Identifying Potential Biomarkers for Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex, heterogeneous, neurodevelopmental disorder characterized by core symptoms that include social interaction deficits and language difficulties. Consequently, this has created hurdles in not only understanding the disorder, but also in developing effective drug treatments. Our goal is to apply a blend of Omic approaches to blood collected from a large and well phenotyped cohort of ASD individuals to identify biomarkers that will help address our research objectives. Blood samples drawn will be used to prepare the matrices (DNA, plasma, serum and PBMCs) required for the different objectives of the study. Next generation sequencing technologies including whole genome sequencing will be used to identify gene variants associated with ASD and controls. RNA sequencing will be used to identify total RNA as well as specific non-coding RNAs as biomarkers to better understand the ASD heterogeneity. Proteomics, using the Olink platform and Sengenics Immunome Protein Array will be used to screen blood samples to identify novel biomarkers (proteins and autoantibodies). Metabolomics profiling will also be used to screen blood samples to identify novel metabolomics signatures of ASD. From this study we will identify and validate molecular biomarkers for early diagnosis of ASD. These markers will facilitate the development of clinical targets for early intervention to prevent, delay, or reduce the severity of the disorder.

Hamad Bin Khalifa University (HBKU)