Familiality of Factor Analysis-Derived YBOCS Dimensions in OCD-Affected Sibling Pairs from the OCD Collaborative Genetics Study

Familiality of Factor Analysis-Derived YBOCS Dimensions in OCD-Affected Sibling Pairs from the OCD Collaborative Genetics Study Gregor Hasler, Anthony Pinto, Benjamin D. Greenberg, Jack Samuels, Abby J. Fyer, David Pauls, James A. Knowles, James T. McCracken, John Piacentini, Mark A. Riddle, Scott L. Rauch, Steven A. Rasmussen, Virginia L. Willour, Marco A. Grados, Bernadette Cullen, O. Joseph Bienvenu, Yin-Yao Shugart, Kung-yee Liang, Rudolf Hoehn-Saric, Ying Wang, Jonne Ronquillo, Gerald Nestadt, and Dennis L. Murphy Background: Identification of familial, more homogenous characteristics of obsessive– compulsive disorder (OCD) may help to define relevant subtypes and increase the power of genetic and neurobiological studies of OCD. While factor-analytic studies have found consistent, clinically meaningful OCD symptom dimensions, there have been only limited attempts to evaluate the familiality and potential genetic basis of such dimensions. Methods: Four hundred eighteen sibling pairs with OCD were evaluated using the Structured Clinical Interview for DSM-IV and the Yale–Brown Obsessive Compulsive Scale (YBOCS) Symptom Checklist and Severity scales. Results: After controlling for sex, age, and age of onset, robust sib–sib intraclass correlations were found for two of the four YBOCS factors: Factor IV (hoarding obsessions and compulsions (p ⫽ .001) and Factor I (aggressive, sexual, and religious obsessions, and checking compulsions; p ⫽ .002). Smaller, but still significant, familiality was found for Factor III (contamination/cleaning; p ⫽ .02) and Factor II (symmetry/ordering/arranging; p ⫽ .04). Limiting the sample to female subjects more than doubled the familiality estimates for Factor II (p ⫽ .003). Among potentially relevant comorbid conditions for genetic studies, bipolar I/II and major depressive disorder were strongly associated with Factor I (p ⬍ .001), whereas ADHD, alcohol dependence, and bulimia were associated with Factor II (p ⬍ .01). Conclusions: Factor-analyzed OCD symptom dimensions in sibling pairs with OCD are familial with some gender-dependence, exhibit relatively specific relationships to comorbid psychiatric disorders and thus may be useful as refined phenotypes for molecular genetic studies of OCD. Key Words: Comorbidity, endophenotypes, epidemiology, genetics, obsessive-compulsive disorder, symptom dimensions

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bsessive– compulsive disorder (OCD) is a neuropsychiatric condition characterized by recurrent, intrusive thoughts (obsessions) or repetitive behaviors that the individual feels driven to perform (compulsions). Individuals with OCD recognize that these thoughts and behaviors are excessive and unreasonable and attempt to suppress them. The From the Laboratory of Clinical Science (GS, JR, DLM), Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland; Department of Psychiatry and Human Behavior (AP, BDG, SAR), Brown Medical School, Butler Hospital, Providence, Rhode Island; Department of Psychiatry and Behavioral Sciences (JS, MAR, VLW, MAG, BC, OJB, Y-YS, K-yL, RH-S, YW, GN), Johns Hopkins University School of Medicine, Baltimore, Maryland; Department of Psychiatry (AJF, JAK), College of Physicians and Surgeons at Columbia University and the New York State Psychiatric Institute, New York City, New York; Psychiatric and Neurodevelopmental Genetics Unit (DP), Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts; Department of Psychiatry and Biobehavioral Sciences (JTM) and Division of Child and Adolescent Psychiatry (JP), School of Medicine, University of California—Los Angeles, Los Angeles, California; Psychiatric Neuroimaging Research Program and Obsessive Compulsive Disorders Program (SLR), Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts. Address reprint requests to Dennis L. Murphy, M.D., Laboratory of Clinical Science, Building 10, Room 3D41, 10 Center Drive, MSC 1264, NIMH, NIH, Bethesda, MD 20892; E-mail: [email protected]. Received February 27, 2006; revised May 17, 2006; accepted May 23, 2006.

0006-3223/07/$32.00 doi:10.1016/j.biopsych.2006.05.040

obsessions and compulsions cause marked distress, are timeconsuming, and significantly interfere with social and occupational functioning. According to the World Health Organization, OCD is among the 10 most disabling medical conditions (Murray and Lopez 1996). In many cases, symptoms first appear in childhood and early adolescence, and the majority of cases have onset before 20 years of age (Rasmussen and Eisen 1992). The lifetime prevalence of the disorder is estimated to be 1%– 4% in adults, based on population surveys in the United States and other countries (Angst et al 2004; Weissman et al 1994). There is substantial evidence for the heritability of OCD. Twin studies indicate that the concordance rate for OCD is greater in monozygotic twin pairs (80%– 87%) than in dizygotic twin pairs (47%– 50%; Carey and Gottesman 1981). In family studies of OCD, the disorder is found to be five- to sevenfold more frequent in relatives of cases than in relatives of control subjects (Hanna et al 2005; Nestadt et al 2000b; Pauls et al 1995). A complex segregation analysis provided evidence for a major gene effect and for other familial effects in OCD vulnerability and for important gender differences with respect to familial aggregation of OCD (Nestadt et al 2000a). Phenotypic heterogeneity is increasingly being recognized as a major impediment to the elucidation of the pathophysiology and etiology of neuropsychiatric disorders (Baer 1994; Hasler et al 2004; Korszun et al 2004). Although standard classification systems such as DSM-IV and ICD-10 regard OCD as a unitary nosological entity, there is increasing evidence that this severe and potentially disabling condition is phenotypically heterogeneous (Mataix-Cols et al 2005). Recognizing this heterogeneity, investigators have attempted to dissect the phenotype into BIOL PSYCHIATRY 2007;61:617– 625 © 2007 Society of Biological Psychiatry

