Calibrated Severity Scores Research Articles

Stratification of Gut Microbiota Profiling Based on Autism Neuropsychological Assessments

Autism spectrum disorder (ASD) is a neurodevelopmental disorder. Investigations of gut microbiota (GM) play an important role in deciphering disease severity and symptoms. Overall, we stratified 70 ASD patients by neuropsychological assessment, based on Calibrated Severity Scores (CSSs) of the Autism Diagnostic Observation Schedule-Second edition (ADOS-2), Child Behavior Checklist (CBCL) and intelligent quotient/developmental quotient (IQ/DQ) parameters. Hence, metataxonomy and PICRUSt-based KEGG predictions of fecal GM were assessed for each clinical subset. Here, 60% of ASD patients showed mild to moderate autism, while the remaining 40% showed severe symptoms; 23% showed no clinical symptoms, 21% had a risk of behavior problems and 56% had clinical symptoms based on the CBCL, which assesses internalizing problems; further, 52% had no clinical symptoms, 21% showed risk, and 26% had clinical symptoms classified by CBCL externalizing problems. Considering the total CBCL index, 34% showed no clinical symptoms, 13% showed risk, and 52% had clinical symptoms. Here, 70% of ASD patients showed cognitive impairment/developmental delay (CI/DD). The GM of ASDs with severe autism was characterized by an increase in Veillonella, a decrease in Monoglobus pectinilyticus and a higher microbial dysbiosis index (MDI) when compared to mild-moderate ASDs. Patients at risk for behavior problems and showing clinical symptoms were characterized by a GM with an increase of Clostridium, Eggerthella, Blautia, Intestinibacter, Coprococcus, Ruminococcus, Onthenecus and Bariatricus, respectively. Peptidoglycan biosynthesis and biofilm formation KEGGs characterized patients with clinical symptoms, while potential microbiota-activated PPAR-γ-signaling was seen in CI/DD patients. This evidence derived from GM profiling may be used to further improve ASD understanding, leasing to a better comprehension of the neurological phenotype.

Longitudinal change in symptom severity in children with ASD: Results from the ELENA cohort.

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition and understanding the changes in autism symptoms over time is crucial for tailoring support and interventions. This study therefore aimed to investigate the changes in symptom severity in a large cohort of children with ASD over a three-year follow-up period and identify factors that influence these changes. The study included 575 children diagnosed with ASD, ranging in age from 2 to 12 years, who were assessed at baseline and again 3 years later using the Autism Diagnostic Observational Schedule-2 (ADOS-2). ASD severity changes were investigated using the ADOS calibrated severity score (CSS) scores for total, social affect (SA) and restricted and repetitive behaviors (RRB). Results highlight four distinct patterns: stable high, stable low, increased, and decreased severity. The ADOS CSS total score changed for half of the sample, reflecting an increase in ASD severity for 21.9% and a decrease for 29.1% of children. For the other half, the ADOS CSS score remained stable, either high (34.4%) or low (14.6%). While the majority of previous studies reported stability in ASD severity, our findings revealed significant variability with frequent improvements in SA symptoms whereas RRBs remained stable or worsened. Our findings also showed that an improvement in SA was associated with the youngest group and early diagnosis. However, no clinical or sociodemographic factors were linked to changes in RRB, emphasizing the necessity for RRB-specific therapies. The third six-year follow-up point of the ongoing ELENA cohort study will map the long-term trajectories of the severity of ASD symptoms and their potential risk factors.

Factors Associated with Confirmed and Unconfirmed Autism Spectrum Disorder Diagnosis in Children Volunteering for Research.

