Format

Send to

Choose Destination
Depress Anxiety. 2008;25(8):680-8. doi: 10.1002/da.20444.

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

Author information

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

Abstract

BACKGROUND:

Some symptom dimensions in obsessive-compulsive disorder (OCD) patients have a familial and putative genetic foundation, based on replicated findings in studies of sib-pairs with OCD. However, these symptom dimensions are all from exploratory factor analyses of Yale-Brown Obsessive-Compulsive Scale Symptom Checklist ratings based on non-empirically derived symptom categories, rather than individual symptoms.

METHODS:

In this study, we used a novel latent variable mixture model analysis to identify meaningful patient subgroupings. This was preceded by a confirmatory factor analysis of a 65-item OCD symptom inventory from 398 OCD probands, which yielded a five-factor solution. Data from all five symptom factors were used in a latent variable mixture model analysis, which identified two statistically separate OCD subpopulations.

RESULTS:

One group of probands had a significantly higher proportion of OCD-affected afflicted relatives (parents or close parental relatives), whereas the other group had a less prevalent familial OCD. The group with the more familial OCD was also found to have an earlier age of OCD onset, more severe OCD symptoms, and greater psychiatric comorbidity and impairment.

CONCLUSIONS:

Especially if the results are verified in other samples, this research paradigm, which identified characteristics of individuals with familial OCD, should prove useful in carrying out genome-wide linkage and association studies of OCD and may provide a model for other symptom-based studies of additional medical disorders.

PMID:
18729144
PMCID:
PMC2730946
DOI:
10.1002/da.20444
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Wiley Icon for PubMed Central
Loading ...
Support Center