Clinical Autism Spectrum Disorder Research Articles

Probiotics in autism spectrum disorders: a systematic review of clinical studies and future directions.

It is hypothesized that gut dysbiosis, a typical feature of patients with autism spectrum disorder (ASD), could be involved in the origin of this neurodevelopmental disorder. Therefore, the use of probiotics to restore gastrointestinal (GI) equilibrium might be a promising therapeutic strategy due to its capacity to balance the gut-brain axis and behavioral responses. To summarize current knowledge on the use of probiotics to treat core clinical ASD symptoms and concomitant GI signs, compare the design of published studies with those of ongoing trials, assess the near future of this field, and provide recommendations for improving novel studies. The literature search was conducted in February 2020 and updated in March 2021, using a broad range of bibliographic and clinical trial-specific databases. Data were extracted using a standardized form, and articles reporting on 28 clinical studies (already published or still ongoing) were included. The risk of bias in clinical studies was evaluated using the Cochrane Collaboration Risk of Bias Assessment tool for randomized trials and the Risk of Bias in Nonrandomized Studies-Interventions tool for nonrandomized trials. The results suggest that probiotics improve ASD-like social deficits, GI symptoms, and gut microbiota profile. However, inconsistencies among studies and their methodological limitations make it difficult to draw any conclusions regarding the efficacy of probiotics in ASD. This review provides specific suggestions for future research to improve the quality of the studies. Although ongoing studies have improved designs, the available knowledge does not permit solid conclusions to be made regarding the efficacy of probiotics in ameliorating the symptoms (psychiatric and/or GI) associated with ASD. Thus, more high-quality research and new approaches are needed to design effective probiotic strategies for ASD.

Autism spectrum disorder in ICD-11-a critical reflection of its possible impact on clinical practice and research.

This perspective article compares and contrasts the conceptualization of Autism Spectrum Disorder (ASD) in ICD-11 and DSM-5. By guiding the user through the ICD-11 text, it is argued that, in contrast to DSM-5, ICD-11 allows a high variety in symptom combinations, which results in an operationalization of ASD that is in favor of an extreme diverse picture, yet possibly at the expense of precision, including unforeseeable effects on clinical practice, care, and research. The clinical utility is questionable as this conceptualization can hardly be differentiated from other mental disorders and autism-like traits. It moves away from an observable, behavioral, and neurodevelopmental disorder to a disorder of inner experience that can hardly be measured objectively. It contains many vague and subjective concepts that lead to non-falsifiable diagnoses. This bears a large danger of false positive diagnoses, of further increased prevalence rates, limitations of access to ASD-specific services and of increasing the non-specificity of treatments. For research, the hypothesis is that the specificity of ASD will be reduced and this will additional increase the already high heterogeneity with the effect that replication of studies will be hampered. This could limit our understanding of etiology and biological pathways of ASD and bears the risk that precision medicine, i.e., a targeted approach for individual treatment strategies based on precise diagnostic markers, is more far from becoming reality. Thus, a more precise, quantitative description and more objective measurement of symptoms are suggested that define the clinical ASD phenotype. Identification of core ASD subtypes/endophenotypes and a precise description of symptoms is the necessary next step to advance diagnostic classification systems. Therefore, employing a more finely grained, objective, clinical symptom characterization which is more relatable to neurobehavioral concepts is of central significance.

