Human genome meeting 2016

Human Genomics, 2016

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1186/s40246-016-0063-5
Data confidence 70 medium
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Abstract

ObjectivesFrom the first description by Leo Kanner [1], autism has been an enigmatic neurobehavioral phenomenon.The new genetic/genomic technologies of the past decade have not been as productive as originally anticipated in unveiling the mysteries of autism.The specific etiology of the majority of cases of autism spectrum disorder (ASD) is unknown, although numerous genetic/genomic variants and alterations of diverse cellular functions have been reported.Prompted by this failure, we have investigated whether the metabolomics approach might yield results which could simultaneously lead to a blood-based screening/diagnostic test and to treatment options. MethodsPlasma samples from a clinically well-defined cohort of 100 male individuals, ages 2-16+ years, with ASD and 32 age-matched typically developing (TD) controls were subjected to global metabolomic analysis. ResultsWe have identified more than 25 plasma metabolites among the approximately 650 metabolites analyzed, representing over 70 biochemical pathways, that can discriminate children with ASD as young as 2 years from children that are developing typically.The discriminating power was greatest in the 2-10 year age group and weaker in older age groups.The initial findings were validated in a second cohort of 83 children, males and females, ages 2-10 years, with ASD and 76 age and gender-matched TD children.The discriminant metabolites were associated with several key biochemical pathways suggestive of potential contributions of increased oxidative stress, mitochondrial dysfunction, inflammation and immune dysregulation in ASD.Further, targeted quantitative analysis of a subset of discriminating metabolites using tandem mass spectrometry provided a reliable laboratory method to detect children with ASD. ConclusionMetabolic profiling appears to be a robust technique to identify children with ASD ages 2-10 years and provides insights into the altered metabolic pathways in ASD, which could lead to treatment strategies.