Autism Spectrum Disorder Cases Research Articles

O DIAGNÓSTICO DE CRIANÇAS E ADOLESCENTES AUTISTAS E SUA RECEPÇÃO PELOS SEUS RESPONSÁVEIS

This study aims to address the significant theme of the experience of those responsible for atypical children in the process of diagnosing Autism Spectrum Disorder (ASD). The growing number of ASD cases highlights the importance of understanding family experiences during this procedure, given the complexity of this condition and its impact on the environment or family context. ASD is a complex condition that affects child development and presents significant challenges for families. Understanding how caregivers perceive the diagnosis, face challenges, and experience emotions can provide valuable insights for healthcare professionals, educators, and psychologists. The general objective of the study is to reduce a gap in the literature by exploring the ASD diagnostic process from the perspective of those responsible, with potential implications for clinical practice and the well-being of affected families and children. The method used was a systematic bibliographic review, the research seeks not only to understand the technical aspects of ASD diagnosis, but also to highlight the importance of the emotional and social dimensions involved, highlighting the need for an interdisciplinary approach.

Consanguinity

Objective: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with genetic and environmental factors. Although consanguinity is a common practice in the Middle Eastern population, the association between consanguinity and ASD severity is not clear. Methods: This retrospective study analyzed the records of 139 children (1.5-14 years) diagnosed with ASD from June 2011 to May 2024. The study analyzed the correlation between consanguinity, homozygosity, and ASD severity. Results: Of 139 cases, 74.1% were male, with an average age of diagnosis of 4.5 years (SD+- 2). Most ASD cases were at severity levels 2 (63.3%) and 3 (35.3%). Consanguinity was reported in 59% of cases, with a mean homozygosity rate of 4.6%. No significant correlation was found between consanguinity or homozygosity rates and ASD severity. Conclusion: No significant association was found between consanguinity or homozygosity rates and ASD severity. Further research is needed to explore the genetic mechanisms of ASD in consanguineous populations.

Prenatal Exposure to Source-Specific Fine Particulate Matter and Autism Spectrum Disorder.

In this study, associations between prenatal exposure to fine particulate matter (PM2.5) from 9 sources and development of autism spectrum disorder (ASD) were assessed in a population-based retrospective pregnancy cohort in southern California. The cohort included 318,750 mother-child singleton pairs. ASD cases (N = 4559) were identified by ICD codes. Source-specific PM2.5 concentrations were estimated from a chemical transport model with a 4 × 4 km2 resolution and assigned to maternal pregnancy residential addresses. Cox proportional hazard models were used to estimate the hazard ratios (HR) of ASD development for each individual source. We also adjusted for total PM2.5 mass and in a separate model for all other sources simultaneously. Increased ASD risk was observed with on-road gasoline (HR [CI]: 1.18 [1.13, 1.24]), off-road gasoline (1.15 [1.12, 1.19]), off-road diesel (1.08 [1.05, 1.10]), food cooking (1.05 [1.02, 1.08]), aircraft (1.04 [1.01, 1.06]), and natural gas combustion (1.09 [1.06, 1.11]), each scaled to standard deviation increases in concentration. On-road gasoline and off-road gasoline were robust for other pollutant groups. PM2.5 emitted from different sources may have different impacts on ASD. The results also identify PM source mixtures for toxicological investigations that may provide evidence for future public health policies.

Biomarkers and pathways in autism spectrum disorder: An individual meta-analysis based on proteomic and metabolomic data.

The utilization of biomarkers for the diagnosis and management of autism spectrum disorders (ASD) remains a relatively unexplored frontier in clinical practice. Proteomics and metabolomics are important tools for revealing key biomarkers and evaluating biological pathways in ASD. We conducted an individual meta-analysis to compare the consistency of biomarkers of ASD from central nervous system (brain and cerebrospinal fluid), circulatory system (blood), and non-invasive samples (urine, saliva, and faeces) and performed pathway enrichment analyses to identify pathways enriched in ASD. After screening 926 proteomics and 619 metabolomics articles, we collected data from 10 studies involving 940 differential proteins and 16 studies assessing a total of 748 differential metabolites. In brain tissue, blood, and urine of ASD cases and controls, flotillin-2 (FLOT2), apolipoprotein E (ApoE), and EH domain-containing protein 3 (EHD3) exhibit differential expression, while vinculin (VCL) displays variations in saliva, blood, and urine. Similarly, in case-control studies, gelsolin (GSN) shows differential expression in brain tissue, saliva, and urine, and malate dehydrogenase 2 (MDH2) in brain tissue, blood, and saliva. Hippuric acid and salicyluric acid were simultaneously found in the brain, blood, urine, and faeces. In terms of pathways, glycolysis/gluconeogenesis, carbon metabolism, and glutathione metabolism were enriched in the brain as well as in saliva or urine. In our study, we identified six shared protein and two metabolic markers in central nervous system, circulatory system, and non-invasive samples, underscoring their potential value for ASD diagnosis and management, warranting further research.

