Precise Objective Automated Assessment System of Autism Spectrum Disorder From an Existing Big Cohort

Overview

The project's significance includes a big cohort of Autism spectrum disorder (ASD), originality/novelty (new approaches and technologies including next-generation sequencing, multi-echo functional MRI, metabolomics, microbiomics, and machine learning), and the integration of multi-dimentional measures. With the accomplishment of this project, we will establish the most comprehensive ASD bio-bank in Asia, develop ASD NGS panel, identify several ASD biomarkers, publish at least 15 SCI papers in total, and in the end, have patents registration and technology transfer of our precise objective, automated assessment system for ASD. Our findings will further advance our understanding of ASD, ultimately contribute to the early detection, diagnosis, and treatment of ASD, and be the first step of precise medicine for ASD.

Autism spectrum disorder (ASD) is a common highly heritable neurodevelopmental disorder with high genetic and clinical heterogeneity. Due to its high prevalence, long-term impairment, unclear etiologies, and a lack of effective detection, prevention and biological treatment for this disorder, this catastrophic disorder has been prioritized for molecular genetic and brain research. The main PI Gau has established a cohort of more than 900 ASD probands and their families with clinical, neuropsychological, image, and genetic data. With the advance in digit health, this integrated project aims to develop and potentially commercialize an objective, automated assessment system for early diagnosis of ASD based on the clinical, behavioral, neuropsychological, neuroimaging, genetic (whole exome sequencing, WES), metabolomics, and microbiomics data of probands with ASD and typically developing controls(TDC) without ASD This 3-year, 5 subprojects (SP) project is based on an existing big cohort of \> 900 ASD probands and their families with high-quality genetic data, clinical diagnoses, symptoms, psychopathology, social functions, neuropsychological functions (n= 600 for CPT, 300 for CANTAB), and structural and functional images (n=196), data. Due to a limited budget, SP1 will only select 360 ASD (ages 4-25 years old) and 90 TDC for this integrated project. SP1 will check the quality and presence of the data followed by recollecting DNAs of 100 ASD, MRI data of 205 ASD (360-196=164, 164/0.8(successful rate)=205), and CANTAB of 60 ASD to have a complete dataset of clinical/phenotype/neurocognition/image measures. SP1 will prepare DNAs for SP2's WES analyses; and will collect serum and stool of 360 ASD and 90 TDC and provide these samples to SP3 and SP4 for metabolomics and microbiomics analyses, respectively. All the data collected and results generated from SP1-4 will be saved and managed in the ASD bank (SP1, main PI) and analyzed by SP5 using AI machine learning to develop the precise objective automatic assessment platform for ASD. The topics of the five subprojects: Subproject 1. Establishing the standard procedure for data collection and clinical-biological bank of autism spectrum disorder including clinical, behavioral, cognitive, neuroimaging, genetic, and biological data Subproject 2. Deciphering genetic cause in autistic spectrum disorder using whole exome sequencing Subproject 3. Metabolomics investigation of Autism Spectrum Disorder Subproject 4. Intestinal microbiota and disease outcome in children with autism spectrum disorder Subproject 5. A computerized assessment system from genome, gut-brain, and metabolic mechanisms