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. Author manuscript; available in PMC: 2015 May 13.
Published in final edited form as: Psychol Med. 2014 Feb 20;44(13):2867–2876. doi: 10.1017/S0033291714000269

Partitioning the etiology of hoarding and obsessive compulsive symptoms

Carol A Mathews 1,*, Kevin Delucchi 1,@, Danielle Cath 2,@, Gonneke Willemsen 3, Dorret Boomsma 3
PMCID: PMC4429876  NIHMSID: NIHMS688020  PMID: 25066062

Abstract

Background

Until recently, hoarding was considered an obsessive-compulsive symptom (OCS). However, current evidence suggests that these two phenotypes may be clinically, and perhaps etiologically, distinct. Both hoarding and OCS have a genetic etiology, but the degree of unique and shared genetic contributions to these phenotypes is not well studied.

Methods

Prevalence rates were assessed for hoarding and OCS in a sample of adult twin pairs (N = 7,906 twins) and their family members from the Netherlands Twin Register (total sample = 15,914). Using Mplus, genetic analyses using liability threshold models were conducted for both phenotypes, for their comorbidity, and for specific hoarding symptoms (cluttering, discarding, and acquiring).

Results

6.7% of the total sample met criteria for clinically significant hoarding; endorsement of all three hoarding symptoms was over 85%. Men had slightly higher rates than women. 5.7% met criteria for clinically significant OCS; rates were similar in males and females. Genetic factors accounted for 36% of the variance for hoarding and 40% of the variance for OCS. The genetic correlation between hoarding and OCS was 0.10. There was no evidence of sex-specific genetic contributions for hoarding or OCS. There was evidence for a genetic contribution to all hoarding symptom subtypes. Only cluttering showed evidence of a contribution from shared environment.

Conclusions

OCS and hoarding are common in this population-based sample, are similar to previously reported prevalence rates, and show significant heritability. Genetic factors contributed to the comorbidity of both traits, although the genetic correlation between them was low.

Background

Hoarding is a common but under-recognized social behavior that when severe is quite maladaptive and results in significant morbidity and mortality (Frost et al., 2000a, Frost et al., 2000b, Tolin et al., 2008). Pathological hoarding is defined as the excessive acquisition of and/or inability or unwillingness to discard seemingly useless items, causing significant distress or functional impairment, and resulting in living and/or work spaces that are unusable for their intended purposes (Frost and Gross, 1993, Steketee and Frost, 2003). The population prevalence of clinically significant pathological hoarding is between 2-4%, and increases substantially over age 55, where the prevalence is over 6% (Best-Lavigniac, 2006, Frost and Gross, 1993, Grisham et al., 2006, Iervolino et al., 2009, Timpano et al., 2011). Pathological hoarding is a chronic problem, and is associated with high levels of distress, functional impairment, social disruption, and maladjustment (low marriage rates, high social anxiety, work loss, and withdrawal) (Ayers et al., 2010, Frost et al., 2000a, Frost et al., 2000b, Kim et al., 2001, Tolin et al., 2007).

Although previously classified as a subtype of obsessive-compulsive disorder (OCD), multiple lines of evidence suggest that pathological hoarding is etiologically distinct, and for this reason, Hoarding Disorder (HD) appears in the DSM-V as a new diagnosis (American Psychiatric Association, 2013, Mataix-Cols et al., 2010, Pertusa et al., 2010, Pertusa et al., 2008). Hoarding symptoms commonly co-occur with OCD, however, and there is evidence of genetic overlap between these disorders from family studies (Katerberg et al., 2010, Lochner et al., 2005, Mataix-Cols et al., 2010, Mathews et al., 2007b, Pertusa et al., 2008, Samuels et al., 2007, Saxena, 2007). The etiological relationships between HD and OCD are complex, and additional information on the heritabilities and genetic relationships between these phenotypes is needed to inform future genetic and other etiologic studies.