Clinical, developmental and serotonemia phenotyping of a sample of 70 Italian patients with Phelan-McDermid Syndrome

BackgroundPhelan-McDermid syndrome (PMS) is caused by monoallelic loss or inactivation at the SHANK3 gene, located in human chr 22q13.33, and is often associated with Autism Spectrum Disorder (ASD).ObjectivesTo assess the clinical and developmental phenotype in a novel sample of PMS patients, including for the first time auxometric trajectories and serotonin blood levels.Methods70 Italian PMS patients were clinically characterized by parental report, direct medical observation, and a thorough medical and psychodiagnostic protocol. Serotonin levels were measured in platelet-rich plasma by HPLC.ResultsOur sample includes 59 (84.3%) cases with chr. 22q13 terminal deletion, 5 (7.1%) disruptive SHANK3 mutations, and 6 (8.6%) ring chromosome 22. Intellectual disability was present in 69 (98.6%) cases, motor coordination disorder in 65 (92.9%), ASD in 20 (28.6%), and lifetime bipolar disorder in 12 (17.1%). Prenatal and postnatal complications were frequent (22.9%-48.6%). Expressive and receptive language were absent in 49 (70.0%) and 19 (27.1%) cases, respectively. Decreased pain sensitivity was reported in 56 (80.0%), hyperactivity in 49 (80.3%), abnormal sleep in 45 (64.3%), congenital dysmorphisms in 35 (58.3%), chronic stool abnormalities and especially constipation in 29 (41.4%). Parents reported noticing behavioral abnormalities during early childhood immediately after an infective episode in 34 (48.6%) patients. Brain MRI anomalies were observed in 53 (79.1%), EEG abnormalities in 16 (23.5%), kidney and upper urinary tract malformations in 18 (28.1%). Two novel phenotypes emerged: (a) a subgroup of 12/44 (27.3%) PMS patients displays smaller head size at enrollment (mean age 11.8 yrs) compared to their first year of neonatal life, documenting a deceleration of head growth (p < 0.001); (b) serotonin blood levels are significantly lower in 21 PMS patients compared to their 21 unaffected siblings (P < 0.05), and to 432 idiopathic ASD cases (p < 0.001).ConclusionsWe replicate and extend the description of many phenotypic characteristics present in PMS, and report two novel features: (1) growth trajectories are variable and head growth appears to slow down during childhood in some PMS patients; (2) serotonin blood levels are decreased in PMS, and not increased as frequently occurs in ASD. Further investigations of these novel features are under way.

Decomposing the variance: The unique and shared associations of fine and ultrafine particulate matter exposed during pregnancy with child autism spectrum disorder

While fine particulate matter (PM2.5) has been associated with autism spectrum disorder (ASD), few studies focused on ultrafine particles (PM0.1). Given that fine and ultrafine particles can be highly correlated due to shared emission sources, challenges remain to distinguish their health effects. In a retrospective cohort of 318,371 mother-child pairs (4549 ASD cases before age 5) in Southern California, pregnancy average PM2.5 and PM0.1 were estimated using a California-based chemical transport model and assigned to residential addresses. The correlation between PM2.5 and PM0.1 was 0.87. We applied a two-step variance decomposition approach: first, decomposing PM2.5 and PM0.1 into the shared and unique variances using ordinary least squares linear regression (OLS) and Deming regression considering errors in both exposures; then assessing associations between decomposed PM2.5 and PM0.1 and ASD using Cox proportional hazard models adjusted for covariates. Prenatal PM2.5 and PM0.1 each was associated with increased ASD risk. OLS decomposition showed that associations were driven mainly by their shared variance, not by their unique variance. Results from Deming regression considering assumptions of measurement errors were consistent with those from OLS. This decomposition approach has potential to disentangle health effects of correlated exposures, such as PM2.5 and PM0.1 from common emissions sources.

