Prevalence and Heritability of Skin Picking in
an Adult Community Sample: A Twin Study
Benedetta Monzani,1* Fruhling Rijsdijk,2Lynn Cherkas,3Juliette Harris,3
Nancy Keuthen,4and David Mataix-Cols1,5
1Department of Psychosis Studies. King’s College London, Institute of Psychiatry, London, UK
2Social, Genetic & Developmental Psychiatry Research Centre (SDGP), Institute of Psychiatry, London, UK
3Department of Twin Research and Genetic Epidemiology, King’s College London, UK
4Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
5Department of Psychology. King’s College London, Institute of Psychiatry, London, UK
Manuscript Received: 1 February 2012; Manuscript Accepted: 25 April 2012
Skin-pickingdisorder(SPD) isadisabling psychiatriccondition
that can lead to skin damage and other medical complications.
Epidemiological data is scarce and its causes are unknown.
The present study examined the prevalence and heritability of
twins completed a valid and reliable self-report measure of
skin-picking behavior. The prevalence of clinically significant
skin picking was established using empirically derived cut-offs.
Twin modeling methods were employed to decompose the
variance in the liability to skin picking into additive genetic
and shared and non-shared environmental factors. A total of
1.2% of twins scored above the cut-off, indicative of clinically
significant skin picking. All these participants were women.
Univariate model-fitting analyses (female twins only, N¼2,191)
showed that genetic factors accounted for approximately 40%
(95% CI 19–58%) of the variance in skin picking, with non-
shared environmental factors and measurement error account-
environmental factors were negligible. It is concluded that
ularly among women, and that it tends to run in families
primarily due to genetic factors. Non-shared environmental
factors are also likely to play an important role in its etiology.
? 2012 Wiley Periodicals, Inc.
Key words: pathological skin picking; psychogenic excoria-
tion; dermatillomania; etiology; genetics; twins
Pathological skin picking (PSP) has heretofore been unrecognized
in the diagnostic nomenclature as an independent syndrome with
diagnostic validity and clinical utility. Currently, however, it is
under recommendation for inclusion in the fifth edition of the
Skin Picking Disorder (SPD) with suggested clustering along with
other disorders of the obsessive––compulsive spectrum [Stein
et al., 2010]. The proposed DSM-5 diagnostic criteria for SPD
(2) repeated attempts to decrease or stop picking, (3) significant
being attributable to a medical condition or other mental or
substance use disorder.
Reported prevalence estimates for PSP vary in clinical and non-
and Odlaug, 2009; Hayes et al., 2009; Keuthen et al., 2010]. A
recent large-scale (N¼2,513) randomized telephonic survey of
US households reported that 1.4% of respondents satisfied criteria
for PSP parallel to those proposed for DSM-5 [Keuthen et al.,
Grant sponsor: Welcome Trust; Grant sponsor: Department of Health via
the National Institute for Health Research (NIHR) Comprehensive
Biomedical Research Centre Award; Grant sponsor: St Thomas’ NHS
Foundation Trust in partnership with King’s College London.
Conflicts of interest: none.
Benedetta Monzani, M.Sc., King’s College London, Institute of Psychiatry
PO 69, De Crespigny Park Rd., London SE5 8AF, UK.
Article first published online in Wiley Online Library
(wileyonlinelibrary.com): 22 May 2012
How to Cite this Article:
Monzani B, Rijsdijk F, Cherkas L, Harris J,
Keuthen N, Mataix-Cols D. 2012. Prevalence
and Heritability of Skin Picking in an Adult
Community Sample: A Twin Study.
Am J Med Genet Part B 159B:605–610.
? 2012 Wiley Periodicals, Inc.
accompanying distress/impact. There is some evidence to suggest
elevated PSP prevalence rates in college student samples [Keuthen
et al., 2000], possibly due to the prominence of specific dermato-
logic conditions in this age sector. Little data exist on skin-picking
cohorts with advanced age. Cross-cultural investigation of PSP
prevalence has been limited. While one study reported lower
prevalence rates in a German student sample than those for
American student skin pickers [Bohne et al., 2002], subsequent
utilization of similar operational criteria for PSP yielded more
similar prevalence rates.
