Deciphering the Autism Spectrum Disorder Beyond Genomics

Deciphering the Autism Spectrum Disorder Beyond Genomics: AI Learning for Whole Exome Sequencing, Metabolomics and Phenotype

The investigators propose to study the molecular etiology of autism spectrum disorder(ASD) from a genomic, metabolomics and network biology perspective by combining data of gene expression, sequence variations and metabolism conditions of patients with ASD. As the complexity of ASD, the investigators consider both science-based and clinic-based measurements to ensure no missing of any relevant domain of the complex relations. In addition to the collection of biological factors, the investigators will also collect the comprehensive clinical, environmental, neurocognitive, MRI images to integrate the multiple factors into the matrix features. Finally the investigators will apply the machine learning to provide us the aspects of the underline pathway back into the other sample distribution published as the open dataset to verify and adjust the features in order to achieve satisfactory level of the reliability and stability of the algorithms. With Next Generation Sequencing (NGS) technology, the investigators will sequence the whole exome sequencing (WES) (MiSeq System) of approximately 120 ASD probands, 40 unaffecting siblings and 40 healthy controls of Taiwanese Han population to identify ASD-associated transcriptome profiles. The results will be using real-time PCR (qPCR) or conventional Sanger sequencing to verified. The investigators will use both liquid chromatography/time-of-flight mass spectrometry (LC-MS) and gas chromatography/quadrupole mass spectrometry (GC-MS) for a full assessment of a wide range of metabolites with over 820 metabolites. Hence, this 3-year proposal consists two main parts - the ASD transcriptome sequence analysis by NGS technology and the metabolomics study of ASD via LC-MS and GC-MS technology.

Study Overview

• Status: Completed
• Conditions: Autism Spectrum Disorder
• Intervention / Treatment: Other: Psychiatric diagnosis

Detailed Description

Primary Aim: To establish a stable and reliable neurogenesis molecular level pathways and potential pathogenesis mechanisms for ASD by using the machine learning approach of the integrated data of biological variables (NGS data and metabolomics) and the comprehensive clinical, environmental, neurocognitive, and MRI images data.

1. To investigate the majority of candidate risk factors from the multiple domains collected in this project;
2. To apply network-based algorithms (including deep learning) to approach the underlining pathogenesis mechanism of ASD;
3. To further verify the machine learning algorithm based on the data collected in this project through other open access database for stability and reliability of our algorithm.

Secondary Aims:

Aim I: To identify the ASD biomarkers and disease mechanism using NGS technology.

1. To investigate the transcriptome profiles occurring in ASD patients;
2. To identify ASD-associated exome sequence variations from a network biology perspective;
3. To identify ASD-associated gene-gene interaction sub-networks; and
4. To explore how the sequencing outcomes, regulate and interact with brain structure and function even linking to neuropsychological functions and behavioral phenotypes.

Aim II: To characterize ASD-affected metabolites.

1. By using LC-MS and GC-MS, we will perform metabolomics analysis, including targeted and untargeted analysis;
2. To identify the potential metabolomics profiles and pathways related to behavioral phenotypes, neuropsychological functions, neuroanatomy and brain functions in patients with ASD; and
3. To identify how the metabolites variance distributions are manipulated through the genetic expressions.

• Study Type: Observational
• Enrollment (Actual): 200

Contacts and Locations

Study Locations

• Taiwan
  • Taipei, Taiwan
    • National Taiwan Univeristy Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 3 years to 20 years (Child, Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

This study will recruit (1) 120 patients with clinical diagnosis of ASD according to the DSM-5 diagnostic criteria for the transcriptome NGS and the metabolites profiles from the Children's Mental Health Center at National Taiwan University Hospital (NTUH); (2) 40 unaffected siblings (SIB) of ASD probands; and (3) 40 healthy age/gender-matched TD controls according to age and neighborhood distribution of the ASD group after interviewed by the Chinese K-SADS-E-DSM-5.

Description

Inclusion Criteria:

• a clinical diagnosis of ASD defined by the DSM-5 made by board-certificated child psychiatrists at the first visit and following visits
• ages range from 3 to 20
• at least one biological parent
• parents that are both Taiwanese
• subjects and their biological parents consent to participate in this study for complete phenotype assessments and blood withdraw for this study.

Exclusion Criteria:

• schizophrenia
• schizoaffective disorder
• organic psychosis.
• Probands with fragile X, intellectual disability, epilepsy, ADHD, and autoimmune diseases will be noted.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
ASD group; 120 patients with clinical diagnosis of ASD according to the DSM-5 diagnostic criteria	Other: Psychiatric diagnosis; Kiddie Schedule for Affective Disorders & Schizophrenia (K-SADS) for DSM-5
Unaffected siblings of ASD; 40 unaffected siblings of ASD probands	Other: Psychiatric diagnosis; Kiddie Schedule for Affective Disorders & Schizophrenia (K-SADS) for DSM-5
TD group; 40 healthy age/gender-matched TD controls according to age and neighborhood distribution of the ASD group after interviewed by the Chinese K-SADS-E-DSM-5	Other: Psychiatric diagnosis; Kiddie Schedule for Affective Disorders & Schizophrenia (K-SADS) for DSM-5

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
ASD-associated transcriptome profiles	With Next Generation Sequencing (NGS) technology, the investigators will sequence the whole exome sequencing (WES) (MiSeq System) of approximately 120 ASD probands, 40 unaffecting siblings and 40 healthy controls of Taiwanese Han population to identify ASD-associated transcriptome profiles.	Baseline

Collaborators and Investigators

• Sponsor: National Taiwan University Hospital

Study record dates

Study Major Dates

• Study Start (Actual): August 1, 2018
• Primary Completion (Actual): December 31, 2021
• Study Completion (Actual): December 31, 2021

Study Registration Dates

• First Submitted: September 17, 2018
• First Submitted That Met QC Criteria: September 17, 2018
• First Posted (Actual): September 19, 2018

Study Record Updates

• Last Update Posted (Actual): September 26, 2022
• Last Update Submitted That Met QC Criteria: September 23, 2022
• Last Verified: September 1, 2022

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Mental Disorders; Neurodevelopmental Disorders; Autistic Disorder; Autism Spectrum Disorder; Child Development Disorders, Pervasive
• Other Study ID Numbers: 201801044RINC

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No