scholarly journals The subcortical morphology correlates of autistic traits in school-age children: a population-based neuroimaging study

2021 ◽  
Author(s):  
Tamsin Sharp ◽  
Mayada Elsabbagh ◽  
Andrew Pickles ◽  
Rachael Bedford
Keyword(s):  
Cognitive Development ◽  
Brain Size ◽  
Autistic Traits ◽  
Brain Morphology ◽  
School Age Children ◽  
Social Responsiveness ◽  
Imaging Data ◽  
Subcortical Structures ◽  
Development Study ◽  
Cortical Morphology

Background There is emerging evidence that the neuroanatomy of autism forms a spectrum which extends into the general population. However, whilst several studies have identified cortical morphology correlates of autistic traits, it is not established whether morphological differences are present in the subcortical structures of the brain. Additionally, it is not clear to what extent previously reported structural associations may be confounded by co-occurring psychopathology. To address these questions, we utilised neuroimaging data from the Adolescent Brain Cognitive Development Study to assess whether a measure of autistic traits was associated with differences in child subcortical morphology, and if any observed differences persisted after adjustment for child internalising and externalising symptoms. Methods Our analyses included data from 7,005 children aged 9-10 years (female: 47.19%) participating in the Adolescent Brain Cognitive Development Study. Autistic traits were assessed using scores from the Social Responsiveness Scale. Volumes of subcortical regions-of-interest were derived from structural magnetic resonance imaging data. Results Overall, we did not find strong evidence for an association of autistic traits with differences in subcortical morphology in this sample of school-aged children. Whilst lower absolute volumes of the nucleus accumbens and putamen were associated with higher scores of autistic traits, these differences did not persist once a global measure of brain size was accounted for. Conclusions These findings from our well-powered study suggest that other metrics of brain morphology, such as cortical morphology or shape-based phenotypes, may be stronger candidates to prioritise when attempting to identify robust neuromarkers of autistic traits.

The Influence of Language Context on Repetitive Speech Use in Children With Autism Spectrum Disorder

2020 ◽  
Vol 29 (1) ◽  
pp. 327-334 ◽  
Author(s):  
Allison Gladfelter ◽  
Cassidy VanZuiden
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Individual Characteristics ◽  
Receptive Vocabulary ◽  
Spectrum Disorder ◽  
School Age Children ◽  
Social Responsiveness ◽  
Contributing Factors ◽  
Children With Asd ◽  
Language Context

Purpose Although repetitive speech is a hallmark characteristic of autism spectrum disorder (ASD), the contributing factors that influence repetitive speech use remain unknown. The purpose of this exploratory study was to determine if the language context impacts the amount and type of repetitive speech produced by children with ASD. Method As part of a broader word-learning study, 11 school-age children with ASD participated in two different language contexts: storytelling and play. Previously collected language samples were transcribed and coded for four types of repetitive speech: immediate echolalia, delayed echolalia, verbal stereotypy, and vocal stereotypy. The rates and proportions of repetitive speech were compared across the two language contexts using Wilcoxon signed-ranks tests. Individual characteristics were further explored using Spearman correlations. Results The children produced lower rates of repetitive speech during the storytelling context than the play-based context. Only immediate echolalia differed between the two contexts based on rate and approached significance based on proportion, with more immediate echolalia produced in the play-based context than in the storytelling context. There were no significant correlations between repetitive speech and measures of social responsiveness, expressive or receptive vocabulary, or nonverbal intelligence. Conclusions The children with ASD produced less immediate echolalia in the storytelling context than in the play-based context. Immediate echolalia use was not related to social skills, vocabulary, or nonverbal IQ scores. These findings offer valuable insights into better understanding repetitive speech use in children with ASD.

Brain Structure and Internalizing Psychopathology in Children 9-10 Years of Age: Results From the Adolescent Brain Cognitive Development Study

2021 ◽  
Vol 89 (9) ◽  
pp. S367
Author(s):  
Matthew Albaugh ◽  
Max Owens ◽  
DeKang Yuan ◽  
Jonatan Ottino-Gonzalez ◽  
Bader Chaarani ◽  
...  
Keyword(s):  
Cognitive Development ◽  
Brain Structure ◽  
Development Study ◽  
Internalizing Psychopathology

scholarly journals Advances in studying brain morphology: The benefits of open-access data

2017 ◽  
Author(s):  
Christopher R Madan
Keyword(s):  
Open Access ◽  
Brain Structure ◽  
Large Scale ◽  
Open Data ◽  
Brain Morphology ◽  
Subcortical Structures ◽  
Open Access Data ◽  
Age Related ◽  
Neuroimaging Data ◽  
Access Data

