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Anxiety disorders are heightened in specific genetic syndromes in comparison to intellectual disability of heterogeneous aetiology. In this study, we described and contrasted anxiety symptomatology in fragile X (FXS), Cornelia de Lange (CdLS) and Rubinstein–Taybi syndromes (RTS), and compared the symptomatology to normative data for typically-developing children and children diagnosed with an anxiety disorder. Scores did not differ between children diagnosed with an anxiety disorder and (a) participants with FXS on social phobia, panic/agoraphobia, physical injury fears, and obsessive–compulsive subscales (b) participants with CdLS on separation anxiety, generalized anxiety, panic/agoraphobia, physical injury fears and obsessive–compulsive subscales, and (c) participants with RTS on panic/agoraphobia and obsessive–compulsive subscales. The results highlight divergent profiles of anxiety symptomatology between these groups.
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Vol:.(1234567890)
J Autism Dev Disord (2017) 47:3728–3740
DOI 10.1007/s10803-016-3015-y
1 3
S.I. : ANXIETY IN AUTISM SPECTRUM DISORDERS
Diverse Profiles ofAnxiety Related Disorders inFragile X,
Cornelia de Lange andRubinstein–Taybi Syndromes
HayleyCrawford1,2 · JaneWaite2· ChrisOliver2
Published online: 31 January 2017
© The Author(s) 2017. This article is published with open access at Springerlink.com
Introduction
Anxiety is evident more often in individuals with intellec-
tual disability than those of typical development. Preva-
lence rates for an anxiety disorder in children and adoles-
cents with an intellectual disability range from 3 to 21.9%
(Reardon et al. 2015; Royston et al. 2016). These preva-
lence rates are higher than those for the general popula-
tion for which the prevalence rate for typically developing
children and adolescents is 3 to 6.5% (Green etal. 2005;
Polanczyk etal. 2015). DSM-5 lists 12 types of anxiety dis-
order (American Psychiatric Association 2013): separation
anxiety disorder, selective mutism, specific phobia, social
anxiety disorder, panic disorder, panic attack, agoraphobia,
generalized anxiety disorder, substance-induced anxiety
disorder, anxiety disorder due to another medical condition,
other specified anxiety disorder and unspecified anxiety
disorder.
Genetic syndromes can be associated with a height-
ened prevalence of particular characteristics (Dykens etal.
2000); for example, heightened levels of self-injurious
behavior in Lesch–Nyhan syndrome, aggression in Angel-
man syndrome and excessive friendliness in Williams syn-
drome (see Waite et al. 2014 for a review). Furthermore,
research has indicated that some genetic syndromes, such
as Williams syndrome, 22q11.2 deletion, fragile X (FXS)
and Cornelia de Lange syndrome (CdLS), are also at
greater risk of anxiety compared to the general population
(CdLS: Basile etal. 2007; FXS: Cordeiro etal. 2011; Wil-
liams syndrome: Dykens 2003; 22q deletion: Fung et al.
2010). These genetic syndromes are often associated with
specific types of anxiety disorder. For example, anxiety in
people with Williams syndrome is more likely to be gen-
eralized, or related to specific phobias and fears, than to
social situations (Leyfer etal. 2009).
Abstract Anxiety disorders are heightened in specific
genetic syndromes in comparison to intellectual disability
of heterogeneous aetiology. In this study, we described and
contrasted anxiety symptomatology in fragile X (FXS),
Cornelia de Lange (CdLS) and Rubinstein–Taybi syn-
dromes (RTS), and compared the symptomatology to nor-
mative data for typically-developing children and children
diagnosed with an anxiety disorder. Scores did not differ
between children diagnosed with an anxiety disorder and
(a) participants with FXS on social phobia, panic/agora-
phobia, physical injury fears, and obsessive–compulsive
subscales (b) participants with CdLS on separation anxi-
ety, generalized anxiety, panic/agoraphobia, physical injury
fears and obsessive–compulsive subscales, and (c) partici-
pants with RTS on panic/agoraphobia and obsessive–com-
pulsive subscales. The results highlight divergent profiles
of anxiety symptomatology between these groups.
Keywords Anxiety· Genetic syndromes· Fragile X
syndrome· Cornelia de Lange syndrome· Rubinstein–
Taybi syndrome· Intellectual disability
* Hayley Crawford
hayley.crawford@coventry.ac.uk
1 Centre forResearch inPsychology, Behaviour
andAchievement, Coventry University, James Starley
Building (JSG12), Priory Street, CoventryCV15FB, UK
2 Cerebra Centre forNeurodevelopmental Disorders, School
ofPsychology, University ofBirmingham, Edgbaston,
BirminghamB152TT, UK
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3729J Autism Dev Disord (2017) 47:3728–3740
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Anxiety has previously been investigated in FXS, CdLS
and Rubinstein–Taybi syndromes (RTS), which form the
focus of the current study. Although previous research has
suggested a heightened risk of anxiety in these populations,
this research has not explored the symptoms of different
types of anxiety disorder using comparable assessment
instruments. Identifying the symptomatology of differ-
ent types of anxiety disorder most associated with these
genetic syndromes will further understanding of the diffi-
culties experienced by these groups. This will provide valu-
able information to clinicians, aiding them in developing
early intervention strategies and targeted syndrome-sensi-
tive interventions.
The aim of the present study is to delineate the profile
of anxiety symptomatology in individuals with FXS, CdLS
and RTS. To aid interpretation, the symptomatology of
anxiety disorders in these genetic syndromes will be com-
pared to normative data from samples of typically devel-
oping children, and children who have received a clinical
diagnosis of an anxiety disorder.
Fragile X Syndrome
FXS affects approximately 1 in 2500–5000 males and 1 in
4000–6000 females (Coffee etal. 2009; Hirst etal. 1993),
and is caused by abnormalities in the Fragile X Mental
Retardation 1 (FMR1) gene located at Xq27.3, resulting
in excessive cytosine–guanine–guanine (CGG) repeats and
reduced production of the FMRP protein. As an X-linked
disorder, males with the full mutation of FXS are more
severely affected than females, and due to these gender dif-
ferences, males form the focus of this study. A recent meta-
analysis indicated that approximately 30% of males with
FXS are diagnosed with autism spectrum disorder (ASD;
Richards etal. 2015), although a milder profile of autism
characteristics is observed than in those with idiopathic
autism (Moss etal. 2013).
Individuals with FXS are more likely to meet criteria
for an anxiety disorder compared to individuals with Wil-
liams syndrome, heterogeneous intellectual disability, and
to the general population. Cordeiro etal. (2011) reported
that 86.2% of males with FXS met criteria for one anxiety
disorder, and 60.3% met criteria for multiple disorders on
an informant interview based on DSM-IV criteria. Specific
phobia and social phobia were most commonly reported;
64.9 and 60.3% respectively. These phobias occurred more
frequently in those meeting criteria for an ASD, but this
was not statistically significant. An additional diagnosis of
ASD, however, was associated with selective mutism; the
third most commonly reported anxiety disorder in males
with FXS. The overall figures for anxiety reported by Cord-
eiro et al. (2011) are similar to those reported by Bailey
et al. (2008), in which parental reports demonstrated that
70% of males with FXS had received a formal diagnosis of
anxiety or were being treated for anxiety symptoms.
Cordeiro et al. (2011) reported that participants with
FXS demonstrated significantly higher rates of anxiety dis-
order than individuals with idiopathic intellectual disabil-
ity and individuals with Williams syndrome. This literature
highlights the heightened prevalence of anxiety in individu-
als with FXS compared to that of other syndrome groups
and those with idiopathic intellectual disability, suggesting
that anxiety is a core phenotypic feature of FXS. The pre-
sent study aims to contribute to this literature by investigat-
ing anxiety in FXS at a symptom-level.
Cornelia de Lange Syndrome
CdLS affects approximately 1 in 40,000 live births (Beck
1976) and is associated with intellectual disability, as well
as specific physical characteristics including distinctive
facial features and limb abnormalities. CdLS is caused pri-
marily by a deletion in the NIPBL gene located on chromo-
some 5 (Gillis etal. 2004; Krantz etal. 2004; Miyake etal.
2005), with fewer cases being caused by mutations on the
SMC3 gene on chromosome 10 (Deardorff etal. 2007), the
SMC1A gene (Musio etal. 2006), the RAD21 gene (Minor
etal. 2014), and the HDAC8 gene (Deardorff etal. 2012).
Similarly to FXS, CdLS is associated with an increased
risk of ASD with current prevalenceestimates around 43%
(Richards et al. 2015). In addition, and similar to FXS,
individuals show a subtly different profile of autism symp-
tomatology with more impairment in social interaction and
communication than in restricted and repetitive behavior
(Moss etal. 2013).
Anxiety has been reported in between 10 and 64% of
individuals with CdLS (Basile et al. 2007; Berney et al.
1999; Gualtieri 1991; Kline et al. 2007), and existing lit-
erature suggests that this increases with age (Basile etal.
2007; Collis et al. 2006; Liu and Krantz 2009) and IQ
(Basile etal. 2007). Although anxiety has been reported in
CdLS, the symptomatology associated with specific types
of anxiety disorder has not yet been extensively investi-
gated in this population.
Social anxiety has been studied independently of other
types of anxiety disorder in CdLS and evidence suggests
that there may be heightened levels of social anxiety when
individuals are presented with particular social demands,
such as communication (Richards etal. 2009). Collis etal.
(2006) found that behavioral indicators of social anxiety
were reported to occur in 75–100% of individuals. This is
in agreement with observations of behavioral markers of
social anxiety in CdLS, such as being shy and quiet, and
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3730 J Autism Dev Disord (2017) 47:3728–3740
1 3
high levels of selective mutism (Goodban 1993; Kline etal.
2007; Moss etal. 2016).
Rubinstein–Taybi Syndrome
RTS is a multiple congenital anomaly syndrome affecting
approximately one in 100,000–125,000 live births and is
caused by mutations, breakpoints, and microdeletions on
chromosome 16p13.3, or by mutations in the E1A Binding
Protein, P300, or CREB-binding protein (Hennekam 2006;
Lacombe et al. 1992; Petrif et al. 1995; Roelfsema etal.
2005).
Levitas and Reid (1998) reported that 31% of 13 indi-
viduals with RTS were diagnosed with a tic/obsessive
compulsive disorder. In support of this, Stevens et al.