To date, only a few twin studies have been published examining the heritability of hoarding symptoms (Iervolino et al., 2009, Iervolino et al., 2011, Ivanov et al., 2013, Nordsletten et al., 2013, Taylor et al., 2010). The earliest found that 42% of the phenotypic variance of hoarding was attributable to genetic factors in 167 MZ and 140 DZ male and female twin pairs from Canada; sex differences in heritability were not examined (Taylor et al., 2010). Two subsequent studies used different assessment tools to examine the heritability of hoarding in the same sample of female twin pairs (4,355 twins in 2,053 twin pairs) ages 16 and older (mean age 55) from the TwinsUK twin registry. The genetic contribution to hoarding symptoms was ~50%, with 45% of the genetic variance shared with other OCS dimensions, and 55% of the variance specific to hoarding (Iervolino et al., 2009, Iervolino et al., 2011). A study in 15 year-old male and female twins from the Swedish Twin Register (3,974 twins in 1,555 twin pairs) found a substantial genetic component to hoarding for males only, with 35% of the phenotypic variance explained by genes. There was also a familial resemblance in females (32%), but this was ascribed to shared environment (Ivanov et al., 2013). Thus, there appears to be some evidence for a genotype by sex interaction in the etiology of hoarding, at least in young twins (Ivanov et al., 2013). However, this sample also included 444 opposite-sex twin pairs, whose significant correlation of 0.16 for hoarding cannot be explained if familial resemblance is genetic in men and environmental in women.

The relationship between the three core characteristics of hoarding behavior, i.e., excessive acquisition, difficulty discarding, and excessive clutter, is not yet fully understood. It has been suggested that difficulty discarding may be the primary determinant of pathological hoarding, and that excessive acquisition is a secondary behavior that occurs in some, but not all, cases, while cluttering may be a non-specific symptom that occurs across a variety of disorders (Mataix-Cols et al., 2010). The only previous study to assess the genetic contributions to specific hoarding symptoms found heritabilities of 0.45 for difficulty discarding and 0.49 for excessive acquisition, as well as significant genetic correlation between the two in the UKtwin sample (0.77) (Nordsletten et al., 2013). However, the role of genetics and environment in the development of cluttering has not yet been examined. As cluttering is a very common symptom in pathological hoarding, developing a better understanding of the etiology of this behavior is important.

Therefore, the primary aims of our study were to replicate and expand upon previous results by examining the genetic and environmental contributions to hoarding and obsessive-compulsive symptoms (OCS) in an independent population-based twin sample that includes both male, female, and opposite-sex twin pairs. Specifically, we aimed to 1) quantify the shared and independent genetic contributions to hoarding and OCS, 2) examine whether sex differences play a role in the etiology of hoarding, and 3) examine the genetic and environmental contributions to the three main symptom types that make up hoarding behaviors—problematic cluttering, excessive acquiring, and difficulty discarding.

Methods

Participants

Participants were registered with the Netherlands Twin Register (NTR), which includes twin pairs and their extended family members (details in Supplemental Materials). 15,914 participants completed one or both of the OCS and hoarding scales. The final twin sample included 7,567 individuals from 5,064 twin pairs (Supplemental Figure 1). 2,503 twin pairs were complete, while 2,561 had data available for only one of the two twins. All data from pairs where at least one twin had available data were included in the analyses (Supplemental Table 1). Ethical approval for the study was obtained from the Medical Ethical Committee of the VU University Medical Centre.

Assessment Instruments

The assessment instruments consisted of the Hoarding Rating Scale-Self-Report (HRS-SR) and the Padua Inventory Revised-Abbreviated (PI-ABBR) (see Supplemental Materials). The HRS-SR contains five items that assess cluttering, difficulty discarding, problems with excessive acquiring or collecting, and functional impairment and distress from hoarding symptoms, each on a 0-8 scale (Tolin et al., 2010). Due to restrictions in the number of items approved for inclusion in the larger participant questionnaire, the impairment item of the HRS-SR (item 4) was eliminated for this study. The PI-ABBR is a 12-item questionnaire derived from the larger 41 item Padua Inventory that contains two to three items from each of five obsessive-compulsive symptom dimensions, including Checking, Impulses, Precision, Rumination, and Washing (Cath et al., 2008). Each item is scored on a 0-4 scale. Because the data were not normally distributed, but rather exhibited a right skew (Supplemental Figure 2), a liability threshold model was used, and a categorical variable was generated for each measure using several cut points across the entire distribution of scores (Cath et al., 2008, Iervolino et al., 2009, van Grootheest et al., 2008). The liability threshold model assumes that the risk, or liability, for a given trait (i.e, hoarding or OCS), is normally distributed in the population, but is not directly measured. In this model, categorical data, such as presence or absence of a diagnosis or multiple categorical cutoffs in a questionnaire aimed at measuring the trait, are considered to be a measure (although imprecise) of this underlying liability to disease; the presence of disease, for example, represents the extreme end of the underlying liability distribution. The HRS-SR was divided into four categories (total scores of 0, 1-4, 5-9, and ≥10), with roughly equal numbers of individuals in each category (Iervolino et al., 2009). Each symptom-specific question (excessive clutter, difficulty discarding, and excessive acquiring) was divided into four categories, with scores of 0, 1, 2-3, and 4 and above. We also examined the heritability of the hoarding phenotype using cutoffs (scores of 0, 1-5, 6-16, and ≥17), that more closely approximate clinical patterns (no hoarding, mild symptoms, subclinical hoarding, and clinically significant hoarding), but had unequal distributions of individuals within each group, to determine the stability of the heritability estimates. The PI-ABBR was divided into four categories based on the previous literature (scores of 0, 1-6, 7-15, and ≥16) (Cath et al., 2008).

