Autism Spectrum DisorderNCT04873674
A Deep Learning Algorithm Platform to Predict Autism Diagnosis and Subtypes
An observational study of Autism Spectrum Disorder, run by National Taiwan University Hospital at 1 site in Taiwan.
Trial summary
This is the first human study on ASD microbiome with robust methodologies: prospective and sibling designs, metagenomics profiles, establishing an ASD multi-dimensional databank (clinic, behavior, neurocognition, brain imaging, metabolomics, and microbiome) collected using the same methodology and genetic biology… Read more about this study
- Who is it for?
- Ages 4 to 25 years
- Conditions the study is for
- Autism Spectrum Disorder
- What is being tested?
- ASD diagnosis and Psychiatric diagnosis
- How many people
- 420 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 May 2020to Apr 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 4 to 25 years
- All sexes
- No healthy volunteers
- Child, Adult
Study population: The sample includes 240 ASD (aged 4 to 25 years), 60~100 (estimated average 80) unaffected siblings (US), and 120 TDC. 240 ASD and 80 US, aged 4-25 will be recruited from the ASD follow-up cohort established by PI Gau's NHRI project or the Department of Psychiatry of all the branches of NTUH.
Who may be able to join
- ASD participants are (1) they have a clinical diagnosis of ASD defined by the DSM-5 criteria,1 made by board-certificated child psychiatrists and confirmed by the ADI-R/ADOS; (2) their ages range from 4 to 25; (3) both parents are Han Chinese; (4) they and their parents cooperate with all the assessments and stool and blood collection.
- Inclusion Criteria for US and TDC are (1) they do not reach the clinical diagnosis of ASD according to DSM-5 diagnostic criteria and the same criteria as described in the (2), (3), (4) and of Inclusion Criteria for ASD participants.
Who cannot join
- (1) comorbidity with DSM-5 diagnoses of schizophrenia, schizoaffective disorder, delusional disorder, other psychotic disorders, organic psychosis, schizotypal personality disorder, bipolar disorder, depression, severe anxiety disorders or substance use; (2) comorbidity with neurological or systemic disorders; and (3) having a first degree relative who may have ASD based on family history method assessment (the TDC group).
Trial locations and contacts
1 site in 1 country.
Taiwan1 site, 1 recruiting
- Recruiting
National Taiwan Univeristy Hospital
Taipei
Susan Shur-Fen Gau, MD, PhD, 886-2-23123456 ext. 66802, gaushufe@ntu.edu.tw
About this study
Official title: A Deep Learning Algorithm Platform to Predict Autism Diagnosis and Subtypes by Integrating Clinical, Cognitive, Imaging, Gut Microbiome, and Metabolome Data
This is the first human study on ASD microbiome with robust methodologies: prospective and sibling designs, metagenomics profiles, establishing an ASD multi-dimensional databank (clinic, behavior, neurocognition, brain imaging, metabolomics, and microbiome) collected using the same methodology and genetic biology simultaneously, and developing a deep learning platform for ASD diagnosis and prevention. With the accomplishment of this project, we anticipate establishing a web application for clinical and academic use. Our findings will further advance the knowledge in the pathogenetic mechanisms of ASD to enhance early detection, diagnosis, and treatment, subsequently contributing to precision medicine.
Read the detailed description
Due to the high prevalence (1% in Taiwan), long-lasting impairment, unclear etiologies, and a lack of effective detection, prevention, and biological treatment, autism spectrum disorder (ASD) has been prioritized for biomarker, mechanism, and treatment research. Recently the gut-brain-axis has been proved, mainly with animal models, to be altered in psychiatric disorders and notably in ASD. With PI Gau's long-term achievement in ASD multi-dimensional research and our preliminary finding of altered gut microbiota in ASD and their unaffected siblings, we propose this 4-year prospective large-scale study with sibling design and multi-dimensional measures (environmental, clinical, cognitive, imaging, gut microbiome, metabolome) to establish a deep learning algorithm platform for predicting ASD and searching potential biomarkers and probiotic treatment for ASD.
Specific Aims:
- To demonstrate the metagenomics profiles analysis based on the gut microbiome and metabolome of ASD patients, unaffected siblings, and typically developing controls (TDC).
- To investigate environmental factors such as pregnancy and birth history from the mother's medical records and interviews or national health insurance data, for the microbiome, metagenomics, and brain anatomy and function.