(2011) reported that 31% of individuals with RTS had
received a psychiatric diagnosis, and that most of these
were for obsessive compulsive disorder, anxiety, or depres-
sion. Item-level analysis revealed that 33% of participants
were described as having “unreasonable” fears or anxi-
ety. However, the questionnaire used was not standardised
or validated. Rather, it consisted of ‘yes or no’ answers to
140 questions about behavior, independence, education
and medical problems, limiting the extent to which strong
conclusions can be drawn. When comparing anxiety-like
symptoms in those with RTS to those without, internalizing
behavioral problems including anxiety have been reported
to be comparable to a group matched for developmental
level, age and gender (Galéra etal. 2009).
Scores on a measure of anxiety/depression were found
to be higher in older compared to younger individuals with
RTS (Yagihashi et al. 2012). The scores were still in the
typical range, although they approached borderline clinical
cut-off in the older participants. In contrast, a measure of
internalizing, which includes features of anxiety, remained
constant over the two age groups. Scores on this subscale
were within the borderline clinical cut-off range for older
participants with RTS. Item level analyses revealed that
37.5% of younger participants and 64.5% of older par-
ticipants were reported as ‘too fearful or anxious’. Simi-
larly, 31.3% of the younger participants and 67.7% of the
older participants were reported as ‘nervous, high-strung,
or tense’. These results suggest that although anxiety is
reported in individuals with RTS, it may not be of clinical
significance.
Previous research has explored the prevalence of psychi-
atric disorders in individuals with RTS, which has revealed
mixed results. Although these studies provide useful infor-
mation, the research is limited by small sample sizes and a
lack of a comparison groups. Whilst some of these studies
have highlighted the presence of anxiety in individuals with
RTS, exploration of the symptomatology associated with
sub-types of anxiety in this population is warranted.
Summary andAims
In summary, evidence suggests the presence of anxiety in
individuals with FXS, CdLS and RTS. However, knowl-
edge of the symptoms associated with different types of
anxiety in these groups, which is important for targeted
interventions, is limited. Furthermore, cross syndrome
comparisons of anxiety in these populations have not yet
been conducted. These comparisons have the potential to
delineate the relationship between anxiety symptomatol-
ogy, the presence of a particular genetic syndrome, and
intellectual disability, which are important factors associ-
ated with heightened anxiety. Finally, the phenomenology
of anxiety in comparison to individuals with and with-
out diagnosed anxiety disorders has not been extensively
exploredin these populations.
Measuring anxiety in individuals with an intellec-
tual disability poses a challenge. Tools typically used to
assess anxiety include psychiatric interviews, clinical rat-
ing scales, and self- and parent-report measures (Bern-
stein etal. 1996). These often rely on the individualthat is
experiencing anxiety to self-identify and report symptoms,
which may not be possible for people with limited verbal
abilities. The diagnosis of anxiety disorders is based on the
presence and severity of clusters of symptoms. The present
study aims to enhance understanding of anxiety in indi-
viduals with FXS, CdLS and RTS by investigating anxiety
at this symptom-level. Symptom-based approaches have
important implications for assessment, understanding the
experiences of an individual with anxiety, and effectiveness
of treatments (see Watson 2009 for a review). This is par-
ticularly important given the difficulties in applying some
elements of the diagnostic criteria of anxiety to individuals
with an intellectual disability, and the resultant underdiag-
nosis (see Cooray and Bakala 2005 for a review).
Data are presented on parental reports of anxiety symp-
tomatology using the Spence Child Anxiety Scale-Parent
Version (SCAS-P; Spence 1999), which provides a contin-
uous measure of anxiety symptoms. Due to the heightened
prevalence of ASD, particularly in FXS and CdLS, and the
potential associations between anxiety and ASD, chrono-
logical age and adaptive ability, these associations will be
investigated. The anxiety disorders investigated in the cur-
rent study are not inclusive of every disorder listed in the
DSM-5 but do include separation anxiety, generalized anxi-
ety disorder, panic attack and agoraphobia, physical injury
fears, social phobia and obsessive–compulsive disorder.
The SCAS-P was designed as a parental report measure
to assess anxiety symptomatology in children. Although
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3731J Autism Dev Disord (2017) 47:3728–3740
1 3
the present study investigates symptoms of anxiety in chil-
dren and adults with FXS, CdLS and RTS, a parent-report
measure designed for children was deemed most appropri-
ate due to the severity and range of intellectual disability in
these populations. Self-report data, particularly in combi-
nation with other measures, is a valuable source of infor-
mation. However, due to the reliance on understanding and
labeling emotions for accurate self-report of anxiety, along-
side heightened levels of acquiescence in individuals with
an intellectual disability (Stancliffe 2000), and the severity
of intellectual disability of participants in the current study,
a parental measure was most likely to yield robust data in
this case.
The data obtained from participants with FXS, CdLS
and RTS were compared to normative data from typically
developing participants and normative data from par-
ticipants diagnosed with an anxiety disorder (Nauta etal.
2004). Although it was not possible to match the norma-
tive participant samples to the participants with FXS, CdLS
and RTS due to the rarity of the genetic syndrome groups,
the normative data serve as a benchmark for comparison,
which aids interpretation. As existing literature on anxiety
in these populations is limited, these data provide a strong
starting point for further research questions and studies to
be developed.
In this study, we address three primary research ques-
tions: (1) How do individuals with FXS, CdLS and RTS
differ in their profile of anxiety symptomatology? (2) What
is the relationship between anxiety and chronological age,
and anxiety and ASD? (3) How do individuals with FXS,
CdLS and RTS differ in anxiety symptomatology to typi-
cally developing children and individuals diagnosed with
anxiety?
Method
Participants
Parents of 19 individuals with FXS (0 female,
Mage = 24.19, SD 7.51), 13 individuals with CdLS (7
female, Mage = 18.75, SD 9.75), and 27 individuals with
RTS (17 female, Mage = 23.55, SD 10.74) completed
the measures for this study. Participants with FXS were
recruited through the database held at the Cerebra Cen-
tre for Neurodevelopmental Disorders, University of
Birmingham. Participants with CdLS and RTS were
recruited through the Cornelia de Lange Foundation (UK
and Ireland), and the Rubinstein–Taybi Syndrome UK
Support Group, respectively. All participants had previ-
ously received a diagnosis of FXS, CdLS, or RTS from a
pediatrician or clinical geneticist. Participant characteris-
tics are presented in Table1. Due to documented gender
differences in FXS, all participants with FXS were male.
Therefore, participants are not matched on sex. However,
the three participant groups are comparable for chrono-
logical age, global adaptive behavior, verbal adaptive
behavior, and severity of autism symptomatology.
Normative data on typically developing individuals
with and without a diagnosed anxiety disorder (obtained
from Nauta et al. 2004) are used in the present study.
These normative data are from 261 typical controls
aged 6–18 years (Mage = 11.5, SD 2.0) and 484 children
diagnosed with an anxiety disorder aged 6–17 years
(Mage = 10.4, SD 2.5).
Measures
The following measures were completed by the partici-
pant’s primary caregiver.
Vineland Adaptive Behavior Scale—Second Edition,
Survey Interview Form (VABS; Sparrow etal. 2005)
This semi-structured interview was administered to pri-
mary caregivers of participants with FXS, CdLS and RTS,
in order to assess adaptive behavior in the areas of commu-
nication, daily living skills and socialization. The interview
yields an Adaptive Behavior Composite (ABC) and stand-
ard scores based on a sample of 3000 children.
Table 1 Participant
characteristics and comparison
statistics for participants with
FXS, CdLS and RTS
Fragile X Cornelia de Lange Rubinstein–Taybi p value for
comparison
(n = 19) (n = 13) (n = 27)
Chronological age (SD) 24.19 (7.51) 18.75 (9.75) 23.55 (10.74) 0.247
Gender % male 100.00 46.15 37.04 <0.001
Adaptive behavior compos-
ite standard score mean
(SD)
46.05 (16.67) 50.08 (17.50) 43.59 (16.51) 0.522
Verbal adaptive behavior
standard score mean (SD)
38.47 (19.34) 47.23 (22.02) 42.30 (18.78) 0.470
SCQ total score 17.99 (6.61) 19.60 (6.56) 17.76 (6.06) 0.679
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3732 J Autism Dev Disord (2017) 47:3728–3740
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Social Communication Questionnaire (SCQ; Rutter etal.
2003)
The SCQ is an informant questionnaire designed to assess
behaviors associated with ASD such as repetitive behav-
ior, communication and social interaction. The authors of
the SCQ suggest that a score of 15 or above indicates the
presence of ASD, whereas a score of 22 or above indicates
the presence of autism. Internal consistency and concurrent
validity with the Autism Diagnostic Observation Schedule
(Lord etal. 1999) are good (Howlin and Karpf 2004).
The Spence Child Anxiety Scale—Parent Version (Spence
1999)
The SCAS-P is a 38-item informant questionnaire designed
to assess anxiety symptoms in children. The SCAS-P
assesses symptomatology associated with the following six
domains of anxiety: physical injury fears, obsessive–com-
pulsive disorder, separation anxiety, social phobia, panic/
agoraphobia, and generalized anxiety. Psychometric prop-
erties show the scale to significantly differentiate those
with and without an anxiety disorder (Nauta etal. 2004).
In addition, when used with children and adolescents with
ASD, the SCAS-P demonstrates good to excellent internal
consistency for the total score, acceptable to good internal
consistency at a subscale level, and convergent validity
with the Development Behavior Checklist-Parent Version
total score and anxiety subscale (Einfeld and Tongue 2002;
Zainal et al. 2014). Zainal et al. (2014) suggested that
psychometric properties of the SCAS-P are similar when
the measure is used with children and adolescents with
and without ASD, based on data reported by Nauta et al.
(2004), and that a diagnosis of a neurodevelopmental disor-
der such as ASD does not appear to compromise the valid-
ity of the measure. The measure has also been described as
robust for use in the ASD population (Wigham and McCo-
nachie 2014).
Procedure
The measures in this study were included in a questionnaire
pack given to parents and caregivers of participants taking
part in a larger study on cognitive and social difficulties in
FXS, CdLS and RTS (Crawford et al. 2016). Parents and
carers of participants were given the questionnaire pack
either at a syndrome support group meeting or during a
research visit. The questionnaires were either returned on
the same day or via post following the meeting or visit. The
VABS was either administered during the research visit or
over the phone following the meeting or visit.