Analysis

In order to assess the population prevalence and characteristics of hoarding symptoms, means, standard deviations, and distributions were calculated for both measures along with rates of clinically significant symptoms in the entire sample of 15,914 individuals. Conducting these analyses takes full advantage of the entire age range available, thus increasing the generalizability of the results. The analyses were repeated in the twin sample only to ensure that the twin sample did not substantially differ from the entire sample phenotypically. Phenotypic correlations within the sample were calculated using Kendall’s tau, as the measures are not normally distributed. Polychoric twin correlations, i.e. correlations on the underlying liability scale, were calculated using Mplus for both the HRS-SR and the PI-ABBR in MZ and DZ twin pairs by sex, and in the total MZ and DZ samples (including all twin pairs of both sexes). All twin data were analyzed, i.e. from complete and incomplete pairs.

Genetic model fitting

Genetic model fitting was conducted in Mplus using the weighted least squares mean and variance adjusted (WLSMV) estimation option (Prescott, 2004). Genetic and environmental influences on hoarding and OCS were calculated using the liability thresholds described above. Univariate analyses were conducted to identify the relative contributions of additive genetic (A), common environmental factors (C) shared by family members, and non-shared or unique environmental (E) factors, along with the standard errors and associated significance values, to each phenotype. Univariate genetic models were examined for OCS, hoarding, and the three specific hoarding symptoms (cluttering, discarding, and acquiring), in addition to the distress item. To partition the covariance between hoarding and OCS into genetic and environmental components, bivariate genetic models were examined. Bivariate models were fitted to the OCS and hoarding data.

The effects of sex by genotype interaction were examined in a five-group model (MZ male, MZ female, DZ male, DZ female, and DZ opposite-sex twin pairs) for all phenotypes. A potential role for differing contributions of genes and environment in males and females was examined for each trait by freeing up the genetic correlations in opposite-sex twin pairs rather than restricting them to 0.5 in the model fitting analyses. By using WLSMV for estimation, all data were included in the analysis. The full genetic model, where sex differences were allowed, was then compared to a constrained model, where genetic contributions for males and females were set to equal, using the Wald test of parameter constraints.

Results

Means and distribution of hoarding and OCS

Table 1 shows the demographic characteristics of the sample. The mean age of the entire sample was 41.3 years (SD = 16.0). The mean age of the twin sample was 33.2 years (SD = 14.5), and the mean age of the family members was 49.2 (SD = 13.1). The mean total HRS-SR score was 6.2 (SD = 5.8, range = 0-32) for the entire sample and 5.7 (5SD = 5.6, range 0-32) for the twin sample only. Males had significantly higher HRS-SR scores than did females (mean for males = 6.7, mean for females = 6.0, t = 7.90, p < 0.0001). The mean total PI-ABBR score was 6.7 (SD = 4.9, range 0-48) for the entire sample and 6.9 (SD = 5.2, range 0-48) for the twin sample only. There were no significant differences in mean score by sex for the PI-ABBR (t = 0.79, p = 0.43). The distributions of the scales are shown in Supplemental Figure 2.

Table 1.