Diagnostic accuracy of autism spectrum disorder (ASD) is crucial to track and characterize ASD, as well as to guide appropriate interventions at the individual level. However, under-diagnosis, over-diagnosis, and misdiagnosis of ASD are still prevalent. We describe 232 children (MAge = 10.71 years; 19% female) with community-based diagnoses of ASD referred for research participation. Extensive assessment procedures were employed to confirm ASD diagnosis before study inclusion. The sample was subsequently divided into two groups with either confirmed ASD diagnoses (ASD+) or unconfirmed/inaccurate diagnoses (ASD-). Clinical characteristics differentiating the groups were further analyzed. 47% of children with community-based ASD diagnoses did not meet ASD criteria by expert consensus. ASD + and ASD- groups did not differ in age, gender, ethnicity, or racial make-up. The ASD + group was more likely to have a history of early language delays compared to the ASD- group; however, no group differences in current functional language use were reported by caregivers. The ASD + group scored significantly higher on ADI-R scores and on the ADOS-2 algorithm composite scores and calibrated severity scores (CSSs). The ASD- group attained higher estimated IQ scores and higher rates of psychiatric disorders, including anxiety disorder, disruptive behavior, and mood disorder diagnoses. Broadly, caregiver questionnaires (SRS-2, CCC-2) did not differentiate groups. Increased reported psychiatric disorders in the ASD- group suggests psychiatric complexity may contribute to community misdiagnosis and possible overdiagnosis of ASD. Clinician-mediated tools (ADI-R, ADOS-2) differentiated ASD + versus ASD- groups, whereas caregiver-reported questionnaires did not.

Intrinsic network abnormalities in children with autism spectrum disorder: an independent component analysis.

Aberrant intrinsic brain networks are consistently observed in individuals with autism spectrum disorder. However, studies examining the strength of functional connectivity across brain regions have yielded conflicting results. Therefore, this study aimed to investigate the functional connectivity of the resting brain in children with low-functioning autism, including during the early developmental stages. We explored the functional connectivity of 43 children with autism spectrum disorder and 54 children with typical development aged 2 to 12 years using resting-state functional magnetic resonance imaging data. We used independent component analysis to classify the brain regions into six intrinsic networks and analyzed the functional connectivity within each network. Moreover, we analyzed the relationship between functional connectivity and clinical scores. In children with autism, the under-connectivities were observed within several brain networks, including the cognitive control, default mode, visual, and somatomotor networks. In contrast, we found over-connectivities between the subcortical, visual, and somatomotor networks in children with autism compared with children with typical development. Moderate effect sizes were observed in entire networks (Cohen's d = 0.43-0.77). These network alterations were significantly correlated with clinical scores such as the communication sub-score (r = - 0.442, p = 0.045) and the calibrated severity score (r = - 0.435, p = 0.049) of the Autism Diagnostic Observation Schedule. These opposing results observed based on the brain areas suggest that aberrant neurodevelopment proceeds in various ways depending on the functional brain regions in individuals with autism spectrum disorder.

The Developmental Autism Early Screening (DAES): A Novel Test for Screening Autism Spectrum Disorder.

This study was undertaken to set a novel developmental screening test for autism spectrum disorder (ASD) using the Griffiths Scales of Child Development (Griffith III) (Green et al., 2016; Stroud et al., 2016), in order to intercept the early atypical developmental patterns indicating ASD risk in the first 3years of age. An observational and interactive ASD screener, the Developmental Autism Early Screening (DAES), was developed by detecting Griffiths III items differentiating toddlers with ASD risk from those with global developmental delay (DD) or neurotypical development. The DAES was validated with ASD-specific diagnostic instruments (ADOS-2) and the cut-off score based on sensitivity, specificity and positive predictive value that best differentiates between ASD and non-ASD children was identified. We enrolled a total sample of 297 subjects, including children at risk for ASD or DD and neurotypical children. At a cut-off score of 12.5, the DAES had a sensitivity of 93%, specificity of 98.4%, positive predictive value of 96.3% and negative predictive value of 96.9% for identifying children at risk for ASD from non-ASD participants (DD/neurotypical children). The DAES total score correlated significantly with the ADOS-2 calibrated severity scores (CSS) (R = 0.53, p < 0.001). Three ASD risk ranges were identified according to DAES total and ADOS-2 CSS: Little-to-no risk (CSS: 1-3, DAES: 1-7); Mild-to-moderate risk (CSS: 4-5, DAES: 8-14); Moderate-to-severe risk (CSS: 6-10, DAES ≥ 15). The DAES provides a direct approach based on developmental profiles to stratify risk for ASD in early childhood ensuring at risk children the most appropriate diagnostic procedures and targeted intervention.