618 BIOL PSYCHIATRY 2007;61:617– 625 subtypes such as “checkers” and “washers” (Khanna and Mukherjee 1992). Because OCD patients are rarely monosymptomatic, however, it has been difficult to recruit “pure” cases of OCD subtypes for genetic studies, and the possible familial aggregation of such potential clinical subtypes has not been demonstrated. Thus, success has been limited in relating these possible OCD subtypes to neurobiological and genetic factors. Other, more promising approaches to identify homogenous familial OCD subtypes have been proposed on the basis of age at onset (Nestadt et al 2000b), comorbid diagnoses (Nestadt et al 2003), and latent class analysis (Nestadt et al 2003). Factor analysis of psychiatric symptoms have been fruitful in the dissection of heterogeneous phenotypes in schizophrenia (Andreasen et al 1995), bipolar disorder (Cassidy et al 1998), and depression (Korszun et al 2004). In OCD, recent factor-analytic studies have found quite consistent and clinically meaningful symptom dimensions that have shown promise in segregation analysis (Alsobrook et al 1999), neuroimaging experiments (Mataix-Cols et al 2004; Rauch et al 1998; Saxena et al 2004) and genetic studies (Cavallini et al 2002). This study was conducted to evaluate sib–sib correlation of OCD symptom dimensions and evaluate the relationship of comorbid psychiatric conditions to these symptom dimensions. First, we identified OCD symptom dimensions by performing a factor analysis on a range of OCD symptom categories, following Leckman’s method (Leckman et al 1997), in a large, well-defined sample of affected sib pairs with OCD. Second, we analyzed correlations between siblings on the YBOCS symptom categories and the symptom dimensions derived from factor analysis, controlling for gender and age of symptom onset. Third, we evaluated the relationship of psychiatric comorbidity to these dimensions.

Methods and Materials Sample Data were derived from the OCD Collaborative Genetics Study (OCGS; Samuels et al 2006), with sites in six cities (Baltimore, Bethesda, Boston, Los Angeles, New York, and Providence) and headquarters at John Hopkins University School of Medicine. The OCGS targeted families with OCD-affected sibling pairs. Subjects were recruited into the study from outpatient and inpatient clinics, referrals from clinicians in the community, web sites, media advertisements, self-help groups, and referrals from the Obsessive Compulsive Foundation, including its annual conventions. To be considered affected, a subject had to meet lifetime DSM-IV OCD criteria. Probands were included if their first onset of obsessions or compulsions (or both) occurred before age 18 because the early-onset form of OCD appears more familial (Samuels et al 2006). Probands with schizophrenia, severe mental retardation, or OCD that occurred exclusively in the context of depression (secondary OCD) were excluded. Also excluded as probands were individuals with Tourette’s syndrome to maximize homogeneity toward a focus on OCD without additional complicating symptoms (or additional genes). Subjects had to be at least 7 years old to participate in the study. For our study, only data on affected sib pairs (excluding twins) were used (n ⫽ 418 individuals). Written, informed consent (or assent, for children under age 18, plus consent by their parent or legal guardian) to study procedures was obtained before the clinical interview. Subjects were compensated $50 for their participation. The protocol was approved by the institutional review board at each site. www.sobp.org/journal

G. Hasler et al Clinical Assessment Diagnostic assessments were conducted by psychiatrists or doctorate-level clinicians experienced with clinical evaluations, especially in the use of semistructured diagnostic instruments, informant interviews, and integrative diagnostic formulations in which the rationale for all diagnostic decisions is explicit. Before initiation of fieldwork, interviewers from sites met at Johns Hopkins for training (Samuels et al 2006). During fieldwork, interviewers at each site participated in regular case conferences under the supervising clinician. At each site, each case was reviewed independently by two expert diagnosticians who reviewed all case materials and completed a Diagnostic Assignment Checklist form. Any disagreements between the two diagnosticians regarding diagnoses or age of onset of diagnoses (within 2 years) were resolved between the two. Materials were then reviewed by one of the five consensus psychiatrists at JHU. Any disagreements between the sites and JHU were resolved before the case materials were edited and sent for data entry. Cases from all sites were included in the reliability exercises; comparisons were made between sites (Samuels et al 2006). The interrater reliability (kappa values) of definite diagnoses for the most prevalent clinical symptoms or disorders were as follows: .81 for obsessions, .88 for compulsions, .81 for OCD, .77 for separation anxiety disorder, 1.00 for panic disorder, .69 for social phobia, .64 for specific phobia, .60 for generalized anxiety disorder, and .82 for major depression (Samuels et al 2006). Examiners used the OCGS Assessment Package, modified and developed for the study, as a semistructured format for the evaluation of psychopathology (Samuels et al 2006). The OCD section was adapted from the Schedule for Affective Disorders and Schizophrenia—Lifetime Version (Mannuzza et al 1986) and includes 1) detailed screening questions; 2) the YBOCS Symptom Checklist (YBOCS-SC; Goodman et al 1989), refined to include the level of severity (i.e., categorical variables from 1 to 4 coding the amount of time and the level of distress during the worst period), together with the age of onset of each symptom; 3) the Yale–Brown Obsessive Compulsive Scale (YBOCS; Goodman et al 1989), to assess severity based on the amount of time, extent of interference, degree of distress, extent of resistance, and degree of control that the subject had over obsessions and compulsions during the worst episode); and 4) additional questions on onset, course, and history of treatment for these symptoms. A similar section was developed for assessing tics. The Structured Clinical Interview for DSM-IV (SCID; Spitzer et al 1992) was used for assessing other major Axis I diagnoses in adults, and the KSADS was used in children. A semistructured assessment protocol was used for assessing additional diagnoses of interest in OCD (e.g., pathological nail biting, pathological skin picking, trichotillomania). The Family Informant Schedule and Criteria (Mannuzza et al 1985) was used to obtain additional information about each subject from a knowledgeable informant. Examiners completed a narrative formulation for each case. The JHU Diagnostic Assignment Checklist was used to collate all the clinical information from a variety of sources (the semistructured direct interview, case formulation, informant interview, and medical records). The checklist presents logical algorithms with specified rules, allowing assignment of definite, probable, absent, or unknown for each disorder. All psychiatric diagnoses were made according to strict DSM-IV criteria (American Psychiatric Association 1994). If all criteria required for having the disorder were met, then a “definite” diagnosis was given. If any necessary criterion was clearly not met, then the diagnosis was considered “absent.” If