Demographic and clinical characteristics of the NTR sample, for the twin sample and for relatives of twins. Individuals who were missing data for both the HRS-SR and PI-ABBR were excluded (N = 906). N with available HRS-SR data = 15,429. N with available PI-ABBR data = 15,258. N with both HRS-SR and PI-ABBR data = 14,773.

Total sample
N = 15,914		 Twin sample
N = 7,906		 Relative sample
N = 8,008		 X2 or t, p value
Percent male (N) 35.9% (5,719) 30.6% (2,418) 41.2% (3,301) 195.5, p<0.0001
Mean age (SD) 41.3 (16.0) 33.2 (14.5) 49.2 (13.1) 72.9, p<0.00001
Mean HRS-SR (SD) 6.2 (5.8) 5.7 (5.6) 6.7 (6.1) 10.6, p<0.00001
Mean PI-ABBR (SD) 6.7 (4.9) 6.9 (5.2) 6.4 (4.7) −6.3, p<0.00001
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Prevalence of hoarding symptoms

The highest possible total score on the original HRS-SR is 40, while the highest possible total score on the current modified version is 32. Using the original scale, Tolin et al proposed a cutoff of ≥ 14 for clinically significant hoarding (Tolin et al., 2010), while Iervolino et al used a cutoff of ≥ 17 to determine hoarding “caseness” (Iervolino et al., 2009). We examined the prevalence of hoarding symptoms using each of these cutoffs, which are conservative in our sample (the equivalent cutoffs for the 4-item scale would be 11 and 14, respectively). 12.6% of the entire sample had HRS-SR scores of ≥ 14, while 6.8% of the entire sample had HRS-SR scores of ≥ 17. As a cutoff of 17 is the most conservative, and the prevalence of hoarding caseness in our sample using this cutoff most closely approximates the previously reported population prevalence of HD (Best-Lavigniac, 2006, Iervolino et al., 2009, Timpano et al., 2011), we used a score of ≥ 17 to indicate clinically significant hoarding (termed hoarding) in the NTR sample. Males were more likely to have hoarding than were females (7.% vs. 6.3%, X2 = 8.3, p = 0.004). Individuals with hoarding were older than those without (48.0 years vs. 40.7 years, z = 14.5, p < 0.0001). 81% of those with hoarding reported difficulties with clutter (score of ≥ 4), while 79% reported problematic acquiring, and 93% reported difficulty discarding (score of ≥ 4). These three items were all significantly correlated with one another, and with total HRS-SR and total PI-ABBR scores (see Supplemental Table 2). The correlation between total HRS-SR and total PI-ABBR scores was 0.20, p<0.0001 (Supplemental Table 2).

Prevalence of obsessive compulsive symptoms

5.7% of the entire sample had PI-ABBR scores of ≥ 16, corresponding to clinically significant OCS (termed OCS). There were no statistically significant differences in rates of OCS between males and females (6.0% vs. 5.5%, X2 = 1.78, p = 0.18). Individuals with OCS were 4 years younger than those without, on average (37.7 vs. 41.6 years, z = −3.5, p = 0.0005).

Relationship between hoarding and OCS

Of the individuals with clinically significant hoarding, 16.5% also had clinically significant OCS. Of those with OCS, 19.4% had hoarding. When the sample was divided into those with hoarding-only, those with OCS-only, or those with both, there were statistically significant differences in the gender ratios, ages, and types of hoarding symptoms endorsed between the groups (Supplemental Table 3). All three groups endorsed problems with discarding, acquiring, and cluttering at fairly high levels. As expected, individuals with hoarding (with or without OCS) endorsed these symptoms the most frequently (> 80%); however, ≥ 25% of those with OCS-only also endorsed these symptoms. Symptom endorsement rates were the lowest for all hoarding symptoms among individuals with neither hoarding nor OCS (Supplemental Table 3). Although individuals with both hoarding and OCS were younger on average than those with hoarding-only and more likely to be male, none of the specific hoarding symptoms differentiated the hoarding-only from the hoarding + OCS groups.

Twin correlations

Polychoric correlations for the HRS-SR and for the PI-ABBR are presented in Table 2. As a comparison, previously reported twin correlations for these or similar measures are also presented. Twin correlations were very similar to previously reported figures for the OCS phenotype. Twin correlations for hoarding were at the low end of the range of previously reported heritabilities. The overall monozygotic twin correlations for both hoarding and OCS were approximately twice the dizygotic twin correlations, suggesting a genetic component to both traits. The DOS twin correlations for hoarding were significantly lower in our sample than the correlations in DZ same sex twins, suggesting qualitative sex differences in hoarding symptoms.