Screen Time and Autism Spectrum Disorder

ImportanceContemporary studies raise concerns regarding the implications of excessive screen time on the development of autism spectrum disorder (ASD). However, the existing literature consists of mixed and unquantified findings.ObjectiveTo conduct a systematic review and meta-analyis of the association between screen time and ASD.Data SourcesA search was conducted in the PubMed, PsycNET, and ProQuest Dissertation & Theses Global databases for studies published up to May 1, 2023.Study SelectionThe search was conducted independently by 2 authors. Included studies comprised empirical, peer-reviewed articles or dissertations published in English with statistics from which relevant effect sizes could be calculated. Discrepancies were resolved by consensus.Data Extraction and SynthesisThis study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Two authors independently coded all titles and abstracts, reviewed full-text articles against the inclusion and exclusion criteria, and resolved all discrepancies by consensus. Effect sizes were transformed into log odds ratios (ORs) and analyzed using a random-effects meta-analysis and mixed-effects meta-regression. Study quality was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. Publication bias was tested via the Egger z test for funnel plot asymmetry. Data analysis was performed in June 2023.Main Outcomes and MeasuresThe 2 main variables of interest in this study were screen time and ASD. Screen time was defined as hours of screen use per day or per week, and ASD was defined as an ASD clinical diagnosis (yes or no) or ASD symptoms. The meta-regression considered screen type (ie, general use of screens, television, video games, computers, smartphones, and social media), age group (children vs adults or heterogenous age groups), and type of ASD measure (clinical diagnosis vs ASD symptoms).ResultsOf the 4682 records identified, 46 studies with a total of 562 131 participants met the inclusion criteria. The studies were observational (5 were longitudinal and 41 were cross-sectional) and included 66 relevant effect sizes. The meta-analysis resulted in a positive summary effect size (log OR, 0.54 [95% CI, 0.34 to 0.74]). A trim-and-fill correction for a significant publication bias (Egger z = 2.15; P = .03) resulted in a substantially decreased and nonsignificant effect size (log OR, 0.22 [95% CI, −0.004 to 0.44]). The meta-regression results suggested that the positive summary effect size was only significant in studies targeting general screen use (β [SE] = 0.73 [0.34]; t58 = 2.10; P = .03). This effect size was most dominant in studies of children (log OR, 0.98 [95% CI, 0.66 to 1.29]). Interestingly, a negative summary effect size was observed in studies investigating associations between social media and ASD (log OR, −1.24 [95% CI, −1.51 to −0.96]).Conclusions and RelevanceThe findings of this systematic review and meta-analysis suggest that the proclaimed association between screen use and ASD is not sufficiently supported in the existing literature. Although excessive screen use may pose developmental risks, the mixed findings, the small effect sizes (especially when considering the observed publication bias), and the correlational nature of the available research require further scientific investigation. These findings also do not rule out the complementary hypothesis that children with ASD may prioritize screen activities to avoid social challenges.

A hybrid graph network model for ASD diagnosis based on resting-state EEG signals

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12 % and 85.32 % in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.

Development and validation of an Arabic language eye-tracking paradigm for the early screening and diagnosis of autism spectrum disorders in Qatar.

Abnormal eye gaze is a hallmark characteristic of autism spectrum disorder (ASD). The primary aim of the present research was to develop an Arabic version of an objective measure of ASD, the "autism index" (AI), based on eye gaze tracking to social and nonsocial stimuli validated initially in the United States. The initial phase of this study included the translation of English language eye-tracking stimuli into stimuli appropriate for an Arabic-speaking culture. During the second phase, we tested it on a total of 144 children with ASD, and 96 controls. The AI had excellent internal consistency and test-retest reliability. Moreover, the AI showed good differentiation of ASD from control cases (AUC = 0.730, SE = 0.035). The AI was significantly positively correlated with SCQ total raw scores (r = 0.46, p < 0.001). ADOS-2 scores were only available in the ASD group and did not show a significant relationship with AI scores (r = 0.10, p = 0.348), likely due to the restricted range. The AI, when implemented using Arabic-translated stimuli in a Qatari sample, showed good diagnostic differentiation and a strong correlation with parent-reported ASD symptoms. Thus, the AI appears to have cross-cultural validity and may be useful as a diagnostic aide to inform clinical judgment and track ASD symptom levels as part of the evaluation process.

Differences between subclinical attention-deficit/hyperactivity and autistic traits in default mode, salience, and frontoparietal network connectivities in young adult Japanese

Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are associated with attentional impairments, with both commonalities and differences in the nature of their attention deficits. This study aimed to investigate the neural correlates of ADHD and ASD traits in healthy individuals, focusing on the functional connectivity (FC) of attention-related large-scale brain networks (LSBNs). The participants were 61 healthy individuals (30 men; age, 21.9 ± 1.9 years). The Adult ADHD Self-Report Scale (ASRS) and Autism Spectrum Quotient (AQ) were administered as indicators of ADHD and ASD traits, respectively. Performance in the continuous performance test (CPT) was used as a behavioural measure of sustained attentional function. Functional magnetic resonance imaging scans were performed during the resting state (Rest) and auditory oddball task (Odd). Considering the critical role in attention processing, we focused our analyses on the default mode (DMN), frontoparietal (FPN), and salience (SN) networks. Region of interest (ROI)-to-ROI analyses (false discovery rate < 0.05) were performed to determine relationships between psychological measures with within-network FC (DMN, FPN, and SN) as well as with between-network FC (DMN-FPN, DMN-SN, and FPN-SN). ASRS scores, but not AQ scores, were correlated with less frequent commission errors and shorter reaction times in the CPT. During Odd, significant positive correlations with ASRS were demonstrated in multiple FCs within DMN, while significant positive correlations with AQ were demonstrated in multiple FCs within FPN. AQs were negatively correlated with FPN-SN FCs. During Rest, AQs were negatively and positively correlated with one FC within the SN and multiple FCs between the DMN and SN, respectively. These findings of the ROI-to-ROI analysis were only partially replicated in a split-half replication analysis, a replication analysis with open-access data sets, and a replication analysis with a structure-based atlas. The better CPT performance by individuals with subclinical ADHD traits suggests positive effects of these traits on sustained attention. Differential associations between LSBN FCs and ASD/ADHD traits corroborate the notion of differences in sustained and selective attention between clinical ADHD and ASD.

Academic achievement of children with autistic symptoms compared to typically developing children

AbstractChildren with autistic symptoms experience challenges in school settings, yet little is known about their academic profiles and the mechanisms underlying the association between autistic symptoms and academic achievement. This study examined the association between autistic symptoms and academic achievement in a population-based sample of children with and without (sub)clinical autism spectrum disorder (ASD). We also investigated potential sex differences and assessed if the association is mediated by vocabulary skills and behavior problems. Information was available for 2038 participants (48.3% boys), and autistic symptoms were assessed using the Social Responsiveness Scale (M = 6.8 years). Diagnosis of ASD was clinically confirmed in 28 children. Academic achievement was determined by a nationwide, standardized test assessed at the end of primary school (M = 11.8 years). Children with more autistic symptoms in early childhood had lower achievement scores in language, mathematics, and world orientation by the end of primary education. There were no sex differences. Furthermore, vocabulary skills and behavior problems partly mediated the association between autistic symptoms and academic achievement. Then, by using propensity matching technique, we compared 140 matched typically developing peers with 28 children diagnosed with ASD. These results indicated no differences in academic achievement between children diagnosed with ASD and their matched typically developing peers. We conclude that autistic symptoms associate with lower academic achievement but by carefully matching on background variables and potential confounders, the academic achievement of children with clinical ASD might not differ from that of their typically developing peers.

Persistence of Autism Spectrum Disorder From Early Childhood Through School Age

While the prevalence of autism spectrum disorder (ASD) continues to increase and early diagnosis is emphasized, there is limited information on outcomes for children diagnosed with ASD in early childhood using contemporary diagnostic criteria. To determine the frequency with which children who are clinically diagnosed with ASD at 12 to 36 months of age continue to meet diagnostic criteria for ASD at 5 to 7 years of age and to evaluate whether baseline child-specific and demographic characteristics and receipt of interventions are associated with ASD persistence. In this natural history cohort study, children who received a clinical ASD diagnosis at 12 to 36 months of age underwent a research diagnostic assessment at 5 to 7 years of age. Research assessments occurred from August 14, 2018, to January 8, 2022. Children received community-based interventions, and parents provided details about interventions received. The main outcome was persistence of ASD diagnosis based on current functioning. An experienced research psychologist assigned an ASD diagnosis (present or absent) according to criteria from the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) after the research assessment. The research assessment included administration of the Autism Diagnostic Observation Schedule-2, Autism Diagnostic Interview-Research, and a cognitive measure. Of the 213 participants diagnosed with ASD at initial clinical assessment (mean [SD] age, 24.6 [3.9] months; 177 boys [83.1%]), 79 (37.1%) did not continue to meet diagnostic criteria for ASD (nonpersistent ASD) at research assessment (mean [SD] age, 74.3 [7.1] months). All children with nonpersistent ASD had IQ of at least 70, while there was a bimodal distribution of IQ for those with persistent ASD (46 with IQ <70 and 88 with IQ ≥70). All children received some interventions, and 201 (94.4%) received ASD-specific intervention, mostly applied behavioral analysis. In a multilevel logistic regression model, the only variables associated with increased odds of being in the nonpersistent ASD group at 6 years of age were higher baseline adaptive skills (b coefficient = -0.287 [SE, 0.108]) and female sex (b = 0.239 [SE, 0.064]). The findings of this cohort study suggest that among toddlers diagnosed with ASD, baseline adaptive function and sex may be associated with persistence of ASD.