G. Hasler et al

Figure 1. Scree plot.

the diagnostician was uncertain about the necessary criterion and the majority of necessary criteria were present, then the diagnosis was made at the “probable” level. If the diagnosticians could not be sure of the presence or absence of a given diagnosis, it was recorded as “unknown” (Samuels et al 2006).

BIOL PSYCHIATRY 2007;61:617– 625 619 items and its familiality (Pinto et al., in preparation), which was first explored in a separate sample of individual OCD probands from a longitudinal study of OCD at Brown Medical School and Butler Hospital (Pinto et al., under review). Symptoms present at time of assessment, in the past, or both (i.e., lifetime symptoms) were coded as 1, and symptoms that were never present were coded as 0. Lifetime symptoms were summed for each category. Initial factors were extracted using the principal component method, and rotations were then performed by the PROMAX method because that method of oblique rotation is appropriate if the factors are expected to be correlated with each other (De Geus and Denys 2004), as here. Reanalysis using the VARIMAX method yielded closely similar results. We selected the number of meaningful factors on the basis of Cattell’s scree plot. As indicated in Figure 1, the two usual criteria for determining the number of factors to extract were in agreement, that is, the curve made an elbow toward less steep decline after the first four factors (Cattell’s scree test), and the eigenvalues were less than 1 after the first four factors. We also performed a parallel analysis, using 1,000 randomly generated datasets with 418 subjects and 13 variables, to address empirically whether the number of components we retained account for more variance than components derived from random data. Specifically we used a program developed by O’Connor (2000) to compare our study eigenvalues to the 95th percentile of the distribution of random data eigenvalues. The first five 95th-percentile random data eigenvalues were 1.37, 1.28, 1.21, 1.56, and 1.11, suggesting that our decision to retain four components was sound (i.e., when these eigenvalues are compared with the first five on our scree plot). A cluster analysis using Ward’s method also revealed a four-factor solution (Abramowitz et al 2003; Hasler et al 2005a; Figure 2).

Subject Characteristics We included 418 subjects from six sites who were from families containing a proband diagnosed with OCD and had at least one sibling recruited and diagnosed with OCD. The study sample included 173 pairs, 20 trios, and 3 quartets of siblings; 33% were men, and 67% were women. Most of the subjects (97%) were Caucasians. The mean age at assessment was 33.6 years (SD ⫽ 14.4), and 72 subjects were under age 18. The mean age of OCD onset was 8.7 years (SD ⫽ 6.1). The mean YBOCS severity score for obsessions was 12.8 (SD ⫽ 4.1), the mean severity score for compulsions was 12.8 (SD ⫽ 3.8) and the mean total severity score was 25.6 (SD ⫽ 6.9). For analyses on the familiality of clinical characteristics, we used all possible combinations of sib pairs from families with more than two members, resulting in a sample of 251 sib pairs. Data Analysis To evaluate whether this new, large sample of affected siblings with OCD would manifest a YBOCS-SC factor structure similar to those previously reported, factor analysis was performed on seven of the eight obsession categories and six of the seven compulsion categories using the method developed by Leckman and colleagues (Baer 1994; Leckman et al 1997; MataixCols et al 2005). The miscellaneous obsessions and compulsions categories were excluded from the analysis because previous studies have shown that these are not clearly associated with any of Leckman and colleagues’ four OCD symptom dimensions (Baer 1994; Leckman et al 1997). Another group of OCGS colleagues will report on a fresh factor analysis of the YBOCS-SC

Figure 2. Yale–Brown Obsessive Compulsive Scale (YBOCS) Symptom Checklist Cluster Analysis. For the cluster analysis, symptom scores were calculated for each of the symptom categories in the YBOCS Symptom Checklist. Ward’s method for partitioning the data was used to minimize within-groups variance and to maximize between-groups variance (Abramowitz et al 2003). Squared Euclidian distance was calculated as the similarity measure. Scores for each symptom category were standardized to correct for range differences within each category. The SPSS statistical package, version 12.0 (SPSS, Chicago, Illinois), was used to conduct the cluster analyses.