Data Analysis
All data were subjected to the Shapiro–Wilk test for nor-
mality. Non-parametric tests were used to confirm results
from parametric tests for data that were not normally dis-
tributed. For consistency, results from parametric tests are
reported where non-parametric tests revealed the same
results. Except where mentioned, the alpha level for signifi-
cance was 0.05.
Results
Figure1 displays the mean scores on each subscale for par-
ticipants with FXS, CdLS and RTS, as well as the mean
scores from normative data on typically developing chil-
dren and children with an anxiety disorder. The total scores
on the SCAS-P were: FXS: Mean = 19.71, SD 16.50;
CdLS: Mean = 27.66, SD 13.08; RTS: Mean = 15.32, SD
11.05. The total scores on the SCAS-P from normative data
are: typically developing children: Mean = 14.2, SD 9.7;
anxiety disorder: Mean = 31.8; SD 14.1 (Nauta etal. 2004).
The percentage of participants scoring outside of the nor-
mal range, as defined by the mean + 1 standard deviation
using the national normal data, is displayed in Table2.
Syndrome Group Comparison
One-way ANOVAs revealed a significant between-groups
difference in the following subscales of the SCAS-P: sepa-
ration anxiety (F (2, 58) = 6.379, p = 0.003), generalized
anxiety (F (2, 58) = 3.667, p = 0.032), and total score (F
(2, 58) = 3.697, p = 0.031). There were no between-groups
differences in the subscales assessing panic attack and ago-
raphobia, physical injury fears, social phobia, and obses-
sive–compulsive disorder (p > 0.05). Bonferroni post-hoc
analyses revealed that differences in the separation anxi-
ety subscale were due to participants with CdLS scoring
higher than participants with FXS (p = 0.038) and RTS
(p = 0.002). Differences in the generalized anxiety subscale
were also due to participants with CdLS scoring higher
than participants with FXS (p = 0.033) and par ticipants
with RTS (p = 0.006). Finally, differences in the total score
were due to participants with CdLS scoring higher than
participants with RTS (p = 0.026).
Relationship Between Anxiety, Chronological Age
andAutism Symptomatology
Spearman’s rho correlational analyses were conducted for
each group to investigate whether there was a relationship
between any subscale on the SCAS-P and chronological
age, global adaptive behavior, verbal adaptive behavior and
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3733J Autism Dev Disord (2017) 47:3728–3740
1 3
autism symptomatology. The alpha level was adjusted to
0.01 to account for multiple correlations. Significant cor-
relations are depicted in Fig.2.
For the FXS group, the analyses revealed a positive
relationship between scores on the obsessive–compulsive
subscale and chronological age (Fig. 2a; rs (17) = 0.643,
p = 0.003), and a negative relationship between scores
on the obsessive–compulsive subscale and global adap-
tive behavior (Fig. 2b; rs (17) = −0.597, p = 0.007). For
the CdLS group, significant positive relationships were
revealed between chronological age and scores on the panic
attack and agoraphobia subscale (Fig. 2c; rs (11) = 0.688,
p = 0.009), and the obsessive–compulsive subscale
(Fig. 2a; rs (11) = 0.785, p = 0.001), and a marginally sig-
nificant positive relationship was revealed between chrono-
logical age and scores on the generalized anxiety disorder
subscale (Fig.2d;rs (11) = 0.680, p = 0.011). There were no
significant correlations between the subscales of the SCAS-
P and participant characteristics for the RTS group.
Comparison toNormative Data
One sample t tests were carried out using the mean and
standard deviation on each subscale of the SCAS-P for
each syndrome group in order to compare their data to nor-
mative data for typically developing individuals with and
without a diagnosed anxiety disorder (obtained from Nauta
etal. 2004). For children with an anxiety disorder, means
and standard deviations on each subscale of the SCAS-P
are also available by the type of anxiety disorder that they
have been diagnosed with (separation anxiety, generalized
anxiety, social phobia, panic/agoraphobia, specific phobia
and OCD). Where possible, for any subscale in which par-
ticipants with FXS, CdLS or RTS scored similarly to the
group of children with an anxiety disorder, further com-
parisons were made to investigate whether scores remained
similar when compared to children diagnosed with the sub-
type of anxiety reflected in the subscale of the SCAS-P. For
example, if participants with FXS did not score differently
-5
-3
-1
1
3
5
7
9
11
13
Mean subscale score
SCAS-P subscale
FXSCdLSRTS TD Anxiety diagnosis
*
*
*
*
*
*
*
**
**
*
*
*
**
*
*
Fig. 1 The mean scores on each subscale of the SCAS-P for each syndrome group and two normative comparison groups. Error bars represent
standard deviation, as standard error data were not available for normative data
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3734 J Autism Dev Disord (2017) 47:3728–3740
1 3
Table 2 Summary of comparisons between syndrome groups and
normative data on subscales of the SCAS-P (< group at the top of
the table scored lower than the group listed in the column, = no dif-
ference between scores, > group at the top of the table scored higher
than the group listed in the column)
Significant associations between subscale scores and participant characteristics (+ positive correlation; − negative correlation), and the percent-
age of participants scoring above the normal range, are also noted. Significant differences are indicated in bold
TD typically developing, AD anxiety diagnosis
a Marginally significant result
Fragile X (FXS) Cornelia de Lange (CdLS) Rubinstein–Taybi (RTS)
Separation anxiety <CdLS >FXS =FXS
=RTS >RTS <CdLS
=TD >TD =TD
<AD =AD <AD
Percentage of participants scoring
above normal range
26.3% 61.5% (50% of males, 71.4% of
females)
14.8% (20% of males, 11.8% of
females)
Social phobia =CdLS =FXS =FXS
=RTS =RTS =CdLS
=TD =TD <TD
=AD <AD <AD
Percentage of participants scoring
above normal range
15.8% 7.7% (16.7% of males, 0% of females) 3.7% (10% of males, 0% of females)
Generalized anxiety <CdLS >FXS =FXS
=RTS >RTS <CdLS
=TD >TD =TD
<AD =AD <AD
Percentage of participants scoring
above normal range
26.3% 61.5% (33.3% of males, 85.7% of
females)
18.5% (30% of males, 11.8% of
females)
Trajectory +Agea
Panic/Agoraphobia =CdLS =FXS =FXS
=RTS =RTS =CdLS
>TDa>TD >TD
=AD =AD =AD
Percentage of participants scoring
above normal range
47.4% 53.8% (50% of males, 57.1% of
females)
37% (50% of males, 29.4% of females)
Trajectory +Age
Physical injury fears =CdLS =FXS =FXS
=RTS =RTS =CdLS
=TD >TD =TD
=AD =AD <AD
Percentage of participants scoring
above normal range
36.8% 46.2% (33.3% of males, 57.1% of
females)
22.2% (40% of males, 11.8% of
females)
Obsessive–compulsive disorder =CdLS =FXS =FXS
=RTS =RTS =CdLS
=TD =TD >TD
=AD =AD =AD
Percentage of participants scoring
above normal range
36.8% 38.5% (33.3% of males, 42.9% of
females)
40.7% (60% of males, 29.4% of
females)
Trajectory +Age
−Adaptive behavior +Age
Total score =CdLS =FXS =FXS
=RTS >RTS <CdLS
=TD >TD =TD
<AD =AD <AD
Percentage of participants scoring
above normal range
36.8% 53.8% (50% of males, 57.1% of
females)
18.5% (30% of males, 11.8% of
females)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
3735J Autism Dev Disord (2017) 47:3728–3740
1 3
to the children with an anxiety disorder on the social pho-
bia subscale of the SCAS-P, their scores were then com-
pared to scores of children diagnosed with social phobia.
As a specific type of anxiety disorder does not represent the
physical injury fears subscale, the above comparisons were
not conducted when there were no differences between
participants with FXS, CdLS or RTS and children with an
anxiety disorder on the physical injury fears subscale. Due
to multiple analyses, the p-value was adjusted to 0.01.
Fragile X Syndrome
In comparison to normative data collected from typically
developing participants, participants with FXS only scored
marginally higher on the panic/agoraphobia subscale (t
(279) = 2.570, p = 0.01). On all other subscales, no signifi-
cant differences were revealed between participants with
FXS and normative data collected from typically develop-
ing participants (all p > 0.01).
Scores did not differ between children diagnosed with
an anxiety disorder and participants with FXS on the social
phobia subscale (t (502) = −2.170, p = 0.03), the panic
attack/agoraphobia subscale (t (502) = 0.019, p = 0.985),
the physical injury fears subscale (t (502) = −0.706,
p = 0.481), and the obsessive–compulsive disorder subscale
(t (502) = −2.033, p = 0.043). For all other subscales and
the total score, participants with FXS scored significantly
lower than the children diagnosed with an anxiety disorder
(all p < 0.01).
Cornelia de Lange Syndrome
Participants with CdLS scored higher than a normative
sample of typically developing children on the separation
anxiety subscale (t (273) = 4.671, p < .001), t he generalized
anxiety subscale (t (273) = 2.940, p = 0.004), the panic/ago-
raphobia subscale (t (273) = 3.284, p = 0.001), the physical
injury fears subscale (t (273) = 3.009, p = 0.003), and on the
total score (t (273) = 3.677, p < 0.001). No differences were
revealed between participants with CdLS and the norma-
tive sample of typically developing children on the social
phobia subscale and the obsessive–compulsive disorder
subscale (all p < 0.01).
No differences were revealed between participants with
CdLS and children diagnosed with an anxiety disorder
on any subscale (all p > 0.01), except on the social pho-
bia subscale, where participants with CdLS scored sig-
nificantly lower than children with an anxiety disorder (t
(495) = −0.704, p < 0.001). No differences were revealed
between participants with CdLS and children diagnosed
with generalized anxiety disorder on the generalized anxi-
ety subscale (t (175) = −1.411, p = 0.160).
