1. Abbeduto L, Thurman AJ, McDuffie A, Klusek J, Feigles RT, Ted Brown W, Harvey DJ, Adayev T, LaFauci G, Dobkins C, Roberts JE. {{ASD Comorbidity in Fragile X Syndrome: Symptom Profile and Predictors of Symptom Severity in Adolescent and Young Adult Males}}. {Journal of autism and developmental disorders}. 2018.
Many males with FXS meet criteria for ASD. This study was designed to (1) describe ASD symptoms in adolescent and young adult males with FXS (n = 44) and (2) evaluate the contributions to ASD severity of cognitive, language, and psychiatric factors, as well as FMRP (the protein deficient in FXS). A few ASD symptoms on the ADOS-2 were universal in the sample. There was less impairment in restricted and repetitive behaviors (RRB) than in the social affective (SA) domain. The best predictor of overall ASD severity and SA severity was expressive syntactic ability. RRB severity was best predicted by the psychiatric factors. Implications for clinical practice and for understanding the ASD comorbidity in FXS are discussed.
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2. Aran A, Cassuto H, Lubotzky A, Wattad N, Hazan E. {{Brief Report: Cannabidiol-Rich Cannabis in Children with Autism Spectrum Disorder and Severe Behavioral Problems-A Retrospective Feasibility Study}}. {Journal of autism and developmental disorders}. 2018.
Anecdotal evidence of successful cannabis treatment in autism spectrum disorder (ASD) are accumulating but clinical studies are lacking. This retrospective study assessed tolerability and efficacy of cannabidiol-rich cannabis, in 60 children with ASD and severe behavioral problems (age = 11.8 +/- 3.5, range 5.0-17.5; 77% low functioning; 83% boys). Efficacy was assessed using the Caregiver Global Impression of Change scale. Adverse events included sleep disturbances (14%) irritability (9%) and loss of appetite (9%). One girl who used higher tetrahydrocannabinol had a transient serious psychotic event which required treatment with an antipsychotic. Following the cannabis treatment, behavioral outbreaks were much improved or very much improved in 61% of patients. This preliminary study supports feasibility of CBD-based cannabis trials in children with ASD.
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3. Dalla Vecchia E, Mortimer N, Palladino VS, Kittel-Schneider S, Lesch KP, Reif A, Schenck A, Norton WHJ. {{Cross-species models of attention-deficit/hyperactivity disorder and autism spectrum disorder: lessons from CNTNAP2, ADGRL3, and PARK2}}. {Psychiatric genetics}. 2018.
Animal and cellular models are essential tools for all areas of biological research including neuroscience. Model systems can also be used to investigate the pathophysiology of psychiatric disorders such as attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In this review, we provide a summary of animal and cellular models for three genes linked to ADHD and ASD in human patients – CNTNAP2, ADGRL3, and PARK2. We also highlight the strengths and weaknesses of each model system. By bringing together behavioral and neurobiological data, we demonstrate how a cross-species approach can provide integrated insights into gene function and the pathogenesis of ADHD and ASD. The knowledge gained from transgenic models will be essential to discover and validate new treatment targets for these disorders.
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4. Dekhil O, Hajjdiab H, Shalaby A, Ali MT, Ayinde B, Switala A, Elshamekh A, Ghazal M, Keynton R, Barnes G, El-Baz A. {{Using resting state functional MRI to build a personalized autism diagnosis system}}. {PloS one}. 2018; 13(10): e0206351.
Autism spectrum disorder (ASD) is a neuro-developmental disorder associated with social impairments, communication difficulties, and restricted and repetitive behaviors. Yet, there is no confirmed cause identified for ASD. Studying the functional connectivity of the brain is an emerging technique used in diagnosing and understanding ASD. In this study, we obtained the resting state functional MRI data of 283 subjects from the National Database of Autism Research (NDAR). An automated autism diagnosis system was built using the data from NDAR. The proposed system is machine learning based. Power spectral densities (PSDs) of time courses corresponding to the spatial activation areas are used as input features, feeds them to a stacked autoencoder then builds a classifier using probabilistic support vector machines. Over the used dataset, around 90% of sensitivity, specificity and accuracy was achieved by our machine learning system. Moreover, the system generalization ability was checked over two different prevalence values, one for the general population and the other for the of high risk population, and the system proved to be very generalizable, especially among the population of high risk. The proposed system generates a full personalized report for each subject, along with identifying the global differences between ASD and typically developed (TD) subjects and its ability to diagnose autism. It shows the impacted areas and the severity of implications. From the clinical aspect, this report is considered very valuable as it helps in both predicting and understanding behavior of autistic subjects. Moreover, it helps in designing a plan for personalized treatment per each individual subject. The proposed work is taking a step towards achieving personalized medicine in autism which is the ultimate goal of our group’s research efforts in this area.
