Journal of Neurodevelopmental Disorders最新文献

Background: Quantitative measures of autism spectrum disorder (ASD)-related traits can provide insight into trait presentation across the population. Previous studies have identified epigenomic variation associated with ASD diagnosis, but few have evaluated quantitative traits. We sought to identify DNA methylation patterns in child blood associated with Social Responsiveness Scale score, Second Edition (SRS).

Methods: We conducted an epigenome-wide association study of SRS in child blood at approximately age 5 in the Study to Explore Early Development, a case-control study of ASD in the United States. We measured DNA methylation using the Illumina 450K array with 857 samples in our analysis after quality control. We performed regression of the M-value to identify single sites or differentially methylated regions (DMRs) associated with SRS scores, adjusting for sources of biological and technical variation. We examined methylation quantitative trait loci and conducted gene-ontology-term pathway analyses for regions of interest.

Results: We identified a region about 3.5 kb upstream of ZFP57 on chromosome 6 as differentially methylated (family-wise error rate [fwer] < 0.1) by continuous SRS T-score in the full sample (N = 857; fwer = 0.074) and among ASD cases only (N = 390; fwer = 0.021). ZFP57 encodes a transcription factor involved in imprinting regulation and maintenance, and this DMR has been previously associated with ASD in brain and buccal samples.

Conclusions: Blood DNA methylation near ZFP57 was associated (fwer < 0.1) with SRS in the full population sample and appears to be largely driven by trait heterogeneity within the autism case group. Our results indicate DNA methylation associations with ASD quantitative traits are observable in a population and provide insights into specific biologic changes related to autism trait heterogeneity.

Background: Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children, typically characterized by persistent patterns of inattention or hyperactivity-impulsivity. Its diagnosis relies on criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and is primarily based on subjective observations and information provided by parents and teachers. Despite the availability of assessment tools such as the Swanson, Nolan, and Pelham questionnaire, diagnosing ADHD in children remains challenging. Such scales predominantly offer subjective insights into the disorder. Therefore, in this study, we developed an objective method that employs load cells for the objective diagnosis of ADHD.

Methods: A simulated classroom environment was constructed to replicate a real-world setting. The setup included a desk, chair, and large screen. Load cells, which deform under applied force, were integrated into the four legs of the chair to capture movement data. This study involved 30 children with ADHD (14 boys and 16 girls; mean age: 8 years and 1 month ± 1 year and 10 months) and 30 age- and sex-matched children without ADHD (mean age: 8 years and 3 months ± 1 year and 10 months). Participants were instructed to sit on the chair and watch an age-appropriate educational video on mathematics. Movement data, captured through the load cells, were analyzed to calculate the average trajectory length (ATL) as a measure of activity. For participants with ADHD, SNAP-IV questionnaires were completed by parents and teachers.

Results: The ATL values for the ADHD and non-ADHD groups were 0.0378 ± 0.0191 and 0.0157 ± 0.0119 (p < 0.0001), respectively. In the ADHD group, boys exhibited a higher ATL (0.0443 ± 0.0100) than girls (0.0303 ± 0.0228; p = 0.0432). The SNAP-IV scores assigned by parents and teachers for participants with ADHD were 33.14 ± 13.75 and 30.95 ± 14.32, respectively. Decision tree classifiers incorporating sex as a variable demonstrated robust performance, achieving an accuracy of 90.67%, sensitivity of 92.33%, specificity of 89.00%, and area under the curve of 91.06%.

Conclusion: The smart chair equipped with load cells is an interesting development in progress tool for the objective diagnosis of ADHD and can aid clinical physicians in making decisions regarding ADHD evaluation.

Background: Although experienced clinicians are capable of diagnosing autism in children before they reach the age of 2, the average age of diagnosis reported internationally is between 4 and 5 years, indicating a significant delay. This study aimed to determine the factors influencing the diagnostic delay time (DDT) in Chinese autistic children.

Methods: We employed the Cox proportional hazard model to examine the effects of individual, family, sociodemographic, and healthcare system indicators on DDT in 480 Chinese autistic children (age range: 16.10-190.16 months; male-to-female ratio: 5.67:1) recruited from a tertiary hospital between 2021 and 2023.