Dysregulated plasma autoantibodies are associated with B cell dysfunction in young Arab children with autism spectrum disorder in Qatar.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interaction and communication, as well as the occurrence of stereotyped and repetitive behaviors. Previous studies have provided solid evidence of dysregulated immune system in ASD; however, limited studies have investigated autoantibody profiles in individuals with ASD. This study aims to screen plasma autoantibodies in a well-defined cohort of young children with ASD (n = 100) and their matched controls (n = 60) utilizing a high-throughput KoRectly Expressed (KREX) i-Ome protein-array technology. We identified differential protein expression of 16 autoantibodies in ASD, which were correlated with differential gene expression of these markers in independent ASD cohorts. Meanwhile, we identified a distinct list of 33 autoantibodies associated with ASD severity; several of which were correlated with maternal age and birth weight in ASD. In addition, we found dysregulated numbers of circulating B cells and activated HLADR+ B cells in ASD, which were correlated with altered levels of several autoantibodies. Further in-depth analysis of B cell subpopulations revealed an increased frequency of activated naïve B cells in ASD, as well as an association of resting naïve B cells and transitional B cells with ASD severity. Pathway enrichment analysis revealed disrupted MAPK signaling in ASD, suggesting a potential relevance of this pathway to altered autoantibodies and B cell dysfunction in ASD. Finally, we found that a combination of eight autoantibodies associated with ASD severity showed an area under the curve (ROC-AUC) of 0.937 (95% CI = 0.890, 0.983; p < 0.001), which demonstrated the diagnostic accuracy of the eight-marker signature in the severity classification of ASD cases. Overall, this study determined dysregulated autoantibody profiles and B cell dysfunction in children with ASD and identified an eight-autoantibody panel for ASD severity classification.

Cognitive behavioral phenotyping of DSCAM heterozygosity as a model for autism spectrum disorder.

It is estimated that 1 in 36 children are affected by autism spectrum disorder (ASD) in the United States, which is nearly a twofold increase from a decade ago. Recent genetic studies have identified de novo loss-of-function (dnLoF) mutations in the Down Syndrome Cell Adhesion Molecule (DSCAM) as a strong risk factor for ASD. Previous research has shown that DSCAM ablation confers social interaction deficits and perseverative behaviors in mouse models. However, it remains unknown to what extent DSCAM underexpression captures the full range of behaviors, specifically cognitive phenotypes, presented in ASD. Here, we conducted a comprehensive cognitive behavioral phenotyping which revealed that loss of one copy of DSCAM, as in the DSCAM2J+/-, that is, DSCAM heterozygous mice, displayed hyperactivity, increased anxiety-like behavior, and motor coordination deficits. Additionally, hippocampal-dependent learning and memory was affected, including impairments in working memory, long-term memory, and contextual fear learning. Interestingly, implicit learning processes remained intact. Therefore, DSCAM LoF produces autistic-like behaviors that are similar to those observed in human cases of ASD. These findings further support a role for DSCAM dnLoF mutations in ASD and suggest DSCAM2J+/- as a suitable model for ASD research.

HCBiLSTM-WOA: hybrid convolutional bidirectional long short-term memory with water optimization algorithm for autism spectrum disorder

Autism Spectrum Disorder (ASD) is a type of brain developmental disability that cannot be completely treated, but its impact can be reduced through early interventions. Early identification of neurological disorders will better assist in preserving the subjects’ physical and mental health. Although numerous research works exist for detecting autism spectrum disorder, they are cumbersome and insufficient for dealing with real-time datasets. Therefore, to address these issues, this paper proposes an ASD detection mechanism using a novel Hybrid Convolutional Bidirectional Long Short-Term Memory based Water Optimization Algorithm (HCBiLSTM-WOA). The prediction efficiency of the proposed HCBiLSTM-WOA method is investigated using real-time ASD datasets containing both ASD and non-ASD data from toddlers, children, adolescents, and adults. The inconsistent and incomplete representations of the raw ASD dataset are modified using preprocessing procedures such as handling missing values, predicting outliers, data discretization, and data reduction. The preprocessed data obtained is then fed into the proposed HCBiLSTM-WOA classification model to effectively predict the non-ASD and ASD classes. The initially randomly initialized hyperparameters of the HCBiLSTM model are adjusted and tuned using the water optimization algorithm (WOA) to increase the prediction accuracy of ASD. After detecting non-ASD and ASD classes, the HCBiLSTM-WOA method further classifies the ASD cases into respective stages based on the autistic traits observed in toddlers, children, adolescents, and adults. Also, the ethical considerations that should be taken into account when campaign ASD risk communication are complex due to the data privacy and unpredictability surrounding ASD risk factors. The fusion of sophisticated deep learning techniques with an optimization algorithm presents a promising framework for ASD diagnosis. This innovative approach shows potential in effectively managing intricate ASD data, enhancing diagnostic precision, and improving result interpretation. Consequently, it offers clinicians a tool for early and precise detection, allowing for timely intervention in ASD cases. Moreover, the performance of the proposed HCBiLSTM-WOA method is evaluated using various performance indicators such as accuracy, kappa statistics, sensitivity, specificity, log loss, and Area Under the Receiver Operating Characteristics (AUROC). The simulation results reveal the superiority of the proposed HCBiLSTM-WOA method in detecting ASD compared to other existing methods. The proposed method achieves a higher ASD prediction accuracy of about 98.53% than the other methods being compared.

