High Risk For Autism Spectrum Disorder Research Articles

Comparison between the Clancy Behavior Scale and the Modified Checklist for Autism in Toddlers in Taiwan.

(1) Background: Precise diagnosis and early intervention are crucial for toddlers with autism spectrum disorder (ASD) to achieve a better prognosis. This study investigated the efficacy of the Clancy Behavior Scale (CBS) and Modified Checklist for Autism in Toddlers (M-CHAT) in detecting ASD among toddlers under 30 months of age. (2) Methods: A total of 215 toddlers (117 with ASD and 98 with development delays) aged between 18 and 29 months participated in this study. All the primary caregivers of these toddlers were recruited to complete the CBS and M-CHAT. (3) Results: The findings indicated that the accuracy of the CBS and M-CHAT was promising, and the short forms of these two instruments performed better than their full versions. The CBS:9 critical items presented a sensitivity of 0.75 and a specificity of 0.74, while the M-CHAT:14 brief items showed a sensitivity of 0.72 and a specificity of 0.85. (4) Conclusions: The diagnostic accuracy of high-risk ASD toddlers improved via the combination of CBS and M-CHAT, particularly when the information gathered from these two instruments were consistent. The findings may provide implications for enhancing the early detection of ASD.

Prenatal, perinatal and parental risk factors for autism spectrum disorder in China: a case- control study.

Autism spectrum disorder (ASD) is heritable neurodevelopmental disorders (NDDs), but environmental risk factors have also been suggested to a play a role in its development. Prenatal, perinatal and parental factors have been associated with an increased risk of ASD in children. The aim of the present study was to explore the prenatal, perinatal, and parenting risk factors in children with autism spectrum disorder (ASD) from Beijing, China by comparing them with typically developing (TD) children. A sample of 151 ASD children's parents who from rehabilitation institutions in Beijing were enrolled in this study, and an additional 151 children from kindergartens in Beijing were recruited as a control group (child age: mean = 4.4 years). TD children were matched according to age, sex and maternal education. We explored the maternal AQ (Autism Spectrum Quotient) scores (mean:19.40-19.71, no significant difference between two groups) to referring the genetic baseline. This study evaluated 17 factors with unadjusted and adjusted analyses. Birth asphyxia was associated with a more than a thirteen-fold higher risk of ASD (adjusted odds ratio (AOR) = 13.42). Breastfeeding difficulties were associated with a higher risk of ASD(AOR = 3.46). Parenting influenced the risk of ASD, with low responding (LR) and harsh or neglectful parenting associated with a higher risk of ASD in offspring (AOR = 2.37 for LR, AOR = 3.42 for harsh parenting and AOR = 3.01 for neglectful parenting). Maternal fever during pregnancy was associated with a higher risk of ASD in offspring (AOR = 3.81). Many factors were associated with ASD in offspring. Further assessment is needed to elucidate the role of modifiable environmental factors to inform prevention strategies.

The correlation between brain structure characteristics and emotion regulation ability in children at high risk of autism spectrum disorder.

As indicated by longitudinal observation, autism has difficulty controlling emotions to a certain extent in early childhood, and most children's emotional and behavioral problems are further aggravated with the growth of age. This study aimed at exploring the correlation between white matter and white matter fiber bundle connectivity characteristics and their emotional regulation ability in children with autism using machine learning methods, which can lay an empirical basis for early clinical intervention of autism. Fifty-five high risk of autism spectrum disorder (HR-ASD) children and 52 typical development (TD) children were selected to complete the skull 3D-T1 structure and diffusion tensor imaging (DTI). The emotional regulation ability of the two groups was compared using the still-face paradigm (SFP). The classification and regression models of white matter characteristics and white matter fiber bundle connections of emotion regulation ability in the HR-ASD group were built based on the machine learning method. The volume of the right amygdala (R2 = 0.245) and the volume of the right hippocampus (R2 = 0.197) affected constructive emotion regulation strategies. FA (R2 = 0.32) and MD (R2 = 0.34) had the predictive effect on self-stimulating behaviour. White matter fiber bundle connection predicted constructive regulation strategies (positive edging R2 = 0.333, negative edging R2 = 0.334) and mother-seeking behaviors (positive edging R2 = 0.667, negative edging R2 = 0.363). The emotional regulation ability of HR-ASD children is significantly correlated with the connections of multiple white matter fiber bundles, which is a potential neuro-biomarker of emotional regulation ability.