Significant rates of psychiatric comorbidity [Arnold et al., 1998;
Wilhelm et al., 1999; Odlaug and Grant, 2007; Odlaug and Grant,
2008a,b] as well as distress and functional disability [Arnold et al.,
1998; Wilhelm et al., 1999; Flessner and Woods, 2006;
Neziroglu et al., 2008; Odlaug and Grant, 2008a; Tucker et al.,
2011] have been reported for PSP. Medical sequelae can vary in
ring [Odlaug and Grant, 2008a]. In more severe cases, significant
physical disfigurement, systemic infections, and even temporary
paralysis [Weintraub et al., 2000] have been reported and neuro-
surgical intervention was even warranted in one case [Kondziolka
et al., 2011].
disorders, it is thought to result from the complex interplay of
genetic and environmental factors. There is some evidence that
PSP runs in families. Elevated comorbidity rates of PSP have been
Bienvenu et al., 2009; Grant et al., 2010a; Bienvenu et al., 2012].
There is also evidence for familiality within OCD and its spectrum
disorders with greater occurrence rates of PSP in the first-degree
relatives of OCD probands than in the relatives of comparison
control probands [Bienvenu et al., 2012]. Direct comparison of
of co-occurring compulsive nail biting and were more likely to
have a first-degree relative with a grooming disorder [Grant et al.,
2010b]. In summary, considerable work remains to be done to
explicate the relative influences of genetic and environmental
variables in PSP and its relationship to other related conditions.
The twin design is ideally suited to address this question.
the prevalence of clinically significant skin-picking symptoms in a
the extent to which skin-picking behavior is explained by genetic
and environmental risk factors. To this end, we administered a
widely used measure of skin-picking symptoms which has empiri-
cally derived cut-offs and fitted twin models to decompose the
variance in the liability to skin picking into genetic, shared, and
non-shared environmental factors.
Participants were monozygotic (MZ) and dizygotic (DZ) twins
from the TwinsUK adult twin registry, based at the Department
of Twin Research and Genetic Epidemiology, King’s College
London (www.twinsuk.ac.uk). The registry consists of a volunteer
sample of Caucasian adult twins, aged between 16 and 90 years
[Spector and William, 2006] ascertained from the general popu-
lation. The registry contains an excess of female members as
historically only female twins were recruited to study conditions
of higher prevalence in women, such as osteoporosis. The registry
later expanded to allow inclusion of male twins as well. The
twin sample has been shown to be comparable to age-matched
population singletons in terms of disease related and lifestyle
characteristics [Andrew et al., 2001]. The Peas in the Pod ques-
tionnaire [Sarna et al., 1978] was used to ascertain zygosity, which
was further confirmed by DNA fingerprinting or from genome-
wide scans in cases of uncertainty. All participants provided
informed consent approved by the St Thomas’ Hospital Research
A total of 4,205 individual twins were invited to complete the
Skin-Picking Scale [Keuthen et al., 2001] over the Internet. A total
Of those, 37 participants returned an incomplete SPS and were
not included in the analyses. There were no significant differences
vs. 59% MZ, respectively). There was however a significant differ-
ence in terms of gender (12% males among responders vs. 17%
among non-responders; c2¼23.272, df¼1, P<0.01) and age
(mean 53.8 years [SD¼13.4] for responders vs. 48.2 years
[SD¼14.06] for non-responders; t¼9.712, df¼4203, P<0.01),
with non-responders more likely to be male and younger.
Assessment of Skin Picking
self-report instrument assessing the extent/severity of skin-picking
behavior.Itconsistsofsixitems,including frequency andintensity
of urges, frequency of skin-picking behavior, associated interfer-
on a 4-point Likert scale, with a total score ranging from 0 to 24.
The scale has excellent psychometric properties, with empirical
been found to differentiate between self-injurious versus non-self-
injurious skin pickers, with sensitivity of 96.4% and specificity of
92.2% [Keuthen et al., 2001]. In the current study, the SPS
demonstrated good internal consistency (Cronbach’s alpha¼.84)
and a single-factor structure, explaining 59.4% of the variance
(principal component analysis). Factor loadings ranged from 0.56
(interference) to 0.90 (urges).
