Aim and methods: Artificial neural networks were used to unravel connections among blood gene methylation levels, sex, maternal risk factors and symptom severity evaluated using the Autism Diagnostic Observation Schedule 2 (ADOS-2) score in 58 children with autism spectrum disorder (ASD). Results: Methylation levels of MECP2, HTR1A and OXTR genes were connected to females, and those of EN2, BCL2 and RELN genes to males. High gestational weight gain, lack of folic acid supplements, advanced maternal age, preterm birth, low birthweight and living in rural context were the best predictors of a high ADOS-2 score. Conclusion: Artificial neural networks revealed links among ASD maternal risk factors, symptom severity, gene methylation levels and sex differences in methylation that warrant further investigation in ASD.
Autism spectrum disorders (ASD) encompass a heterogeneous group of neurodevelopmental disorders resulting from the complex interaction between genetic and environmental factors. Thanks to the chromosome microarray analysis (CMA) in clinical practice, the accurate identification and characterization of submicroscopic deletions/duplications (copy number variants, CNVs) associated with ASD was made possible. However, the widely acknowledged excess of males on the autism spectrum reflects on a paucity of CMA studies specifically focused on females with ASD (f-ASD). In this framework, we aim to evaluate the frequency of causative CNVs in a single-center cohort of idiopathic f-ASD. Among the 90 f-ASD analyzed, we found 20 patients with one or two potentially pathogenic CNVs, including those previously associated with ASD (located at 16p13.2 16p11.2, 15q11.2, and 22q11.21 regions). An exploratory genotype/phenotype analysis revealed that the f-ASD with causative CNVs had statistically significantly lower restrictive and repetitive behaviors than those without CNVs or with non-causative CNVs. Future work should focus on further understanding of f-ASD genetic underpinnings, taking advantage of next-generation sequencing technologies, with the ultimate goal of contributing to precision medicine in ASD.
The effects of environmental factors [including Socio-Economic Status, Cultural Capital, and Social Capital (Socio-Cultural Level) of both parents] on the Vineland-II adaptive behavior dimensions of toddlers with autism spectrum disorder (ASD), in addition to individual factors, was investigated in 148 Italian toddlers (82% males), aged 18 to 37 months with ASD. Toddlers’ age and Griffiths Mental Development Scales general development affected all of the adaptive behavior dimensions, with negative and positive associations, respectively. The Child Behavior Checklist comorbid conditions were negatively associated with some adaptive behavior dimensions while the ADOS-2 Social affect only with the communication dimension. Mothers’ and fathers’ specific Socio-Cultural Level dimensions were positively associated with toddlers’ specific adaptive behavior dimensions with the same magnitude as comorbid conditions.
Aim: To detect early-life environmental factors leading to DNA methylation changes of autism spectrum disorder (ASD)-related genes in young ASD females and reveal epigenetic biomarkers of disease severity. Materials & methods: We investigated blood methylation levels of MECP2, OXTR, BDNF, RELN, BCL2, EN2 and HTR1A genes in 42 ASD females. Results: Maternal gestational weight gain correlated with BDNF methylation levels (Bonferroni-corrected p = 0.034), and lack of folic acid supplementation at periconception resulted in higher disease severity in the ASD children (Bonferroni-corrected p = 0.048). RELN methylation levels were inversely correlated with disease severity (Bonferroni corrected p = 0.042). Conclusion: The present study revealed gene–environment interactions and potential epigenetic biomarkers of disease severity in ASD females.
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