Development of Deep Ensembles to Screen for Autism and Symptom Severity Using Retinal Photographs

Screening for autism spectrum disorder (ASD) is constrained by limited resources, particularly trained professionals to conduct evaluations. Individuals with ASD have structural retinal changes that potentially reflect brain alterations, including visual pathway abnormalities through embryonic and anatomic connections. Whether deep learning algorithms can aid in objective screening for ASD and symptom severity using retinal photographs is unknown. To develop deep ensemble models to differentiate between retinal photographs of individuals with ASD vs typical development (TD) and between individuals with severe ASD vs mild to moderate ASD. This diagnostic study was conducted at a single tertiary-care hospital (Severance Hospital, Yonsei University College of Medicine) in Seoul, Republic of Korea. Retinal photographs of individuals with ASD were prospectively collected between April and October 2022, and those of age- and sex-matched individuals with TD were retrospectively collected between December 2007 and February 2023. Deep ensembles of 5 models were built with 10-fold cross-validation using the pretrained ResNeXt-50 (32×4d) network. Score-weighted visual explanations for convolutional neural networks, with a progressive erasing technique, were used for model visualization and quantitative validation. Data analysis was performed between December 2022 and October 2023. Autism Diagnostic Observation Schedule-Second Edition calibrated severity scores (cutoff of 8) and Social Responsiveness Scale-Second Edition T scores (cutoff of 76) were used to assess symptom severity. The main outcomes were participant-level area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The 95% CI was estimated through the bootstrapping method with 1000 resamples. This study included 1890 eyes of 958 participants. The ASD and TD groups each included 479 participants (945 eyes), had a mean (SD) age of 7.8 (3.2) years, and comprised mostly boys (392 [81.8%]). For ASD screening, the models had a mean AUROC, sensitivity, and specificity of 1.00 (95% CI, 1.00-1.00) on the test set. These models retained a mean AUROC of 1.00 using only 10% of the image containing the optic disc. For symptom severity screening, the models had a mean AUROC of 0.74 (95% CI, 0.67-0.80), sensitivity of 0.58 (95% CI, 0.49-0.66), and specificity of 0.74 (95% CI, 0.67-0.82) on the test set. These findings suggest that retinal photographs may be a viable objective screening tool for ASD and possibly for symptom severity. Retinal photograph use may speed the ASD screening process, which may help improve accessibility to specialized child psychiatry assessments currently strained by limited resources.

EEG functional connectivity in infants at elevated familial likelihood for autism spectrum disorder

BackgroundMany studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy.MethodsWe used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between cortical sources of EEG during video watching using the corrected imaginary part of phase-locking values.ResultsOur main analysis found no significant association between functional connectivity and ASD, showing only significant effects for age, sex, age-sex interaction, and site. Given these null results, we performed an exploratory analysis and observed, at 12 months, a negative correlation between functional connectivity and ADOS calibrated severity scores for restrictive and repetitive behaviors (RRB).LimitationsThe small sample of ASD participants inherent to sibling studies limits diagnostic group comparisons. Also, results from our secondary exploratory analysis should be considered only as potential relationships to further explore, given their increased vulnerability to false positives.ConclusionsThese results are inconclusive concerning an association between EEG functional connectivity and ASD in infancy. Exploratory analyses provided preliminary support for a relationship between RRB and functional connectivity specifically, but these preliminary observations need corroboration on larger samples.

Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males.

Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males. Multi-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated. All dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores. Using TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.