TABLE I. Demographic Characteristics of the Participants
Mean age (SD) 53.8 (13.4) 52.1 (14.1) 56.9 (11.3) 34.1 (10.3)
MZ, monozygotic twins; DZ, dizygotic twins; UZ, unknown zygosity.
606 AMERICAN JOURNAL OF MEDICAL GENETICS PART B
Prevalence. Basic statistics and prevalence estimates were
computed on the total sample (N¼2,481) using STATA for
for the effects of clustering of individuals within families.
Twin analyses. Twin research has relied on different
approaches over time to examine the heritability of behavioral
traits and mental disorders, ranging from case series of twins with
the specific disorder under investigation to twin studies using a
dimensional approach [Macdonald et al., 1991]. The latter
approach views a disorder as equivalent to the extreme end of a
trait distributed along a continuum. The main advantage of the
with the full-blown disorder of interest and the resulting statistical
power issues. The current study is embedded in this tradition and
conceptualizes skin picking as a trait along a continuum, at the
severe end of which individuals can be said to be likely to fulfill
diagnostic criteria for PSP.
using Mx (http://www.vcu.edu/mx/). Male twins (N¼272), DZ
and twins for whom co-twin sex was unknown (N¼15) were
excluded as the small number of cases in these categories did not
differences in the liability to skin picking.
liability-threshold modeling was applied to (1) calculate polychoric
correlations for MZ and DZ twins (i.e., the correlation in liability
within twins) and (2) to estimate genetic and environmental influ-
ences on skin-picking behavior [for a review see Rijsdijk and Sham,
when assessing the liability to a trait/disease in a population. The
assumptions of this approach are that: (1) the ordered categories
reflect an imprecise measurement of an underlying continuous and
normal distribution of liability; and (2) the liability distribution
of the trait/disorder has one or more thresholds that discriminate
between the different categories; once the liability passes a certain
critical threshold, an individual will experience a specific trait/
disorder. For our analysis, we used three thresholds, resulting in
four classes/categories of severity of the extent of skin-picking
behavior: no symptoms (SPS score¼0); minimal symptoms (SPS
scores 1––3); moderate symptoms (SPS scores 4––6); and clinically
(as opposed to more than three) because these provided a good
representation of variability in symptom severity within our sample
while ensuring sufficient numbers of cases within each category.
Twin analyses seek to decompose the observed phenotypic
variance into A (additive genetic factors, i.e., the proportion of
phenotypic variation that can be attributed to additive genetic
factors); D (non-additive/dominance genetic factors; i.e., a single
gene of major influence and/or gene––gene interaction); C
(common/shared environment, i.e., environmental effects shared
by twins), and E (unique/non-shared environment, i.e., environ-
mental effects unique to each twin, plus measurement error).
is based on the difference in genetic sharing between MZ and DZ
pairs and on the assumption that MZ and DZ twin pairs share the
same family environment. Comparing the correlations within MZ
and DZ pairs therefore provides a first impression of the contri-
bution of genetic and environmental factors on a phenotype/trait.
separate the observed phenotypic variance into additive (A), or
dominant (D), genetic components and common (C) and unique
(E) environmental influences (including measurement error).
Polychoric correlation analyses were first performed on our
female sample (N¼2,143) to test our model assumptions and
and DZ twins. Maximum-likelihood univariate model-fitting
analyses [Neale and Cardon, 1992] were then undertaken to
estimate the contribution of genetic and environmental factors
environmental (E) components. Specifically, data were fitted to a
saturated model, in which twin correlations and thresholds are
estimated freely. Goodness of fit of the full models is then assessed
by comparing the ?2 log-likelihood c2(?2LL) value to that of the
saturated model. To explain the observed pattern of the data using
E submodels) were additionally tested and compared to the full
model. The difference in the c2value relative to the change in
parsimony [Neale and Cardon, 1992]. The Akaike Information
in the ?2LL minus twice the difference in degrees of freedom
relative fit of unnested models. More negative AIC values reflect a
superior balance between goodness-of-fit and parsimony. A com-
monly used rule of thumb also states that unnested models are
indistinguishable by AIC criterion if the difference in AIC is <2.0
[Burnham and Anderson, 2002]. A graphical representation of the
classic twin model adapted for this study is depicted in Figure 1.