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5. Garon M, Forgeot d’Arc B, Lavallee MM, Estay EV, Beauchamp MH. {{Visual Encoding of Social Cues Contributes to Moral Reasoning in Autism Spectrum Disorder: An Eye-Tracking Study}}. {Frontiers in human neuroscience}. 2018; 12: 409.
Eye-tracking studies suggest that visual encoding is important for social processes such as socio-moral reasoning. Alterations to the visual encoding of faces, for example, have been linked to the social phenotype of autism spectrum disorders (ASDs) and are associated with social and communication impairments. Yet, people with ASD often perform similarly to neurotypical participants on measures of moral reasoning, supporting the hypothesis of differential mechanisms of moral reasoning in ASD. The objective of this study was to document visual encoding and moral reasoning in ASD and neurotypical individuals using a visual, ecological, sociomoral reasoning paradigm paired with eye-tracking. Two groups (ASD, Control) matched for age and IQ completed the SoMoral task, a set of picture situations describing everyday moral dilemmas, while their eye movements and pupil dilation were recorded. Moral understanding, decision-making, and justification were recorded. Participants with ASD presented a longer time to first fixation on faces. They also understood fewer dilemmas and produced fewer socially adaptive responses. Despite a similar average level of moral maturity, the justifications produced by participants with ASD were not distributed in the same way as the neurotypical participants. Visual encoding was a significant predictor of moral decision-making and moral justification for both groups. The results are discussed in the context of alternative mechanisms of moral reasoning in ASD.
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6. Houghton R, Liu C, Bolognani F. {{Psychiatric Comorbidities and Psychotropic Medication Use in Autism: A Matched Cohort Study with ADHD and General Population Comparator Groups in the United Kingdom}}. {Autism research : official journal of the International Society for Autism Research}. 2018.
Psychiatric comorbidities and use of psychotropic medications are common among patients with autism spectrum disorder (ASD). However, most previous research used data from the United States (US) and few studies have compared medication use in ASD to control groups, making contextualization of results difficult. In the United Kingdom (UK), general practitioners play a key role in the management of ASD. We conducted a retrospective, cross-sectional study over calendar year 2015, using primary care data from the UK. We identified a prevalent cohort of ASD cases (n = 10,856) and matched control groups of (a) general population (n = 21,712) and (b) attention deficit hyperactivity disorder (ADHD; n = 7,058) on age, sex and region. We described psychiatric comorbidities, psychotropic medications, and healthcare utilization in all three cohorts. Within the ASD cohort, we used multivariable logistic regression models to explore associations between patient characteristics and the outcomes of: any psychotropic medication, polypharmacy, and number of primary care visits. We used conditional logistic regression to compare the ASD and control groups. Psychiatric comorbidities were recorded for 41.5% of ASD patients; 32.3% received psychotropic medication and 9.8% received polypharmacy. Increased age and all psychiatric comorbidities (except conduct disorder) were associated with treatment use. Males were less likely to receive a treatment than females [Odds ratio (OR) 0.74 (0.66-0.83)]. ASD patients were more likely to take psychotropic medications than the general population [OR 4.91 (4.46-5.40)], but less likely compared to ADHD patients [OR 0.40 (0.37-0.44)]. Overall, rates of medication use in the UK were lower than those previously reported in the US. Autism Research 2018. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We used electronic medical records from the UK, to describe the amount of psychiatric comorbidities, psychotropic medication use and healthcare resource use in ASD. Around one in three people with ASD were prescribed a psychotropic medication, which was more than the general population, but less than for those with ADHD. Increased age, psychiatric comorbidities and female gender were all independently associated with psychotropic medication use. Rates of medication use in the UK were lower than those previously reported in the US.
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7. Janecka M, Kodesh A, Levine SZ, Lusskin SI, Viktorin A, Rahman R, Buxbaum JD, Schlessinger A, Sandin S, Reichenberg A. {{Association of Autism Spectrum Disorder With Prenatal Exposure to Medication Affecting Neurotransmitter Systems}}. {JAMA psychiatry}. 2018.