Targeted sequencing identifies risk variants in 202 candidate genes for neurodevelopmental disorders

With the continuous deepening of genetic research on neurodevelopmental disorders (NDDs), more patients have been identified the causal or candidate genes. However, it is still urgent needed to increase the sample size to confirm the associations between variants and clinical manifestations. We previously performed molecular inversion probe sequencing of autism spectrum disorder (ASD) candidate genes in 1543 ASD patients. In this study, we used the same method to detect de novo variants (DNVs) in 665 NDD patients with intellectual disability (ID) and/or epilepsy (EP) for genetic analysis and diagnosis. We compared findings from ID/EP and ASD patients to improve our understanding of different subgroups of NDDs. We identified 72 novel variants and 39 DNVs. A totally of 5.71 % (38/665) of the patients were genetically diagnosed by this sequencing strategy. ID/EP patients demonstrated a higher prevalence of likely gene disruptive DNVs in ASD genes than the healthy population. Regarding high-risk genes, SCN1A and CKDL5 were more frequently mutated in ID/EP patients than in ASD patients. Our data provide an overview of the mutation burden in ID/EP patients from the perspective of high risk ASD genes, indicating the differences and association of NDDs subgroups.

A sensory signature of unaffected biological parents predicts the risk of autism in their offspring.

Despite the emphasis on sensory dysfunction phenotypes in the revised diagnostic criteria for autism spectrum disorder (ASD), there has been limited research, particularly in the field of neurobiology, investigating the concordance in sensory features between individuals with ASD and their genetic relatives. Therefore, our objective was to examine whether neurobehavioral sensory patterns could serve as endophenotypic markers for ASD. We combined questionnaire- and lab-based sensory evaluations with sensory fMRI measures to examine the patterns of sensory responsivity in 30 clinically diagnosed with ASD, 26 matched controls (CON), and 48 biological parents for both groups (27 parents of individuals with ASD [P-ASD] and 21 for individuals with CON [P-CON]). The ASD and P-ASD groups had higher sensory responsivity and rated sensory stimuli as more unpleasant than the CON and P-CON groups, respectively. They also exhibited greater hemodynamic responses within the sensory cortices. Overlapping activations were observed within these sensory cortices in the ASD and P-ASD groups. Using a machine learning approach with robust prediction models across cohorts, we demonstrated that the sensory profile of biological parents accurately predicted the likelihood of their offspring having ASD, achieving a prediction accuracy of 71.4%. These findings provide support for the hereditary basis of sensory alterations in ASD and suggest a potential avenue to improve ASD diagnosis by utilizing the sensory signature of biological parents, especially in families with a high risk of ASD. This approach holds promising prospects for early detection, even before the birth of the offspring.

Evaluation of Autism Spectrum Disorder Risk in Infants With Intraventricular Hemorrhage.

Background This study evaluates the long-term risk of autism spectrum disorder (ASD) in infants with intraventricular hemorrhage (IVH) using the Modified Checklist for Autism in Toddlers-Revised with Follow-Up (M-CHAT-R/F) screening tool. Methods This retrospective cohort study compared IVH (exposed) infants across all gestational age groupswith no-IVH(non-exposed)infants admitted to level IV neonatal intensive care unit (NICU). The M-CHAT-R/F screening tool was used to assess the ASD risk at 16-30 months of age. Discharge cranial ultrasound (CUS) findings also determined the ASD risk. Descriptive statistics comprised median and interquartile range for skewed continuous dataand frequencies and percentages for categorical variables. Comparisons for non-ordinal categorical measures in bivariate analysis were carried out using the χ2test or Fisher exact test. Results Of the 334 infants,167had IVH, and 167 had no IVH. High ASD risk (43% vs. 20%, p = 0.044) and cerebral palsy (19% vs. 5%, p = 0.004) were significantly associated with severe IVH. Infants with CUS findings of periventricular leukomalacia had 3.24 odds of developing high ASD risk (odds ratios/OR: 3.24, 95% confidence interval/CI: 0.73-14.34), and those with hydrocephalus needing ventriculoperitoneal (VP) shunt had 4.75 odds of developing high ASD risk (OR: 4.75, 95% CI: 0.73-30.69). Conclusion Severe IVH, but not mild IVH,increased the risk of ASD and cerebral palsy. This study demonstrates the need for timely screening for ASD in high-risk infants. Prompt detection leads to earlier treatment and better outcomes.

