Autism Spectrum Disorder in an Unselected Cohort of Children with Neurofibromatosis Type 1 (NF1)
Journal of Autism and Developmental Disorders
Autism Spectrum Disorder in an Unselected Cohort of Children with Neurofibromatosis Type 1 (NF1)
S. Eijk 0 1 2 4 5 6
S. E. Mous 0 1 2 4 5 6
G. C. Dieleman 0 1 2 4 5 6
B. Dierckx 0 1 2 4 5 6
A. B. Rietman 0 1 2 4 5 6
P. F. A. de Nijs 0 1 2 4 5 6
L. W. ten Hoopen 0 1 2 4 5 6
R. van Minkelen 0 1 2 4 5 6
Y. Elgersma 0 1 2 4 5 6
C. E. Catsman‑Berrevoets 0 1 2 4 5 6
R. Oostenbrink 0 1 2 4 5 6
J. S. Legerstee 0 1 2 4 5 6
0 Department of Neuroscience, Erasmus Medical Centre Rotterdam , 3015 CN Rotterdam , The Netherlands
1 Department of Clinical Genetics, Erasmus Medical Center , P.O. Box 2040, 3000 CA Rotterdam , The Netherlands
2 ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus Medical Center Sophia Children's Hospital , P.O. Box 2060, 3000 CB Rotterdam , The Netherlands
3 J. S. Legerstee
4 Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center-Sophia Children's Hospital , Room Sp-2509, P.O. Box 2060, 3000 CB Rotterdam , The Netherlands
5 Department of General Paediatrics, Erasmus Medical Center-Sophia Children's Hospital , P.O. Box 2060, 3000 CB Rotterdam , The Netherlands
6 Department of Pediatric Neurology, Erasmus Medical Center-Sophia Children's Hospital , P.O. Box 2060, 3000 CB Rotterdam , The Netherlands
In a non-selected sample of children with Neurofibromatosis type 1 (NF1) the prevalence rate of autism spectrum disorder (ASD) and predictive value of an observational (ADOS)-and questionnaire-based screening instrument were assessed. Complete data was available for 128 children. The prevalence rate for clinical ASD was 10.9%, which is clearly higher than in the general population. This prevalence rate is presumably more accurate than in previous studies that examined children with NF1 with an ASD presumption or solely based on screening instruments. The combined observational- and screening based classifications demonstrated the highest positive predictive value for DSM-IV diagnosis, highlighting the importance of using both instruments in children with NF1.
Neurofibromatosis type 1; Autistic traits; Autism spectrum disorder; Prevalence; Autism diagnostic observation schedule; Social responsiveness scale
Department of Child and Adolescent Psychiatry/Psychology,
Erasmus Medical Center-Sophia Children’s Hospital, P.O.
Box 2060, 3000 CB Rotterdam, The Netherlands
Neurofibromatosis type 1 (NF1) is an autosomal dominant
disorder affecting 1 in 2500–3000 individuals
et al. 2009)
. The disorder is inherited in half of the cases,
and in the other half the mutation is de novo
(Messiaen et al.
. The NF1 gene encodes for the protein neurofibromin,
which activates the protein RasGTPase
RasGTPase functions as a negative regulator of Ras, a protein
involved in the regulation of the cell cycle, growth and
differentiation. As a result of mutations in NF1, a decrease
in neurofibromin activity causes increased cell growth.
Affected individuals are recognized by the representation
of at least two distinctive physical features, including
caféau-lait spots, intertriginous freckling, Lisch nodules,
neurofibromas, optic pathway gliomas or distinctive bone-forming
(Williams et al. 2009)
Children with NF1 often experience cognitive and
(Hachon et al. 2011; Lehtonen et al. 2013)
Generally, intelligence scores of affected children are
significantly lower compared to the general population, and
learning problems and attention-deficit-hyperactivity
disorder (ADHD) are common. However, the problems are
highly variable across the NF1 population
(Lehtonen et al.