Prevalence of Clinically Significant Skin Picking
As shown in Table II, about 1.2% (N¼31; mean SPS score 8.9
[SD¼2.39]) of the total sample scored 7 or higher on the SPS,
indicative of clinically significant skin picking. All of the 31 res-
ponders scoring above the cut-off value were female.
Heritability of Skin-Picking Behavior
Our results show that the MZ correlation (r¼0.42 [95% CI
0.20––0.60]) was substantially greater than the DZ correlation
(r¼0.09 [95% CI 0.001––0.42]), indicating a meaningful genetic
influenceonskinpicking.The moderateMZ correlation, however,
MZ and DZ correlations, which may be suggestive of potential
dominant genetic effects, anADE modelwasalso fittedtothedata.
The ADE and ACE models gave similar fits, with an AIC difference
MONZANI ET AL.
of <2.0. Because the ACE fitted as well as the ADE model and
because there is little power to detect dominance (D) effects in this
sample, particularly for categorical data, much larger samples of
which nested sub-models were tested. Model-fitting analyses
showed the best-fitting model for skin picking to be the AE model.
It was possible to drop the shared environmental parameter (C)
without a significant reduction in fit, while dropping A or E on the
other hand resulted in a worse or significant decrease in fit. On the
basis of a liability threshold model, approximately 40% (95% CI
19––58%) of the variation in liability to skin picking was due to
additive genetic factors, while 60% (95% CI 42––81%) of the
variation in skin picking was attributable to non-shared environ-
mental influences plus measurement error. Model-fitting results
and parameter estimates are summarized in Table III.
In this large-sample study of twin pairs from the UK, 1.2% of our
sample exceeded the severity cut-off score on the SPS, indicating
clinically significant symptoms and increased likelihood of a diag-
nosis of SPD according to proposed DSM-5 criteria. This occur-
rence rate is consistent with the prevalence estimate reported in a
were considerably older (average age 54) than those of previous
studies, our results suggest that PSP persists well into middle
adulthood. Further, these results confirm that PSP is a prevalent
disorder, at least in the West, and a reason for significant public
health concern [Tucker et al., 2011]. Given the potentially serious
medical complications associated with it, both mental health pro-
fessionals and other health practitioners, such as dermatologists,
should be aware of it, as adequate identification and diagnosis are
essential for treatment.
All of our participants with clinical-level severity scores on the
SPS were female. This parallels the female predominance of skin
pickers consistently reported in clinic samples [e.g., Arnold et al.,
picking severity though not to the same extent as documented in
clinic studies [Bienvenu et al., 2000; Keuthen et al., 2010].
indicated that it probably runs in families [Grant et al., 2010a;
design to disentangle the potential sources of this familiality.
Model-fitting analyses showed that genetic factors accounted
for approximately 40% of the genetic variance in skin-picking
FIG. 1. Twinmodelusedinthisstudy.Therectanglesrepresentthe
genetic correlations for dizygotic (DZ) twins pairs are 0.5 and
0.25, respectively as DZ twins share on average half of their
genetic make-up and stand only a 25% chance of sharing both
areassumed tobe1for both MZandDZtwins, what isknown as
the equal environment assumption. Abbreviation: A, additivie
genetic effects; D, dominance genetic effects; C, common/
shared environment; E, unique/non-shared environment.
TABLE II. Distribution of Skin Picking Symptoms and Prevalence of Problematic skin-Picking Problems Based on Empirically Defined
Cut-Off Scores on the Skin Picking Scale
No symptoms (Score¼0)
% 95% CI
% 95% CI
% 95% CI
% 95% CI
Total Sample (N¼2,481)b
Male Twins (N¼290)
Female twins (N¼2,191)
aSPS, Skin-Picking Scale.
bN¼2,518 twins returned the self-report questionnaire but the questionnaires were incomplete in 37 twins, who were excluded from prevalence estimations.
cCut-off ?7 (sensitivity 96.4%; specificity 92.2%).