Risk of autism spectrum disorder and association of its symptoms with psychiatric and substance use disorders in non-clinical student sample in Kenya: cross-sectional study.

The prevalence and patterns of autism spectrum disorder (ASD) symptoms/traits and the associations of ASD with psychiatric and substance use disorders has not been documented in non-clinical students in Sub-Saharan Africa, and Kenya in particular. To document the risk level of ASD and its traits in a Kenyan student population (high school, college and university) using the Autism-Spectrum Quotient (AQ); and to determine the associations between ASD and other psychiatric and substance use disorders. This was a cross-sectional study among students (n = 9626). We used instruments with sufficient psychometric properties and good discriminative validity to collect data. A cut-off score of ≥32 on the AQ was used to identify those at high risk of ASD. We conducted the following statistical tests: (a) basic descriptive statistics; (b) chi-squared tests and Fisher's exact tests to analyse associations between categorical variables and ASD; (c) independent t-tests to examine two-group comparisons with ASD; (d) one-way analysis of variance to make comparisons between categorical variables with three or more groups and ASD; (e) statistically significant (P < 0.05) variables fitted into an ordinal logistic regression model to identify determinants of ASD; (f) Pearson's correlation and reliability analysis. Of the total sample, 54 (0.56%) were at high risk of ASD. Sociodemographic differences were found in the mean scores for the various traits, and statistically significant (P < 0.05) associations we found between ASD and various psychiatric and substance use disorders. Risk of ASD, gender characteristics and associations with psychiatric and substance use disorders are similar in this Kenyan sample to those found in Western settings in non-clinical populations.

From neurodevelopmental to neurodegenerative disorders: Investigating symptoms of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in patients with dementia

Dementia is characterized by a progressive cognitive decline that could be caused by several disorders. Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are two prevalent neurodevelopmental disorders that might overlap with dementia symptoms. Hence, this study aimed to evaluate the ASD and ADHD symptoms in dementia patients referred to a memory clinic in Iran. We recruited 65 dementia patients and instructed them to fill out the autism quotient (AQ) and the Conners’ Adult ADHD Rating Scales (CAARS) questionnaires. Considering the cutoff points of AQ and CAARS questionnaires, 18.5% of participants were at higher risk of ASD, and 35.4% were at higher risk of ADHD. The results indicated that ADHD and ASD symptoms might be common comorbidities in patients with dementia which can increase the disease burden. Specialized ADHD and ASD screening tools in the elderly population with dementia are needed to prevent misdiagnoses due to symptom overlaps.

National screening for Egyptian children aged 1 year up to 12 years at high risk of Autism and its determinants: a step for determining what ASD surveillance needs

This study aimed to provide a national estimate of the prevalence of the high risk of autism spectrum disorder (ASD) and their determinants. A national screening survey was conducted for 41,640 Egyptian children aged 1 to 12 years in two phases. Tools used were Vineland's Adaptive Behavior Scales, Modified Checklist for Autism in Toddlers, Gilliam Autism Rating scale, and Denver II Developmental screening test. The overall prevalence of children at high risk of ASD was 3.3% (95% CI:3.1%–3.5%). Children living without mothers in homes, suffered from convulsions (AOR = 3.67; 95%CI:2.8–4.8), a history of cyanosis after birth (AOR = 1.87; 95% CI:1.35–2.59) or history of LBW babies (AOR = 1.53; 95% CI:1.23–1.89) carried higher odds of being at high risk of ASD.