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620 BIOL PSYCHIATRY 2007;61:617– 625 Factor Analysis The principal component factor analysis of the 13 OCD symptom categories yielded a four-factor solution. The four factors accounted for 64.0% of the variance in the YBOCS-SC data, with the PROMAX rotated factor structure mirroring the solution of Leckman and colleagues (1997). Aggressive, sexual, religious, and somatic obsessions plus checking compulsions loaded highly on the first factor, accounting for 17.7% of the variance (ignoring other factors). The second factor included symmetry obsessions and repeating, counting, and ordering/ arranging compulsions, explaining 16.7% of the variance. Contamination obsessions and cleaning compulsions loaded highly on the third factor, accounting for 15.4% of the variance. The fourth factor reflected hoarding obsessions and compulsions, explaining 14.2% of the variance of the YBOCS-SC data. Internal consistency of summated factor scales was acceptable for all four factors (Cronbach alpha for Factor I, .66; Factor II, .62; Factor III, .76; Factor IV, .84). When factor intercorrelations were examined, Factors I, II, and III were all significantly related (rs between .1 and .2), whereas factor IV was only correlated with factor 2 (r ⫽ .20, p ⬍ .0001) and not the other factors. Familiality Analysis To estimate the familiality of OCD dimensions, we removed the effects of sex, age, and age of OCD symptom-onset to ensure that the results were not unduly influenced by such demographic characteristics (Korszun et al 2004; Wickham et al 2001). The SAS PROC MIXED (Littell et al 1996) procedure was used to fit a linear model with age and age at first onset of OCD symptoms as covariates and gender as a fixed effect. To correct for the effect of latent dependencies between sib pairs stemming from being in the same family, we included family as a random effect in the models (Littell et al 1996). The residuals were considered as continuous variables and used for further analysis (Korszun et al 2004). Intraclass correlations (ICC) were derived as (MSb – MSw)/(MSb ⫹ [k – 1]MSw), where MSb and MSw was mean squares between and within siblings, respectively, obtained using analysis of variance for the random effect models, and k was the number of subjects in the class (k ⫽ 2 for siblings). This approach is based on the original use of ICCs to evaluate sib–sib relationships splitting the total variance into within- and between-group variability (Fisher 1925). In families with more than two affected siblings, information from all possible pair combinations was used. Including the variable coding the site of the assessment as an additional random effect (Littell et al 1996) did not substantially change the sib–sib correlations. Consistent with the analytic plan for this study, four primary statistical tests evaluated the familiality of the Leckman and our four OCD symptom factors. Because the additional tests for the familiality of the separate symptom categories were exploratory and were not independent from the tests of the factors/dimensions, we did not correct for multiple testing in the statistical analyses of these. Comorbidity The sample of 418 affected siblings was tested for associations between the factor-analytically derived OCD symptom dimensions and psychiatric comorbidity. Associations were expressed as odds ratios derived from logistic regression with the comorbid psychiatric condition as the binary response variable and all four standardized OCD symptom factor scores as independent variables in the same model. Regression models were adjusted for gender. To correct for correlated observations within sibling www.sobp.org/journal

G. Hasler et al pairs, we used generalized estimating equations (Lipsitz et al 1991) implemented in SAS PROC GENMOD. Given the exploratory nature of this part of the analysis, we used a significance level of p ⬍ .01, without correcting for multiple comparisons.

Results Familiality of Clinical Characteristics Table 1 shows the intraclass correlations (ICC) between sibs for symptom factors and YBOCS symptom categories for the 418 individuals with OCD. Table 2 provides the PROMAX rotated factor structure that yielded four distinct factors used for the ICC analysis. Among these four OCD factors, Factor IV (hoarding obsessions and compulsions) showed the highest familiality (p ⫽ .001; Table 1). Both hoarding obsessions and hoarding compulsions contributed to the familiality of this factor. Factor I (aggressive, sexual, religious and somatic obsessions, and checking compulsions) was also familial (p ⫽ .002; Table 1), with religious and aggressive obsessions as the most familial YBOCS symptom categories and somatic obsessions as a non-familial symptom category. Factor II (obsessions of symmetry, and repeating, counting, and ordering/arranging compulsions) and Factor III (contamination obsessions and cleaning compulsions) showed relatively weak, albeit statistically significant, sib–sib correlations; none of the YBOCS symptom categories loading on these factors showed greater sib–sib correlations than the factors. Among general clinical characteristics, age of OCD onset showed a statistically significant, low sib–sib correlation (ICC ⫽ .13, p ⫽ .04). Severity of YBOCS-assessed obsessions (ICC ⫽ .014, p ⫽ .84) and compulsions (ICC ⫽ ⫺.025, p ⫽ .72) and total YBOCS severity scores (ICC ⫽ ⫺.008, p ⫽ .91) were clearly nonfamilial. Table 1. Familiality Based on Intraclass Correlations (ICC) of OCD Symptom Factors and Dimensions Between Siblings Adjusted for Age, Gender, and Age of OCD Symptom Onset

OCD Characteristic Factor I Religious obsessions Aggressive obsessions Sexual obsessions Checking compulsions Somatic obsessions Factor II Repeating rituals Obsessions of symmetry Ordering and arranging Counting compulsions Factor III Cleaning compulsions Contamination obsessions Factor IV Hoarding obsessions Hoarding compulsions

Frequency (Sum Score ⬎ 0) (%)

28.2 65.5 26.1 61.2 37.1 5.7 5.9 47.6 33.5 57.4 57.6 34.5 35.2

ICC (95% CI)

p Value

.200 (.072, .327) .205 (.078, .332) .178 (.051, .305) .125 (.001, .249) .127 (.002, .252) .101 (⫺.024, .226) .132 (.064, .576) .125 (.000, .250) .116 (⫺.010, .242) .077 (⫺.048, .202) .051 (⫺.074, .176) .147 (.021, .273) .129 (.003, .255) .116 (⫺.009, .241) .214 (.085, .344) .189 (.061, .317) .168 (.040, .296)

.002 .002 .006 .05 .05 .11 .04 .05 .07 .23 .42 .02 .04 .07 .001 .004 .01

CI, confidence interval; ICC, intraclass correlations; OCD, obsessive– compulsive disorder. ICCs of factors are printed in bold. Factor I: aggressive, sexual, religious and somatic obsessions, and checking compulsions; Factor II: obsessions of symmetry, and repeating, counting and ordering/arranging compulsions; Factor III: contamination obsessions and cleaning compulsions; Factor IV: hoarding obsessions and compulsions.