Breastfeeding patterns in infants are associated with a later diagnosis of autism Spectrum disorder.

Breastfeeding is associated with medical and developmental benefits. This study aimed to assess associations between nutritional patterns in the first year of life and the likelihood of autism spectrum disorder (ASD). 270 children diagnosed with ASD (cases) and 500 neurotypical children (controls) matched to cases by sex, ethnicity, and birth date (± 3 months) were included in this retrospective case-control study. Both groups were ascertained from children born between 2014 and 2017 whose development/nutrition were monitored at mother-child health clinics in southern Israel. Conditional logistic regression was used to determine the independent association of nutritional patterns with ASD while adjusting for socio-demographic and clinical characteristics. Both exclusive and partial breastfeeding modes were associated with decreased odds of ASD diagnosis (aOR = 0.221, 95%CI = 0.136-0.360; aOR = 0.494, 95%CI = 0.328-0.743, respectively). A breastfeeding duration of >12 months was associated with lower ASD odds (aOR = 0.418, 95%CI = 0.204-0.855), while the introduction of solids after 6 months of age was associated with higher ASD odds than the introduction of solids at 6 months (aOR = 2.455, 95%CI = 1.116-4.201). These findings suggest that a longer period of exclusive breastfeeding is associated with a subsequent reduced likelihood of ASD diagnosis, thus reiterating the importance of proper post-natal nutrition for infant neurodevelopment.

Association between prenatal air pollutant exposure and autism spectrum disorders in young children: A matched case-control study in Canada

The direction and magnitude of association between maternal exposure to ambient air pollutants across gestational windows and offspring risk of autism spectrum disorders (ASD) remains unclear. We sought to evaluate the time-varying effects of prenatal air pollutant exposure on ASD. We conducted a matched case-control study of singleton term children born in Ontario, Canada from 1-Apr-2012 to 31-Dec-2016. Provincial birth registry data were linked with applied behavioural analysis services and ambient air pollutant datasets to ascertain prenatal exposure to nitrogen dioxide (NO2), ground-level ozone (O3), fine particulate matter (PM2.5), and ASD diagnoses. Covariate balance between cases and controls was established using coarsened exact matching. Conditional logistic regression was used to assess the association between prenatal air pollutant exposure and ASD. Distributed lag non-linear models (DLNM) were used to examine the effects of single-pollutant exposure by prenatal week. Sensitivity analyses were conducted to assess the impact of exposure period on the observed findings. The final sample included 1589 ASD cases and 7563 controls. Compared to controls, cases were more likely to be born to mothers living in urban areas, delivered by Caesarean section, and assigned male sex at birth. NO2 was a consistent and significant contributor to ASD risk after accounting for co-exposure to O3, PM2.5 and covariates. The odds ratio per interquartile range increase was 2.1 (95%CI 1.8–2.3) pre-conception, 2.2 (2.0–2.5) for the 1st trimester, 2.2 (1.9–2.5) for the 2nd trimester, and 2.1 (1.9–2.4) for the 3rd trimester. In contrast, findings for O3 and PM2.5 with ASD were inconsistent. Findings from DLNM and sensitivity analyses were similar. Exposure to NO2 before and during pregnancy was significantly associated with ASD in offspring. The relationship between prenatal O3 and PM2.5 exposure and ASD remains unclear. Further investigation into the combined effects of multi-pollutant exposure on child neurodevelopment is warranted.