Sociocultural factors associated with detection of autism among culturally and linguistically diverse communities in Australia

BackgroundThe age at which parents or caregivers first develop concerns about their child’s development has significant implications on formal diagnosis and intervention. This study aims to determine the sociocultural factors that are associated with the age and type of first concern reported by parents of autistic children among culturally and linguistically diverse (CALD) communities in Australia. We also assessed whether sociocultural factors predict autism traits measured in terms of social affect (SA), restricted and repetitive behaviours (RRB), and calibrated severity scores (CSS).MethodsThis study is a secondary data analysis of the data collected from six Autism Specific Early Learning and Care Centres (ASELCCs) as part of the Autism Co-operative Research Centre (CRC) program between 2015 and 2019. Data analysed in this study included a family history questionnaire with sociodemographic and sociocultural information, parent-reported age and type of first concern, and clinician/researcher administered Autism Diagnostic Observation Schedule - Second Edition (ADOS-2) which includes standardised domain-wise scores of social affect (SA) and restricted and repetitive behaviours (RRB) as well as calibrated severity scores (CSS), a measure of severity of autism. Primary analysis included multivariable linear regression models to examine the predictive influence of sociodemographic and sociocultural factors on the dependant variables of age of concern (AOC) and the autism traits (SA, RRB, and CSS).ResultsThe mean AOC in the sample was 18.18 months and the most common concerns were speech/language delay, limited social interaction, and hyperactivity/behavioural changes. The multivariable linear regression models showed factors such as increase in age of child, those from a CALD background, annual family income, sibling’s autism diagnosis, and developmental concerns to be significantly associated with parental AOC. Additionally, we also found that increase in child’s age and CALD status to be significant predictors of autism trait (RRB) and severity measured in terms of the CSS score. Further, females (compared to males) were associated with higher difficulties with social communication and interaction skills.ConclusionUnderstanding key factors that contribute to early identification of autism can help tailor awareness programs for parents and caregivers, whilst also informing the development of services focused on serving all CALD communities.

Social visual preference mediates the effect of cortical thickness on symptom severity in children with autism spectrum disorder.

Evidence suggests that there is a robust relationship between altered neuroanatomy and autistic symptoms in individuals with autism spectrum disorder (ASD). Social visual preference, which is regulated by specific brain regions, is also related to symptom severity. However, there were a few studies explored the potential relationships among brain structure, symptom severity, and social visual preference. The current study investigated relationships among brain structure, social visual preference, and symptom severity in 43 children with ASD and 26 typically developing (TD) children (aged 2-6 years). Significant differences were found in social visual preference and cortical morphometry between the two groups. Decreased percentage of fixation time in digital social images (%DSI) was negatively related to not only the thickness of the left fusiform gyrus (FG) and right insula, but also the Calibrated Severity Scores for the Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA-CSS). Mediation analysis showed that %DSI partially mediated the relationship between neuroanatomical alterations (specifically, thickness of the left FG and right insula) and symptom severity. These findings offer initial evidence that atypical neuroanatomical alterations may not only result in direct effects on symptom severity but also lead to indirect effects on symptom severity through social visual preference. This finding enhances our understanding of the multiple neural mechanisms implicated in ASD.

Objective Measurement of Social Gaze and Smile Behaviors in Children with Suspected Autism Spectrum Disorder During Administration of the Autism Diagnostic Observation Schedule, 2nd Edition.

Best practice for the assessment of autism spectrum disorder (ASD) symptom severity relies on clinician ratings of the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2), but the association of these ratings with objective measures of children's social gaze and smiling is unknown. Sixty-six preschool-age children (49 boys, M = 39.97months, SD = 10.58) with suspected ASD (61 confirmed ASD) were administered the ADOS-2 and provided social affect calibrated severity scores (SA CSS). Children's social gaze and smiling during the ADOS-2, captured with a camera contained in eyeglasses worn by the examiner and parent, were obtained via a computer vision processing pipeline. Children who gazed more at their parents (p = .04) and whose gaze at their parents involved more smiling (p = .02) received lower social affect severity scores, indicating fewer social affect symptoms, adjusted R2 = .15, p = .003.