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G. Hasler et al Table 2. PROMAX Rotated Factor Structure of Obsessive–Compulsive Disorder Symptoms Factor Loading Symptom Category

Factor I Factor II Factor III Factor IV

Aggressive obsessions Contamination obsessions Sexual obsessions Hoarding obsessions Religious obsessions Obsessions of symmetry Somatic obsessions Cleaning compulsions Checking compulsions Repeating rituals Counting compulsions Ordering and arranging Hoarding compulsions Percentage of variance explained Internal consistencya

.77 .31 .66 .10 .63 .07 .53 .10 .61 .26 .19 .03 .03 17.7 .640

.16 .12 ⫺.04 .16 .07 .81 .22 .27 .28 .53 .50 .82 .19 16.7 .632

.16 .89 ⫺.09 .10 .23 .13 .36 .87 .32 .25 .20 .11 .08 15.4 .743

.08 .12 .02 .93 .01 .16 .15 .05 .05 .03 .12 .19 .93 14.2 .833

Robust loadings (ⱖ .50) are printed in bold. Factor I: aggressive, sexual, religious and somatic obsessions, and checking compulsions; Factor II: obsessions of symmetry, and repeating, counting and ordering/arranging compulsions; Factor III: contamination obsessions and cleaning compulsions; Factor IV: hoarding obsessions and compulsions. a Internal consistency was estimated by Cronbach’s alpha of the summated scales of the symptom categories with loadings ⬎ .5.

Limiting the sample to women only (121 female affected sib pairs) increased the familiality estimates (Factor I, ICC ⫽ .29, 95% CI: .10 to .48, p ⫽ .002; Factor II, ICC ⫽ .28, 95% CI: .09 to .46, p ⫽ .003; Factor III, ICC ⫽ .22, 95% CI: .04 to .45, p ⫽ .02; Factor IV, ICC ⫽ .26, 95% CI: .07 to .45, p ⫽ .007). The sample including only male sib pairs (n ⫽ 31 pairs) was too small for statistical analyses. In a secondary analysis, we summed the four distress ratings for each YBOCS-SC item [instead of the absent/present item coding] to yield a total score for each category. In this analysis, the factor analysis yielded the identical four-factor solution as shown in Table 2; Factor IV again appeared as the most familial factor (ICC ⫽ .32; 95% CI: .184 to .452; p ⬍ .001), followed by Factor I (ICC ⫽ .18, 95% CI: .05 to .31; p ⫽ .006), whereas distress on Factor II and Factor III were not familial. Comorbidity with Psychiatric Disorders Table 3 shows odds ratios derived from models for comorbid psychiatric disorders including all four OCD factors as independent variables. Comorbid psychiatric disorders showed relatively specific associations with OCD symptom dimensions. Factor I was positively related to affective disorders, certain anxiety disorders such as hypochondriasis and separation anxiety disorder, body dysmorphic disorder, and tic disorder. Factor II was positively associated with substance use and eating disorders. OCD-associated conditions such as grooming disorders did not show specific associations with OCD symptom dimensions. Correcting the sib–sib correlation of Factor I for bipolar I/II diagnoses, hypochondriasis, and tic disorder, which were associated with Factor I and showed high sib–sib associations (data not shown), led to a modest increase in the ICC (comorbidityadjusted ICC for Factor I ⫽ .23, p ⬍ .001).

Discussion There is increasing evidence that OCD, like other genetically complex neuropsychiatric disorders, is etiologically heteroge-

neous and that the identification of more homogeneous, familial subtypes might considerably increase the power of genetic studies in OCD (Angst et al 2004; Baer 1994; Hasler et al 2004; Mataix-Cols et al 2005; Miguel et al 2005; Nestadt et al 2000b; Pauls et al 1995; Rasmussen and Eisen 1992). Factor-analytic studies have consistently identified multiple symptom dimensions of OCD across obsessions and compulsions, as recently reviewed by Mataix-Cols and colleagues (2005). This study provides evidence for considerable familiality of Factors IV and I in a large-scale affected sib-pair sample with OCD. Familiality of symptom dimensions was generally higher when limiting the analyses to female subjects, particularly for Factor II. Controlling for other familial characteristics such as age of OCD symptom onset and certain comorbid psychiatric conditions did not substantially change the results. Overall severity of OCD symptoms as assessed by total YBOCS scores or YBOCS obsessions or compulsions was not familial, strongly supporting the utility of considering discrete OCD symptom cluster (rather than OCD as a unitary entity) in future investigations of OCD familiality and genetics, including genome scans and candidate gene association studies. Thus, this identification of symptom dimensions with familial, possibly genetic, etiologies opens up the potential for more homogenous phenotypic definitions for molecular genetic studies in OCD. Consistent with our inclusion of only familial cases of OCD with sib pairs as a selection criteria, the age of disease onset tended to be relatively early (as expected because only probands with an age of onset prior to 18 were selected; Nestadt et al 2000b; Pauls et al 1995). The mean worst-ever YBOCS score of 25 indicates that the majority of cases in the sample had substantial severity at least sometime in their illness. As previously described in the first report of clinical features in this sample, all specific types of obsessions and compulsions were prevalent and, on average, affected individuals experienced more than three different categories of obsessions and three different categories of compulsions (Samuels et al 2006). Most participants were female, consistent with typical survey response patterns (Eaton et al 1992), even though the genders are roughly equally affected in the population (Karno et al 1988). Factor analysis has been used in prior studies to evaluate obsessive– compulsive symptom dimensions that appear to be more homogenous than global OCD diagnosis (Baer 1994; Leckman et al 1997; Mataix-Cols et al 1999), and several recent brain imaging and genetic studies have provided evidence for the biological validity of these dimensions (Alsobrook et al 1999; Mataix-Cols et al 2004; Rauch et al 1998); however, there have only been a few studies evaluating the familiality of OCD symptom dimensions. Separating obsessions from compulsions, Nestadt and colleagues found that obsessions, overall, were more closely related to the familiality of OCD than were compulsions (Nestadt et al 2000b). Using Leckman’s four OCD symptom dimensions (Leckman et al 1997), two segregation analyses of extended families provided evidence for some within-family associations of a factor including aggressive, sexual, and religious obsessions, and checking compulsions (similar to our Factor I), and for a symmetry and ordering factor (similar to our Factor II) (Alsobrook et al 1999; Leckman et al 2003). Cavallini and associates found an association between the serotonin transporter gene 5HTTLPR polymorphism and the OCD symptom factor including counting and repeating rituals (similar to our Factor II), which reached statistical significance when the subgroup of OCD patients with comorbid tics was considered (Cavallini et al 2002), a result that was partially replicated in a www.sobp.org/journal