0
5
10
15
20
25
30
35
40
45
50
0246810 12
Chronological Age
Obsessive-Compulsive Subscale Score
0
10
20
30
40
50
60
70
80
0246810 12
ABC Score
Obsessive-Compulsive Subscale Score
0
5
10
15
20
25
30
35
40
45
50
0510 15 20
Chronological Age
Panic Aack and Agoraphobia Subscale Score
0
5
10
15
20
25
30
35
40
45
50
02468101214
Chronological Age
Generalized Anxiety Disorder Subscale Score
ab
cd
Fig. 2 The relationship between participant characteristics and the SCAS-P for each syndrome group
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
3736 J Autism Dev Disord (2017) 47:3728–3740
1 3
Rubinstein–Taybi Syndrome
Participants with RTS scored significantly lower than the
normative typically developing sample on the social pho-
bia subscale (t (287) = −5.662, p < 0.001), and significantly
higher than typically developing children on both the panic
and agoraphobia subscale (t (287) = 3.163, p = 0.002) and
the OCD subscale (t (287) = 2.633, p = 0.009). Scores
between typically developing participants and participants
with RTS did not differ on the other subscales of separation
anxiety, generalized anxiety, physical injury fears, and the
total score (all p > 0.01).
Participants with RTS did not evidence significantly dif-
ferent scores to children with an anxiety disorder on the
subscales of panic/agoraphobia and obsessive–compulsive
disorder (t (509) = −0.587, p = 0.557), but they did evi-
dence lower scores than children diagnosed with obses-
sive–compulsive disorder (t (43) = −5.337, p < 0.001). For
all other subscales, participants with RTS scored signifi-
cantly lower than the children diagnosed with an anxiety
disorder (all p < 0.01). The results from the comparative
and correlational analyses are presented in Table2.
Discussion
This study conducted subscale level analysis using the
SCAS-P to identify similarities and differences in the pro-
file of anxiety symptomatology in individuals with FXS,
CdLS and RTS. The relationship between anxiety and
participant characteristics was also examined. In addition,
subscale scores on the SCAS-P were compared to norma-
tive data available from typically developing children, chil-
dren diagnosed with an anxiety disorder, and, where pos-
sible, children diagnosed with the specific anxiety disorder
reflected in each subscale of the informant report measure.
To summarise, participants with CdLS scored higher
than participants with FXS and RTS on the separation
anxiety and generalized anxiety subscales of the SCAS-P.
In addition, there were no differences between participants
with FXS and children diagnosed with an anxiety disorder
on the social phobia, panic attack/agoraphobia, obsessive-
compulsive disorder,or the physical injury fears subscales.
There were also no differences between participants with
RTS and children diagnosed with an anxiety disorder
on the panic attack/agoraphobia and obsessive–compul-
sive disorder subscales. Finally, there were no differences
between participants with CdLS and children diagnosed
with an anxiety disorder on the separation anxiety, general-
ized anxiety, panic attack/agoraphobia, physical injury and
obsessive–compulsive disorder subscales, and on the total
score. When compared to children diagnosed with specific
types of anxiety disorder reflected in the subscales of the
SCAS-P, only the scores from participants with CdLS on
the generalized anxiety subscale could not be differentiated
from those diagnosed with generalized anxiety disorder.
It is important to note that the genetic syndrome groups
were not matched to the typically developing children and/
or children diagnosed with an anxiety disorder. Therefore,
these normative data should be viewed as a benchmark
comparison to aid interpretation of the results from the
genetic syndrome groups.
Positive associations were reported between the chron-
ological age of participants with CdLS and their scores
on the generalized anxiety, panic attack/agoraphobia and
obsessive–compulsive disorder subscales, supporting exist-
ing literature indicating that heightened anxiety may coin-
cide with increasing age in this group (Basile etal. 2007;
Collis et al. 2006). The associations between anxiety and
chronological age were not seen in the RTS group and only
emerged in the FXS group on the obsessive–compulsive
disorder subscale. In addition, there was no relationship
between autism symptomatology and anxiety for any par-
ticipant group. This supports previous research indicating
no difference in anxiety symptomatology in participants
with FXS and an additional diagnosis of ASD compared
to those without an additional diagnosis (Cordeiro et al.
2011).
The findings of this study support previous literature
demonstrating elevated levels of social phobia, panic disor-
der with agoraphobia, and obsessive–compulsive disorder
in individuals with FXS compared to a matched compari-
son group (Cordeiro etal. 2011), and extends this by sug-
gesting the severity of symptomatology of these disorders
are similar in FXS to those seen in individuals diagnosed
with an anxiety disorder. In addition, heightened levels of
specific phobia have been reported in FXS (Cordeiro etal.
2011). Whilst the measure utilized in the present study
did not assess specific phobia, it did demonstrate elevated
scores on the ‘physical injury fears’ subscale, which may
be considered a specific phobia. Previous research has also
demonstrated higher rates of generalized anxiety disorder
in FXS (Cordeiro etal. 2011), a finding not replicated in
the present study. A potential reason for these contrasting
findings is the utilization of different methodologies to
study anxiety diagnosis versus anxiety symptomatology.
For example, in the present study, a parent-report measure
was used to delineate the profile and investigate the symp-
tomatology of different subtypes of anxiety, whereas the
study conducted by Cordeiro etal. (2011) investigated the
prevalence rates of individuals with FXS meeting diagnos-
tic criteria for a range of anxiety disorders. It is important
to note that, in the present study, the FXS group did not
score higher on any subscales of the measure used than
the other two genetic syndrome groups matched for adap-
tive behavior and chronological age. Therefore, the higher
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3737J Autism Dev Disord (2017) 47:3728–3740
1 3
levels of social phobia, panic with agoraphobia, physical
injury fears, and obsessive–compulsive disorder may be
related to developmental ability, although the comparison
groups have also been associated with anxiety both in the
present study and in previous literature.
The findings reported here document the severity and
breadth of anxiety symptomatology in individuals with
CdLS. In particular, individuals with CdLS demonstrated
higher levels of generalized anxiety disorder and separation
anxiety than both typically developing children and indi-
viduals with different genetic syndromes associated with
intellectual disability. For these two types of anxiety disor-
der, no differences were revealed between individuals with
CdLS and those diagnosed with an anxiety disorder, high-
lighting the severity of anxiety disorders in this population.
Aside from social phobia, participants with CdLS demon-
strated similar levels of all other types of anxiety disorders
measured here to normative data obtained from individuals
diagnosed with an anxiety disorder, thus highlighting the
broad nature of anxiety disorder in this group. The results
from the present study support previous literature sug-
gesting obsessive–compulsive features in individuals with
CdLS (Kline etal. 2007), and extends this to indicate the
range of additional anxiety disorders present in this group.
In the present study, individuals with RTS did not dem-
onstrate heightened levels of anxiety in comparison to the
other genetic syndrome groups. However, levels of panic
attack/agoraphobia and obsessive–compulsive disorder
were reported to be higher in RTS than typically develop-
ing children, and similar to those diagnosed with an anxi-
ety disorder. This supports previous literature highlight-
ing the presence of obsessive–compulsive features in this
population (Levitas and Reid 1998; Stevens etal. 2011). It
is important to note that repetitive behavior is a well-doc-
umented characteristic of RTS (Waite etal. 2015). There-
fore, the elevated scores on the obsessive–compulsive dis-
order subscale may reflect heightened levels of repetitive
behavior, rather than the full range of symptomatology
associated with obsessive-compulsive disorder.
The results reported here highlight that different types
of anxiety disorder may be problematic for individuals
with different genetic syndromes. However, it is possible
that whilst there may be similarities in the ways in which
these anxiety disorders manifest behaviorally in individu-
als with genetic syndromes and the general population,
differences may exist between these populations in the
mechanisms subserving these behaviors. This notion is
supported by the conceptual differences in anxiety that
have been reported between individuals with and with-
out ASD (Kerns etal. 2014). In particular, it may be the
case that ASD-related impairments, such as adherence
to routine, may contribute to the anxiety in individuals
with ASD that are not consistent with anxiety diagnostic
categories such as intolerance to uncertainty (Rodg-
ers et al. 2016). In the current study, elevated levels of
panic attack and agoraphobia symptomatology in indi-
viduals with FXS may be related to hypersensitivity of
sensory stimuli, a common feature of this genetic syn-
drome (Baranek et al. 2009; Cornish et al. 2008). This
behavioral characteristic may contribute to anxiety in set-
tings where sensory input is heightened, such as crowded
places like shopping centers and busy playgrounds. The
presence of anxiety in crowded places features as an
item of the panic attack and agoraphobia subscale of the
SCAS-P. Further understanding the underlying mecha-
nisms of anxiety disorder in neurodevelopmental disor-
ders is paramount to developing targeted interventions.
The results of the present study should be considered in
light of some limitations. First, whilst the genetic syndrome
groups were statistically comparable on chronological age,
these groups were not matched to the samples from which
normative data were obtained. Therefore, comparisons
between the syndrome groups and normative data groups
should be treated with caution and future research should
conduct comparisons with matched groups. Second, the
SCAS-P was designed to measure anxiety symptomatol-
ogy in young, typically developing children. There is a
lack of suitable measures of anxiety that are designed for
children and adults with an intellectual disability and fur-
ther research is required to develop such measures. Despite
the limitations, this study conducted an initial investiga-
tion into the profile of anxiety disorder and has reported
elevated levels of symptoms associated with different sub-
types of anxiety in individuals with three different genetic
syndromes. This requires further investigation using diag-
nostic parent report measures alongside behavioral obser-
vation and clinical consultation. Extrapolating these pheno-
typic differences is crucial to further understand the nature
and severity of anxiety that people with these genetic syn-
dromes experience.
Acknowledgments The research reported here was supported
by a grant from the Economic and Social Research Council (Grant
Number: ES/I901825/1) awarded to HC and by Cerebra. The authors
would like to thank all participants and their families. The authors are
indebted to the Cornelia de Lange Foundation UK & Ireland and the
Rubinstein–Taybi Syndrome Support Group for their assistance with
recruitment of children and adults with Cornelia de Lange syndrome
and Rubinstein–Taybi syndrome, respectively. The authors are grate-
ful to Robyn Dowlen and Laura Groves for their help with recruitment
and posting questionnaires to participants.
Authors’ Contributions HC conceived of the study, participated
in its design and coordination, performed the statistical analyses, par-
ticipated in the interpretation of the data, and drafted the manuscript.
JW participated in the interpretation of the data and helped to draft
the manuscript. CO conceived of the study, participated in its design
and interpretation of the data, and helped to draft the manuscript. All
authors read and approved the final manuscript.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
3738 J Autism Dev Disord (2017) 47:3728–3740
1 3
Funding This study was funded by a grant from the Economic
and Social Research council (Grant Number: ES/I901825/1) and by
Cerebra.
Compliance with Ethical Standards
Conflict of interest The authors declare that they have no conflict
of interest.