. Besides these common cognitive and behavioral
characteristics, social difficulties have been reported in
children with NF1. Children with NF1 often have poorer social
skills, tend to be socially isolated and rejected by peers, and
experience problems in social information processing
(Barton and North 2004; Huijbregts et al. 2010; Noll et al. 2007)
Similar to the general population, social problems in
children with NF1 are more prevalent in boys (Garg et al. 2016)
and in children with low intellectual functioning
and De Sonneville 2011)
Recently, studies have focused on the prevalence and
profile of autism spectrum disorders (ASD) in children with
NF1. Compared to global ASD prevalence estimates of
0.8% in the general population
(Baxter et al. 2015)
screening-based prevalence rates of clinical ASD symptoms of
13–29% have been found in children with NF1. On top of
this, an additional percentage of 27–31% of children were
found to show subclinical symptoms, leading to total
estimated screening-based prevalence rates of ASD symptoms
ranging between 30–56%
(Adviento et al. 2014; Constantino
et al. 2015; Garg et al. 2013; Van Eeghen et al. 2013; Walsh
et al. 2013)
. In a recent, internationally compiled sample of
children with NF1 (N = 531), a screening-based prevalence
rate of clinical ASD of 13% and an additional prevalence
rate of 26% of subclinical symptoms was reported
et al. 2016)
, resulting in a total prevalence rate of ASD traits
of 39%. It should be noted, though, that these estimates are
based on screening instruments. Because of their
measurement purposes, these instruments are highly sensitive and
thus may result in a biased (slightly overestimated) ASD
The possible overestimation of the screening-based
prevalence rates highlights the importance of studies assessing
clinical ASD prevalence rates. Only a few studies have
examined clinically assessed ASD prevalence rates in
children with NF1. In the studies by Garg et al. (2013) and
Plasschaert et al. (2015), children with a presumption of
ASD (preselected based on elevated scores on a screening
instrument) were assessed with clinical diagnostic
instruments. In these subsamples of children with NF1, ASD
prevalence estimates of 25%
(Garg et al. 2013)
(Plasschaert et al. 2015) were reported. Because these
prevalence rates were based on samples of children with an initial
suspicion of autism spectrum problems, these prevalence
rate are probably not representative for the general pediatric
NF1 population as a whole. To our knowledge, there are
no reports available in the literature in which an unselected
sample of children with NF1 has been clinically assessed
The primary aim of this study was to examine the
prevalence of clinically assessed ASD in children with
NF1 visiting a specialized NF1 outpatient clinic without
a presumption of ASD. The secondary aim was to
investigate the predictive value of a screening instrument and
an observational assessment in relation to clinical
DSMIV ASD diagnosis in a pediatric NF1 population. Also, the
association of gender, age and intellectual functioning with
ASD diagnosis was examined.
Eligible for participation were children (aged 2–10) with
either genetically or clinically diagnosed NF1. All children
were patients of ENCORE, a multidisciplinary expertise
center for genetic neurocognitive disorders (including NF1)
in Rotterdam. As part of the standard multidisciplinary care
for and follow-up of children with NF1, these children were
routinely referred to the Department of Child and Adolescent
Psychiatry/Psychology, between August 2011 and August
2016. In the current study, a total of 128 children between 2
and 10 years of age with NF1 were enrolled (45.3% female,
mean age = 5.27, SD = 1.81).
As standard procedure, all children underwent
neuropsychological evaluation and clinical assessment of autistic
symptomatology. Additionally, parents and teachers
provided information concerning the child’s development and
the primary caregiver was asked to complete several
questionnaires, including the SRS. The data in this prospective
study was collected based on a fixed protocol in the context
of the longitudinal follow-up for the assessment of clinical
symptoms in children with NF1.
ASD Symptom Screening
ASD symptoms were screened with the social
responsiveness scale (SRS)
(Constantino et al. 2003)
. Completion of
the 65 items by one of the parents provides information
concerning functioning in the domains social awareness,
social cognition, reciprocal social communication, social
motivation, and autistic mannerisms. The total raw score,
the sum of the 65 items, can be converted into a T-score
(M = 50; SD = 10) using a Dutch normative reference group
(Constantino and Gruber 2015)
. T-scores of 60 or higher
indicate mild to moderate problems, and T-scores of 76 or
more indicate severe (clinical) problems. The SRS has been
shown to be a valid and reliable instrument the scores are
independent from IQ scores (Constantino et al. 2003).