Evaluating the Role of Susceptibility Inducing Cofactors and of Acetaminophen in the Etiology of Autism Spectrum Disorder.

More than 20 previously reported lines of independent evidence from clinical observations, studies in laboratory animal models, pharmacokinetic considerations, and numerous temporal and spatial associations indicate that numerous genetic and environmental factors leading to inflammation and oxidative stress confer vulnerability to the aberrant metabolism of acetaminophen during early development, leading to autism spectrum disorder (ASD). Contrary to this conclusion, multivariate analyses of cohort data adjusting for inflammation-associated factors have tended to show little to no risk of acetaminophen use for neurodevelopment. To resolve this discrepancy, here we use in silico methods to create an ideal (virtual) population of 120,000 individuals in which 50% of all cases of virtual ASD are induced by oxidative stress-associated cofactors and acetaminophen use. We demonstrate that Cox regression analysis of this ideal dataset shows little to no risk of acetaminophen use if the cofactors that create aberrant metabolism of acetaminophen are adjusted for in the analysis. Further, under-reporting of acetaminophen use is shown to be a considerable problem for this analysis, leading to large and erroneously low calculated risks of acetaminophen use. In addition, we argue that factors that impart susceptibility to acetaminophen-induced injury, and propensity for acetaminophen use itself, can be shared between the prepartum, peripartum, and postpartum periods, creating additional difficulty in the analysis of existing datasets to determine risks of acetaminophen exposure for neurodevelopment during a specific time frame. It is concluded that risks of acetaminophen use for neurodevelopment obtained from multivariate analysis of cohort data depend on underlying assumptions in the analyses, and that other evidence, both abundant and robust, demonstrate the critical role of acetaminophen in the etiology of ASD.

Short tandem repeat expansions in cortical layer-specific genes implicate in phenotypic severity and adaptability of autism spectrum disorder.

Short tandem repeats (STRs) are repetitive DNA sequences and highly mutable in various human disorders. While the involvement of STRs in various genetic disorders has been extensively studied, their role in autism spectrum disorder (ASD) remains largely unexplored. In this study, we aimed to investigate genetic association of STR expansions with ASD using whole genome sequencing (WGS) and identify risk loci associated with ASD phenotypes. We analyzed WGS data of 634 ASD families and performed genome-wide evaluation for 12,929 STR loci. We found rare STR expansions that exceeded normal repeat lengths in autism cases compared to unaffected controls. By integrating single cell RNA and ATAC sequencing datasets of human postmortem brains, we prioritized STR loci in genes specifically expressed in cortical development stages. A deep learning method was used to predict functionality of ASD-associated STR loci. In ASD cases, rare STR expansions predominantly occurred in early cortical layer-specific genes involved in neurodevelopment, highlighting the cellular specificity of STR-associated genes in ASD risk. Leveraging deep learning prediction models, we demonstrated that these STR expansions disrupted the regulatory activity of enhancers and promoters, suggesting a potential mechanism through which they contribute to ASD pathogenesis. We found that individuals with ASD-associated STR expansions exhibited more severe ASD phenotypes and diminished adaptability compared to non-carriers. Short tandem repeat expansions in cortical layer-specific genes are associated with ASD and could potentially be a risk genetic factor for ASD. Our study is the first to show evidence of STR expansion associated with ASD in an under-investigated population.

Systematic Review of Parents with Autism Spectrum Disorder (ASD) Children in Southeast Asia: Work-related Factors

Considering the rising cases of ASD among children, this paper aims to investigate the extent to which work-related factors have been examined in studies conducted on parents of children with ASD within the Southeast Asia (SEA) region. Using the PRISMA framework, a search was conducted on three databases (Scopus, PubMed, Web of Science), yielding 38 studies that met the following inclusion criteria: (1) focusing on parents of ASD children, (2) conducted in the SEA region, and (3) articles, excluding systematic and meta-analyses. Of the 38 studies, 24 were from Malaysia, 9 from Singapore, 3 from the Philippines, 1 from Indonesia, and 1 from Vietnam. No articles were found for Brunei, Burma, Myanmar, Cambodia, Timor-Leste, Laos and Thailand. The focus, across the 38 studies, was primarily on the effects of the ASD child's therapies and interventions on parents, followed by parenting stress and quality of life (QOL). Employment-related factors were seen in sub-themes of five studies from Malaysia and Singapore. The review showed a limited focus on employment-related concerns amongst working parents with ASD children within the SEA region. The study's limitations include the lack of studies from other SEA countries such as Brunei, Burma, Myanmar, Cambodia, Timor-Leste, Laos, and Thailand. It is suggested that future research should focus on work-related factors for this underrepresented population while considering the roles of individual, gender, cultural, and religious factors.