Ethical Approval All procedures performed in studies involving
human participants were in accordance with the ethical standards of
the institutional research committee and with the 1964 Helsinki decla-
ration and its later amendments or comparable ethical standards.
Informed Consent Informed consent was obtained from all indi-
vidual participants included in the study.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted
use, distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
made.
References
American Psychiatric Association. (2013). Diagnostic and statistical
manual of mental disorders (5thed.). Arlington, VA: Amercian
Psychiatric Publishing.
Bailey, D. B., Raspa, M., Olmsted, M., & Holiday, D. B. (2008). Co-
occurring conditions associated with FRM1 gene variations:
Findings from a national parent survey. American Journal of
Medical Genetics Part A, 146(16), 2060–2069.
Baranek, G. T., Roberts, J. E., David, F. J., Sideris, J., Mirrett, P. L.,
Hatton, D. D., & Bailey, D. B. (2009). Developmental trajec-
tories and correlates of sensory processing in young boys with
fragile X syndrome. Physical and Occupational Therapy in Pedi-
atrics, 28(1), 79–98.
Basile, E., Villa, L., Selicorni, A., & Molteni, M. (2007). The behav-
ioural phenotype of Cornelia de Lange syndrome: A study of 56
individuals. Journal of Intellectual Disability Research, 51(9),
671–681.
Beck, B. (1976). Epidemiology of Cornelia de Lange’s syndrome.
Acta Paediatrica, 65(4), 631–638.
Berney, T. P., Ireland, M., & Burn, J. (1999). Behavioural phenotype
of Cornelia de Lange syndrome. Archives of Disease in Child-
hood, 81(4), 333–336.
Bernstein, G. A., Borchardt, C. M., & Perwien, A. R. (1996). Anxiety
disorders in children and adolescents: A review of the past 10
years. Journal of the American Academy of Child & Adolescent
Psychiatry, 35(9), 1110–1119.
Bhuiyan, Z. A., Klein, M., Hammond, P., van Haeringen, A., Man-
nens, M. M., Van Berckelaer-Onnes, I., & Hennekam, R. (2006).
Genotype-phenotype correlations of 39 patients with Cornelia
de Lange syndrome: The Dutch experience. Journal of Medical
Genetics, 43(7), 568–575.
Coffee, B., Keith, K., Albizua, I., Malone, T., Mowrey, J., Sherman,
S. L., & Warren, S. T. (2009). Incidence of fragile X syndrome
by newborn screening for methylated FMR1 DNA. The Ameri-
can Journal of Human Genetics, 85(4), 503–514.
Collis, L., Oliver, C., & Moss, J. (2006). Low mood and social anxi-
ety in Cornelia de Lange syndrome. Journal of Intellectual Dis-
ability Research, 50, 792–792.
Cooray, S. E., & Bakala, A. (2005). Anxiety disorders in people with
learning disabilities. Advances in Psychiatric Treatment, 11,
355–361.
Cordeiro, L., Ballinger, E., Hagerman, R., & Hessl, D. (2011). Clini-
cal assessment of DSM-IV anxiety disorders in fragile X syn-
drome: Prevalence and characterization. Journal of Neurodevel-
opmental Disorders, 3(1), 57–67.
Cornish, K., Turk, J., & Hagerman, R. (2008). The fragile X con-
tinuum: New advances and perspectives. Journal of Intellectual
Disability Research, 52(6), 469–482.
Crawford, H., Moss, J., Oliver, C., Elliott, N., Anderson, G. M., &
McCleery, J. P. (2016). Visual preference for social stimuli in
individuals with autism or neurodevelopmental disorders: An
eye-tracking study. Molecular Autism, 7(1), 1.
Deardorff, M. A., Bando, M., Nakato, R., Watrin, E., Itoh, T.,
Minamino, M., etal. (2012). HDAC8 mutations in Cornelia de
Lange syndrome affect the cohesin acetylation cycle. Nature,
489(7415), 313–317.
Deardorff, M. A., Kaur, M., Yaeger, D., Rampuria, A., Korolev, S.,
Pie, J., et al. (2007). Mutations in cohesin complex members
SMC3 and SMC1A cause a mild variant of Cornelia de Lange
syndrome with predominant mental retardation. The American
Journal of Human Genetics, 80(3), 485–494.
Dykens, E. M. (2003). Anxiety, fears, and phobias in persons with
Williams syndrome. Developmental Neuropsychology, 23(1–2),
291–316.
Dykens, E. M., Hodapp, R. M., & Finucane, B. M. (2000). Genetics
and mental retardation syndromes: A new look at behavior and
interventions. Baltimore, MD: Paul H Brookes Publishing.
Einfeld, S. L., & Tongue, B. J. (2002). Manual for the developmental
behaviour checklist: Primary carer version (DBC-P) and teacher
version (DBC-T) (2nd ed.). Melbourne: Monash University Cen-
tre for Developmental Psychiatry and Psychology.
Fung, W. L. A., McEvilly, R., Fong, J., Silversides, C., Chow, E., &
Bassett, A. (2010). Elevated prevalence of generalized anxiety
disorder in adults with 22q11.2 deletion syndrome. American
Journal of Psychiatry, 167(8), 998–998.
Galéra, C., Taupiac, E., Fraisse, S., Naudion, S., Toussaint, E.,
Rooryck-Thambo, C., etal. (2009). Socio-behavioral character-
istics of children with Rubinstein–Taybi syndrome. Journal of
Autism and Developmental Disorders, 39(9), 1252–1260.
Gillis, L. A., McCallum, J., Kaur, M., DeScipio, C., Yaeger, D., Mari-
ani, A., etal. (2004). NIPBL mutational analysis in 120 individu-
als with Cornelia de Lange syndrome and evaluation of geno-
type-phenotype correlations. The American Journal of Human
Genetics, 75(4), 610–623.
Goodban, M. T. (1993). Survey of speech and language skills with
prognostic indicators in 116 patients with Cornelia de Lange
syndrome. American Journal of Medical Genetics, 47(7),
1059–1063.
Green, H., McGinnity, A., Meltzer, H., Ford, T., & Goodman, R. H.
(2005). Mental health of children and young people in Great
Britain, 2004. London: Palgrave Macmillan.
Gualtieri, C. T. (1991). Behaviour in the Cornelia de Lange syndrome
Neuropsychiatry and Behavioral Pharmacology (pp.173–186).
New York: Springer.
Hennekam, R. C. (2006). Rubinstein–Taybi syndrome. European
Journal of Human Genetics, 14(9), 981–985.
Hirst, M. C., Knight, S. J., Christodoulou, Z., Grewal, P. K., Fryns,
J. P., & Davies, K. E. (1993). Origins of the fragile X syndrome
mutation. Journal of Medical Genetics, 30, 647–650.
Howlin, P., & Karpf, J. (2004). Using the social communication ques-
tionnaire to identify “autistic spectrum” disorders associated
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
3739J Autism Dev Disord (2017) 47:3728–3740
1 3
with other genetic conditions: Findings from a study of individu-
als with Cohen syndrome. Autism: The International Journal of
Research and Practice, 8, 175–182.
Kerns, C. M., Kendall, P. C., Berry, L., Souders, M. C., Franklin, M.
E., Schultz, R. T., etal. (2014). Traditional and atypical presenta-
tions of anxiety in youth with autism spectrum disorder. Journal
of Autism and Developmental Disorders, 44, 2851–2861.
Kline, A. D., Grados, M., Sponseller, P., Levy, H. P., Balagowidow,
N., Schoedel, C., etal. (2007). Natural history of aging in Cor-
nelia de Lange syndrome. American Journal of Medical Genet-
ics Part C: Seminars in Medical Genetics, 145 C(3), 248–260.
Krantz, I. D., McCallum, J., DeScipio, C., Kaur, M., Gillis, L. A.,
Yaeger, D., etal. (2004). Cornelia de Lange syndrome is caused
by mutations in NIPBL, the human homolog of Drosophila mel-
anogaster Nipped-B. Nature Genetics, 36(6), 631–635.
Lacombe, D., Saura, R., Taine, L., & Battin, J. (1992). Confirma-
tion of assignment of a locus for Rubinstein–Taybi syndrome
gene to 16p13.3. American Journal of Medical Genetics, 44(1),
126–128.
Levitas, A., & Reid, C. S. (1998). Rubinstein–Taybi syndrome and
psychiatric disorders. Journal of Intellectual Disability Research,
42(4), 284–292.
Leyfer, O., Woodruff-Borden, J., & Mervis, C. B. (2009). Anxiety dis-
orders in children with Williams syndrome, their mothers, and
their siblings: Implications for the etiology of anxiety disorders.
Journal of Neurodevelopmental Disorders, 1(1), 4–14.
Liu, J., & Krantz, I. D. (2009). Cornelia de Lange syndrome, cohesin,
and beyond. Clinical Genetics, 76(4), 303–314.
Lord, C., Rutter, M., DiLavore, P. C., & Risi, S. (1999). Autism diag-
nostic observation schedule-WPS (ADOS-WPS). Los Angeles,
CA: Western Psychological Services.
Minor, A., Shinawi, M., Hogue, J. S., Vineyard, M., Hamlin, D. R.,
Tan, C., etal. (2014). Two novel RAD21 mutations in patients
with mild Cornelia de Lange syndrome-like presentation and
report of the first familial case. Genetics in Medicine, 537(2),
279–284.
Miyake, N., Visser, R., Kinoshita, A., Yoshiura, K.-I., Niikawa, N.,
Kondoh, T., etal. (2005). Four novel NIPBL mutations in Japa-
nese patients with Cornelia de Lange syndrome. American Jour-
nal of Medical Genetics Part A, 135(1), 103–105.
Moss, J., Nelson, L., Powis, L., Richards, C., Waite, J., & Oliver, C.
(2016). A comparative study of sociability and selective mutism
in autism spectrum disorder, Angelman, Cri du Chat, Cornelia
de Lange, Fragile X and Rubinstein–Taybi syndromes. Ameri-
can Journal on Intellectual and Developmental Disabilities, 121,
465–486.
Moss, J., Oliver, C., Berg, K., Kaur, G., Jephcott, L., & Cornish, K.
(2008). Prevalence of autism spectrum phenomenology in Cor-
nelia de Lange and Cri du Chat syndromes. American Journal of
Mental Retardation, 113(4), 278–291.
Moss, J., Oliver, C., Nelson, L., Richards, C., & Hall, S. (2013).