Table 2.

Twin correlations for hoarding and obsessive compulsive symptoms (OCS). HRS-SR = Hoarding Rating Scale-Self Report. OCI-R = Obsessive Compulsive Inventory, Revised. PI-ABBR = Padua Inventory, Abbreviated. YASR-OCS = Young Adult Self Report Obsessive Compulsive Scale. PI = Padua Inventory. MOCI = Maudsley Obsessive Compulsive Inventory. STAGE = Screening Twin Adults: Genes and Environment Study Scale. CBCL-OCS = Child Behavior CheckList, Obsessive Compulsive Scale. ADIS-C/P = Anxiety Disorders Interview Schedule for Children and parents. NTR = Netherlands Twin Register. MOTWIN = Missouri Twin Registry. TEDS = Twins Early Development Study. MZ = monozygotic. DZ=dizygotic. MZM = monozygotic male. DZM = dizygotic male. MZF = monozygotic female. DZF = dizygotic female. DOS = dizygotic opposite-sex.

MZ total
N = 1218		 DZ total
N = 983		 MZM
N = 304		 DZM
N = 170		 MZF
N = 914		 DZF
N = 414		 DOS
N = 399
Hoarding
HRS-SR, NTR, current study, mean age 33.2 0.34 0.17 0.36 0.18 0.34 0.17 0.09
HRS-SR, UKTwins, mean age 55.5 (Iervolino et al., 2009)# 0.50 0.27
OCI-R hoarding subscale, UKTwins, mean age 55.5 (Iervolino et al., 2011)# 0.52 0.27
HRS-SR, Swedish Twin Register, age 15 (Ivanov et al., 2013) 0.44 0.17 0.35 0.41 0.16
OCS adults
PI-ABBR, NTR, current study, mean age 33.3* 0.40 0.20 0.40 0.20 0.40 0.20 0.20
OCI-R, UKTwins, mean age 55.5 (Iervolino et al., 2011) 0.47 0.28
YASR-OCS, NTR, mean age 22.4 (Van Grootheest et al., 2007)* 0.44 0.13 0.50 0.26 0.21
PI 20 item, compulsiveness, Virginia Twin Registry, mean age 36 (Jonnal et al.,
2000)		 0.34 0.14
PI 20 item, obsessiveness, Virginia Twin Registry, mean age 36 (Jonnal et al., 2000) 0.28 0.06
OCS adolescents
YASR-OCS age 16, NTR (van Grootheest et al., 2008)* 0.45 0.30 0.58 0.33 0.22
YASR-OCS age 14, NTR (van Grootheest et al., 2008)* 0.57 0.17 0.60 0.30 0.22
MOCI (Hur and Jeong) ages 13-23, (Hur and Jeong, 2008) 0.56 0.24 0.39 0.36
STAGE, Swedish National Patient Register, mean age 30-33 (Mataix-Cols et al.,
2013)		 0.45 0.20 0.49 0.12 0.12
CBCL-OCS ages 7-12, MOTWIN, (Hudziak et al., 2004), 0.51 0.34 0.46 0.10 0.32
OCS children
CBCL-OCS age 7, NTR (Hudziak et al., 2004) 0.55 0.31 0.57 0.21 0.30
CBCL-OCS age 10, NTR (Hudziak et al., 2004) 0.59 0.35 0.54 0.22 0.33
CBCL-OCS age 12, NTR (Hudziak et al., 2004) 0.57 0.30 0.50 0.40 0.33
YASR-OCS age 12, NTR (van Grootheest et al., 2008)* 0.50 0.38 0.45 0.36 0.21
ADIS-C/P age 6, TEDS (Bolton et al., 2007) 0.57 0.22
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*

samples for these studies overlap.

#

samples for these studies are the same.

Genetic model fitting

The total estimated heritability for the hoarding phenotype using the equally distributed cutoffs was 0.36 (SE = 0.05, p<0.0001), and the estimated non-shared environment was 0.64 (SE = 0.05, p<0.0001). As expected from the pattern of twin correlations, there was no evidence for the effects of common environment. The total estimated heritability for hoarding using the clinical cutoffs was 0.33 (SE = 0.02), and the estimated non-shared environment was 0.67 (SE = 0.03). The total estimated heritability for OCS was 0.40 (SE = 0.03, p < 0.0001), and the estimated non-shared environment was 0.60 (SE = 0.03, p < 0.0001).