Validation and determining an optimal cut-off score of the Infant Behavior Checklist for autism spectrum disorder.

Given the escalating prevalence of autism spectrum disorder (ASD), the persistent paucity of child psychiatrists in Japan, and the need to prepare for unforeseen situations, such as the COVID-19 pandemic, it is essential to establish a reliable screening tool. This study aims to validate the Infant Behavior Checklist (IBC) developed by Japanese experts and determine its appropriate cut-off score. A total of 354 clinic-referred children, along with their caregivers, participated in this research. Clinical records, including diagnoses established through the sub-structured diagnostic interviews, and the IBC assessments, were subjected to rigorous statistical analysis. Among the 24 items, six failed to reach significance to differentiate ASD from non-ASD cases. The Cronbach's alpha coefficient for the IBC was calculated at 0.77. The IBC total score for ASD cases was significantly higher than that of non-ASD cases. With the chosen cut-off score, the IBC demonstrated an area under the ROC curve of 0.803, along with sensitivity, specificity, positive predictive value, and negative predictive value of 8.03, 0.79, 0.69, 0.34, and 0.94, respectively. The IBC exhibits satisfactory internal consistency and content and discriminant validity. The high sensitivity and other associated indices for the optimal cut-off score of the IBC affirm its validity as a screening instrument for ASD. Nevertheless, further investigations are warranted to ascertain the clinical utility of the IBC.

The Association Between Gastrointestinal Issues and Psychometric Scores in Children with Autism Spectrum Disorder, Developmental Delays, Down Syndrome, and Typical Development.

Investigate the association between gastrointestinal (GI) issues and psychometric scores among children with developmental delays and typical development. We examined the association between GI issues and the Mullen Scale of Early Learning (MSEL), Vineland Adaptive Behavior Subscales (VABS), and Aberrant Behavior Checklist (ABC) scores from participants with autism spectrum disorder (ASD), Down syndrome (DS),other developmental delays (DD) and typical development (TD) from the CHildhood Autism Risk from Genetics and Environment (CHARGE) Study (n = 1603). Approximately 32% of children with ASD, 31% of children with DD, and 20% of children with DS reported at least one GI issue, compared to 7% of TD controls.Constipation was the most frequently reported symptom for the entire population, including controls. In general, GI issues correlated with poorer behavioral scores (decreased communication, daily living, socialization, and motor skills on the VABS, and increased irritability/agitation, lethargy/social withdrawal, stereotypic behavior, and hyperactivity/noncompliance on the ABC) among ASD cases. Analysis by sex indicated that GI issues also correlated with poorer cognitive scores (fine motor, receptive language, expressive language, and MSEL composite scores), and adaptive behavior (communication skills, daily living skills, motor, and VABS composite scores) among boys with DD, but not girls with DD-suggesting sex differences among DD cases. Even TD controls showed increased stereotypic behavior and social withdrawal in association with GI issues. However, GI issues were not correlated with impairments in psychometric scores among DS cases. Given that GI issues correlate with deficits in behavioral and cognitive scores, future studies should investigate the treatment of GI symptoms in children with ASD and DD.

Prenatal &amp; Perinatal Risk Factors of Autism Spectrum Disorder

Background: Autism spectrum disorder (ASD) is lifelong neurodevelopmental disorder characterized by impairments in social function, communication, and certain behaviors. The etiology of ASD is unclear &amp; it is believed to be multi-factorial, among those several prenatal &amp; perinatal factors are found to be significant. So, the necessity of this study is to detect the presence of known risk factors of ASD which in turn may help in the early diagnosis and intervention for better long-term outcomes. Objective: To find out prenatal and perinatal risk factors of ASD. Method: A case control study was conducted with 112 cases of ASD and 201 controls of 2-6 years of age. The study was carried out in Center for Neurodevelopment and Autism in Children (CNAC), in the department of Paediatrics, Bangabandhu Sheikh Mujib Medical University and Autism Welfare Foundation (AWF). ASD was diagnosed by DSM-IV TR criteria. Mothers were interviewed and data were collected by semistructured questionnaires. Results: Total 5 risk factors were identified as the risk factors of ASD. They were: advanced paternal age (OR=2.84) and maternal age (OR=1.87); male baby (OR=2.01); environmental stress during pregnancy (OR=1.61) and preterm delivery (OR=1.80). Conclusions: It is concluded that advanced paternal age, maternal age, male baby, environmental stress during pregnancy and preterm delivery are associated with increased risk of ASD. BANGLADESH J CHILD HEALTH 2022; VOL 46 (3) : 115-121