IQ trajectories in autistic children through preadolescence.

We extended our study of trajectories of intellectual development of autistic individuals in early (mean age 3 years; T1), and middle childhood (mean age 5 years, 7 months; T2) into later middle childhood/preadolescence (mean age 11 years, 6 months; T3) in the longitudinal Autism Phenome Project cohort. Participants included 373 autistic children (115 females). Multivariate latent class growth analysis was used to identify distinct IQ trajectory subgroups. Baseline and developmental course group differences and predictors of trajectory membership were assessed using linear mixed effects models with repeated measures with pairwise testing, multinomial logistic regression models, and sensitivity analyses. We isolated three IQ trajectories between T1 and T3 for autistic youth that were similar to those found in our prior work. These included a group with persistent intellectual disability (ID; 45%), a group with substantial increases in IQ (CHG; 39%), and a group with persistently average or above IQs (P-High; 16%). By T3, the groups did not differ in ADOS-2 calibrated severity scores (CSS), and there were no group differences between Vineland (VABS) communication scores in CHG and P-High. T1-T3 externalizing behaviors declined significantly for CHG, however, there were no significant T3 group differences between internalizing or externalizing symptoms. T1 correlates for CHG and P-High versus ID group membership included higher VABS communication and lower ADOS-2 CSS. A T1 to T2 increase in VABS communication scores and a decline in externalizing predicted CHG versus ID group membership at T3, while T1 to T2 improvement in VABS communication and reduction in ADOS-2 CSS predicted P-High versus ID group membership. Autistic youth exhibit consistent IQ developmental trajectories from early childhood through preadolescence. Factors associated with trajectory group membership may provide clues about prognosis, and the need for treatments that improve adaptive communication and externalizing symptoms.

Autistic traits of children born very preterm assessed using Autism Diagnostic Observation Schedule, Second Edition

Preterm birth has been linked with increased incidence of autism spectrum disorder (ASD). Despite the remarkable difference in the clinical backgrounds between ASD children born preterm and term, cross-sectional studies have found no striking difference in their autistic traits. To highlight autistic traits related with preterm birth, children born very preterm (prospective birth cohort, n = 50) and term (case cohort, n = 16), who were diagnosed as “Autism” by the Autism Diagnostic Observation Schedule (ADOS), 2nd edition, were compared using the calibrated severity scores of ADOS-2 and T-scores of the Social Responsiveness Scale, 2nd edition. No significant difference was found in the calibrated severity scores between ASD children born preterm and term. There was a trend that T-scores were smaller for the preterm cohort, which did not reach a statistical significance. Even when detailed cross-sectional information was obtained using ADOS-2, no difference in autistic traits was observed between children born very preterm and term. Our findings were consistent with a previous study, which assessed the entire prospective cohort of children born very preterm and found no difference in original ADOS scores. Further studies are warranted to delineate how preterm birth affects the autistic traits and their parental perception in a large prospective cohort.

Gray matter microstructure differences in autistic males: A gray matter based spatial statistics study

BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition. Understanding the brain’s microstructure and its relationship to clinical characteristics is important to advance our understanding of the neural supports underlying ASD. In the current work, we implemented Gray-Matter Based Spatial Statistics (GBSS) to examine and characterize cortical microstructure and assess differences between typically developing (TD) and autistic males. MethodsA multi-shell diffusion MRI (dMRI) protocol was acquired from 83 TD and 70 autistic males (5-to-21-years) and fit to the DTI and NODDI models. GBSS was performed for voxelwise analysis of cortical gray matter (GM). General linear models were used to investigate group differences, while age-by-group interactions assessed age-related differences between groups. Within the ASD group, relationships between cortical microstructure and measures of autistic symptoms were investigated. ResultsAll dMRI measures were significantly associated with age across the GM skeleton. Group differences and age-by-group interactions are reported. Group-wise increases in neurite density in autistic individuals were observed across frontal, temporal, and occipital regions of the right hemisphere. Significant age-by-group interactions of neurite density were observed within the middle frontal gyrus, precentral gyrus, and frontal pole. Negative relationships between neurite dispersion and the ADOS-2 Calibrated Severity Scores (CSS) were observed within the ASD group. DiscussionFindings demonstrate group and age-related differences between groups in neurite density in ASD across right-hemisphere brain regions supporting cognitive processes. Results provide evidence of altered neurodevelopmental processes affecting GM microstructure in autistic males with implications for the role of cortical microstructure in the level of autistic symptoms. ConclusionUsing dMRI and GBSS, our findings provide new insights into group and age-related differences of the GM microstructure in autistic males. Defining where and when these cortical GM differences arise will contribute to our understanding of brain-behavior relationships of ASD and may aid in the development and monitoring of targeted and individualized interventions.