Importance: Prenatal exposure to certain medications has been hypothesized to influence the risk of autism spectrum disorders (ASD). However, the underlying effects on the neurotransmitter systems have not been comprehensively assessed. Objective: To investigate the association of early-life interference with different neurotransmitter systems by prenatal medication exposure on the risk of ASD in offspring. Design, Setting, and Participants: This case-control study included children born from January 1, 1997, through December 31, 2007, and followed up for ASD until January 26, 2015, within a single Israeli health maintenance organization. Using publicly available data, 55 groups of medications affecting neurotransmitter systems and prescribed to pregnant women in this sample were identified. Children prenatally exposed to medications were compared with nonexposed children. Data were analyzed from March 1, 2017, through June 20, 2018. Main Outcome and Measures: Hazard ratios (HRs) and 95% CIs of ASD risk associated with exposure to medication groups using Cox proportional hazards regression, adjusted for the relevant confounders (eg, birth year, maternal age, maternal history of psychiatric and neurologic disorders, or maternal number of all medical diagnoses 1 year before pregnancy). Results: The analytic sample consisted of 96249 individuals (1405 cases; 94844 controls; mean [SD] age at the end of follow-up, 11.6 [3.1] years; 48.8% female), including 1405 with ASD and 94844 controls. Of 34 groups of medications, 5 showed nominally statistically significant association with ASD in fully adjusted models. Evidence of confounding effects of the number of maternal diagnoses on the association between offspring exposure to medication and ASD was found. Adjusting for this factor, lower estimates of ASD risk among children exposed to cannabinoid receptor agonists (HR, 0.72; 95% CI, 0.55-0.95; P = .02), muscarinic receptor 2 agonists (HR, 0.49; 95% CI, 0.24-0.98; P = .04), opioid receptor kappa and epsilon agonists (HR, 0.67; 95% CI, 0.45-0.99; P = .045), or alpha2C-adrenergic receptor agonists (HR, 0.43; 95% CI, 0.19-0.96; P = .04) were observed. Exposure to antagonists of neuronal nicotinic acetylcholine receptor alpha was associated with higher estimates of ASD risk (HR, 12.94; 95% CI, 1.35-124.25; P = .03). Conclusions and Relevance: Most of the medications affecting neurotransmitter systems in this sample had no association with the estimates of ASD risk. Replication and/or validation using experimental techniques are required.
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8. Jia H, Yu D. {{Aberrant Intrinsic Brain Activity in Patients with Autism Spectrum Disorder: Insights from EEG Microstates}}. {Brain topography}. 2018.
Autism spectrum disorder (ASD) involves aberrant organization and functioning of large-scale brain networks. The aim of this study was to examine whether the resting-state EEG microstate analysis could provide novel insights into the abnormal temporal and spatial properties of intrinsic brain activities in patients with ASD. To achieve this goal, EEG microstate analysis was conducted on the resting-state EEG datasets of 15 patients with ASD and 18 healthy controls from the Healthy Brain Network. The parameters (i.e., duration, occurrence rate, time coverage and topographical configuration) of four classical microstate classes (i.e., class A, B, C and D) were statistically tested between two groups. The results showed that: (1) the occurrence rate and time coverage of microstate class B in ASD group were significantly larger than those in control group; (2) the duration of microstate class A, the duration and time coverage of microstate class C were significantly smaller than those in control group; (3) the map configuration and occurrence rate differed significantly between two groups for microstate class D. These results suggested that EEG microstate analysis could be used to detect the deviant functions of large-scale cortical activities in ASD, and may provide indices that could be used in clinical researches of ASD.
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9. Kang E, McPartland JC, Keifer CM, Foss-Feig JH, Levy EJ, Lerner MD. {{Reply to: Can the N170 Be Used as an Electrophysiological Biomarker Indexing Face Processing Difficulties in Autism Spectrum Disorder?}}. {Biological psychiatry Cognitive neuroscience and neuroimaging}. 2018.
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10. Ko JA, Miller AR, Vernon TW. {{Social conversation skill improvements associated with the Social Tools And Rules for Teens program for adolescents with autism spectrum disorder: Results of a randomized controlled trial}}. {Autism : the international journal of research and practice}. 2018: 1362361318808781.
There has been a significant increase in the development of interventions to improve the social competence and success of adolescents with autism spectrum disorder. The current investigation used direct observation and coding of social conversations as a rigorous method to further assess the efficacy of the Social Tools And Rules for Teens socialization intervention for adolescents with autism spectrum disorder in the context of a randomized controlled trial. A total of 35 adolescents with high-functioning autism spectrum disorder were randomized to either a treatment or waitlist control group. The 20-week group intervention took place once a week for 90 min per session. Brief video-recorded conversations between participants and unfamiliar, untrained peers were recorded at pre- and post-time points and coded for selected social behaviors (i.e. questions asked, positive facial expressions, and mutual engagement). Results revealed a significant Group x Time treatment effect for both questions asked and positive facial expressions. The findings support that the Social Tools And Rules for Teens intervention can positively impact specific, observable social behaviors through systematic coding of live social conversations within the context of a randomized controlled trial. This investigation is one of the first randomized controlled trials of a group socialization intervention to use systematic coding of live social conversations to assess social competence improvements.