Novel protein-truncating variants of a chromatin-modifying gene MSL2 in syndromic neurodevelopmental disorders

Numerous large scale genomic studies have uncovered rare but recurrent pathogenetic variants in a significant number of genes encoding epigenetic machinery in cases with neurodevelopmental disorders (NDD) especially autism spectrum disorder (ASD). These findings provide strong support for the functional importance of epigenetic regulators in neurodevelopment. After the clinical genomics evaluation of the patients using exome sequencing, we have identified, three novel protein-truncating variants (PTVs) in the MSL2 gene (OMIM: 614802) which encodes a chromatin modifying enzyme. MSL2 modifies chromatin through both mono-ubiquitination of histone 2B on lysine 34 (K34) and acetylation of histone H4 on lysine 16 (K16). We reported first time the detailed clinical features associated with 3 MSL2 PTVs. There are 15 PTVs (13 de novo) reported from the large genomics studies (12 cases) or ClinVar (3 cases) of NDD, ASD, and developmental disorders (DD) but the specific clinical features for these cases are not described. Taken together, our descriptions of dysmorphic face and other features support the causal role of MSL2 in a likely syndromic neurodevelopmental disorder and add MSL2 to a growing list of epigenetic genes implicated in ASD.

Trends in the Prevalence of Autism Spectrum Disorder in California: Disparities by Sociodemographic Factors and Region Between 1990-2018.

Autism Spectrum Disorders (ASD) prevalence has risen globally, with regional variation and sociodemographic disparities affecting diagnosis and intervention. This study examines ASD trends from 1990 to 2018 in California (CA), focusing on sociodemographic factors that may inform policy/interventions. Using CA Department of Public Health birth records (1990-2018) and Developmental Services ASD cases (1994-2022), we analyzed diagnosis incidence by age 4 or 8, stratified by sociodemographic and regional factors. From 1990 to 2018, for each birth year the cumulative incidence of ASD by 4 and 8 years of age in CA increased while the diagnosis age decreased. Distinct patterns emerged over these three decades. Children born to White and Asian and Pacific Islander (API) mothers, or to mothers with higher education or living in high socioeconomic status (SES) neighborhoods exhibited higher ASD cumulative incidences throughout the 1990s and early 2000s. However, in the mid-2000s, ASD incidence in children born to Black or Hispanic mothers, with low education, or living in low SES neighborhoods surpassed that of White/API children or those living in high SES neighborhoods. Black or Hispanic children now have the highest ASD cumulative incidence, even though age at first diagnosis remains lowest in high SES regions, for the highly educated, and for White/API children. ASD cumulative incidence in CA from 1990 to 2018 exhibited demographic reversals with higher rates in children born to Black or Hispanic mothers or lower SES neighborhoods. Black and Hispanic children still have delayed age at diagnosis compared to White/API children.

Study of the genetic association between selected 3q29 region genes and schizophrenia and autism spectrum disorder in the Japanese population.

Psychiatric disorders are highly inheritable, and most psychiatric disorders exhibit genetic overlap. Recent studies associated the 3q29 recurrent deletion with schizophrenia (SCZ) and autism spectrum disorder (ASD). In this study, we investigated the association of genes in the 3q29 region with SCZ and ASD. TM4SF19 and PAK2 were chosen as candidate genes for this study based on evidence from previous research. We sequenced TM4SF19 and PAK2 in 437 SCZ cases, 187 ASD cases and 524 controls in the Japanese population. Through targeted sequencing, we identified 6 missense variants among the cases (ASD & SCZ), 3 missense variants among controls, and 1 variant common to both cases and controls; however, no loss-of-function variants were identified. Fisher's exact test showed a significant association of variants in TM4SF19 among cases (p=0.0160). These results suggest TM4SF19 variants affect the etiology of SCZ and ASD in the Japanese population. Further research examining 3q29 region genes and their association with SCZ and ASD is thus needed.