Symptom dimensions in OCD: item-level factor analysis and heritability estimates

Behav Genet. 2010 Jul;40(4):505-17. doi: 10.1007/s10519-010-9339-z. Epub 2010 Apr 2.

Abstract

To reduce the phenotypic heterogeneity of obsessive-compulsive disorder (OCD) for genetic, clinical and translational studies, numerous factor analyses of the Yale-Brown Obsessive Compulsive Scale checklist (YBOCS-CL) have been conducted. Results of these analyses have been inconsistent, likely as a consequence of small sample sizes and variable methodologies. Furthermore, data concerning the heritability of the factors are limited. Item and category-level factor analyses of YBOCS-CL items from 1224 OCD subjects were followed by heritability analyses in 52 OCD-affected multigenerational families. Item-level analyses indicated that a five factor model: (1) taboo, (2) contamination/cleaning, (3) doubts, (4) superstitions/rituals, and (5) symmetry/hoarding provided the best fit, followed by a one-factor solution. All 5 factors as well as the one-factor solution were found to be heritable. Bivariate analyses indicated that the taboo and doubts factor, and the contamination and symmetry/hoarding factor share genetic influences. Contamination and symmetry/hoarding show shared genetic variance with symptom severity. Nearly all factors showed shared environmental variance with each other and with symptom severity. These results support the utility of both OCD diagnosis and symptom dimensions in genetic research and clinical contexts. Both shared and unique genetic influences underlie susceptibility to OCD and its symptom dimensions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Cohort Studies
  • Data Interpretation, Statistical
  • Factor Analysis, Statistical*
  • Family* / psychology
  • Female
  • Genotype
  • Humans
  • Male
  • Models, Psychological
  • Obsessive-Compulsive Disorder / diagnosis*
  • Obsessive-Compulsive Disorder / genetics*
  • Obsessive-Compulsive Disorder / psychology
  • Phenotype
  • Principal Component Analysis
  • Psychometrics