A principal components analysis of the Autism Diagnostic Interview-Revised

Area of Science:

• Psychiatry
• Genetics
• Developmental Psychology

Background:

• The Autism Diagnostic Interview-Revised (ADI-R) is a key tool for diagnosing autism spectrum disorder (ASD).
• Identifying genetically relevant components of the autism phenotype is crucial for etiological research.
• Existing ADI-R data requires analysis to extract distinct, valid phenotypic factors.

Purpose of the Study:

• To develop and validate factors from the ADI-R that represent separate, genetically relevant components of the autism phenotype.
• To ensure these factors correlate with standard measures of relevant constructs.
• To assess the utility of these factors in genetic studies.

Main Methods:

• Principal components analysis (VARCLUS) was applied to ADI-R data from 292 individuals with autism.
• Resulting variable clusters were validated against established measures of related constructs.
• Internal consistency, face validity, discriminant validity, and construct validity were assessed.

Main Results:

• Six distinct clusters of variables emerged: spoken language, social intent, compulsions, developmental milestones, savant skills, and sensory aversions.
• Five factors demonstrated significant correlations with validating measures.
• Factors exhibited good internal consistency and validity, with adequate sibling correlations for genetic studies.

Conclusions:

• The ADI-R data can be reliably clustered into distinct variables.
• These validated factors are genetically relevant and suitable for diverse research applications.
• The developed factors enhance the utility of the ADI-R in autism research.