave amplitudes associated with ADHD were observed at 1.204 log phot cd.s.m ⁻² flash strength ( p < .0001), at which the b-wave amplitude in ASD was significantly lower than that in the controls. Using this measure, ADHD could be distinguished from ASD with an area under the curve of 0.88. Conclusions The ERG b-wave amplitude appears to be a distinctive differential feature for both ADHD and ASD, which produced a reversed pattern of b-wave responses. These findings imply imbalances between glutamate and GABA neurotransmission which primarily regulate the b-wave formation. Abnormalities in the b-wave amplitude could provisionally serve as a biomarker for both neurodevelopmental conditions.
 
Background Autism spectrum disorder is a neurodevelopmental disorder, affecting 1–2% of children. Studies have revealed genetic and cellular abnormalities in the brains of affected individuals, leading to both regional and distal cell communication deficits. Methods Recent application of single-cell technologies, especially single-cell transcriptomics, has significantly expanded our understanding of brain cell heterogeneity and further demonstrated that multiple cell types and brain layers or regions are perturbed in autism. The underlying high-dimensional single-cell data provides opportunities for multilevel computational analysis that collectively can better deconvolute the molecular and cellular events altered in autism. Here, we apply advanced computation and pattern recognition approaches on single-cell RNA-seq data to infer and compare inter-cell-type signaling communications in autism brains and controls. Results Our results indicate that at a global level, there are cell-cell communication differences in autism in comparison with controls, largely involving neurons as both signaling senders and receivers, but glia also contribute to the communication disruption. Although the magnitude of changes is moderate, we find that excitatory and inhibitor neurons are involved in multiple intercellular signaling that exhibits increased strengths in autism, such as NRXN and CNTN signaling. Not all genes in the intercellular signaling pathways show differential expression, but genes in the affected pathways are enriched for axon guidance, synapse organization, neuron migration, and other critical cellular functions. Furthermore, those genes are highly connected to and enriched for genes previously associated with autism risks. Conclusions Overall, our proof-of-principle computational study using single-cell data uncovers key intercellular signaling pathways that are potentially disrupted in the autism brains, suggesting that more studies examining cross-cell type effects can be valuable for understanding autism pathogenesis.
 
Top-cited authors
David Hessl
  • University of California, Davis
Randi J Hagerman
  • University of California, Davis
Elizabeth Berry-Kravis
  • Rush University Medical Center
Takao K Hensch
  • Harvard University
Michela Fagiolini
  • Boston Children's Hospital