LAMP1 as a novel molecular biomarker to predict the prognosis of the children with autism spectrum disorder using bioinformatics approaches

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that usually manifests in childhood and is thought to be caused by a complex interaction of genetic, environmental, and immune factors. The majority of current ASD diagnostic methods rely on subjective behavioral observation and scale assessment, making early detection difficult. In this study, we confirmed that lysosomal-associated membrane protein 1 (LAMP1), a functional marker of immune cell activation and cytotoxic degranulation, was upregulated in ASD blood, brain cortex, and various genetic animal models or cells using bioinformatics approaches. The prognostic value of LAMP1 was investigated by correlating its expression with clinical ASD rating scales, and the receiver operating characteristic (ROC) curve analysis in ASD also revealed that it has a favorable diagnostic ability in distinguishing ASD from control cohort. According to gene set enrichment analysis (GSEA) results, LAMP1 correlated with genes that were enriched in natural kill and T cell immune function. Taking all of the evidence into account, we discovered that abnormal elevations of LAMP1 mRNA and protein in the blood of ASD children, may influence the development of ASD through its involvement in immune cell activity regulation. This report highlights a novel marker for ASD early detection as well as potential therapeutic targets.

Exploring relationships between autistic traits and body temperature, circadian rhythms, and age

The number of clinical diagnoses of autism spectrum disorder (ASD) is increasing annually. Interestingly, the human body temperature has also been reported to gradually decrease over the decades. An imbalance in the activation of the excitatory and inhibitory neurons is assumed to be involved in the pathogenesis of ASD. Neurophysiological evidence showed that brain activity decreases as cortical temperature increases, suggesting that an increase in brain temperature enhances the inhibitory neural mechanisms. Behavioral characteristics specific to clinical ASD were observed to be moderated when people with the diagnoses had a fever. To explore the possible relationship between ASD and body temperature in the general population, we conducted a survey study using a large population-based sample (N ~ 2000, in the age groups 20s to 70s). Through two surveys, multiple regression analyses did not show significant relationships between axillary temperatures and autistic traits measured by questionnaires (Autism Spectrum (AQ) and Empathy/Systemizing Quotients), controlling for covariates of age and self-reported circadian rhythms. Conversely, we consistently observed a negative relationship between AQ and age. People with higher AQ scores tended to have stronger eveningness. Our findings contribute to the understanding of age-related malleability and the irregularity of circadian rhythms related to autistic traits.

Altered behavior, brain structure, and neurometabolites in a rat model of autism-specific maternal autoantibody exposure

Maternal immune dysregulation is a prenatal risk factor for autism spectrum disorder (ASD). Importantly, a clinically relevant connection exists between inflammation and metabolic stress that can result in aberrant cytokine signaling and autoimmunity. In this study we examined the potential for maternal autoantibodies (aAbs) to disrupt metabolic signaling and induce neuroanatomical changes in the brains of exposed offspring. To accomplish this, we developed a model of maternal aAb exposure in rats based on the clinical phenomenon of maternal autoantibody-related ASD (MAR-ASD). Following confirmation of aAb production in rat dams and antigen-specific immunoglobulin G (IgG) transfer to offspring, we assessed offspring behavior and brain structure longitudinally. MAR-ASD rat offspring displayed a reduction in pup ultrasonic vocalizations and a pronounced deficit in social play behavior when allowed to freely interact with a novel partner. Additionally, longitudinal in vivo structural magnetic resonance imaging (sMRI) at postnatal day 30 (PND30) and PND70, conducted in a separate cohort of animals, revealed sex-specific differences in total and regional brain volume. Treatment-specific effects by region appeared to converge on midbrain and cerebellar structures in MAR-ASD offspring. Simultaneously, in vivo 1H magnetic resonance spectroscopy (1H-MRS) data were collected to examine brain metabolite levels in the medial prefrontal cortex. Results showed that MAR-ASD offspring displayed decreased levels of choline-containing compounds and glutathione, accompanied by increased taurine compared to control animals. Overall, we found that rats exposed to MAR-ASD aAbs present with alterations in behavior, brain structure, and neurometabolites; reminiscent of findings observed in clinical ASD.