Social attention during object engagement: toward a cross-species measure of preferential social orienting

BackgroundA 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.MethodsPlay 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.ResultsIn 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.ConclusionsThis 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.

Sex-related differences in clinical characteristics of children with ASD without ID: Results from the ELENA cohort.

The literature on sex related-clinical differences for children with autism spectrum disorder (ASD) is highly contradictory, whereas this topic has major clinical implications. We aimed to investigate sex-related clinical differences in children with ASD without intellectual disability (ID). We compared 319 boys and 65 girls with ASD without ID, aged from 2 to 12 years, recruited from a multiregional cohort on their clinical profiles based on the scores for the Vineland-II, the SRS-2, the ADOS calibrated severity score, sensory processing, aberrant behaviors, and comorbidity rates. Our results confirm a high sex ratio of 4.9 males/females. Many similarities were found in the clinical profiles. However, we found that girls had higher SRS-2 total scores. In addition, there was a negative correlation between the SRS-2 total score and the intellectual quotient level (IQ) for girls only. We confirm the higher rates of boys with ASD without ID. A comparison between the girls and boys showed them to have similar clinical profiles, except for the SRS- 2 total scores, which were higher among girls, suggesting more severe social impairment perceived by parents. Our findings that the cognitive level is related to ASD severity in girls should be taken into account during the diagnostic procedure in the clinical interpretation of gold-standard measures of ASD, and additional clinical observations are necessary. [ClinicalTrials.gov], identifier [NCT02625116s].

The importance of low IQ to early diagnosis of autism.

Some individuals can flexibly adapt to life's changing demands while others, in particular those with Autism Spectrum Disorder (ASD), find it challenging. The origin of early individual differences in cognitive abilities, the putative tools with which to navigate novel information in life, including in infants later diagnosed with ASD remains unexplored. Moreover, the role of intelligence quotient (IQ) vis-à-vis core features of autism remains debated. We systematically investigate the contribution of early IQ in future autism outcomes in an extremely large, population-based study of 8000 newborns, infants, and toddlers from the US between 2 and 68 months with over 15,000 cross-sectional and longitudinal assessments, and for whom autism outcomes are ascertained or ruled out by about 2-4 years. This population is representative of subjects involved in the National Institutes of Health (NIH)-funded research, mainly on atypical development, in the US. Analyses using predetermined age bins showed that IQ scores are consistently lower in ASD relative to typically developing (TD) children at all ages (p < 0.001), and IQ significantly correlates with social, non-social, and total Calibrated Severity Scores (CSS) on the Autism Diagnostic Observation Schedule (ADOS) (p<0.01). Lower IQ is associated with greater autistic impairments. Note, verbal IQ (VIQ) is no better than the full-scale IQ to predict ASD cases. These findings raise new, compelling questions about potential atypical brain circuitry affecting performance in both verbal and nonverbal abilities and preceding an ASD diagnosis. This study is the first to establish prospectively that low early IQ is a major feature of ASD in early childhood. LAY SUMMARY: The role of IQ scores in autism remains debated. We systematically investigate the contribution of early IQ in an extremely large study of 8,000 children between 2 and 68 months with autism outcomes by about 2-4 years. We show that IQ scores are consistently lower in ASD relative to TD children. This study is the first to establish prospectively that low early IQ is a predictor for ASD diagnosis in early childhood.