Sleep quality and temperament in association with autism spectrum disorder among infants in Japan

BackgroundSleep problems and irritable temperaments are common among infants with autism spectrum disorder (ASD). The prospective association between such sleep problems and irritable temperaments and ASDs needs to be determined for elucidating the mechanism and exploring the future intervention study. Thus, in this study, we investigated whether sleep quality and temperament in 1-month-old infants are associated with the onset of ASD in 3-year-old children. We also assessed its sex-stratified associations.MethodsWe conducted a longitudinal study using data from 69,751 mothers and infants from a large-cohort study, the Japan Environment and Children’s Study. We examined the prospective association between infant sleep quality and temperament at 1 month of age and ASD diagnosis by 3 years of age.ResultsHere we show infants with longer daytime sleep have a higher risk of later ASD than those with shorter daytime sleep (risk ratio [RR]: 1.33, 95% confidence interval [CI]: 1.01–1.75). Infants who experienced intense crying have a higher risk of ASD than those who did not (RR: 1.31, 95% CI: 1.00–1.72). There is a difference in sex in the association between a bad mood and later ASD. In particular, female infants experiencing bad moods have a higher risk of ASD than others (RR: 3.59, 95% CI: 1.91–6.75).ConclusionsThe study findings provide important information for future intervention to reduce the risk of future ASD.

Neurodevelopmental outcome in children with congenital cytomegalovirus infection: A prospective multicenter cohort study

BackgroundCongenital cytomegalovirus infection (cCMV) is the most common congenital infection worldwide and is a major cause of neurodevelopmental impairment in children. At this point there are insufficient data on neurodevelopmental outcome of children with cCMV, both symptomatic and asymptomatic. AimThis study aimed to describe the neurodevelopmental outcome in a large prospective cohort of children with cCMV. MethodsAll children with cCMV, included in the Flemish cCMV register, were eligible for this study. Data on neurodevelopmental outcome was available in 753 children. Data on neuromotor, cognitive, behavioral, audiological and ophthalmological outcome were analyzed. ResultsNeurodevelopmental outcome was normal in 530/753 (70,4 %) at any age of last follow-up. Mild, moderate and severe neurodevelopmental impairment was found in 128/753 (16,9 %), 56/753 (7,4 %) and 39/753 (5,2 %), respectively. Adverse outcome is found both in the symptomatic and asymptomatic children (53,5 % versus 17,8 %). Autism spectrum disorder (ASD) was diagnosed more often than in the general population in Flanders (2,5 % versus 0,7 %). Speech and language impairment was found in 2 %, even in absence of hearing loss. ConclusionBoth symptomatic and asymptomatic cCMV children are at risk of sequelae, with higher risk in case of first trimester infection. During follow-up of this population, special attention should be given to the audiological follow-up, the presence of hypotonia at young age, the possible higher risk of ASD and the risk of speech and language impairment even in absence of hearing loss. Our results emphasize the need for multidisciplinary neurodevelopmental follow-up of all cCMV infected children.

Diffusion tensor imaging analysis of the corpus callosum in children with high-risk autism spectrum disorder.

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that begins in early infancy and childhood and is characterized by impaired social communication and repetitive stereotyped behaviors. The purpose of this study was to examine the development of the corpus callosum and its relationship to neurobehavior in young children with high-risk (HR) ASD using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Twenty-one children with HR-ASD who visited Anhui Children's Hospital between January 2020 and December 2021 were selected as the study group, while 19 matched children with normal development during the same time were adopted as the control group. Cranial MRI+DTI were performed for all of the enrolled children and fractional anisotropy (FA) measurements were taken in each region of the corpus callosum. The FA values in all regions of the corpus callosum were higher in the study group than in the control group (0.417 ± 0.016 vs. 0.412 ± 0.02 in the corpus callosum knee, 0.439 ± 0.018 vs. 0.431 ± 0.023 in the corpus callosum body, and 0.446 ± 0.017 vs. 0.434 ± 0.019 in the splenium of corpus callosum [SCC]), where the difference in the FA in the SCC was statistically significant between the two groups (P< 0.05). There was a positive correlation between the FA in the corpus callosum knee and speech scores in the neuropsychological development of the study group (P< 0.05). There was a premature development tendency for corpus callosum myelination in young children with HR-ASD, and the developmental tendency was visible in the SCC. There was also a positive relationship between corpus callosum knee development and language function.