For ASD, Psychiatrists Must Continuously Monitor Patients, Assess Therapies

For ASD, Psychiatrists Must Continuously Monitor Patients, Assess Therapies

A multimodal discrimination method for the response to name behavior of autistic children based on human pose tracking and head pose estimation

The incidence rate of autism spectrum disorder (ASD) has been rising in the past decades, and has reached 1 ∼ 2%. Clinical ASD screening requires long testing time, complicated doctor training and high cost. Therefore, an objective and accurate automated method is urgently needed for large-scale early screening of autistic children. The lack of response to one’s own name is one of the early warning signals of ASD. Response to name is included in various ASD early screening and diagnostic assessments. In this paper, we propose an algorithm that combines automatic name detection with human pose tracking and head pose estimation in computer vision. The final prediction is determined by the combination of shoulder rotation angle, head pose information and duration. The experimental data comes from the process of clinical screening for ASD, which has less laboratory control, more realistic child response, and a flexible number of accompanying parents. Thirty subjects including 29 children with ASD and 1 typical developing (TD) child participated in the experiment. The experimental results show that the consistency between our proposed method and clinical diagnosis achieves 93.3%, which indicates our method can play an effective auxiliary role in the early screening of ASD.

Autism spectrum disorder symptom expression in individuals with 3q29 deletion syndrome

BackgroundThe 1.6 Mb 3q29 deletion is associated with neurodevelopmental and neuropsychiatric phenotypes, including a 19-fold increased risk for autism spectrum disorder (ASD). Previous work by our team identified elevated social disability in this population via parent-report questionnaires. However, clinical features of ASD in this population have not been explored in detail.MethodsThirty-one individuals with 3q29 deletion syndrome (3q29del, 61.3% male) were evaluated using two gold-standard clinical ASD evaluations: the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and the Autism Diagnostic Interview, Revised (ADI-R). Four matched comparators for each subject were ascertained from the National Database for Autism Research. Item-level scores on the ADOS-2 and ADI-R were compared between subjects with 3q29del and matched comparators.ResultsSubjects with 3q29del and no ASD (3q29del-ASD) had greater evidence of social disability compared to typically developing (TD) comparison subjects across the ADOS-2. Subjects with 3q29del and ASD (3q29del + ASD) were largely indistinguishable from non-syndromic ASD (nsASD) subjects on the ADOS-2. 3q29del + ASD performed significantly better on social communication on the ADI-R than nsASD (3q29 + ASD mean = 11.36; nsASD mean = 15.70; p = 0.01), and this was driven by reduced deficits in nonverbal communication (3q29 + ASD mean = 1.73; nsASD mean = 3.63; p = 0.03). 3q29del + ASD reported significantly later age at the first two-word phrase compared to nsASD (3q29del + ASD mean = 43.89 months; nsASD mean = 37.86 months; p = 0.01). However, speech delay was not related to improved nonverbal communication in 3q29del + ASD.LimitationsThere were not enough TD comparators with ADI-R data in NDAR to include in the present analysis. Additionally, our relatively small sample size made it difficult to assess race and ethnicity effects.Conclusions3q29del is associated with significant social disability, irrespective of ASD diagnosis. 3q29del + ASD have similar levels of social disability to nsASD, while 3q29del-ASD have significantly increased social disability compared to TD individuals. However, social communication is reasonably well preserved in 3q29del + ASD relative to nsASD. It is critical that verbal ability and social disability be examined separately in this population to ensure equal access to ASD and social skills evaluations and services.

Higher scores on autonomic symptom scales in pediatric patients with neurodevelopmental disorders of known genetic etiology.