- To develop a deep learning algorithm platform using the environmental, behavioral/clinical phenotypes, neurocognitive/imaging endophenotypes, and metagenomics profiles to identify microbiota (metagenomics, too) makers and other predictors for ASD diagnosis, subtypes, and level of impairments.
- To establish a web application based on our deep learning algorithm platform for clinical use to assist medical doctors in diagnosing ASD.
- Conditions
- Autism Spectrum Disorder
- Being tested
- ASD diagnosis, Psychiatric diagnosis
- Medical subject headings
- Autism Spectrum Disorder
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ASD diagnosisOther
Autism Diagnostic Interview-revised (ADI-R) and Autism Diagnostic Observation Scale (ADOS)
Psychiatric diagnosisOther
Kiddie Schedule for Affective Disorders \& Schizophrenia (K-SADS) for DSM-5
| Study group | Role | What they receive |
|---|---|---|
| ASD group | 240 ASD patients (aged 4-25 years) Receives: Other: ASD diagnosis; Other: Psychiatric diagnosis | |
| Unaffected siblings of ASD | 60-100 unaffected siblings of ASD probands Receives: Other: Psychiatric diagnosis | |
| TD group | 120 age-, and sex matched TDC from the same geographic areas of the ASD group via referral by teachers, or advertisement at college or community. Receives: Other: Psychiatric diagnosis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Autism diagnostic interview (ADI-R)
Including reciprocal social interaction, communication, and repetitive behaviors and stereotyped patterns, for children with a mental age from about 18 months into adulthood
Measured: 4 hours
Neuropsychological functions: Continuous Performance Test(CPT)
The 4 dimensions of CCPT: focused attention, hyperactivity/impulsivity, sustained attention, and vigilance
Measured: 15 minutes
Neuropsychological functions: Cambridge Neuropsychological Test Automated Batteries(CANTAB)
The 4 main cognitive components of CANTAB: Visual Memory, Attention, Working and Planning Memory (Executive Functions), and Decision Making
Measured: 1.5 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 May 2021
- Study start1 May 2020
- Primary completionApr 2024 (estimated)
- Study completionApr 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Autism Spectrum DisorderStudies of the same condition, open and under way.
- More trials run by National Taiwan University HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Cross-sectional
- Enrolment
- 420 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Taiwan University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04873674
- Sponsor's protocol ID
- 202002086RIND
- Status last verified
- Oct 2023
- First submitted
- 29 Apr 2021
- Last updated
- 17 Oct 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Wang YC, Cheng CY, Wu CS, Lee CC, Gau SS. Clinical correlates of errors in machine-learning diagnostic model of autism spectrum disorder: Impact of sample cohorts. Autism. 2025 Dec;29(12):3083-3099. doi: 10.1177/13623613251360271. Epub 2025 Aug 5.
PubMed 40762098
Study at a glance
From the registry record, last updated by the sponsor on 17 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Deep Learning Algorithm Platform to Predict Autism Diagnosis and Subtypes by Integrating Clinical, Cognitive, Imaging, Gut Microbiome, and Metabolome Data
- ClinicalTrials.gov ID
- NCT04873674
- Acronym / sponsor ID
- 202002086RIND
- Conditions
- Autism Spectrum Disorder
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 420 participants (estimated)
- Lead sponsor
- National Taiwan University HospitalUniversity, hospital or other
- Study start
- 1 May 2020 (actual)
- Primary completion
- Apr 2024 (estimated)
- Study completion
- Apr 2024 (estimated)
- First posted
- 5 May 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is the first human study on ASD microbiome with robust methodologies: prospective and sibling designs, metagenomics profiles, establishing an ASD multi-dimensional databank (clinic, behavior, neurocognition, brain imaging, metabolomics, and microbiome) collected using the same methodology and genetic biology simultaneously, and developing a deep learning platform for ASD diagnosis and prevention. With the accomplishment of this project, we anticipate establishing a web application for clinical and academic use. Our findings will further advance the knowledge in the pathogenetic mechanisms of ASD to enhance early detection, diagnosis, and treatment, subsequently contributing to precision medicine.
Detailed description
Due to the high prevalence (1% in Taiwan), long-lasting impairment, unclear etiologies, and a lack of effective detection, prevention, and biological treatment, autism spectrum disorder (ASD) has been prioritized for biomarker, mechanism, and treatment research. Recently the gut-brain-axis has been proved, mainly with animal models, to be altered in psychiatric disorders and notably in ASD. With PI Gau's long-term achievement in ASD multi-dimensional research and our preliminary finding of altered gut microbiota in ASD and their unaffected siblings, we propose this 4-year prospective large-scale study with sibling design and multi-dimensional measures (environmental, clinical, cognitive, imaging, gut microbiome, metabolome) to establish a deep learning algorithm platform for predicting ASD and searching potential biomarkers and probiotic treatment for ASD.
