Molecular subtyping of autism spectrum disorder using blood DNA methylation

Investigation of autism spectrum disorder subtypes using blood DNA methylation analysis - ASD blood DNA methylation study

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000060271

Enrollment

968

Registered

2026-01-06

Start date

2024-04-04

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Autism spectrum disorder

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Individuals aged 4-18 years with autism spectrum disorder and controls included in the Simons Simplex Collection within the NIMH Data Archive, for whom blood DNA methylation data and relevant clinical information are available.

Exclusion criteria

Exclusion criteria: Individuals lacking blood DNA methylation data or essential clinical information in the database.

Design outcomes

Primary

Measure	Time frame
Identification of molecular subtypes of ASD by clustering based on blood DNA methylation data (at the time of analysis)	—

Secondary

Measure	Time frame
Identification of differentially methylated probes (DMPs) between subtypes with FDR correction Functional/pathway analyses based on genes proximal to DMPs (e.g., GO analysis, Ingenuity Pathway Analysis) Estimation of blood cell-type proportions using a reference-based method (e.g., GLINT) and their association with subtypes Associations between subtypes and clinical phenotypes (ADI-R, ADOS, IQ, adaptive behavior, perinatal history, comorbidities, etc.) Development of an AI-based prediction model for subtype classification	—

Measure

Time frame

Identification of differentially methylated probes (DMPs) between subtypes with FDR correction Functional/pathway analyses based on genes proximal to DMPs (e.g., GO analysis, Ingenuity Pathway Analysis) Estimation of blood cell-type proportions using a reference-based method (e.g., GLINT) and their association with subtypes Associations between subtypes and clinical phenotypes (ADI-R, ADOS, IQ, adaptive behavior, perinatal history, comorbidities, etc.) Development of an AI-based prediction model for subtype classification

—

Countries

Japan

Contacts

Public ContactNoritaka Ichinohe

National Center of Neurology and Psychiatry Department of Ultrastructural Research, National Institute of Neuroscience

nichinohe72@gmail.com0423461719

Outcome results