Delineating the profile of autism spectrum disorder character-
istics in Cornelia de Lange and fragile X syndromes. American
Journal on Intellectual and Developmental Disabilities, 118(1),
55–73.
Musio, A., Selicorni, A., Focarelli, M. L., Gervasini, C., Milani, D.,
Russo, S., etal. (2006). X-linked Cornelia de Lange syndrome
owing to SMC1L1 mutations. Nature Genetics, 38(5), 528–530.
Nauta, M. H., Scholing, A., Rapee, R. M., Abbott, M., Spence, S. H.,
& Waters, A. (2004). A parent-report measure of children’s anxi-
ety: Psychometric properties and comparison with child-report in
a clinic and normal sample. Behaviour Research and Therapy,
42, 813–839.
Oliver, C., Arron, K., Sloneem, J., & Hall, S. (2008). Behavioural
phenotype of Cornelia de Lange syndrome: Case-control study.
The British Journal of Psychiatry, 193(6), 466–470.
Petrif, F., Giles, R. H., Dauwerse, H. G., Saris, J. J., Hennekam,
R. C., Masuno, M., etal. (1995). Rubinstein–Taybi syndrome
caused by mutations in the transcriptional co-activator CBP.
Nature, 376(6538), 348–351.
Polanczyk, G. V., Salum, G. A., Sugaya, L. S., Caye, A., & Rohde,
L. A. (2015). Annual research review: A meta-analysis of the
worldwide prevalence of mental disorders in children and ado-
lescents. Journal of Child Psychology and Psychiatry, 56(3),
345–365.
Reardon, T. C., Gray, K. M., & Melvin, G. A. (2015). Anxiety dis-
orders in children and adolescents with intellectual disability:
Prevalence and assessment. Research in Developmental Dis-
abilities, 36, 175–190.
Richards, C., Jones, C., Groves, L., Moss, J., & Oliver, C. (2015).
Prevalence of autism spectrum disorder phenomenology in
genetic disorders: A systematic review and meta-analysis. The
Lancet Psychiatry, 2(10), 909–916.
Richards, C., Moss, J., O’Farrell, L., Kaur, G., & Oliver, C. (2009).
Social anxiety in Cornelia de Lange syndrome. Journal of
Autism and Developmental Disorders, 39(8), 1155–1162.
Rodgers, J., Wigham, S., McConachie, H., Freeston, M., Honey,
E., & Parr, J. R. (2016). Development of the anxiety scale for
children with autism spectrum disorder (ASC-ASD). Autism
Research, 9, 1205–1215.
Roelfsema, J. H., White, S. J., Ariyürek, Y., Bartholdi, D., Niedrist,
D., Papadia, F., etal. (2005). Genetic heterogeneity in Rubin-
stein–Taybi syndrome: Mutations in both the CBP and EP300
genes cause disease. The American Journal of Human Genet-
ics, 76(4), 572–580.
Royston, R., Howlin, P., Waite, J., & Oliver, C. (2016). Anxiety
disorders in Williams syndrome contrasted with intellectual
disability and the general population: A systematic review and
meta-analysis. Journal of Autism and Developmental Disor-
ders. doi:10.1007/s10803-016-2909-z
Rutter, M., Bailey, A., & Lord, C. (2003). The Social Communica-
tion Questionnaire. Los Angeles, CA: Western Psychological
Services.
Sparrow, S. S., Cicchetti, D. V., & Balla, D. A. (2005). Vineland-II
adaptive behavior scales: Survey forms manual. Circle Pines,
MN: AGS Publishing.
Spence, S. H. (1999). Spence children’s anxiety scale (parent ver-
sion). Brisbane: University of Queensland.
Stancliffe, R. J. (2000). Proxy respondents and quality of life. Eval-
uation and Program Planning, 23(1), 89–93.
Stevens, C. A., Pouncey, J., & Knowles, D. (2011). Adults with
Rubinstein–Taybi syndrome. American Journal of Medical
Genetics Part A, 155(7), 1680–1684.
Waite, J., Heald, M., Wilde, L., Woodcock, K., Welham, A., Adams,
D., & Oliver, C. (2014). The importance of understanding the
behavioural phenotypes of genetic syndromes associated with
intellectual disability. Paediatrics and Child Health, 24(10),
468–472.
Waite, J., Moss, J., Beck, S. R., Richards, C., Nelson, L., Arron,
K., et al. (2015). Repetitive behavior in Rubinstein–Taybi
syndrome: Parallels with autism spectrum phenomenol-
ogy. Journal of Autism and Developmental Disorders, 45(5),
1238–1253.
Watson, D. (2009). Differentiating the mood and anxiety disorders: A
quadripartite model. Annual Review of Clinical Psychology, 5,
221–247.
Wigham, S., & McConachie, H. (2014). Systematic review of the
properties of tools used to measure outcomes in anxiety inter-
vention studies for children with autism spectrum disorders. PloS
ONE, 9(1), e85268.
Yagihashi, T., Kenjiro, K., Nobuhiko, O., M, S., Kenji, K., Takao,
T., etal. (2012). Age-dependent change in behavioural feature
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
3740 J Autism Dev Disord (2017) 47:3728–3740
1 3
in Rubinstein–Taybi syndrome. Congenital Anomalies, 52(2),
82–86.
Zainal, H., Magiati, I., Tan, J. W., Sung, M., Fung, D. S. S., &
Howlin, P. (2014). A preliminary investigation of the Spence
Children’s Anxiety Parent Scale as a screening tool for anxiety in
young people with autism spectrum disorders. Journal of Autism
and Developmental Disorders, 44(8), 1982–1994.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
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... For example, the presentation of atypical social behaviour and the presence of restricted behaviour and interests differ between Cornelia de Lange and fragile X syndromes, and those syndromes and non-syndromic autism (Moss et al., 2013). Finally, for a mental health problem such as anxiety, different types of anxiety diagnosis might be more prevalent with different co-morbidities across anxiety diagnosis evident (Crawford et al., 2017). In combination, these differences in clinical course, presentation and trajectory indicate the importance for clinicians' awareness of the association between syndromic ID and the risk and presentation of mental health problems. ...
... Similarly, for profiles of specific anxiety diagnoses, our findings are consistent with previous literature. For FXS, specific phobia and social anxiety were common (Cordeiro et al., 2011;Crawford et al., 2017;Ezell et al., 2019;Gabis et al., 2011;Groves et al., 2018). For 22q11.2 deletion syndrome, specific phobia had the highest prevalence rate and OCD was common in CHARGE syndrome (Bertrán et al., 2018;Blake et al., 2005;Jolin et al., 2012;La Spata, 2019). ...
... The results can inform both clinical practice and potential future research strategies. It is important to note that the current review did not endeavour to include all syndromes associated with ID and there were papers that reported anxiety prevalence that were not identified in the scoping search that subsequently came to light during the individual syndrome searches, for example, Crawford et al. (2017) reported anxiety prevalence in Fragile X, as well as Cornelia de Lange and Rubinstein-Taybi syndromes. The decision not to conduct a scoping review according to defined guidelines e.g., PRISMA Extension for Scoping Reviews (PRISMA-ScR; Tricco et al., 2018) could be considered a limitation of the study (Peters et al., 2015). ...
Article
Full-text available
Individuals with syndromic intellectual disability are at increased risk of experiencing anxiety. Comparing prevalence estimates of anxiety will allow the identification of at-risk groups and inform causal pathways of anxiety. No known study has explored estimates of anxiety symptomatology and diagnosis, including specific anxiety profiles, across groups whilst accounting for methodological quality of studies. This systematic review and meta-analysis aimed to fill this gap. Prior to review completion, methodology and analysis plans were registered and documented in a protocol (CRD42019123561). Data from 83 papers, involving a pooled sample of 13,708 across eight syndromes were synthesised using a random effects model. Anxiety prevalence ranged from 9% (95% CI: 4-14) in Down syndrome to 73% in Rett syndrome (95% CI: 70-77). Anxiety prevalence across syndromic intellectual disability was higher than for intellectual disability of mixed aetiology and general population estimates. Substantial variability between syndromes identified groups at higher risk than others. The identification of high-risk groups is crucial for early intervention, allowing us to refine models of risk and identify divergent profiles.
... There is also a growing body of literature showing that CdLS and RSTS's behavioral phenotypes are not stable over individual developmental trajectories. In adolescence and early adulthood, internalizing and externalizing disorders might arise, enriching the clinical picture of the patient with complexity, as well as, making healthcare even more time-consuming and complicated (Basile et al., 2007;Crawford, Waite, & Oliver, 2017;Waite et al., 2015). RSTS patients are likely to exhibit specific behavioral phenotypes, including anxiety, mood instability, compulsive, and aggressive behaviors, which worsen with age (Stevens, 2002;Stevens, Pouncey, & Knowles, 2011;Yagihashi et al., 2012). ...
... Preliminary studies suggest that social anxiety and selective mutism are typical in the CdLS spectrum of psychopathology and that an upward trend is expected across the lifespan (Cochran et al., 2019;Kline et al., 2007;Moss et al., 2016). However, some studies reported no association with chronological age (Crawford et al., 2017;Wulffaert et al., 2009), whereas no studies outlined lower levels of anxiety in older individuals with CdLS, suggesting that anxiety persists or worsens with age. ...
... Overall, our results indicate that anxiety is a crucial phenotypic hallmark, independent of IQ, that increases from infancy and toddlerhood to adolescence in both CdLS and RSTS. These findings are in line with those reported by previous case reports and studies describing the onset of anxiety and nervousness during adolescence and early adulthood in RSTS (Hellings, Hossain, Martin, & Baratang, 2002;Levitas & Reid, 1998;Verhoeven, Tuinier, Kuijpers, Egger, & Brunner, 2010;Yagihashi et al., 2012) and CdLS individuals (Collis, Oliver, & Moss, 2006;Crawford et al., 2017Crawford et al., , 2020Groves et al., 2021). However, great heterogeneity exists also within the anxiety phenotype. ...
