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Signal Attenuation as a Rat Model of Obsessive Compulsive Disorder

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Predicting genetic loading from symptom patterns in obsessive- compulsive disorder: a latent variable analysis.

Carmi Schooler¹, Andrew J Revell, Kiara R Timpano

¹Section on Socio-Environmental Studies, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland 20892-8408, USA. carmi.schooler@nih.gov

Depression and Anxiety

|August 30, 2008

Summary

This summary is machine-generated.

Researchers identified two distinct obsessive-compulsive disorder (OCD) subpopulations using latent variable mixture modeling. One group exhibited more familial OCD, earlier onset, and greater severity, aiding genetic studies.

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Area of Science:

Psychiatry
Genetics
Computational Biology

Background:

Familial and genetic factors influence some obsessive-compulsive disorder (OCD) symptom dimensions.
Previous studies relied on exploratory analyses of symptom categories, not individual symptoms.

Purpose of the Study:

To identify meaningful patient subgroupings in obsessive-compulsive disorder (OCD).
To utilize a novel latent variable mixture model for subgroup identification.

Main Methods:

Confirmatory factor analysis of a 65-item OCD symptom inventory from 398 probands.
Latent variable mixture model analysis using five symptom factors to identify OCD subpopulations.

Main Results:

Two statistically separate OCD subpopulations were identified.
One subpopulation showed a significantly higher proportion of affected relatives and earlier onset.
This group also presented with more severe OCD symptoms, psychiatric comorbidity, and impairment.

Conclusions:

This research paradigm identified characteristics of individuals with familial OCD.
Findings may aid genome-wide linkage and association studies for OCD.
The approach may serve as a model for other symptom-based medical disorder studies.