Networks of placental DNA methylation correlate with maternal serum PCB concentrations and child neurodevelopment

BackgroundGestational exposure to polychlorinated biphenyls (PCBs) has been associated with elevated risk for neurodevelopmental disorders. Placental epigenetics may serve as a potential mechanism of risk or marker of altered placental function. Prior studies have associated differential placental DNA methylation with maternal PCB exposure or with increased risk of autism spectrum disorder (ASD). However, sequencing-based placental methylomes have not previously been tested for simultaneous associations with maternal PCB levels and child neurodevelopmental outcomes. ObjectivesWe aimed to identify placental DNA methylation patterns associated with maternal PCB levels and child neurodevelopmental outcomes in the high-risk ASD MARBLES cohort. MethodsWe measured 209 PCB congeners in 104 maternal serum samples collected at delivery. We identified networks of DNA methylation from 147 placenta samples using the Comethyl R package, which performs weighted gene correlation network analysis for whole genome bisulfite sequencing data. We tested placental DNA methylation modules for association with maternal serum PCB levels, child neurodevelopment, and other participant traits. ResultsPCBs 153 + 168, 170, 180 + 193, and 187 were detected in over 50% of maternal serum samples and were highly correlated with one another. Consistent with previous findings, maternal age was the strongest predictor of serum PCB levels, alongside year of sample collection, pre-pregnancy BMI, and polyunsaturated fatty acid levels. Twenty seven modules of placental DNA methylation were identified, including five which significantly correlated with one or more PCBs, and four which correlated with child neurodevelopment. Two modules associated with maternal PCB levels as well as child neurodevelopment, and mapped to CSMD1 and AUTS2, genes previously implicated in ASD and identified as differentially methylated regions in mouse brain and placenta following gestational PCB exposure. ConclusionsPlacental DNA co-methylation modules were associated with maternal PCBs and child neurodevelopment. Methylation of CSMD1 and AUTS2 could be markers of altered placental function and/or ASD risk following maternal PCB exposure.

IcoConv : Explainable brain cortical surface analysis for ASD classification.

In this study, we introduce a novel approach for the analysis and interpretation of 3D shapes, particularly applied in the context of neuroscientific research. Our method captures 2D perspectives from various vantage points of a 3D object. These perspectives are subsequently analyzed using 2D Convolutional Neural Networks (CNNs), uniquely modified with custom pooling mechanisms. We sought to assess the efficacy of our approach through a binary classification task involving subjects at high risk for Autism Spectrum Disorder (ASD). The task entailed differentiating between high-risk positive and high-risk negative ASD cases. To do this, we employed brain attributes like cortical thickness, surface area, and extra-axial cerebral spinal measurements. We then mapped these measurements onto the surface of a sphere and subsequently analyzed them via our bespoke method. One distinguishing feature of our method is the pooling of data from diverse views using our icosahedron convolution operator. This operator facilitates the efficient sharing of information between neighboring views. A significant contribution of our method is the generation of gradient-based explainability maps, which can be visualized on the brain surface. The insights derived from these explainability images align with prior research findings, particularly those detailing the brain regions typically impacted by ASD. Our innovative approach thereby substantiates the known understanding of this disorder while potentially unveiling novel areas of study.

Prediction of autistic tendencies at 18 months of age via markerless video analysis of spontaneous body movements in 4-month-old infants

Early intervention is now considered the core treatment strategy for autism spectrum disorders (ASD). Thus, it is of significant clinical importance to establish a screening tool for the early detection of ASD in infants. To achieve this goal, in a longitudinal design, we analyzed spontaneous bodily movements of 4-month-old infants from general population and assessed their ASD-like behaviors at 18 months of age. A total of 26 movement features were calculated from video-recorded bodily movements of infants at 4 months of age. Their risk of ASD was assessed at 18 months of age with the Modified Checklist for Autism in Toddlerhood, a widely used screening questionnaire. Infants at high risk for ASD at 18 months of age exhibited less rhythmic and weaker bodily movement patterns at 4 months of age than low-risk infants. When the observed bodily movement patterns were submitted to a machine learning-based analysis, linear and non-linear classifiers successfully predicted ASD-like behavior at 18 months of age based on the bodily movement patterns at 4 months of age, at the level acceptable for practical use. This study analyzed the relationship between spontaneous bodily movements at 4 months of age and the ASD risk at 18 months of age. Experimental results suggested the utility of the proposed method for the early screening of infants at risk for ASD. We revealed that the signs of ASD risk could be detected as early as 4 months after birth, by focusing on the infant’s spontaneous bodily movements.