Until recently, neuroimaging data for a research study needed to be collected within one’s own lab. However, when studying inter-individual differences in brain structure, a large sample of participants is necessary. Given the financial costs involved in collecting neuroimaging data from hundreds or thousands of participants, large-scale studies of brain morphology could previously only be conducted by well-funded laboratories with access to MRI facilities and to large samples of participants. With the advent of broad open-access data-sharing initiatives, this has recently changed–here the primary goal of the study is to collect large datasets to be shared, rather than sharing of the data as an afterthought. This paradigm shift is evident as increase in the pace of discovery, leading to a rapid rate of advances in our characterization of brain structure. The utility of open-access brain morphology data is numerous, ranging from observing novel patterns of age-related differences in subcortical structures to the development of more robust cortical parcellation atlases, with these advances being translatable to improved methods for characterizing clinical disorders (see Figure 1 for an illustration). Moreover, structural MRIs are generally more robust than functional MRIs, relative to potential artifacts and in being not task-dependent, resulting in large potential yields. While the benefits of open-access data have been discussed more broadly within the field of cognitive neuroscience elsewhere (Gilmore et al., 2017; Poldrack and Gorgolewski, 2014; Van Horn and Gazzaniga, 2013; Voytek, 2016), as well as in other fields (Ascoli et al., 2017; Choudhury et al., 2014; Davies et al., 2017), the current paper is focused specifically on the implications of open data to brain morphology research.

The Utility of Parent-Report Screening Tools in Differentiating Autism vs. ADHD in School-age Children

2021 ◽  
Author(s):  
Sara Guttentag ◽  
Somer Bishop ◽  
Rebecca Doggett ◽  
Rebecca Shalev ◽  
Megan Kaplan ◽  
...  
Keyword(s):  
Statistical Significance ◽  
Parent Report ◽  
Autism Spectrum ◽  
Screening Tools ◽  
School Age Children ◽  
Social Responsiveness ◽  
School Age ◽  
Multiple Sources ◽  
Receiver Operating Characteristic Curves ◽  
Parent Concerns

Symptoms of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) often co-occur, challenging timely and accurate diagnosis. We assessed the performance of three parent-report measures in discriminating ASD from ADHD without ASD (ADHDw/oASD) in school-age verbally fluent children. We examined the Autism Symptom Interview (ASI) School-Age and two widely used parent questionnaires: Social Responsiveness Scale-2nd Edition (SRS-2) and Social Communication Questionnaire-Lifetime (SCQ-L). Receiver operating characteristic curves assessed each instrument’s performance against the best-estimate clinician DSM-5 diagnosis of ASD or of ADHDw/oASD (n=74, n=102, respectively; 6-11 years). These yielded moderate accuracies: AUC=0.85, 0.79, 0.78 for SCQ-L, ASI, SRS-2, respectively. AUC pairwise comparisons reached our statistical significance (p<0.01) for the SCQ-L vs. the SRS-2. Within instruments, sensitivity and specificity varied across ASD cutoffs. Along with the between-instrument variability, this indicates that clinicians and researchers have valid options, depending on the settings and their goals. Comparing children correctly and incorrectly classified as ASD showed no differences in demographics, intellectual abilities, nor in any specific clinical profile(s), except for the degree of parent concerns across ASD- and comorbid psychopathology-related symptoms. Together, results suggest that complementing parent screeners with multiple sources may be needed to best differentiate school-age verbally fluent children with ASD vs. ADHDw/oASD.

scholarly journals The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

2019 ◽  
Vol 50 (4) ◽  
pp. 233-246 ◽  
Author(s):  
Pei-Yin Pan ◽  
Kristiina Tammimies ◽  
Sven Bölte
Keyword(s):  
Autism Spectrum Disorder ◽  
Twin Pair ◽  
Monozygotic Twins ◽  
Twin Studies ◽  
Autistic Traits ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Social Responsiveness ◽  
Somatic Health ◽  
Validated Questionnaire

AbstractThis study used a twin cohort to investigate the association of autism spectrum disorder (ASD) and autistic traits with somatic health. A total of 344 twins (172 pairs; mean age 15.56 ± 5.62 years) enriched for ASD and other neurodevelopmental conditions were examined. Medical history and current physical problems were collected with a validated questionnaire to determine twin’s somatic health. The Social Responsiveness Scale (SRS-2) was used to measure the participant’s severity of autistic traits. Identified somatic health issues with significant within-twin pair differences were tested in relation to both ASD diagnosis and autistic traits in a co-twin control model. Twins with ASD exhibited more neurological and immunological health problems compared to those without ASD (p = 0.005 and p = 0.004, respectively). The intra-pair differences of neurological conditions and SRS-2 score were significantly correlated in monozygotic twins differing for autism traits (r = 0.40, p = 0.001), while the correlation was not found for immunological problems. In addition, a conditional model for analysis of within-twin pair effects revealed an association between neurological problems and clinical ASD diagnosis (Odds ratio per neurological problem 3.15, p = 0.02), as well as autistic traits (β = 10.44, p = 0.006), after adjusting for possible effects of co-existing attention deficit hyperactivity disorder and general intellectual abilities. Our findings suggest that neurological problems are associated with autism, and that non-shared environmental factors contribute to the overlap for both clinical ASD and autistic traits. Further population-based twin studies are warranted to validate our results and examine in detailed the shared genetic and environmental contributions of neurological problems and ASD.

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