Features of underlying autonomic dysfunction, including sleep disturbances, gastrointestinal problems, and atypical heart rate, have been reported in neurodevelopmental conditions, including autism spectrum disorder (ASD). The current cross-sectional, between-groups study aimed to quantify symptoms of autonomic dysfunction in a neurodevelopmental pediatric cohort characterized by clinical diagnoses as well as genetic etiology. The Pediatric Autonomic Symptom Scales (PASS) questionnaire was used to assess autonomic features across a group of patients with clinical neurodevelopmental diagnoses (NPD; N=90) and genetic etiologies. Patients were subdivided based on either having a clinical ASD diagnosis (NPD-ASD; n=37) or other non-ASD neurodevelopmental diagnoses, such as intellectual disability without ASD, speech and language disorders, and/or attention deficit hyperactivity disorder (NPD-OTHER; n=53). Analyses focused on characterizing differences between the NPD group compared to previously published reference samples, as well as differences between the two NPD subgroups (NPD-ASD and NPD-OTHER). Our results indicate higher PASS scores in our NPD cohort relative to children with and without ASD from a previously published cohort. However, we did not identify significant group differences between our NPD-ASD and NPD-OTHER subgroups. Furthermore, we find a significant relationship between quantitative ASD traits and symptoms of autonomic function. This work demonstrates the utility of capturing quantitative estimates of autonomic trait dimensions that may be significantly linked with psychosocial impairments and other core clinical features of ASD.

Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection

BackgroundTransgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants.Objectives(1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line.MethodsFamily pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing.ResultsTwenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value < 0.05. The paternal grandparents carry the greatest RR (2.86–2.96) during birth and childhood in the 1950’s–1960, which represent the smallest size clusters, and occur in urban areas. Additionally, seven statistically significant clusters with RR < 1 were relatively large in area, covering more rural areas of the state.ConclusionThis study has identified statistically significant space-time clusters during critical developmental windows that are associated with ASD risk in descendants. The geographic space and time clusters family pedigrees with over 3 + generations, which we refer to as a person’s geographic legacy, is a powerful tool for studying transgenerational effects that may be epigenetic in nature. Our novel use of space-time clustering can be applied to any disease where family pedigree data is available.

Hvor nøyaktig identifiserer screeninginstrumentet Social Communication Questionnaire autismespekterforstyrrelser i BUP?

Background: The accuracy of the Norwegian Social Communication Questionnaire (SCQ) in identifying autism spectrum disorder (ASD) within child psychiatry is not known. Method: We investigated the accuracy of SCQ in identifying clinically diagnosed ASD and ASD classified by the Developmental, Dimensional and Diagnostic Interview (3Di) and the Autism Diagnostic Observation Schedule (ADOS-2). Results: The SCQ cut-off of 15 showed low sensitivity (Se) for correct classification of clinically diagnosed ASD (Se = 38%) and ADOS-2 classified ASD (Se = 30%) with 78% and 76% specificity (SP), respectively. For 3Di classified ASD, Se was somewhat higher (49%) and had good specificity (86%), with the best positive predictive value (.73). Conclusions/Implications: The SCQ showed low accuracy in identifying a clinical ASD diagnosis in child psychiatry. However, children with SCQ scores at or above threshold had a high risk of also being categorised with ASD according to the 3Di. We recommend that future studies include more detailed information about the basis for the final diagnostic conclusions. Furthermore, SCQ's characteristics should be evaluated in samples of children within a broad range of ASD that includes individuals with delayed development. Investigation of the suitability of other screening instruments for ASD for diagnostic work in child psychiatric clinics is also needed. Keywords: Autism Diagnostic Observation Schedule (ADOS-2), Developmental, Dimensional and Diagnostic Interview (3Di), sensitivity; specificity, Social Communication Questionnaire (SCQ)

Prenatal Exposure to Air Pollution and Autism Spectrum Disorder: Sensitive Windows of Exposure and Sex Differences.