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11. Kovarski K, Mennella R, Wong SM, Dunkley BT, Taylor MJ, Batty M. {{Enhanced Early Visual Responses During Implicit Emotional Faces Processing in Autism Spectrum Disorder}}. {Journal of autism and developmental disorders}. 2018.
Research on Autism Spectrum Disorder (ASD) has focused on processing of socially-relevant stimuli, such as faces. Nonetheless, before being ‘social’, faces are visual stimuli. The present magnetoencephalography study investigated the time course of brain activity during an implicit emotional task in visual emotion-related regions in 19 adults with ASD (mean age 26.3 +/- 4.4) and 19 typically developed controls (26.4 +/- 4). The results confirmed previously-reported differences between groups in brain responses to emotion and a hypo-activation in the ASD group in the right fusiform gyrus around 150 ms. However, the ASD group also presented early enhanced activity in the occipital region. These results support that impaired face processing in ASD might be sustained by atypical responses in primary visual areas.
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12. Lawrence KE, Hernandez LM, Bookheimer SY, Dapretto M. {{Atypical longitudinal development of functional connectivity in adolescents with autism spectrum disorder}}. {Autism research : official journal of the International Society for Autism Research}. 2018.
Autism spectrum disorder (ASD) is consistently associated with alterations in brain connectivity, but there are conflicting results as to where and when individuals with ASD display increased or reduced functional connectivity. Such inconsistent findings may be driven by atypical neurodevelopmental trajectories in ASD during adolescence, but no longitudinal studies to date have investigated this hypothesis. We thus examined the functional connectivity of three neurocognitive resting-state networks-the default mode network (DMN), salience network, and central executive network (CEN)-in a longitudinal sample of youth with ASD (n = 16) and without ASD (n = 22) studied during early/mid- and late adolescence. Functional connectivity between the CEN and the DMN displayed significantly altered developmental trajectories in ASD: typically developing (TD) controls-but not youth with ASD-exhibited an increase in negative functional connectivity between these two networks with age. This significant interaction was due to the ASD group displaying less negative functional connectivity than the TD group during late adolescence only, with no significant group differences in early/mid-adolescence. These preliminary findings suggest a localized age-dependency of functional connectivity alterations in ASD and underscore the importance of considering age when examining brain connectivity. Autism Research 2018. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Brain connectivity may develop differently during adolescence in youth with autism spectrum disorder (ASD). We looked at changes in brain connectivity over time within individuals and found that, for some brain regions, adolescents with ASD did not show the same changes in brain connectivity that typically developing adolescents did. This suggests it is important to consider age when studying brain connectivity in ASD.
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13. Lopata C, Thomeer ML, Rodgers JD, Donnelly JP, McDonald CA, Volker MA, Smith TH, Wang H. {{Cluster Randomized Trial of a School Intervention for Children with Autism Spectrum Disorder}}. {Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53}. 2018: 1-12.
There are currently no empirically supported, comprehensive school-based interventions (CSBIs) for children with autism spectrum disorder (ASD) without concomitant intellectual and language disability. This study compared outcomes for a CSBI (schoolMAX) to typical educational programming (services-as-usual [SAU]) for these children. A total of 103 children (6-12 years of age) with ASD (without intellectual and language disability) were randomly assigned by school buildings (clusters) to receive the CSBI (n = 52 completed) or SAU (n = 50 completed). The CSBI was implemented by trained school personnel and targeted social competence and ASD symptoms using social skills groups, emotion recognition instruction, therapeutic activities, behavioral reinforcement, and parent training. Outcome measures tested the effects of the CSBI on social competence and ASD symptoms, as well as potential collateral effects on academic achievement. Outcomes (baseline-to-follow-up) were assessed using tests of social cognition and academic skills and behavioral observations (by masked evaluators) and parent-teacher ratings of ASD symptoms and social/social-communication skills (nonmasked; ClinicalTrials.gov, NCT03338530, https://www.clinicaltrials.gov/ ). The CSBI group improved significantly more than the SAU group on the test of emotion recognition skills and parent-teacher ratings of ASD symptoms (primary outcomes) and social/social-communication skills (secondary outcome). No differences between groups were detected for recess social interactions or academic skills. The CSBI improved several core areas of functioning for children with ASD compared to usual educational programming. Additional intervention elements may be needed to expand the efficacy of the CSBI so that the observed skills/symptom improvements generalize to recess social interactions and/or academic skills are enhanced.