Observational Assessment of ASD
Observational assessment of ASD was carried out with the
autism diagnostic observation schedule-generic (ADOS-G)
(Lord et al. 1999)
and the autism diagnostic observation
schedule—second edition (ADOS-2)
(Lord et al. 2012)
most cases (i.e. 88.3%), the ADOS-2 was used. With the
ADOS, social interaction, play and imaginative skills are
assessed. The ADOS was performed by trained and
certified psychologists. Depending on the developmental age and
level of expressive language of the child, one of the four
available modules of the ADOS was chosen. The ADOS
has been shown to be a reliable and valid measure for ASD
symptoms (Gotham et al. 2007).
ADOS-G scores were converted to ADOS-2 scores
according to the manual
(Lord et al. 2012)
classifications were obtained and to enable comparison between
ASD severity across the four different modules, continuous
calibrated severity scores (CSS) were calculated
et al. 2009; Hus et al. 2014; Hus and Lord 2014)
. The CSS
range from zero to ten with zero indicating no or very little
symptoms and ten indicating severe ASD symptoms.
Clinical (DSM‑IV) Diagnosis
A clinical DSM-IV diagnosis of ASD was established by a
multidisciplinary team consisting of a child and adolescent
psychiatrist and psychologists, combining information from
all assessments, questionnaires, observation of the child
and heteroanamnestic information provided by parents and
Depending on the child’s age, the level of intellectual
functioning was assessed with either the wechsler preschool and
primary scale of intelligence (WPPSI-III)
or the wechsler intelligence scale for children-iii (WISC-III)
. Reliability and validity of these
intelligence tests have been demonstrated. Standardized verbal-,
performance-, and full scale IQ scores were calculated
(M = 100, SD = 15). For one child, a nonverbal intelligence
test (i.e. the Wechsler Non Verbal scale of Ability; WNV)
(Wechsler and Naglieri 2006)
was used, for which the total
IQ score was calculated as well. In two children, assessment
with the Wechsler scales was not possible due to a
developmental delay. In these children, assessment of intellectual
functioning was done using the Bayley Scales of Infant and
Toddler Development third edition
, and a
developmental quotient was calculated (developmental age/
chronological age × 100, with M = 100, SD = 15).
To study the prevalence of ASD, frequencies of the SRS
classifications, ADOS-2 classifications, and clinically
derived DSM-IV diagnosis were calculated. Sensitivity,
specificity, positive predictive (PPV) and negative
predictive values (NPV) were calculated to assess the screening
accuracy of the instruments’ classifications. The association
of intelligence and age with clinically derived DSM-IV ASD
diagnosis was examined with independent t tests. Missing
full-scale IQ scores were imputed using mean imputation.
The association of gender with clinically derived DSM-IV
ASD diagnosis was examined with a Chi square test. Data
were analyzed using IBM SPSS Statistics version 22. Results
were considered statistically significant if the (two-tailed)
alpha level was below .05. Sensitivity, specificity, PPV and
NPV values were interpreted according to the guidelines
Patient characteristics are summarized in Table 1. Of the
total sample of 128 children, 58 were female (45.3%).
The mean age at assessment of the sample was 5.27 years
(SD = 1.81). Intelligence scores were significantly lower
than the general population mean of 100 (SD = 15; total
IQ t(122) = − 9.40, p < .001, verbal IQ t(123) = − 6.77,
p < .001, performance IQ t(124) = − 9.24, p < .001).
Mutations in NF1 were detected as described before
Minkelen et al. 2014)
. The mutations were familiarly inherited in
17.2% (N = 22) of the children and de novo in 41.4% (N = 53)
of the children. In 41.4% of the cases it was unknown
whether the mutation was familial or de novo, caused by
the fact that parents were not genetically tested, one of the
parents was not genetically tested, or the child was not
genetically tested yet. The SRS questionnaire was completed by
the primary caregiver in 103 children. The mean SRS total
T-score was 54.7 (SD = 12.60), which is significantly higher
compared to the general population mean of 50 (SD = 10),
t(102) = 3.79, p < .001. There were no significant
differences between the group of children with and without
available SRS scores regarding gender, intelligence scores, age,
ADOS CSS or DSM-IV diagnosis.