Results: The median DDT was 9.58 months (IQR = 15.01). Independent risk factors for delayed diagnosis included normal language competence (RR = 1.747, p < 0.001), non-core symptoms as first concerns (RR = 1.642, p = 0.013), school attendance (RR = 1.941, p < 0.001), irregular well-child visits (RR = 1.264, p = 0.028), and misdiagnosis history (RR = 0.648, p = 0.001).

Conclusions: Diagnosis delay in Chinese autistic children is heterogeneous. Early monitoring for children with normal language skills and school-aged children, alongside improved healthcare system practices, is critical.

Background: High heritability (80-90%) of the autism spectrum disorder (ASD) and sex-biased incidence (3-4 times more boys than girls) suggest the roles of genetic predisposition and sex in the etiopathogenesis of the disorder. As ASD is commonly diagnosed in early childhood, most of the research is focused on children, yet animal research predominantly uses adult-aged animals. The effect of aging on the core and secondary ASD symptomatology is understudied, both in patients and animal models of ASD.

Methods: To investigate the effect of aging on sociability, repetitive behavior, exploration, locomotor activity, anxiety-like behavior, and object-avoidance behavior, behavioral phenotyping was conducted in Shank3B^-/- (n = 67) and C57BL/6J wild-type (WT, n = 68) mice of both sexes (female n = 70, male n = 65) in adolescence (1-2 months of age, n = 42), adulthood (3-6 months of age, n = 40), and old age (12-18 months of age, n = 53).

Results: Social deficits were observed only in old Shank3B^-/- males. Anxiety-like behavior peaked in adulthood with Shank3B^-/- mice roughly 20% more anxious than controls. Repetitive grooming and object-induced avoidance behavior were twice more prevalent in Shank3B^-/- mice consistently across the lifespan. Hypoactivity (20% less distance moved) and reduced exploration (30% less rearing behavior) were recorded in Shank3B^-/- mice and were more prevalent in female animals (30% less rearing behavior). Data were analyzed using the Three-way ANOVA (genotype, sex, age), followed by a posthoc Bonferroni correction to compare respective subgroups.

Conclusions: Present study shows that aging affects ASD-like phenotype in the Shank3B-mutant mouse model, even though the effect size seems to be small. The mechanisms underlying these partially sex-specific effects should be the subject of further research with potential translational implications.

Background: The impact of genetic intellectual disability (GID) on daily life is significant. To better understand the impact of GID, it is essential to measure relevant patient reported outcomes (PROs). The aim of this study is to provide an overview of PROs used for individuals with GID, laying the groundwork for a future generic core PRO set for GID.

Methods: To identify PROs used for individuals with GID, results of two literature reviews were integrated; (1) PROs extracted from a scoping review on outcomes in clinical trials, and (2) PROs identified from a scoping review on core outcome sets (COSs) for specific GIDs through a search in MEDLINE (Ovid), PsycINFO, Embase, and the COMET database. Descriptive analyses were performed.

Results: In the first scoping review, 66 different PROs were identified. In the second scoping review, 22 different PROs were identified. After integrating PROs, 18 unique PROs remained, which were classified into a conceptual framework. Most frequently reported PROs were quality of life, perceived health, cognitive functioning, anxiety/stress, and depressive symptoms.

Conclusion: This study provides an overview of PROs used for individuals with GID. These results will assist in developing a generic core PRO set for GID, to harmonize PROs used in care and research.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and interaction, and repetitive behaviors. Males are three times more likely to be diagnosed with ASD than females, and sex-dependent alterations in behavior and communication have been reported both in clinical and animal research. Animal models are useful for understanding ASD-related manifestations and their associated neurobiological mechanisms. However, even though ASD is diagnosed during childhood, relatively few animal studies have focused on neonatal development.

Methods: Here, we performed a detailed analysis of neonatal developmental milestones and maternal separation-induced ultrasonic vocalizations (USVs) in two genetic animal models of ASD, neurofibromatosis type 1 (Nf1^±) and tuberous sclerosis complex 2 (Tsc2^±).