Specific Aims:
- To demonstrate the metagenomics profiles analysis based on the gut microbiome and metabolome of ASD patients, unaffected siblings, and typically developing controls (TDC).
- To investigate environmental factors such as pregnancy and birth history from the mother's medical records and interviews or national health insurance data, for the microbiome, metagenomics, and brain anatomy and function.
- To develop a deep learning algorithm platform using the environmental, behavioral/clinical phenotypes, neurocognitive/imaging endophenotypes, and metagenomics profiles to identify microbiota (metagenomics, too) makers and other predictors for ASD diagnosis, subtypes, and level of impairments.
- To establish a web application based on our deep learning algorithm platform for clinical use to assist medical doctors in diagnosing ASD.
Study design
- Observational model
- Case-control
- Time perspective
- Cross-sectional
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| ASD group | – | Other: ASD diagnosis, Other: Psychiatric diagnosis240 ASD patients (aged 4-25 years) |
| Unaffected siblings of ASD | – | Other: Psychiatric diagnosis60-100 unaffected siblings of ASD probands |
| TD group | – | Other: Psychiatric diagnosis120 age-, and sex matched TDC from the same geographic areas of the ASD group via referral by teachers, or advertisement at college or community. |
Who may qualify
- Ages
- 4 to 25 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult
- Study population
- The sample includes 240 ASD (aged 4 to 25 years), 60~100 (estimated average 80) unaffected siblings (US), and 120 TDC. 240 ASD and 80 US, aged 4-25 will be recruited from the ASD follow-up cohort established by PI Gau's NHRI project or the Department of Psychiatry of all the branches of NTUH.
Key inclusion criteria (2 listed)
- ASD participants are (1) they have a clinical diagnosis of ASD defined by the DSM-5 criteria,1 made by board-certificated child psychiatrists and confirmed by the ADI-R/ADOS; (2) their ages range from 4 to 25; (3) both parents are Han Chinese; (4) they and their parents cooperate with all the assessments and stool and blood collection.
- Inclusion Criteria for US and TDC are (1) they do not reach the clinical diagnosis of ASD according to DSM-5 diagnostic criteria and the same criteria as described in the (2), (3), (4) and of Inclusion Criteria for ASD participants.
Key exclusion criteria (1 listed)
- (1) comorbidity with DSM-5 diagnoses of schizophrenia, schizoaffective disorder, delusional disorder, other psychotic disorders, organic psychosis, schizotypal personality disorder, bipolar disorder, depression, severe anxiety disorders or substance use; (2) comorbidity with neurological or systemic disorders; and (3) having a first degree relative who may have ASD based on family history method assessment (the TDC group).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ASD diagnosisAutism Diagnostic Interview-revised (ADI-R) and Autism Diagnostic Observation Scale (ADOS) | Other | ASD group |
| Psychiatric diagnosisKiddie Schedule for Affective Disorders \& Schizophrenia (K-SADS) for DSM-5 | Other | ASD group, TD group, Unaffected siblings of ASD |
Primary outcome
Autism diagnostic interview (ADI-R)
Time frame: 4 hours
Including reciprocal social interaction, communication, and repetitive behaviors and stereotyped patterns, for children with a mental age from about 18 months into adulthood
Neuropsychological functions: Continuous Performance Test(CPT)
Time frame: 15 minutes
The 4 dimensions of CCPT: focused attention, hyperactivity/impulsivity, sustained attention, and vigilance
Neuropsychological functions: Cambridge Neuropsychological Test Automated Batteries(CANTAB)
Time frame: 1.5 hours
The 4 main cognitive components of CANTAB: Visual Memory, Attention, Working and Planning Memory (Executive Functions), and Decision Making
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Oct 2023.
- Derived from this study: PubMed 40762098Wang YC, Cheng CY, Wu CS, Lee CC, Gau SS. Clinical correlates of errors in machine-learning diagnostic model of autism spectrum disorder: Impact of sample cohorts. Autism. 2025 Dec;29(12):3083-3099. doi: 10.1177/13623613251360271. Epub 2025 Aug 5.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Autism Spectrum Disorder, run by National Taiwan University Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 17 Oct 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Autism diagnostic interview (ADI-R) (time frame: 4 hours). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04873674, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Oct 2023.