Of the 128 children with NF1 included in the analyses, 14
received a clinical DSM-IV ASD diagnosis, resulting in a
prevalence rate of 10.9%. Based on the SRS, 8.7% of the
patients achieved scores in the ‘severe’ (clinical) category
(T ≥ 76) and 16.5% in the ‘mild to moderate’ category
(T ≥ 60), leading to a total prevalence rate of 25.2%. For the
ADOS a total percentage of 18.8% was found, with 10.2%
of the children having an autism classification and 8.6% of
the children met criteria for an ASD classification. These
percentages are lower than the percentages reported earlier
with in-depth assessments
(Garg et al. 2013; Plasschaert
et al. 2015)
Sensitivity, specificity, positive predictive (PPV) and
negative predictive values (NPV) were computed to assess the
screening accuracy of the ADOS’ and SRS’ classifications
in relation to a DSM-IV ASD diagnosis. The results are
displayed in Table 2.
With an SRS total T-score cutoff of T≥ 60 (subclinical),
the sensitivity in relation to the DSM-IV diagnosis was
fair (.72) and the specificity was good (.82). With a cutoff
of T ≥ 76 (clinical), sensitivity was poor (.46) and
specificity was excellent (.97). In this population of children
with NF1, the PPV was poor (.35) when using the SRS
cutoff of T ≥ 60, demonstrating a low probability that a
child with NF1 with a positive (T ≥ 60) SRS score is being
identified as having ASD according to the DSM-IV. Using
this same cutoff of T≥ 60, the NPV was excellent (.96),
indicating a high probability that a child with NF1 with a
negative score (T < 60) on the SRS is correctly identified
as not having ASD according to the DSM-IV. Using the
more stringent (clinical) cutoff of T ≥ 76, the PPV was
poor (.63) and the NPV was excellent (.95).
For the ADOS classification, the sensitivity (.64) was
poor and the specificity was good (.89). In this population
of children with NF1, the PPV (.45) was poor,
demonstrating a low probability that a child with NF1 with an ADOS
classification is being identified as having ASD according
to the DSM-IV. The NPV was excellent (.95), indicating a
high probability that a child with NF1 without an ADOS
classification is correctly identified as not having ASD
according to the DSM-IV.
The sensitivity of the combined classification (classified
with ASD on both the ADOS and SRS) was poor using
both the T ≥ 60 and T ≥ 76 SRS T-score cutoffs (.46 and
.27, respectively). The specificity for both combined
classifications was excellent (.98 and .99, respectively). In this
population of children with NF1, for both combined
classifications the PPV was fair (.71 and .75, respectively) and
the NPV was excellent (.93 and .91, respectively).
In order to explain the finding of the substantially
increased PPV when using the combined classification,
an in-depth examination of the distribution of ADOS and
SRS scores was performed. The number of participants
with an SRS classification (for both T ≥ 60 and T ≥ 76)
and ADOS classification were compared to the number
of participants with a classification on both instruments.
The results are displayed in Table 3. As can be seen, the
percentage of classification agreement is low for both the
ADOS and SRS T ≥ 60 and the ADOS and SRS T ≥ 76
(i.e. 8.7% and 4.9%). Figure 1 demonstrates that the SRS
and ADOS both classify and fail to classify unique cases:
a number of children with a SRS score of T ≥ 60 or T ≥ 76
are classified by the ADOS as ‘non-spectrum’ and a
number of children with an ADOS ASD classification had a
SRS T-score below 60.
Fig. 1 Scatterplot illustrating
the distribution of SRS total
T-scores (dotted lines indicate
the SRS total cutoff scores
T ≥ 60 and T ≥ 76) for the two
(non-spectrum and ASD), demonstrating
low agreement between the
There were no significant differences in full-scale, verbal,
and performance intelligence scores between the group
of children with and without DSM-IV ASD diagnosis
(Table 2). Significantly more boys (N= 11) were clinically
diagnosed with ASD according to the DSM-IV criteria
compared to girls (N = 3). The group of children with a clinical
ASD diagnosis was significantly older (mean age = 6.36)
compared to the group without diagnosis (mean age = 5.13)
The present study aimed to examine the prevalence of ASD
in a sample of children with NF1 without a presumption
of autistic symptoms. In our cohort of children with NF1,
we found a DSM-IV based ASD prevalence rate of 10.9%.