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Table 3. Prevalence of Comorbid Disorders and Their Associations with OCD YBOCS Symptom Factors (N ⫽ 418) OR (95% CI) Adjusted for Gender Variable Male gender Any affective disorder Major depression Bipolar I/II Dysthymia Any substance dependence Alcohol dependence Substance dependence Any eating disorder Anorexia nervosa Bulimia Any anxiety disorder Panic disorder Agoraphobia Social phobia Specific phobia Generalized anxiety disorder Hypochondriasis Posttraumatic stress disorder Separation anxiety disorder Tic disorder (DSM-IV) ADHD Body dysmorphic disorder Trichotillomania Skin picking Nail biting

Prevalence (%)

Factor I

Factor II

Factor III

Factor IV

33.3 69.0 67.3 7.0 14.1 19.1 16.1 9.4 1.4 6.2 5.0 79.5 21.0 16.3 42.6 38.9 45.8 7.7 9.8 23.5 5.9% 9.8% 11.5% 9.3% 26.0% 18.9%

1.0 (.8, 1.3) 1.5 (1.2, 1.8)a 1.6 (1.3, 2.0)b 1.8 (1.3, 2.4)b 1.2 (.9, 1.6) 1.0 (.8, 1.3) 1.2 (.9, 1.5) .8 (.6, 1.2) 1.3 (.9, 2.0) 1.1 (.6, 1.8) 1.8 (1.1, 3.0) 1.1 (.8, 1.4) 1.3 (1.1, 1.7) 1.3 (1.0, 1.6) 1.0 (.8, 1.2) 1.0 (.8, 1.3) 1.0 (.8, 1.3) 1.6 (1.2, 2.2)a 1.1 (.7, 1.6) 1.4 (1.1, 1.7)a 1.6 (1.1, 2.2)a 1.3 (.9, 2.0) 1.6 (1.2, 2.1)a 1.2 (.8, 1.5) 1.0 (.8, 1.2) 1.0 (.7, 1.2)

1.1 (.9, 1.4) 1.1 (09, 1.3) 1.1 (.9, 1.4) 1.3 (.9, 1.8) 1.1 (.8, 1.4) 1.3 (1.1, 1.7)a 1.4 (1.1, 1.8)a 1.5 (1.0, 2.1) 1.6 (1.2, 2.2)a 1.4 (1.0, 1.9) 2.2 (1.3, 3.8)a 1.1 (.8, 1.4) 1.0 (.8, 1.2) 1.3 (1.0, 1.6) 1.0 (.8, 1.2) 1.2 (1.0, 1.5) 1.0 (.8, 1.2) 1.2 (.8, 1.8) 1.0 (.7, 1.5) 1.1 (.9, 1.3) 1.1 (.7, 1.7) 1.8 (1.1, 2.7)a 1.0 (.7, 1.4) 1.2 (.9, 1.6) .9 (.7, 1.2) 1.2 (.9, 1.6)

1.0 (.8, 1.3) 1.1 (.8, 1.4) 1.1 (.8, 1.4) 1.0 (.6, 1.7) .9 (.7, 1.3) 1.0 (.7, 1.3) .8 (.6, 1.1) 1.2 (.8, 1.7) 1.2 (.9, 1.6) 1.2 (.8, 1.8) 1.0 (.6, 1.6) 1.3 (.9, 1.8) 1.3 (1.0, 1.6) 1.3 (1.0, 1.6) 1.0 (.8, 1.3) 1.1 (.8, 1.3) 1.1 (.9, 1.4) 1.3 (.9, 1.9) 1.3 (.9, 1.9) 1.4 (1.1, 1.6)a .8 (.5, 1.5) .7 (.5, 1.1) 1.0 (.7, 1.5) 1.2 (.8, 1.6) 1.1 (.9, 1.5) .7 (.5, .9)