46 Patterns of referrals for evaluation of Autism Spectrum Disorder in the pediatric population of Saskatchewan as a predictor of diagnostic outcome

Abstract Background The Alvin Buckwold Child Development Program (ABCDP) serves Northern and Central Saskatchewan as a tertiary diagnostic centre for Autism Spectrum Disorder (ASD) but data is lacking on referrals and diagnostic outcome. Objectives This study aimed to assess if referral patterns are associated with diagnostic outcome of ASD. Design/Methods We conducted a retrospective cross-sectional study of patients from the ABCDP who were referred and assessed for ASD, or who received a diagnosis of ASD, from January 1st, 2016 to December 31st, 2018. Predictor variables were the referring clinician type and referral content. Suspicion for ASD from referrals were reported as being concerning for one, both or none of the DSM-5 core criteria for ASD (social communication and interaction “criteria A”; restricted and repetitive behaviors “criteria B”). When available, speech-language pathologist (SLP) reports were reviewed to identify concerns of social communication. The main outcome was a diagnosis or not of ASD. Risk ratio (RR) and odds ratio (OR) were estimated by simple logistic regression models to assess the association between individual variables of referral patterns and diagnosis of ASD. Results The final dataset included 527 patients after excluding 128 patients (123 were not seen at our center and 5 had a virtual assessment of ASD). A total of 365 patients received a diagnosis of ASD, 140 did not receive a diagnosis, 21 had their diagnosis deferred and one had this information missing. Referrals by physiotherapist (PT) were 46% more likely than other sources of referrals to lead to a diagnosis of ASD (RR=1,46; 95% CI 1,37-1,54; p=0,022). Referrals by SLP were 25% more likely than other sources of referrals to lead to a diagnosis of ASD (RR=1,25; 95% CI 1,12-1,39; p&amp;lt;0,0001). Referrals identifying concerns of social communication in SLP reports were 29% more likely than other sources of referrals to lead to a diagnosis of ASD (RR=1,29; 95% CI 1,16-1,43; p&amp;lt;0,0001). Using no criteria as reference group, referrals with concerns of criteria A were about 2.7 times more likely to lead to a diagnosis of ASD (OR=2,69; 95% CI 1,427-5,054; p=0,002). Conclusion In our study population, we found that certain referring clinician type (SLP, PT) and content of referrals (concerns for social communication in SLP reports, main concerns related to criteria A) are more likely to lead to a diagnosis of ASD. These findings could be used to identify referrals with a higher risk of ASD and allocate resources accordingly.

Association between history of miscarriage and autism spectrum disorder.

This case-control study was designed to examine the association between different types of miscarriage history and autism spectrum disorder (ASD), and determine whether the number of miscarriage history affects the risk of ASD. All of 2274 children with ASD and 1086 healthy controls were recruited. Sociodemographic and prenatal, perinatal, and neonatal characteristics were compared between the two groups. Multivariable logistic regression analyses were applied to investigate association between miscarriage history and ASD. Stratified analyses based on sex and types of miscarriages were similarly performed. History of miscarriage was potential risk factors for ASD ([aOR] = 2.919; 95% [CI] = 2.327-3.517). Stratified analyses revealed that induced ([aOR] = 2.763, 95% [CI] = 2.259-3.379) and spontaneous miscarriage history ([aOR] = 3.341, 95% [CI] = 1.939-4.820) were associated with high risk of ASD, respectively. A sex-biased ratio in the risk of ASD was observed between females ([aOR] = 3.049, 95% [CI] = 2.153-4.137) and males ([aOR] = 2.538, 95% [CI] = 1.978-3.251). Stratified analysis of induced miscarriage history revealed that only iatrogenic miscarriage history was associated with an increased risk ASD ([aOR] = 2.843, 95% [CI] = 1.534-4.268). Also, multiple spontaneous miscarriage histories ([aOR] = 1.836, 95% [CI] = 1.252-2.693) were associated with higher autism risk than one spontaneous miscarriages history ([aOR] = 3.016, 95% [CI] = 1.894-4.174). In conclusion, miscarriage history is related to an increased risk for ASD in offspring, which is affected by the types of miscarriage and sex of the fetus.