Genotype by sex interaction

Examination of the concordance ratios between MZ twins, DZ same sex twins, and DZ opposite sex twins suggested differences in genetic contributions to hoarding symptoms by sex (Table 2), as the MZ correlations were higher than the DZ same-sex correlations, which were higher than the DZ opposite-sex correlations. This difference was not seen for OCS. Males and females had similar heritability estimates for both hoarding and OCS, however, and the model comparison between the full model and the model where genetic influences for males and females were constrained to be equal suggested that there were no different genetic contributions to hoarding or OCS by sex (Table 3). To test the stability of the analyses for hoarding, we then calculated the twin correlations and heritability estimates for hoarding using cutoffs that more closely approximated clinical patterns. In this analysis, males had a larger genetic contribution to hoarding than did females, although the model comparisons again showed no differences between the full and constrained models (Table 3).

Table 3.

Heritability estimates and fit statistics for ACE models examining the role of sex in hoarding and OCS. The genetic contribution to the phenotype (hoarding or OCS) is allowed to vary by sex in the full model.

Heritability estimates Fit statistics Model difference test
Males Females Wald test
statistic		 p
Hoarding, full model (sex differences in genetic
sources)		 0.36
(SE = 0.05)		 0.33
(SE = 0.12)		 0.059 0.81
Hoarding, same genetic sources in males and
females		 0.34
(SE = 0.10)		 0.34
(SE = 0.10)
Hoarding, clinical cutoffs, full model (sex
differences in genetic sources)		 0.40
(SE = 0.19)		 0.25
(SE = 0.12)		 0.447 0.50
Hoarding, clinical cutoffs, same genetic sources
in males and females		 0.29
(SE = 0.06)		 0.29
(SE = 0.06)
OCS, full model (sex differences in genetic
sources)		 0.40
(SE = 0.05)		 0.40
(SE=0.03)		 0.004 0.95
OCS, same genetic sources in males and
females		 0.40
(SE = 0.03)		 0.40
(SE = 0.03)
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Bivariate analyses

We next examined the shared genetic and environmental contributions to OCS and hoarding using bivariate genetic model fitting. The cross-twin cross-trait correlations were 0.16 (hoarding twin 1 and OCS twin 2) and 0.15 (hoarding twin 2 and OCS twin 1) for MZ twins and 0.07 (hoarding twin 1 and OCS twin 2) and 0.06 (hoarding twin 2 and OCS twin 1) for DZ twins, and the genetic correlation between hoarding and OCS was 0.10. In comparison, the within-person cross-trait correlations were 0.28 and 0.26 for MZ twins and 0.35 and 0.30 for DZ twins. These results suggested that there is little genetic covariance between traits. As shown in Table 4, approximately 31% of the total additive genetic variance for hoarding and 25% of the total additive genetic variance for OCS in this sample is due to genetic factors shared between the two phenotypes. As was also seen in the univariate analyses, the remaining variance for both traits is due to non-shared environmental factors; there is little to no evidence for a role for common environmental factors.

Table 4.

Bivariate genetic model for hoarding and OCS. Residual = amount of variance that is not shared between hoarding and OCS phenotypes. A2 = proportion of variance due to additive genetic factors. C2 = proportion of variance due to common or shared environmental factors. E2 = proportion of variance due to unshared (unique) environmental factors. Note that the first and the last columns sum to 1 for Hoarding total and OCS total, respectively; p = significance level, NS = not significant.

Hoarding total
variance
component		 Hoarding residual
Variance		 Hoarding + OCS
shared variance		 OCS residual
variance		 OCS total
variance
A2 0.307
p<0.0001		 0.201* 0.095
p = 0.01		 0.281
p < 0.0001		 0.376*
C2 0.022
p = NS		 0.018* 0.01
p = NS		 0.008
p = NS		 0.022*
E2 0.549
p < 0.0001		 0.592* 0.034
p < 0.0001		 0.567
p < 0.0001		 0.601*
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*

derived value.