1.0 (.8, 1.2) 1.1 (.9, 1.3) 1.0 (.8, 1.3) 1.1 (.8, 1.6) 1.3 (1.0, 1.7) .9 (.7, 1.2) .9 (.7, 1.2) 1.0 (.7, 1.3) .8 (.6, 1.2) 1.0 (.7, 1.4) .9 (.5, 1.4) 1.3 (1.0, 1.7) 1.1 (.9, 1.4) 1.0 (.7, 1.2) 1.3 (1.0, 1.6) 1.0 (.9, 1.3) 1.2 (1.0, 1.5) 1.3 (.9, 1.9) 1.1 (.8, 1.6) 1.1 (.9, 1.3) 1.1 (.6, 1.7) 1.4 (.9, 2.0) 1.2 (.9, 1.7) .9 (.6, 1.3) 1.3 (1.0, 1.6) 1.1 (.8, 1.4)

ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval; OCD, obsessive– compulsive disorder; OR, odds ratio; YBOCS, Yale–Brown Obsessive Compulsive Scale. Odds ratios were derived from logistic regression on each comorbid psychiatric disorder including all four OCD factors in the same model as independent variables. OCD symptom dimension factors were standardized (mean ⫽ 0, standard deviation ⫽ 1). Significant associations (p ⬍ .01) are printed in bold. Factor I: Aggressive, sexual, religious and somatic obsessions, and checking compulsions; Factor II: Obsessions of symmetry, and repeating, counting and ordering/ arranging compulsions; Factor III: Contamination obsessions and cleaning compulsions; Factor IV: Hoarding obsessions and compulsions. a p ⬍ .01. b p ⬍ .001.

second study (Hasler et al 2006). Zhang and colleagues used the hoarding phenotype for a genome scan in a sib-pair study of Tourette’s syndrome and reported in a simulation study that hoarding considered as a quantitative trait (symptom dimension) was more powerful than hoarding as a binary trait to detect linked chromosomal regions (Feng et al 2004; Zhang et al 2002). In this sample of OCD affected sibling pairs, the factor solutions of the YBOCS symptom categories, based either on the presence/absence of items or on the distress level of items, were almost identical. Both were consistent with the four-factor solution reported by Leckman and colleagues (1997) and with several subsequent studies including cluster analyses that now encompass more than 2000 OCD probands (Hasler et al 2005a; MataixCols et al 2005). Most of the 13 categories including hoarding obsessions and compulsions clearly loaded on only one of the four factors. Other categories such as checking compulsions and somatic obsessions loaded most strongly on Factor I but also showed moderate loadings on Factor III. These findings are similar to most previous reports showing that OCD symptom dimensions are generally correlated with each other and that checking compulsions and somatic obsessions can be associated with different factors (Baer 1994; Rosario-Campos et al 2006; Summerfeldt et al 1999). In our study, however, the hoarding Factor IV was only correlated with the symmetry/ordering Factor II, unlike the other three factors which were all intercorrelated. www.sobp.org/journal

After removing the possible effects of gender, age and age at OCD onset, Factor I showed a statistically significant sib–sib correlation. This correlation increased somewhat when controlling for familial comorbid conditions associated with Factor I. Obsessive symptoms, mainly religious and aggressive obsessions, contributed to the familiality of Factor I, while somatic obsessions did not contribute to the familiality of this factor. Consistent with the nonfamiliality of obsession severity, we observed that using distress levels instead of symptom presence/ absence for the analyses did not lead to an increase in magnitude of the sib–sib correlation of Factor I. This familiality of Factor I is in agreement with a previous study on the segregation of this symptom dimension in affected sib pairs diagnosed with Tourette’s syndrome, of whom 42% had comorbid OCD and in which the highest sib–sib correlation was found for Factor I (Leckman et al 2003). The hoarding factor yielded nonsignificant results in this prior Tourette’s/comorbid OCD sample, however. The hoarding factor (Factor IV) was clearly familial, like Factor I, in this study. There were also significant correlations between siblings when hoarding obsessions were considered separate from hoarding compulsions, although correlation values were lower, suggesting that the hoarding factor was a more robust phenotypic marker than either hoarding symptom category alone. The ICC for Factor IV increased considerably (from .21 to .32) when using distress levels associated with hoarding as

G. Hasler et al the phenotypic characteristic, a result different from that of the other three factors. There is convergent evidence for hoarding as a distinct phenotypic component of OCD (Black et al 1998; Hasler et al 2005a; Lasalle-Ricci et al 2005; Mataix-Cols et al 2002, 2005). The hoarding factor has been consistently replicated across factor-analytic studies of OCD probands (Mataix-Cols et al 2005). A recent cluster analytic study showed that hoarding features might represent a relatively separate symptom cluster in OCD patients (Hasler et al 2005a). Several clinical characteristics have been specifically associated with the hoarding factor in OCD, including somewhat poorer response to standard pharmacotherapy (Black et al 1998) and dropout from clinical trials (Mataix-Cols et al 2002). Family studies on hoarding in patients with Tourette’s syndrome suggested a recessive inheritance (Leckman et al 2003) and joint effects of specific loci on chromosomes 4q, 5q, and 17q (Zhang et al 2002). The ICC for Factor II was relatively low, although statistically significant. This result might appear somewhat at odds with previous studies showing substantial familiality of Factor II (or symptoms associated with Factor II) in three studies of different populations: adult OCD patients (Alsobrook et al 1999), pediatric OCD patients (Hanna et al 2005), and affected sibling pairs with Tourette’s syndrome (Leckman et al 2003). Unlike our study, however, which excluded probands with Tourette’s syndrome, the design of these first two studies did not consider Tourette’s syndrome as an exclusion (Alsobrook et al 1999; Hanna et al 2005). In addition, as noted previously and discussed in the third study, the symmetry and ordering features characteristic of Factor II are overrepresented and are a prominent feature of the familiality of Tourette’s syndrome (De Geus and Denys 2004). Furthermore, these three studies did not adjust for age of OCD onset, which appeared to be associated with Factor II. Moreover, according to the first two studies, scoring high on Factor II appears to represent a marker of familial OCD, and therefore, Factor II may not necessarily appear as a familial characteristic in a sample like ours that is limited to subjects from multiply affected, sibling-pair families rather than proband-only samples. Likewise, the ICCs for Factor III and the two symptom categories loading on Factor III (cleaning compulsions and contamination obsessions) were low. This is in line with previous studies which also observed relatively low familiality of contamination obsessions and cleaning compulsions (Alsobrook et al 1999; Leckman et al 2003). When the sample was restricted to female affected subjects only, the sib–sib correlations for all four factors were considerably higher than in the whole sample. This was particularly true for Factor II, for which the ICC increased more than twofold. Although previous studies found more sexual and aggressive obsessions and less cleaning compulsions and contamination obsessions in male than in female subjects with OCD (Denys et al 2004; Hasler et al 2005a; Mataix-Cols et al 1999; Sobin et al 1999), we did not find any gender differences with respect to mean scores on the four OCD symptom factors. Thus, possible gender differences in the prevalence of OCD symptom dimensions may not explain differences in the familiality of these dimensions. Gender differences in the familiality of OCD symptom dimensions found in our study are in line with a previous study showing etiologic heterogeneity between families ascertained through female and male probands (Nestadt et al 2000a). Consistent with our study, this previous segregation analysis showed more reliable and specific genetic influences in female than in male subjects (Nestadt et al 2000a). It is the rule rather than the exception that patients with OCD are diagnosed with other psychiatric disorders, some of which