Neighborhood Socioeconomic Context and Autism Spectrum Disorder

Background and Aim: Neighborhood deprivation and autism spectrum disorder (ASD) risk associations are inconsistent across countries with different health systems. We examined associations between neighborhood SES during pregnancy and ASD in a U.S. mother-child cohort with good health care access. Methods: This retrospective cohort study included 318,826 children born in Kaiser Permanente Southern California (KPSC) hospitals in 2001-2014. Children were followed through electronic medical records until ASD diagnosis, non-KPSC membership, death, or December 31, 2019, whichever came first. Birth addresses were matched to U.S. Census tracts. A neighborhood deprivation index was developed using principal component analysis of seven census tract-level deprivation indicators (%poverty, %unemployment, %public assistance, %female-headed households, %less than high school, %bachelor and post, %professional occupation) obtained from the 2005-2009 and 2010-2014 American Community Survey and 2000 census. Hazard ratios (HRs) of ASD associated with neighborhood deprivation were scaled to interquartile range (IQR) and estimated using Cox regression models adjusted for birth year, child sex, maternal age, parity, maternal history of comorbidity, maternal race/ethnicity and education. Effect modification by maternal race, education, and child sex was assessed. Results: During follow-up 6,357 children (1.99%) had ASD diagnosis over a median of 9.0 follow-up years. Pregnancy residence in more deprived neighborhoods was associated with child ASD risk [HR=1.07 (95% confidence interval 1.02, 1.11) per deprivation IQR increase]. Maternal race interacted with neighborhood deprivation (p&amp;#x3c;0.05); deprivation-associated ASD risk was only observed among the White population [HR = 1.24 (1.11, 1.37)]. Results were consistent in alternative specifications of neighborhood deprivation. Conclusions: Children living in more deprived neighborhoods had a higher risk of ASD among a population with uniform health care access. This association was mainly observed in White populations, suggesting that in other races factors such as systemic racism may overwhelm effects of ASD-associated neighborhood deprivation. Keywords: Neighborhood deprivation, Autism

The Clinical Implications of the Academic Performance of the Siblings of Individuals With Autism Spectrum Disorder.

We all know that autism spectrum disorder (ASD) can affect academic performance. Many children with autism face different challenges at school. However, less attention is paid to the siblings of autistic children, who are at a high risk of ASD or the broad autism phenotype (BAP). Recent data also shows that many siblings of ASD children suffer from neurodevelopmental disorders, mental health problems as well as poor academic performance. This review will look at the possible etiologies of the poor school performance of autistic children's siblings, with an emphasis on the challenges they face. We will also highlight the clinical implications of these findings, and the possible solutions that can help this vulnerable group.

Cortical Source Analysis of the Face Sensitive N290 ERP Component in Infants at High Risk for Autism.

Appropriate head models for cortical source analysis were investigated and applied to source analyses examining the neural bases of the face-sensitive N290 event-related potential (ERP) component in infants at high risk for autism spectrum disorder (ASD). This included infant siblings of children with ASD (ASIBs) and infants with fragile X syndrome (FXS). First, alternative head models for use with ASIBs and FXS were investigated. Head models created from the infant’s own MRI were examined in relation to five head models based on average MRI templates. The results of the head model comparison identified group-specific (i.e., ASIB or FXS) head models created from a large collection of structural MRIs as the best substitution for the head model created from the participant’s own structural MRI. Second, the cortical source analysis was completed on N290 data collected from a previous study to investigate brain areas associated with face sensitive ERP responses. Participants’ own MRIs were used for head models when available, and the group-specific head model was used when the participants’ own MRIs were not available. The results provide evidence for unique patterns of neural activation during face processing across infants at high and low risk for ASD and across etiologically distinct high-risk groups. All infants demonstrated greater activation to faces than toys in brain areas most associated with specialized face processing. Infants with FXS displayed higher levels of activation to faces across all areas analyzed, while ASIBs show more muted levels of activation. Overall, the results of the current study demonstrate the importance of group-specific head models for accurate cortical source analysis in infants at high risk for ASD. This also allows for further research on early distinctions in brain function based on risk status.