Article
Background and aim: There is mounting evidence highlighting that Cornelia de Lange Syndrome (CdLS) and Rubinstein-Taybi Syndrome’s (RSTS) behavioral phenotypes are not stable over individual developmental trajectories and that several psychiatric disorders might arise with age. Our study aims to examine the specific hallmarks of psychopathology and behavioral phenotypes in four different age ranges: infancy and toddlerhood, early childhood, middle childhood, and adolescence, in both genetic syndromes. Method: The sample included 44 patients with CdLS (48% boys, age = 6.67 ± 4.36) and 31 with RSTS (48% boys, age = 6.89 ± 4.58) recruited through follow-ups. Cognitive, behavioral, and autism assessments were carried out with Griffith's scales or the Leiter-R, the Child Behavior Checklist, and the Child Autism Rating Scales 2. Multiple ANOVA 2x4 were run to outline behavioral phenotypic age-related syndromic markers and ANCOVA to value the weight of IQ and ASD-related traits on the psychopathological outcome. Results: Findings showed that anxiety is a crucial phenotypic hallmark, independent of IQ but associated with autistic traits, that increases from infancy to adolescence in both CdLS and RSTS. Conclusion and implications: Being aware of the developmental challenges that growing children are called to face is essential for drawing up proper standards of assessment turning into target age-related interventions, ensuring these patients personalized healthcare and improvement in life quality.
... Kerns et al. (2014), reported that anxiety symptoms among children with ASD may manifest itself in typical (i.e., similar to neurotypical people, like specific phobias, somatic symptoms, and distress or worries about separating from a caregiver) and atypical (i.e., symptoms associated with autistic characteristics, such as fears related to uncertainty, social discomfort, and idiosyncratic phobias) ways. Crawford et al. (2017), compared anxiety profiles among Fragile X, Cornelia de Lange, and Rubinstein-Taybi syndrome groups and used a symptombased approach to better understand anxiety presentations. This approach identified the presence and severity of distress caused by anxiety and potentially overlapping neurodevelopmental symptoms to pinpoint areas for symptom-specific interventions to reduce anxiety (Crawford et al., 2017). ...
... Crawford et al. (2017), compared anxiety profiles among Fragile X, Cornelia de Lange, and Rubinstein-Taybi syndrome groups and used a symptombased approach to better understand anxiety presentations. This approach identified the presence and severity of distress caused by anxiety and potentially overlapping neurodevelopmental symptoms to pinpoint areas for symptom-specific interventions to reduce anxiety (Crawford et al., 2017). Overall, these studies distinguished clinically significant anxiety symptoms to encompass both typical and atypical presentations that may overlap or resemble traits of the individual's neurodevelopmental condition. ...
Article
Angelman Syndrome (AS) is a neurodevelopmental disorder most commonly caused by the impaired expression of the maternal UBE3A gene on chromosome 15. Though anxiety has been identified as a frequently present characteristic in AS, there are limited studies examining anxiety in this population. Studies of anxiety in other neurodevelopmental disorders have found disorder specific symptoms of anxiety and age specific displays of anxiety symptoms. However, there is a consistent challenge in identifying anxiety in people with neurodevelopmental disorders given the lack of measurement instruments specifically designed for this population. Given the limited information about AS and anxiety, the aims of the current project were to (a) examine symptoms of anxiety in children with AS and (b) determine the correlates of anxiety in children with AS. Participants included 42 adult caregivers of youth with AS in the AS Natural History study who completed the Developmental Behavior Checklist (DBC). The results found that 26% of the sample demonstrated elevated symptoms of anxiety and established a relationship between elevated anxiety in youth with AS and higher levels of irritability, hyperactivity, self-absorbed behaviors, and disruptive/antisocial behaviors. Findings from this research provide a foundation for tailoring evidence-based assessments and treatments for youth with AS and anxiety.
... In a study of children with fragile X syndrome, approximately 7% of children displayed behaviours indicative of anxiety, despite all individuals scoring below the anxiety threshold on the Child Behavior Checklist, a standardised measure (Sullivan et al. 2007). Similarly, on the Spence Children's Anxiety Scale, children with Cornelia de Lange syndrome scored comparably to typically developing children without a diagnosed anxiety disorder for social anxiety, and scored lower than typically developing children diagnosed with anxiety disorders (Crawford et al. 2017). This is inconsistent with reports of up to 40% of verbal children with Cornelia de Lange syndrome presenting with selective mutism, a disorder associated with social anxiety (Moss et al. 2016). ...
... Williams syndrome research and in broader anxiety research (e.g. Dodd & Porter, 2011;Crawford et al. 2017;Ng-Cordell et al., 2018;Reardon et al., 2019;Rodgers et al., 2012). The suggested clinical cut-off is 24. ...
Article
Full-text available
Background: Williams syndrome anxiety research predominantly focuses on disorder prevalence and symptomatology, categorised using standardised mental health classifications. However, the use of these assessments may not fully capture the phenotypic features of anxiety in Williams syndrome. In this study, we examined characteristics of anxiety using a formulation framework. Method: A semi-structured interview was conducted with thirteen parents of individuals with Williams syndrome (median age: 19, age range: 12-45, 8 females). Results: Various anxiety triggers were reported, including anxiety triggered by phobias, uncertainty and negative emotions in others. The range of described behaviours was diverse with both avoidant and active coping strategies for anxiety management reported. Conclusions: Many of the characteristics described were consistent with findings in the intellectual disability and typically developing literature, although novel information was identified. The study demonstrates the utility of a formulation framework to explore anxiety characteristics in atypical populations and has outlined new avenues for research.
... From psychiatric observations, there was non-specific symptoms of autism. Psychiatric observation still continue,because CdLS is a severe genetic disorder[1,2], often has another impact besides physical development disorders, and on the developmental / intellectual level disorders, autism spectrum disorders, self-injury behavior, physical conditions, and medications as well as speech difficulties, anxiety, hyperactivity, and sleep problems[3][4][5][6][7][8][9][10][11]. Psychiatric diagnose based on DSM-5 and psychometric, including: The Checklist for Autism in Toddlers (CHAT) at 18 months old and Childhood Autism Rating Scale (CARS), also consultation needed to psychological test at preschool-age (4-6 years old) for intellectual ability. ...
Article
Full-text available
Cornelia de Lange's syndrome (CdLS) is a genetic disorder characterized by developmental disorders in several organ systems, including the brain, bones, digestion, immunity, endocrine, and others. This syndrome is mainly caused by mutations in the NIPBL, SMC3, and SMC1A genes. CdLS are generally comorbid with developmental or intellectual-level disorders, autism spectrum disorders, self-injury behavior, difficulty speaking, anxiety, hyperactivity, and sleep problems. This CdLS has a significant impact on the quality of life and maladaptive function in patients, as well as causing psychological disorders for families. Therefore, the need for psychiatric assistance for family psychoeducation, psycho-social interventions and cognitive-behavioral education.
Article
Rubinstein–Taybi syndrome (RTS) is a rare genetic syndrome associated with growth delay, phenotypic facial characteristics, microcephaly, developmental delay, broad thumbs, and big toes. Most research on RTS has focused on the genotype and physical phenotype; however, several studies have described behavioral, cognitive, social, and emotional characteristics, elucidating the behavioral phenotype of RTS. The reporting of this review was informed by PRISMA guidelines. A systematic search of CINAHL, Medline, and PsychINFO was carried out in March 2021 to identify group studies describing behavioral, cognitive, emotional, psychiatric, and social characteristics in RTS. The studies were quality appraised. Characteristics reported include repetitive behavior, behaviors that challenge, intellectual disability, mental health difficulties, autism characteristics, and heightened sociability. Findings were largely consistent across studies, indicating that many characteristics are likely to form part of the behavioral phenotype of RTS. However, methodological limitations, such as a lack of appropriate comparison groups and inconsistency in measurement weaken these conclusions. There is a need for multi-disciplinary studies, combining genetic and psychological measurement expertise within single research studies. Recommendations are made for future research studies in RTS.
Article
Full-text available
Background Individuals with genetic syndromes show unique profiles of repetitive behaviours and restricted interests (RRBs). The executive dysfunction account of RRBs suggests that in autistic (AUT) individuals executive function impairments underpin RRBs, but not communication and social interaction autistic characteristics. Aims To 1) describe profiles of behavioural manifestations of executive function (EF behaviours) and 2) explore the relationship between EF behaviours and autistic traits across individuals with Cornelia de Lange (CdLS), fragile X (FXS) and Rubinstein-Taybi syndromes (RTS), and AUT individuals. Method Carers completed the Behavior Rating Inventory of Executive Function – Preschool Version and the Social Communication Questionnaire. Data reporting on 25 individuals with CdLS (Mage = 18.60, SD = 8.94), 25 with FXS (Mage = 18.48, SD = 8.80), 25 with RTS (Mage = 18.60, SD = 8.65) and 25 AUT individuals (Mage = 18.52, SD = 8.65) matched on chronological age and adaptive ability were included in analyses. Results All groups showed impairments across EF behaviours compared to two-to-three-year-old typically developing normative samples with no differences between groups. Different EF behaviours predicted RRBs in the syndrome groups with no associations found in the AUT group. Conclusions Syndrome related differences should be considered when developing targeted interventions that focus on EF behaviours and/or RRBs in these groups.
Article
Background There is evidence that social impairments in Cornelia de Lange Syndrome (CdLS) differ from those observed in idiopathic autism as they are characterized mainly by social anxiety. However, the knowledge of the fundamental features of social anxiety symptoms in this target population is limited. This brief systematic review aims to investigate the relationship between social anxiety and CdLS through multiple cross-sectional comparisons. Methods PRISMA-P guidelines were followed, and the literature research was conducted in Pubmed, EBSCOhost, Google Scholar, and ScienceDirect using “Cornelia de Lange Syndrome” or “CdLS” and “social anxiety” as search terms. Results Six articles met the eligibility criteria. Results show that heightened levels of social anxiety in CdLS individuals occur before and after the social engagement and are mediated by both the nature of the social demand and the familiarity of the examiner they interact with. Limitations The interpretation of results is limited by the wide heterogeneity of patients’ age and sample size across the reviewed studies, and by the absence of a unique observational procedure to detect behaviors indicative of social anxiety in syndromic individuals. Conclusions These findings have considerable clinical implications for intervention planning which might be generalized to all people with intellectual disability linked to a genetic syndrome.
Article
Background Cornelia de Lange syndrsome (CdLS) is a rare genetic syndrome with notable impaired expressive communication characterised by reduced spoken language. We examined gesture use to refine the description of expressive communication impairments in CdLS. Methods During conversations, we compared gesture use in people with CdLS to peers with Down syndrome (DS) matched for receptive language and adaptive ability, and typically developing (TD) individuals of similar chronological age. Results As anticipated the DS and CdLS groups used fewer words during conversation than TD peers (P < .001). However, the CdLS group used twice the number of gestures per 100 words compared with the DS and TD groups (P = .003). Conclusions Individuals with CdLS have a significantly higher gesture rate than expected given their level of intellectual disability and chronological age. This result indicates the cause of reduced use of spoken language does not extend to all forms of expressive communication.