Secondly, we aimed to assess the predictive value of a
screening-based and observational instrument on the clinical
DSM-IV ASD diagnosis. In this population of children with
NF1, combining the classifications from both instruments
yielded the highest predictive value on DSM-IV diagnosis.
Thirdly, we examined several possible correlates and found
a significant effect of gender and age on DSM-IV ASD
diagnosis. Our reported DSM-IV based ASD prevalence rate of
10.9% endorses previous reports of an increased prevalence
rate in children with NF1 as compared to the general
population prevalence of about 0.8%
(Baxter et al. 2015)
confirms the involvement of the various mutations leading to
NF1 in the development of ASD
(Morris et al. 2016)
. To our
knowledge, this is the first study in which ASD prevalence is
assessed in a sample of children with NF1 without an initial
presumption of ASD. The prevalence reported in this study
is likely more representative and accurate for the general
pediatric NF1 population than reported by previous studies
(Garg et al. 2013; Plasschaert et al. 2015)
Earlier reports of ASD prevalence rates have reported
screening-based prevalence rates from 13 to 33%
et al. 2014; Constantino et al. 2015; Garg et al. 2013; Van
Eeghen et al. 2013; Walsh et al. 2013)
and prevalence rates
based on a observational instrument of 25–26%
(Garg et al.
2013; Plasschaert et al. 2015)
. The results from the
observational- and screening instrument demonstrate that not
all children with a classification on one of the instruments
receive an eventual DSM-IV diagnosis. This implies that a
group of children is present with subclinical ASD symptoms
in the sample studied here. The percentage of children with
screening-based subclinical ASD symptoms (i.e. 16.5%)
found in this study supports this. The question for future
research remains whether this group of children with NF1
with subclinical ASD symptoms will receive a DSM-IV
ASD diagnosis at a later age.
The substantial increase in PPV for the combination
of the instruments’ classification scores demonstrates the
complementing effect of the two instruments in predicting
DSM-IV ASD diagnosis. This might be explained by the
difference in the assessment methods (e.g. informant and
situation) of the instruments. In case of the SRS, one of the
primary caregivers of the child acts as informant for ASD
symptoms, whereas in case of the ADOS a trained and
certified clinician observes and scores the behavior of the child.
Different informants provide valuable and unique
information with regard to ASD symptomatology, due to
discrepancies in perspective and context, as demonstrated by
et al. (2015
). Moreover, the ADOS assessment is performed
in a semi-structured observational lab-setting, whereas the
SRS assesses the child’s behavior in daily life. The
instruments provide unique information concerning autistic
symptoms in the child; the classification agreement between the
instruments is low (Table 3) and both instruments classify
and fail to classify unique cases (Fig. 1). This underlines the
importance of combining the findings from both instruments
for ASD assessment in clinical practice.
The group of children with a DSM-IV ASD diagnosis was
significantly older compared to the group without diagnosis.
It has been demonstrated that children with ASD and other
developmental, psychiatric, or neurologic comorbidities are
usually diagnosed with ASD at a later age, possibly because
the ASD symptoms are ‘masked’ by the comorbidities
et al. 2010)
or because assessment and treatment of somatic
complaints are prioritized. As a consequence, our sample of
children with NF1 might receive a DSM-IV ASD diagnosis
at a later age or receive subclinical scores.