Background:Studies have shown that air pollution exposures during pregnancy are associated with an increased risk of autism spectrum disorder (ASD) in children, and the risk appears to be greater for boys. However, studies assessing gestational windows of susceptibility have been mostly limited by trimesters.Objective:We identified sensitive windows of exposure to regional air pollution and risk of ASD and examined sex differences in a large birth cohort.Methods:This population-based retrospective cohort study included 294,937 mother–child pairs with singleton deliveries in Kaiser Permanente Southern California (KPSC) hospitals from 2001 to 2014. Children were followed using electronic medical records until clinical ASD diagnosis, non-KPSC membership, death, or 31 December 2019, whichever came first. Weekly mean fine particulate matter [PM with an aerodynamic diameter of ()], nitrogen dioxide (), and ozone () pregnancy exposures were estimated using spatiotemporal prediction models. Cox proportional hazard models with distributed lags were used to estimate weekly pollutant exposure associations with ASD risk for the entire cohort, and separately for boys and for girls. Models were adjusted for child sex (for full cohort), maternal race/ethnicity, maternal age at delivery, parity, maternal education, maternal comorbidities, medical center, census tract median household income, birth year, and season.Results:There were 5,694 ASD diagnoses (4,636 boys, 1,058 girls). Sensitive exposure windows associated with ASD were found early in pregnancy, statistically significant throughout the first two trimesters [1–27 wk of gestation, cumulative [95% confidence interval (CI): 1.06, 1.23] per interquartile range (IQR) () increase]. exposure during 34–37 wk of gestation was associated with increased risk [ (95% CI: 1.01, 1.11) per IQR () increase] but with reduced risk during 20–28 wk of gestation [ (95% CI: 0.89, 0.98)]. No associations were observed with . Sex-stratified early gestational associations were stronger among boys [boys (95% CI: 1.08, 1.26); girls (95% CI: 0.89, 1.26)]. associations in later gestation were observed only in boys [boys (95% CI: 1.04, 1.16); girls (95% CI: 0.84, 1.05)].Conclusions:Exposures to in the first two gestational trimesters were associated with increased ASD risk in children, with stronger associations observed for boys. The role of exposure on ASD risk merits further investigation. https://doi.org/10.1289/EHP9509

Longitudinal Changes in Cortical Thickness in Adolescents with Autism Spectrum Disorder and Their Association with Restricted and Repetitive Behaviors.

The neuroanatomy of autism spectrum disorder (ASD) shows highly heterogeneous developmental trajectories across individuals. Mapping atypical brain development onto clinical phenotypes, and establishing their molecular underpinnings, is therefore crucial for patient stratification and subtyping. In this longitudinal study we examined intra- and inter-individual differences in the developmental trajectory of cortical thickness (CT) in childhood and adolescence, and their genomic underpinnings, in 33 individuals with ASD and 37 typically developing controls (aged 11–18 years). Moreover, we aimed to link regional atypical CT development to intra-individual variations in restricted and repetitive behavior (RRB) over a two-year time period. Individuals with ASD showed significantly reduced cortical thinning in several of the brain regions functionally related to wider autism symptoms and traits (e.g., fronto-temporal and cingulate cortices). The spatial patterns of the neuroanatomical differences in CT were enriched for genes known to be associated with ASD at a genetic and transcriptomic level. Further, intra-individual differences in CT correlated with within-subject variability in the severity of RRBs. Our findings represent an important step towards characterizing the neuroanatomical underpinnings of ASD across development based upon measures of CT. Moreover, our findings provide important novel insights into the link between microscopic and macroscopic pathology in ASD, as well as their relationship with different clinical ASD phenotypes.

CLEAR Autism Diagnostic Evaluation (CADE): Evaluation of Reliability and Validity.

Recent surveillance efforts indicate that 1 in 54 American children meet the criteria for Autism Spectrum Disorder (ASD), making it the fastest growing neurodevelopmental disorder in the U.S. Despite evidence that ASD can be reliably diagnosed as early as 24 months, the median age at ASD diagnosis in 2016 in the U.S. was 51 months. The CLEAR Autism Diagnostic Evaluation (CADE; Willard & Kroncke, 2019), was developed in response to the need to improve, shorten, and standardize the clinical ASD evaluation process. The CADE is a 33-item rating scale designed to be completed by caregivers and clinicians. The current study was conducted to examine the reliability and validity of the CADE using a sample of 191 individuals who received a private evaluation for ASD. Using the client’s evaluation records, clinicians completed the CADE items. The coefficient alpha was .94, which indicates that the items form a scale that has high internal consistency. The CADE total scores were highly correlated with ADOS scores, with r values ranging from .52—.86, and discriminated between those participants with a diagnosis of ASD and those without (p < .001). Receiver operator characteristic (ROC) curve analyses indicated excellent diagnostic accuracy of the CADE total score (ROC area under the curve = .998). Results suggest that the CADE can be used as an efficient and accurate means of evaluating ASD. Limitations and implications for use of the CADE are discussed.