Results: Nf1^± and Tsc2^± mice display strikingly distinct developmental profiles regarding motor, strength, and coordination skills. Nf1^± mouse pups mostly show genotype-related differences, whereas Tsc2^± mouse pups mainly present sexual dimorphisms. Furthermore, we found several differences regarding the number of USVs, frequency modulation, and temporal and spectral profile. Importantly, Nf1^± animals tend to present sex- and genotype-dependent differences earlier than the Tsc2^± mouse pups, suggesting distinct developmental curves between these two animal models.

Conclusions: This study provides a nuanced understanding of how these two ASD models differ in their developmental trajectories. It underscores the importance of studying sex differences and early-life developmental markers, as these could offer crucial insights into ASD's progression and neurobiology. The distinct profiles of these models may help guide more targeted therapeutic strategies in the future.

Background: Triple X syndrome (TXS, 47,XXX) is a sex chromosome aneuploidy affecting females. The condition is associated with cognitive, emotional, and social challenges. While prior research has primarily focused on children, the social and psychological profile of adult women with TXS remains understudied. This study aims to provide a comprehensive assessment of these aspects in adult women with TXS compared to matched controls.

Methods: A cohort of 44 women with TXS (mean age 30.5 years) was compared to 50 age- and education-matched controls (mean age 29.7 years). Standardized assessments measured verbal IQ, psychological distress, chronic stress, emotion regulation, coping mechanisms, social anxiety, empathy, autistic traits, and personality traits. Group comparisons were conducted using ANOVAs and MANOVAs, with additional χ² tests for categorical variables.

Results: Depression and trait anxiety did not significantly differ between groups, though both groups exhibited notably high scores. However, a greater number of individuals in the TXS group reported elevated social anxiety and autistic traits, and reduced empathy. Moreover, there were indications of increased self-reported social tensions, personal distress, and somatization within the TXS group. No significant differences were found in personality traits, verbal IQ, chronic stress levels, and emotion regulation. Additionally, TXS participants tended to rely less on the maladaptive coping strategy of alcohol and cigarette consumption.

Conclusion: Our findings underscore autistic traits, social anxiety, and reduced empathy as significant challenges for adult women with TXS. While cognitive and emotional characteristics were largely comparable to those of age- and education-matched controls, the heightened social difficulties suggest a potential benefit of targeted interventions, such as social skills training, to support affected individuals. Longitudinal studies are essential to understand the long-term progression of these challenges and to develop effective therapeutic strategies.

Background: fcMRI correlates of autism spectrum disorder (ASD) diagnosis and familial liability were studied in 24-month-olds at high (older affected sibling) and low familial likelihood for ASD.

Methods: fcMRI comparisons of high-familial-likelihood (HL) ASD-positive (HLP, N = 23) and ASD-negative (HLN, N = 91), and low-likelihood ASD-negative (LLN, N = 27) 24-month-olds from the Infant Brain Imaging Study (IBIS) Network were conducted, employing object oriented data analysis (OODA), support vector machine (SVM) classification, and network-level fcMRI enrichment analyses.

Results: OODA (alpha = 0.0167, 3 comparisons) revealed differences in HLP and LLN fcMRI matrices (p = 0.012), but none for HLP versus HLN (p = 0.047) nor HLN versus LLN (p = 0.225). SVM distinguished HLP from HLN (accuracy = 99%, PPV = 96%, NPV = 100%), based on connectivity involving many networks. SVM accurately classified (non-training) LLN subjects with 100% accuracy. Enrichment analyses identified a cross-group fcMRI difference in the posterior cingulate default mode network 1 (pcDMN1)- temporal default mode network (tDMN) pair (p = 0.0070). Functional connectivity for implicated connections in these networks was consistently lower in HLP and HLN than in LLN (p = 0.0461 and 0.0004). HLP did not differ from HLN (p = 0.2254). Secondary testing showed HL children with low ASD behaviors still differed from LLN (p = 0.0036).

Conclusions: 24-month-old high-familial-likelihood infants show reduced intra-DMN connectivity, a potential neural finding related to familial liability, while widely distributed functional connections correlate with ASD diagnosis.