Associations Among Sex, Cognitive Ability, and Autism Symptoms in Individuals with Down Syndrome

This study explores sex-differences in (a) rates and profiles of autism symptoms as well as in (b) the contribution of intellectual quotient (IQ) to autism symptom presentation in Down syndrome (DS). Participants were 40 males and 38 females with DS, aged 6 to 23 years. Autism symptoms were rated through the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2). Results show no sex differences in the ADOS-2 Calibrated Severity Scores (CSS). However, only females with DS who are classified as DS-Only have higher scores on verbal IQ than those classified as DS + autism. Furthermore, associations between IQ and all CSSs are found for females, but not for males. Findings suggest that verbal cognition may play differential roles for females and males with DS.

Online administration of the ADOS for research with adolescents and adults in response to the pandemic.

This study evaluates an online ADOS-2 Module 4 administration. Adolescents and adults with (n=24; 7 females) and without (n=13; 5 females) a history of autism spectrum disorder (ASD) completed the ADOS-2 Module 4 via videoconference. Parents or caregivers completed the Parent/Caregiver Form of the Vineland Adaptive Behavior Scales and the Achenbach Adult Behavior Checklist. The ADOS-2 was reviewed and scored by five trained clinicians and supervised by a senior clinician with established research reliability. The autistic group's scores differed on ADOS total (Calibrated Severity Score, WPS instrument) and domain scores, KSADS domain scores, and Achenbach T-scores. Inter-rater reliability was "moderate" (κ=0.732), and percentage item-wise agreement was r=0.69. The online ADOS-2 showed significant convergence with parent-reported assessments of ASD-relevant symptoms and characteristics, suggesting it was a valid assessment. While any online assessments must be used with caution, results suggest that the approach described here could have sufficient validity and reliability to fill the urgent need to assess and evaluate ASD symptomatology, as one component of a thorough clinical evaluation of ASD-related behaviors. LAY SUMMARY: In this exploratory study, we asked whether it was possible to givethe ADOS-2 to adolescents and adults in a completely online way. Results showed that expert clinicians agreed on 69% of ADOS-2 items; also, participants with autism had higher scores on all parts of the ADOS-2. The online ADOS-2 scores had strong and significant relationships with parents' reports of friendship and social skills. While we need more research that tests this method, this way of doing the ADOS-2 online may be useful for clinicians and researchers who have an urgent need to evaluate autism during the pandemic.

Sleep Problems and 6-Sulfatoxymelatonin as Possible Predictors of Symptom Severity, Adaptive and Maladaptive Behavior in Children with Autism Spectrum Disorder.

In children with autism spectrum disorder (ASD), sleep disturbances are a frequent comorbidity with an adverse effect on their behavior and functioning. It was suggested that melatonin deficit is at least partly responsible for the sleep problems. The study aimed to investigate, in a sample of 56 children with ASD aged 2.8–13.3 years, if the sleep problems and melatonin secretion can serve as predictors of adaptive functioning and severity of the ASD core symptoms. We demonstrated that, after adjustment for age, the Sleep score assessed by the Children’s Sleep Habits Questionnaire predicts the Adaptive behavior composite score only in children younger than 6 years, and the preferred predictive model is for the domain Socialization. The age-adjusted Sleep score predicted Externalizing and Internalizing maladaptive behavior, with a near-zero contribution of age to the relationship between the Internalizing maladaptive behavior and Sleep score. After adjustment for age, the reduced night-time melatonin secretion predicted a higher severity of ASD symptoms in the domain Social affect and the Calibrated Severity Score, but not the sleep problems. Our results emphasize the importance of assessing sleep problems as a modifiable predictor of behavior in children with ASD and support the hypothesis about the role of melatonin in pathophysiology of ASD.