Article
Early identification of behavioral risk markers for anxiety is essential to optimize long-term outcomes in children with neurodevelopmental disorders. This study analyzed attentional avoidance and its relation to anxiety and autism spectrum disorder (ASD) symptomatology during social and nonsocial fear conditions in toddlers with fragile X syndrome (FXS) and Down syndrome (DS). Toddlers with FXS and DS exhibited increased nonsocial attentional avoidance relative to typically developing (TD) toddlers. Attentional avoidance was not related to anxiety symptom severity in any group; however, higher ASD symptom severity was related to more social attentional avoidance in the FXS and TD groups. Findings suggest that there may be different underlying mechanisms driving attentional avoidance across neurodevelopmental disorders.
Article
Full-text available
Individuals with specific genetic syndromes associated with intellectual disability (ID), such as Williams syndrome (WS), are at increased risk for developing anxiety disorders. A systematic literature review identified sixteen WS papers that could generate pooled prevalence estimates of anxiety disorders for WS. A meta-analysis compared these estimates with prevalence estimates for the heterogeneous ID population and the general population. Estimated rates of anxiety disorders in WS were high. WS individuals were four times more likely to experience anxiety than individuals with ID, and the risk was also heightened compared to the general population. The results provide further evidence of an unusual profile of high anxiety in WS. Electronic supplementary material The online version of this article (doi:10.1007/s10803-016-2909-z) contains supplementary material, which is available to authorized users.
Article
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Background Recent research has identified differences in relative attention to competing social versus non-social video stimuli in individuals with autism spectrum disorder (ASD). Whether attentional allocation is influenced by the potential threat of stimuli has yet to be investigated. This is manipulated in the current study by the extent to which the stimuli are moving towards or moving past the viewer. Furthermore, little is known about whether such differences exist across other neurodevelopmental disorders. This study aims to determine if adolescents with ASD demonstrate differences in attentional allocation to competing pairs of social and non-social video stimuli, where the actor or object either moves towards or moves past the viewer, in comparison to individuals without ASD, and to determine if individuals with three genetic syndromes associated with differing social phenotypes demonstrate differences in attentional allocation to the same stimuli. Methods In study 1, adolescents with ASD and control participants were presented with social and non-social video stimuli in two formats (moving towards or moving past the viewer) whilst their eye movements were recorded. This paradigm was then employed with groups of individuals with fragile X, Cornelia de Lange, and Rubinstein-Taybi syndromes who were matched with one another on chronological age, global adaptive behaviour, and verbal adaptive behaviour (study 2). Results Adolescents with ASD demonstrated reduced looking-time to social versus non-social videos only when stimuli were moving towards them. Individuals in the three genetic syndrome groups showed similar looking-time but differences in fixation latency for social stimuli moving towards them. Across both studies, we observed within- and between-group differences in attention to social stimuli that were moving towards versus moving past the viewer. Conclusions Taken together, these results provide strong evidence to suggest differential visual attention to competing social versus non-social video stimuli in populations with clinically relevant, genetically mediated differences in socio-behavioural phenotypes.
Article
Full-text available
Few comparative studies have evaluated the heterogeneity of sociability across a range of neurodevelopmental disorders. The Sociability Questionnaire for People with Intellectual Disability (SQID) was completed by caregivers of individuals with Cornelia de Lange (n = 98), Angelman (n=66), Fragile X (n=142), Down (n=117) and Rubinstein Taybi (n=88) syndromes and autism spectrum disorder (ASD; n = 107). Between groups and age-band (,12yrs; 12-18yrs;.18yrs) comparisons of SQID scores were conducted. Rates of behaviors indicative of selective mutism were also examined. Fragile X syndrome achieved the lowest SQID scores. Cornelia de Lange, ASD, and Fragile X groups scored significantly lower than Angelman, Down and Rubinstein Taybi groups. Selective mutism characteristics were highest in Cornelia de Lange (40%) followed by Fragile X (17.8%) and ASD (18.2%). Age-band differences were identified in Cornelia de Lange and Down syndrome.
Article
Full-text available
Autism spectrum disorder (ASD) phenomenology is reported to be more common in individuals with some genetic syndromes than in the general population; however, no meta-analysis has provided prevalence data within and between syndromes. In this systematic review and meta-analysis, we aimed to synthesise data from a wide range of papers to provide accurate estimates about ASD phenomenology in genetic and metabolic syndromes. We identified syndromes reported as most likely to be associated with ASD. We searched Ovid PsycINFO, Ovid MEDLINE, Ovid Embase, and PubMed Central for English-language papers published from database creation up to early 2014 with use of syndrome-specific keywords and a set of ASD keywords. We screened and extracted papers that had ASD prevalence data for ten or more people within a genetic syndrome. With use of a prespecified set of reliable criteria, we applied quality weighting to papers and estimated a quality-effects prevalence of ASD phenomenology for each syndrome. We then calculated relative risks to compare ASD between all syndromes and also calculated odds ratios to compare prevalence with the general population taking the current estimate of one in 68 people. We identified 168 papers reporting the prevalence of ASD phenomenology and found widely varying methods and quality of data. Quality-weighted effect prevalence estimates of ASD phenomenology were established for Rett's syndrome (female individuals only 61%), Cohen's syndrome (54%), Cornelia de Lange syndrome (43%), tuberous sclerosis complex (36%), Angelman's syndrome (34%), CHARGE syndrome (30%), fragile X syndrome (male individuals only 30%; mixed sex 22%), neurofibromatosis type 1 (18%), Down's syndrome (16%), Noonan's syndrome (15%), Williams' syndrome (12%), and 22q11.2 deletion syndrome (11%). Relative risks and the odds ratio compared with the general population were highest for Rett's syndrome and Cohen's syndrome. In all syndromes, odds ratios showed ASD phenomenology to be significantly more likely than in the general population. ASD phenomenology varied between syndromes, but was consistently more likely than in the general population. Further research is needed in these populations, including how ASD in genetic and metabolic syndromes differs from idiopathic autism and what that can tell us about the mechanisms underlying ASD. Cerebra. Copyright © 2015 Elsevier Ltd. All rights reserved.
Article
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Five hundred and fifty four school children, 8 to 12 years of age, completed the Spanish version of the Spence Children's Anxiety Scale (SCAS), the ITA-UNAM, which measures anxiety in children, and the CES-D measuring depression. The study investigated the structural model of the SCAS found by Spence. Two models were tested using confirmatory factor analysis: one 38-item and a second 32-item model, both involving 6 related first-order factors loading in a higher-order factor. The 38-item model provided a reasonably good ft, confirming the one reported by Spence. However, the second model provided the best ft of the data. Both models coincide with the most common anxiety disorders classified by the DSM-IV-TR. Further psychometric analyses reinforced construct validity of the SCAS and showed acceptable internal consistency.
Article
Full-text available
Background The literature on the prevalence of mental disorders affecting children and adolescents has expanded significantly over the last three decades around the world. Despite the field having matured significantly, there has been no meta-analysis to calculate a worldwide-pooled prevalence and to empirically assess the sources of heterogeneity of estimates.Methods We conducted a systematic review of the literature searching in PubMed, PsycINFO, and EMBASE for prevalence studies of mental disorders investigating probabilistic community samples of children and adolescents with standardized assessments methods that derive diagnoses according to the DSM or ICD. Meta-analytical techniques were used to estimate the prevalence rates of any mental disorder and individual diagnostic groups. A meta-regression analysis was performed to estimate the effect of population and sample characteristics, study methods, assessment procedures, and case definition in determining the heterogeneity of estimates.ResultsWe included 41 studies conducted in 27 countries from every world region. The worldwide-pooled prevalence of mental disorders was 13.4% (CI 95% 11.3–15.9). The worldwide prevalence of any anxiety disorder was 6.5% (CI 95% 4.7–9.1), any depressive disorder was 2.6% (CI 95% 1.7–3.9), attention-deficit hyperactivity disorder was 3.4% (CI 95% 2.6–4.5), and any disruptive disorder was 5.7% (CI 95% 4.0–8.1). Significant heterogeneity was detected for all pooled estimates. The multivariate metaregression analyses indicated that sample representativeness, sample frame, and diagnostic interview were significant moderators of prevalence estimates. Estimates did not vary as a function of geographic location of studies and year of data collection. The multivariate model explained 88.89% of prevalence heterogeneity, but residual heterogeneity was still significant. Additional meta-analysis detected significant pooled difference in prevalence rates according to requirement of funcional impairment for the diagnosis of mental disorders.Conclusions Our findings suggest that mental disorders affect a significant number of children and adolescents worldwide. The pooled prevalence estimates and the identification of sources of heterogeneity have important implications to service, training, and research planning around the world.
Chapter
The Cornelia de Lange Syndrome (CDLS) is a mental retardation syndrome characterized by short stature, hirsutism, and facial and skeletal anomalies (de Lange, 1933, 1938; Hawley et al., 1985). It is interesting by virtue of association with a unique constellation of behavioral and temperamental attributes. One thinks first of self-injurious behavior (SIB), of course, and CDLS has been compared, in this regard, to the Lesch-Nyhan syndrome.
Article
Many children with autism spectrum disorder (ASD) experience high levels of anxiety. A widely used measure for typically developing children is the Revised Child Anxiety and Depression Scale (RCADS). However, such anxiety measures may require adaptation to accommodate characteristics of those with ASD. An adapted version of the RCADS was created based on empirical evidence of anxiety phenomenology in ASD, which included additional items related to sensory anxiety, intolerance of uncertainty, and phobias. Content validity was refined during focus groups with parents. Polychoric factor analysis was undertaken on data from 170 children with ASD, aged 8-16, and their parents. This process resulted in the creation of a new 24 item scale (self and parent report) each with four subscales: Performance Anxiety, Uncertainty, Anxious Arousal, and Separation Anxiety, with evidence of good reliability and validity. The freely available Anxiety Scale for Children - ASD, Parent and Child versions (ASC-ASD) has promising psychometric properties including good internal consistency, validity, and 1 month test-retest reliability. Autism Res 2016. & 2016 International Society for Autism Research, Wiley Periodicals, Inc.