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14. Maras K, Marshall I, Sands C. {{Mock Juror Perceptions of Credibility and Culpability in an Autistic Defendant}}. {Journal of autism and developmental disorders}. 2018.
One-hundred-and-sixty jury-eligible participants read a vignette describing a male who was brought to the attention of police for suspicious and aggressive behaviours and displayed atypical behaviours in court. Half of participants were informed that he had autism spectrum disorder (ASD) and were given background information about ASD; the other half received no diagnostic label or information. The provision of a label and information led to higher ratings of the defendant’s honesty and likeability, reduced blameworthiness, and resulted in fewer guilty verdicts, and more lenient sentencing. Thematic analysis revealed that participants in the label condition were more empathetic and attributed his behaviours to his ASD and mitigating factors, while participants in the No label condition perceived the defendant as deceitful, unremorseful, rude and aggressive.
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15. Muller RA, Fishman I. {{Brain Connectivity and Neuroimaging of Social Networks in Autism}}. {Trends in cognitive sciences}. 2018.
Impairments in social communication (SC) predominate among the core diagnostic features of autism spectrum disorders (ASDs). Neuroimaging has revealed numerous findings of atypical activity and connectivity of ‘social brain’ networks, yet no consensus view on crucial developmental causes of SC deficits has emerged. Aside from methodological challenges, the deeper problem concerns the clinical label of ASD. While genetic studies have not comprehensively explained the causes of nonsyndromic ASDs, they highlight that the clinical label encompasses many etiologically different disorders. The question of how potential causes and etiologies converge onto a comparatively narrow set of SC deficits remains. Only neuroimaging designs searching for subtypes within ASD cohorts (rather than conventional group level designs) can provide translationally informative answers.
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16. Palumbo L, Macinska ST, Jellema T. {{The Role of Pattern Extrapolation in the Perception of Dynamic Facial Expressions in Autism Spectrum Disorder}}. {Frontiers in psychology}. 2018; 9: 1918.
Changes in the intensity and type of facial expressions reflect alterations in the emotional state of the agent. Such « direct » access to the other’s affective state might, top-down, influence the perception of the facial expressions that gave rise to the affective state inference. Previously, we described a perceptual bias occurring when the last, neutral, expression of offsets of facial expressions (joy-to-neutral and anger-to-neutral), was evaluated. Individuals with high-functioning autism (HFA) and matched typically developed (TD) individuals rated the neutral expression at the end of the joy-offset videos as slightly angry and the identical neutral expression at the end of the anger-offset videos as slightly happy (« overshoot » bias). That study suggested that the perceptual overshoot response bias in the TD group could be best explained by top-down « emotional anticipation, » i.e., the involuntary/automatic anticipation of the agent’s next emotional state of mind, generated by the immediately preceding perceptual history (low-level mind reading). The experimental manipulations further indicated that in the HFA group the « overshoot » was better explained by contrast effects between the first and last facial expressions, both presented for a relatively long period of 400 ms. However, in principle, there is another, more parsimonious, explanation, which is pattern extrapolation or representational momentum (RM): the extrapolation of a pattern present in the dynamic sequence. This hypothesis is tested in the current study, in which 18 individuals with HFA and a matched control group took part. In a base-line condition, joy-offset and anger-offset video-clips were presented. In the new experimental condition, the clips were modified so as to create an offset-onset-offset pattern within each sequence (joy-to-anger-to-neutral and anger-to-joy-to-neutral). The final neutral expressions had to be evaluated. The overshoot bias was confirmed in the base-line condition for both TD and HFA groups, while the experimental manipulation removed the bias in both groups. This outcome ruled out pattern extrapolation or RM as explanation for the perceptual « overshoot » bias in the HFA group and suggested a role for facial contrast effects in HFA. This is compatible with the view that ASD individuals tend to lack the spontaneous « tracking » of changes in the others’ affective state and hence show no or reduced emotional anticipation.
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17. Schendel D, Christensen J, Rai D. {{A Biology-First Approach in Perinatal Pharmacoepidemiology of Autism: Potential and Pitfalls}}. {JAMA psychiatry}. 2018.
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18. Vettori S, Jacques C, Boets B, Rossion B. {{Can the N170 Be Used as an Electrophysiological Biomarker Indexing Face Processing Difficulties in Autism Spectrum Disorder?}}. {Biological psychiatry Cognitive neuroscience and neuroimaging}. 2018.