BIOL PSYCHIATRY 2007;61:617– 625 623 may be specifically related to OCD (LaSalle et al 2004). Findings that certain disorders occur more frequently in the relatives of OCD subjects provide compelling evidence for an etiologic relationship (Nestadt et al 2003; Pauls et al 1995). Thus, there is evidence from family studies that tic disorders, panic disorder, agoraphobia, and recurrent major depression aggregate with OCD, suggesting shared etiologic elements between these disorders and OCD. This study, along with a previous study on the relationship between OCD symptom dimensions and comorbid psychiatric disorders (Hasler et al 2005a), provides evidence for specific associations between OCD symptom dimensions and comorbid conditions. Both studies showed associations between affective disorders and Factor I, and substance dependence and Factor II. The lack of a significant association between Factor IV and tic disorder in the present study may be related to the exclusion of Tourette’s syndrome in probands here. Further longitudinal and family research is necessary to elucidate the mechanisms of these relatively specific associations. All comorbid conditions with evidence for a relatively strong sib–sib association, including tic disorder, bipolar I/II, and hypochondriasis (data not shown) loaded on Factor I, suggesting that the familiality of Factor I is associated with the familiality of certain comorbid conditions. This study has several limitations. The sample was recruited from various sources, including treatment settings, self-help groups, web sites, and media advertisements. The sample has a broad age range, including children as young as 7 years, reflecting both the young age at onset of this condition and the successful collaboration of psychiatrists specializing in child and adult psychiatry. Although the variability of the referral patterns may increase the generalizability of the results, the lack of formal, community-based epidemiologic recruitment is a weakness of the study (although this has apparently been the case in prior factor analytic studies of OCD). Restricting probands to an age of onset of OCD symptoms of under 18 may somewhat lessen generalizability to clinical populations with more mixed ages of onset. The majority of subjects were Caucasian, and therefore the results may not generalize to other ethnic groups. In addition, there are potential sources of bias in that volunteering may be more likely in sibling pairs who have more similar types of OCD symptoms and that subjects came from families with more than one sib with OCD. The assessment was cross-sectional, although a longitudinal assessment would have been preferable because genetic studies would be benefited by evaluation of the stability of dimensional phenotypes over time (Hasler et al 2005b) and retrospective assessment is subject to memory bias. Another evident limitation is that this sib-based study could only assess overall familiality, with no basis for evaluating genetic versus environmental causes of similarity on OCD symptom dimensions, which would require a sample of monozygotic (MZ) and dizygotic (DZ) twins. Fully genetically based ICCs could not exceed approximately .5, because sibs share an average of 50% of their genetic variants. Although no twin studies of YBOCS symptom dimensions in OCD probands have been reported, two studies have assessed self-reported obsessive– compulsive symptomatology in general population samples of twins (Clifford et al 1984; Jonnal et al 2000). One of these studies employed the Leyton Obsessional Inventory (Clifford et al 1984) and the other the Padua Inventory of Obsessive–Compulsive Symptoms (Jonnal et al 2000); both found MZ:DZ hereditabilities on the order of .25–.47, with uncorrected Pearson correlations in the latter study of female twins for total Padua severity scale scores of .34 for MZ twins and .14 for DZ twins (the closest equivalent of sib pairs). www.sobp.org/journal

624 BIOL PSYCHIATRY 2007;61:617– 625 Unfortunately, because of differences in subject populations and their characteristics, plus rating scales, there is no way to equate the results of these studies with ours, other than by concluding that they all point toward evidence for some partial familial (and in some samples, genetic) contributions to obsessive– compulsive symptom features. In summary, this study shows that factor-analysis-based OCD symptom dimensions are familial, that familiality estimates are considerably higher when limiting the sample to female sib-pairs, and that OCD symptom dimensions show relatively specific relationships to comorbid psychiatric conditions. Further research on the longitudinal relationship and familial aggregation of OCD symptom dimensions and psychiatric comorbidity is warranted. Stratifying families by subphenotypes that are familial may reduce heterogeneity and facilitate identification of genetic risk factors for OCD. Thus, the identification of more homogenous phenotypic characteristics in OCD has the potential to increase the power of genetic and neurobiological studies of this common, severe, and disabling condition.

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