Intelligence scores were not related to the DSM-IV ASD
diagnosis. This could be due to the lack of dispersion in
intelligence scores in our sample, resulting in a
homogenous sample regarding cognitive functioning. Examination
of gender effects demonstrated an increased number of boys
with a DSM-IV ASD diagnosis. This result is in line with
the male predominance of ASD in the general population
and the presumed female protective effect
(Halladay et al.
and with reports of higher prevalence rates of ASD
in boys with NF1
(Garg et al. 2016)
A limitation in the current study is that SRS was not
available in all children in this study. The parental response
rate of 80% might have provided skewed results, since the
exact reason for not completing the SRS questionnaire is
unknown. However, there were no significant differences
between the group of children from responders and
nonresponders regarding gender, intelligence scores, age,
DSMIV ASD diagnosis or ADOS total CSS, ADOS social affect
CSS and ADOS restricted/repetitive behaviors CSS, thus
it seems unlikely that differences in SRS scores between
responders and non-responders would have been present.
Secondly, the combination of the ADOS and ADI-R are
generally advocated in ASD research, but the ADI-R was not
included in the current study. The data in the current study
was initially collected for patient care and the
implementation of the ADI-R would have been too time-consuming.
Instead, a thorough intake and heteroanamnestic interview
with the parents was conducted. Thirdly, the sample used
in this study included a number of two- and three year old
children and ASD is often diagnosed at a later age. However,
the instruments used in the current study are valid
instruments for the assessment of autism and autism spectrum
disorders in young children. Fourthly, since the data was
collected from 2011 onwards, the ASD diagnoses were
DSMIV based instead of DSM-V. Finally, although all children
within ENCORE with NF1 were referred to the Department
of Child and Adolescent Psychiatry/Psychology for
neuropsychological evaluation and assessment of autistic
symptomatology, a clinical referral bias might still be present in
our sample. The problems experienced in children with NF1
are highly variable, and the severities of the difficulties
fluctuate across the population
(Lehtonen et al. 2013)
of children with for example more severe physical
difficulties or developmental delays might shift their focus to these
more pressing problems and postpone neuropsychological
and behavioral assessment. At the same time, parents of
children who experience limited to no difficulties might not see
the need for neuropsychological or behavioral assessment.
Nevertheless, the sample studied here is a key strength of the
study; to our knowledge, this is the first study in which an
unselected cohort of children with NF1 is referred for
assessment of autistic symptomatology, regardless of an ASD
presumption. The relatively large sample size of children with
NF1 further strengthens our results. All children underwent
uniform neuropsychological and ASD assessments, enabling
unique comparisons between different instruments for ASD
symptoms and comparison with the eventual DSM-IV ASD
diagnosis, as well as the examination of potential correlates
with the diagnosis.
A DSM-IV ASD prevalence rate of 10.9% demonstrates that
the prevalence of ASD symptoms in children with NF1 is
considerably higher compared to the general population,
hereby emphasizing the importance of ASD assessment in
this population. Our results underline the relevance of the
use of multiple instruments (screening- and observational)
for clinicians in order to correctly identify as many
individuals with NF1 with ASD as needed. In addition to the group
of children with a diagnosis, a substantial group of children
with subclinical ASD symptoms is present as well, as was
demonstrated by the screening- and observational
instrument. This demonstrates the necessity to structurally follow
the development of children with NF1.
Acknowledgments This research was financially supported by the
Sophia Children’s Hospital Fund (Rotterdam, the Netherlands) under
Grant Number SSWO B14-02. Funders were not involved in the design
of the study, nor in data collection, analysis, interpretation or writing
Author Contributions SE wrote the manuscript with support from all
the authors. Supervision was carried out by JSL and SEM. Analyses
were performed and supervised by SE, JSL, SEM, BD, and PFAN.
GCD, ABR, LWH, RM, YE, CECB, RO contributed to the
interpretation of the results. All authors discussed the results and contributed to
the final manuscript.
Compliance with Ethical Standards
Conflict of interest The authors declare that they have no conflict of
Ethical Approval All procedures performed in studies involving human
participants were in accordance with the ethical standards of the
institutional and/or national research committee and with the 1964 Helsinki
declaration and its later amendments or comparable ethical standards.
Informed Consent This retrospective study was approved by the
Medical Ethics Committee of the Erasmus Medical Center, the Netherlands
(MEC-2015-203). Written informed consent was formally waived as
there is no patient burden and no privacy concern.
Open Access This article is distributed under the terms of the
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mmons.org/licenses/by/4.0/), which permits unrestricted use,
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