Clinical and genetic evaluation of a family showing both autism and epilepsy

Untargeted urine metabolomics and machine learning provide potential metabolic signatures in children with autism spectrum disorder

Background

Complementary to traditional biostatistics, the integration of untargeted urine metabolomic profiling with Machine Learning (ML) has the potential to unveil metabolic profiles crucial for understanding diseases. However, the application of this approach in autism remains underexplored. Our objective was to delve into the metabolic profiles of autism utilizing a comprehensive untargeted metabolomics platform coupled with ML.

Methods

Untargeted metabolomics quantification (UHPLC/Q-TOF-MS) was performed for urine analysis. Feature selection was conducted using Lasso regression, and logistic regression, support vector machine, random forest, and extreme gradient boosting were utilized for significance stratification. Pathway enrichment analysis was performed to identify metabolic pathways associated with autism.

Results

A total of 52 autistic children and 40 typically developing children were enrolled. Lasso regression identified ninety-two urinary metabolites that significantly differed between the two groups. Distinct metabolites, such as prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, were revealed to be associated with autism through the application of four different ML methods (p<0.05). The alterations observed in the phosphatidylinositol and inositol phosphate metabolism pathways were linked to the pathophysiology of autism (p<0.05).

Conclusion

Significant urinary metabolites, including prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, exhibit associations with autism. Additionally, the involvement of the phosphatidylinositol and inositol phosphate pathways suggests their potential role in the pathophysiology of autism.

MLPA analysis in a cohort of patients with autism

Background

Autism is a global neurodevelopmental disorder which generally manifests during the first 2 years and continues throughout life, with a range of symptomatic variations. Epidemiological studies show an important role of genetic factors in autism and several susceptible regions and genes have been identified. The aim of our study was to validate a cost-effective set of commercial Multiplex Ligation dependent Probe Amplification (MLPA) and methylation specific multiplex ligation dependent probe amplification (MS-MLPA) test in autistic children refered by the neurodevelopmental center and autism unit of a Paediatric Hospital.

Results

In this study 150 unrelated children with autism spectrum disorders were analysed for copy number variation in specific regions of chromosomes 15, 16 and 22, using MLPA. All the patients had been previously studied by conventional karyotype and fluorescence in situ hybridization (FISH) analysis for 15(q11.2q13) and, with these techniques, four alterations were identified. The MLPA technique confirmed these four and identified further six alterations by the combined application of the two different panels.

Conclusions

Our data show that MLPA is a cost effective straightforward and rapid method for detection of imbalances in a clinically characterized population with autism. It contributes to strengthen the relationship between genotype and phenotype of children with autism, showing the clinical difference between deletions and duplications.

The neurobiology of lipid metabolism in autism spectrum disorders

Autism is a neurodevelopmental disorder characterized by impairments in communication and reciprocal social interaction, coupled with repetitive behavior, which typically manifests by 3 years of age. Multiple genes and early exposure to environmental factors are the etiological determinants of the disorder that contribute to variable expression of autism-related traits. Increasing evidence indicates that altered fatty acid metabolic pathways may affect proper function of the nervous system and contribute to autism spectrum disorders. This review provides an overview of the reported abnormalities associated with the synthesis of membrane fatty acids in individuals with autism as a result of insufficient dietary supplementation or genetic defects. Moreover, we discuss deficits associated with the release of arachidonic acid from the membrane phospholipids and its subsequent metabolism to bioactive prostaglandins via phospholipase A(2)-cyclooxygenase biosynthetic pathway in autism spectrum disorders. The existing evidence for the involvement of lipid neurobiology in the pathology of neurodevelopmental disorders such as autism is compelling and opens up an interesting possibility for further investigation of this metabolic pathway.