Genetic model fitting—specific hoarding symptoms

We then examined the heritability for the three specific hoarding symptoms, excessive clutter, excessive acquiring, and difficulty discarding items (see Supplemental Table 4 for twin correlations). For clutter, 0.20 of the total variance was due to additive genetic factors (SE = 0.12, p = 0.105), while 0.11 was due to common environmental factors ((SE = 0.16, p = 0.041) and 0.69 was due to non-shared environment (0.03, p < 0.0001). For acquiring, 0.22 (SE = .05, p < 0.0001) of the total variance was due to additive genetic factors, while 0.78 (SE = .03, p < 0.0001) was due to non-shared environmental factors. For difficulty discarding, 0.37 (SE = .13, p = 0.001) of the total variance was due to additive genetic factors, while 0.63 (SE = 0.03, p < 0 .0001) was due to non-shared environmental factors; there was essentially no contribution from shared environmental factors. As a comparison, 0.31 (SE = 0.03, p < 0.0001) of the total variance for the distress item was due to additive genetic factors, and 0.69 (SE = 0.03, p< 0.0001) was due to non-shared environment. The estimates for the role of additive genetics to excessive acquiring and difficulty discarding were lower than previously reported (0.45 and 0.49, respectively) (Nordsletten et al., 2013); the role of additive genetics to difficulty with clutter has not been previously reported.

Discussion

Using the largest sample of twin pairs available to date, the results of this study confirm the previous findings suggesting that independent genetic factors clearly contribute to the etiology of both hoarding and OCS. In our sample, the overall heritability estimates were 0.36 for hoarding and 0.40 for OCS, which are within the range of what has been previously found, although the heritability estimate for hoarding was at the lower end of the previously reported estimates (40-50% for OCS, and 35-50% for hoarding) (Iervolino et al., 2009, Iervolino et al., 2011, Taylor et al., 2010, van Grootheest et al., 2008, van Grootheest et al., 2005, 2007). There was no evidence for sex differences in the genetic etiology of either hoarding or OCS. These results are consistent with previous studies of OCS, including those that examined OCS in the NTR using different scales (e.g., Van Grootheest et al.), and those that examined OCS in other samples (see Table 2) (Bolton et al., 2007, Hudziak et al., 2004, Iervolino et al., 2011, van Grootheest et al., 2008, Van Grootheest et al., 2007). Previous studies of the genetic contribution to hoarding by sex have been inconsistent, as studies of female twins ages 16 and up suggest strong genetic influences on hoarding, while a study of 15 year old twins showed genetic influences for boys but not girls (Iervolino et al., 2009, Iervolino et al., 2011, Ivanov et al., 2013). The results of our study confirm a genetic contribution to hoarding for both sexes, and do not provide strong evidence for differences in genetic contributions to hoarding by sex.

Although there was evidence of shared genetic variance between hoarding and OCS, the genetic correlation between these phenotypes was substantially lower in our sample than has been previously reported (~0.10 compared to 0.45) (Iervolino et al., 2009, Iervolino et al., 2011). Although there are several possible reasons for this, we suspect that the modifications we made to the HRS-SR may have contributed to both the lower heritability estimate for hoarding and the lower genetic correlation between hoarding and OCS. For this study, the impairment question of the HRS-SR was eliminated, and the question on distress was kept. This may have resulted in a problem of phenocopies, wherein our assessment captures not only true hoarding behaviors, but also non-specific cluttering behaviors arising from a variety of factors, that may or may not be impairing, but are nonetheless distressing. This hypothesis is supported by the unexpectedly high rates of clinically significant hoarding (~7%), despite the stringent cutoff used and the relatively young age of the sample.

Another possibility is that we have truly captured a hoarding phenotype with the modified HRS-SR, but that this phenotype is more heterogeneous than in other studies, such that fewer individuals with hoarding within the sample are also at risk for OCS. Hoarding is etiologically as well as phenotypically heterogeneous, and the genetic relationship between hoarding and OCD is complex. Previous studies suggest that rates of hoarding in relatives differ based on the primary diagnosis of the probands; hoarding symptoms are prevalent in families identified through probands with OCD or probands with hoarding + OCD, but OCD does not appear to be common in relatives of probands with hoarding only (Mathews et al., 2007b, Pertusa et al., 2008, Samuels et al., 2002, Samuels et al., 2007).