608AMERICAN JOURNAL OF MEDICAL GENETICS PART B
symptoms,with non-shared environmental factors(plus measure-
ment error) explaining the remaining 60% of the variance. This
play an important role in this disorder. Shared environmental
factors, that is, those common to both twins growing up in the
same family, were negligible, suggesting that they may play a less
ment of PSP, there has been meager investigation of candidate
genes. Report of excessive grooming in mice with deletion of the
a candidate gene for human ‘‘grooming disorders’’ (i.e., PSP,
study of SAPAP3 variants in individuals with OCD who also
satisfied criteria for such ‘‘grooming disorders’’ [Bienvenu et al.,
2009], nominal associations were reported between PSP and two
single nucleotide polymorphisms (SNPs). Another study con-
ducted in South Africa reported a significant association between
a SNP within SAPAP3 and trichotillomania (n¼45), another
grooming disorder thought to be related to SPD, although this
association became non-significant after correction for multiple
testing [Boardman et al., 2011]. These preliminary results offer
promise that SAPAP3 variants could potentially be implicated in
SPD. Clearly more research is warranted to confirm the involve-
ment of this promisinggenein SPDandothergroomingand OCD
spectrum disorders. Hopefully, our results will encourage more of
such research. To our knowledge, researchers have yet to explore
potential environmental factors in the development of SPD
and, given the current findings, this remains a priority for future
Our study had some limitations. First, our criteria for classi-
fication of clinical skin pickers were based solely on severity scores
on a self-administered assessment instrument. Future studies
should employ face-to-face diagnostic ascertainment to ensure
more rigorous selection of a sample satisfying diagnostic criteria.
Second, we cannot definitively rule out medical etiologies to skin
picking in our cohort. Third, given our 60% response rate of
completion of the SPS, we cannot be sure that our sample of
skin pickers was not skewed due to self-selection variables and
our sample satisfied our SPS score criteria; thus, our data cannot
address the relative influence of genetic versus environmental
factors inPSP inmales. Finally,ourfindingsneedtobeinterpreted
the assumption of equal environment.
absence of a formal diagnosis in the DSM for this disorder. We
applaud the recommendation to include it in DSM-5 to elevate
awareness of this disabling condition, to provide uniformity of
samples across researchers, and to foster research that will result in
effective and enduring treatments. Future studies need to replicate
these results in larger sampleS with improved clinical character-
ization to further explore theinvolvement ofspecific genes andthe
role of environmental variables in elevating the risk for develop-
ment of this disorder.
The TwinsUK register is supported by the Welcome Trust and the
Department of Health via the National Institute for Health
Research (NIHR) comprehensive Biomedical Research Centre
with King’s College London.
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TABLE III. Univariate Twin Model-Fitting Results and Parameter Estimates (N¼2,143 Female Twins)
1. Saturated 1773.860 2129
2. ADE 1785.656 2138 11.796
3. ACE 1786.051 2138 12.191
1786.051 2139 12.191 10 0.27 ?7.81
5. CE1788.211 2139 14.351 10 0.16 ?5.65
6. E1800.014 2140 26.154 11 0.01
Overall fit of modela
Relative fit of modelb
Parameter estimates [95% CI]
9 0.23 ?6.20
9 0.20 ?5.81
0.18 [0.00–0.57] 0.23 [0.00–0.59] 0.58 [0.40–0.80]
0.40 [0.00–0.58] 0.00 [0.00–0.44] 0.60 [0.42–0.81]
0.32 [0.14–0.49] 0.68 [0.51–0.86]
4.15 13.964 1.00 [0–1.00]
Abbreviations: A, additive genetic effects; D, dominance genetic effects, C, common environment; E unique environmental effects; ?2LL, minus twice the log-likelihood; df, degrees of freedom; Dc2,
difference in ?2LL statistic between the sub-model and the full model; Ddf, change in degrees of freedom between the sub-model and the full model; p, probability; AIC, Akaike Information Criterion.
Bold used to highlight which of the model was the best fitting one.
difference in AIC is <2.0.
bRelative fit of the model is determined by the difference between the c2(Dc2) of full ACE model and the reduced sub-models.
cBest fitting model. Shared environmental factors (C) can be dropped without any loss in fit.
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