Cranio-Facial Characteristics in Autism Spectrum Disorder: A Scoping Review

Autism spectrum disorders (ASD) consist of a complex group of neurodevelopmental disorders characterised by qualitative impairments of social interactions, communication abilities, and a limited, stereotyped, and repetitive selection of interests and activities. In light of the imperative to identify a possible biomarker for ASD, it has been determined that craniofacial anomalies serve as significant risk factors for neurodevelopmental disorders. The aim of this scoping review is to deepen the knowledge of the scientific literature related to cranio-facial characteristics in individuals with ASD, with a particular focus on recent research advancements. The review was performed by employing the search strings (("Autism Spectrum Disorder" OR autism OR ASD OR "Autism Spectrum") AND ("facial morphology" OR "facial phenotype")) on the databases PubMed/MEDLINE, Scopus, and ERIC as of March 9, 2023. The review comprised seven studies whose findings were obtained through quantitative analysis of Euclidean distances between anatomical landmarks. The examination of facial abnormalities represents a possible reliable diagnostic biomarker that could aid in the timely identification of ASD. Phenotypic characteristics that may serve as predictive indicators of the severity of autistic symptoms can be observed in certain individuals with ASD by applying anthropometric and instrumental measurements. The presence of a phenotype characterised by an increased intercanthal distance and a reduced facial midline height appears to be associated with a higher degree of severity in autistic symptoms. In addition, it is worth noting that facial asymmetry and facial masculinity can be considered reliable indicators for predicting a more severe manifestation of symptoms

Behavioral aspects in children's brothers affected by Autism Spectrum Disorders

Introduction: Autistic Spectrum Disorder (ASD) is a permanent and complex disability arising within the first three years of life characterized by a socio-communicative disorder and by fixed interests and repetitive behaviors. The present pilot study aims to evaluate behavioral aspects in a small population of siblings of ASD children. Material and methods: Population: 5 school-aged children (2 males, 3 females) (mean age 9.235 ± 2.041) were enrolled, as siblings of ASD children, and for comparison, 12 healthy (7 males, 5 females) children (average age 9,528 ± 3,351). All subjects underwent evaluation of the behavioral with Child Behavior Checklist (CBCL) scale. Results: The two groups were statistically comparable by age (p = 0.86) and gender distribution (p = 0.87). From the behavioral point of view evaluated with the CBCL scale, siblings of ASD have a higher degree of overall problem (Total problems) compared to control children (p=0.003), in addition they have significantly higher scores in the subscales of behavior examined (Anxious/Depressed, Withdrawn, Somatic Complaints, Social, Thought, Attention, Delinquent, Aggressive) as well as a greater share of disturbances both internalizing (p=0.004) and externalizing (p = 0.007) (Table 1). Conclusions: The present preliminary data confirm the need for a global management of the entire family structure for the correct management of Autistic Disorders

ADDICTIONS SUBSTANCE FREE DURING LIFESPAN

The addictions substance free is an umbrella definition comprises internet addiction, sexual addiction, gambling pathological, workholism, videogames and computer addiction. Actually, the technological addictions is frequent in young adolescents. The term Digital Natives indicates the children born in an information system of learning and communication different from that of the generations previous. This temporal range was strongly characterized by growing presence of technological communication toolsin daily life. The effects of hyper-exposition to technological tools tend to create a relational virtuality without a body is born,therefore, already within the family ties and during adolescence he moved to the digital socialization network. The technological object it interacts between the adolescent and the world of peers and adults, becoming the facilitator object that as the psychotropic substance, it conveys new modes of communicatio

Xq27 FRAXA locus is a strong candidate for dyslexia: evidence from a genome-wide scan in French families.

Dyslexia is a frequent neurodevelopmental learning disorder. To date, nine susceptibility loci have been identified, one of them being DYX9, located in Xq27. We performed the first French SNP linkage study followed by candidate gene investigation in dyslexia by studying 12 multiplex families (58 subjects) with at least two children affected, according to categorical restrictive criteria for phenotype definition. Significant results emerged on Xq27.3 within DYX9. The maximum multipoint LOD score reached 3,884 between rs12558359 and rs454992. Within this region, seven candidate genes were investigated for mutations in exonic sequences (CXORF1, CXORF51, SLITRK2, FMR1, FMR2, ASFMR1, FMR1NB), all having a role during brain development. We further looked for 50 UTR trinucleotide repeats in FMR1 and FMR2 genes. No mutation or polymorphism co-segregating with dyslexia was found. This finding in French families with Dyslexia showed significant linkage on Xq27.3 enclosing FRAXA, and consequently confirmed the DYX9 region as a robust susceptibility locus. We reduced the previously described interval from 6.8 (DXS1227–DXS8091) to 4 Mb also disclosing a higher LOD score

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. Aims of this study were to characterize a metabolic signature of ASD, and to evaluate multi-platform analytical methodologies in order to develop predictive tools for diagnosis and disease follow up. Urines were analyzed using: 1H- and 1 H-13C-NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on a HILIC and C18 chromatography column). Data tables obtained from the six analytical modalities on a training set of 46 urines (22 autistic children and 24 controls) were processed by multivariate analysis (OPLS-DA). Prediction of each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and ROC curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLSDA model showed an enhanced performance (R 2Y(cum)=0.88, Q 2 (cum)=0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC=0.91, p-value 0.006). Metabolites that are most significantly different between autistic and control children (p<0.05) are indoxyl sulfate, N-\u2329-Acetyl-L-arginine, methyl guanidine and phenylacetylglutamine. This multi-modality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population