Finally, although the majority of variance for each of the three specific hoarding behaviors was due to environmental rather than genetic factors, all three showed some evidence of a genetic contribution. There has been some suggestion in the literature that difficulty discarding is the most fundamental feature of HD, and that excessive acquiring is most likely a subtype rather than a core feature of HD, while cluttering is non-specific symptom that may also occur in many other contexts or disorders (e.g., due to physical limitations, or to lack of motivation in individuals with depression). We cannot directly answer the question about which symptoms are core to HD in our sample. All three symptoms occurred at high rates in individuals with clinically significant hoarding (>85%), were highly correlated with one another in the overall sample, and had a genetic component, suggesting that all three symptoms are likely to be relevant to a larger hoarding phenotype.

These findings clearly have implications for genetic studies. The complex relationship between hoarding and OCS, and perhaps the heritability estimates for the specific symptom subtypes, should be considered when designing studies aimed at identifying genetic susceptibility variants for hoarding. One way to increase power for genome-wide association studies, for example, is to include individuals with related phenotypes, with the hope that the gains realized by the increase in sample size will outweigh the losses associated with increased heterogeneity. Our data suggest that this approach would not be appropriate for hoarding and OCD, at least as defined here, as the genetic correlation between them is quite low. Similarly, in designing genetic studies of hoarding, investigators would likely benefit from focusing on individuals with prominent difficulty in discarding symptoms rather than those with primary problems with acquisition or clutter, as this was the most highly heritable hoarding symptom in our sample, and was in fact slightly more heritable than the global hoarding phenotype.

In addition to genetics, there is also clearly a role for environment in the development of hoarding behaviors and OCS, as has been demonstrated by all of the twin studies conducted to date. The specific types of environmental factors that influence the development of these phenotypes are unknown. Although trauma, including both abuse and neglect, has been suggested to be a risk factor for OCS and hoarding, the data are somewhat inconsistent (Cromer, 2007, Fontenelle et al., 2007, Hartl et al., 2005, Landau et al., 2011, Mathews et al., 2007a). The identification of genetic variants and/or environmental risk factors at the various developmental stages through adulthood predisposing to HD and/or OCD is clearly a crucial next step in furthering our understanding of the etiology of these impairing conditions.

Limitations

The primary limitations of this work relate to the phenotypes. Because this is a population-based twin study, the phenotypes are derived from self-report symptom-based data rather than structured interviews. We cannot make diagnoses of HD or OCD, but must rely on somewhat arbitrary cutoffs to determine symptom thresholds with potential clinical significance. The choice of cutoffs can affect the point estimates for genetic and environmental effects, as seen for the hoarding phenotype. In addition, the HRS-SR was modified for use in this sample, and we do not have validity data on the modified instrument. As noted above, this change may have resulted in an increased heterogeneity of the hoarding phenotype, leading to an over-estimate of the population prevalence of hoarding in this sample and an under-estimate of the heritability. The prevalence of individuals meeting the clinical cutoff corresponds to the upper end of the range of previously reported prevalence rates for hoarding in the population, despite the comparatively young age of the sample, suggesting that the cutoff used, although very conservative, might still over-estimate the true rates of HD in this population. Although a measure of distress is built into the scale, impairment is also required to meet diagnostic criteria for HD. Nevertheless, while the threshold cutoffs do not correspond to clinical diagnoses of HD or OCD, they do likely represent clinically significant symptoms. Validation of the modified HRS-SR is a needed next step to clarify the utility of this measure as a screening tool. The advantages of the study design compensate to some degree for these potential problems, in that we are able to sample a very large number of individuals and twin pairs, as would not be possible in a clinical sample, therefore obtaining more accurate estimates of both prevalence of symptoms and of the genetic and environmental contributions to the traits (including specific hoarding symptoms).

Supplementary Material

Supplementary Material

Acknowledgements

Data collection was supported by the Addiction program of ZonMW (31160008): Genetic determinants of risk behavior in relation to alcohol use and alcohol use disorder; the European Research Council (ERC-230374): Genetics of Mental Illness; and the Netherlands Organization for Scientific Research (NWO 463-06-001and from a grant from the Tourette Syndrome Association (TSA) in the United States (2008).

Footnotes

The authors have no conflicts of interest.

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