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. Author manuscript; available in PMC: 2026 Sep 5.
Published before final editing as: J Pediatr Neuropsychol. 2026 Sep 3:10.1037/jpn0000048. doi: 10.1037/jpn0000048

Executive Functioning, Attention Problems, and Social Impairments in Youth with Neurofibromatosis Type 1 and Autism Spectrum Disorder

Manali Zope 1, Lisa Blaskey 1,2, Jeffrey I Berman 1,2, Michael J Fisher 1,2, Timothy PL Roberts 1,2, Matthew C Hocking 1,2
PMCID: PMC13543690  NIHMSID: NIHMS2192382  PMID: 42699036

Abstract

Objectives:

Youth with Neurofibromatosis Type 1 (NF1) and children with Autism Spectrum Disorder (ASD) exhibit social impairments and challenges in executive functioning and attention. Biopsychosocial models underscore the interplay between cognitive processes and social functioning and could inform intervention development. This study evaluated whether diagnostic group moderated associations between cognitive functioning and social impairments in youth with NF1 and youth with ASD.

Participants and Methods:

Youth ages 8–12 (M = 10.3) with NF1 (n = 29), ASD (n = 35), and typically developing controls (TDC) (n = 26), matched on age, sex, and race, completed neuropsychological evaluations. Caregivers completed questionnaires assessing executive function and social behavior. Analyses evaluated group differences in cognitive and social functioning, and whether diagnostic group moderated the associations between cognitive processes and social impairments.

Results:

Significant correlations between parent-reported executive functioning and attention problems and social impairments were observed only for the NF1 and ASD groups. Moderation analysis revealed behavior regulation and attention problems were similarly related to social impairments across all three groups, while metacognition was significantly associated with social impairments only for the NF1 and ASD group. Auditory attention was not significantly associated with social impairments for any group.

Conclusions:

Findings highlight shared and distinct cognitive-social associations across NF1 and ASD groups. Interventions targeting executive functioning and attention may improve social functioning for children with NF1 and ASD. Future longitudinal work assessing the underlying neurocognitive mechanisms of social impairments in these populations is needed.

Introduction

Children with neurodevelopmental disorders, such as neurofibromatosis type 1 (NF1) and Autism Spectrum Disorder (ASD), often exhibit social challenges, including fewer reciprocal friendships, increased social isolation, and higher rates of peer rejection and bullying (Barton & North, 2004; Holland et al., 2019; Johnson et al., 1999; Kasari & Rotheram-Fuller, 2007; Noll et al., 2007; Schroeder et al., 2014). Such poor social outcomes and isolation in childhood often persist into adulthood and are shown to have detrimental impacts on overall health and quality of life by impacting biological, psychological, and behavioral processes (Holt-Lunstad, 2021; OSG, 2023; Pride et al., 2013). The U.S Surgeon General’s 2023 advisory highlighting the significance of social connection to overall health outcomes underscores the need to address these significant social impairments, especially for children with NF1 and ASD.

NF1 is a genetic disorder caused by a de novo or inherited loss-of-function mutation in the NF1 gene and impacts around 1 in 3000 individuals (Friedman, 1999). Mutations in the NF1 gene lead to tumor predisposition and altered neurodevelopment through a disinhibition of the RAS-MAPK transduction pathway. This disinhibition impacts neuronal cell signaling, migration, proliferation, and myelination causing downstream disruptions in GABAergic neurotransmission, synaptic plasticity, long-term potentiation, and the development of white matter tracts in the brain (Cui et al., 2008; Mayes et al., 2013; Payne et al., 2010; Violante et al., 2016; Wang et al., 2012). These neurodevelopmental alterations have been implicated in the varying manifestations of social and cognitive impairments within the NF1 population (Adviento et al., 2013; Hachon et al., 2011). Notably, ~60% of children present with features of ASD, with 6–32% having a diagnosis of ASD (Garg et al., 2013; Hocking et al., 2024; Hyman et al., 2005). ASD is characterized by impairments in social interaction and communication and the presence of restricted interests and repetitive behaviors (APA, 2013). Like NF1, alterations in RAS signaling, neuronal connectivity, and synaptic function have been implicated in ASD etiology (Adviento et al., 2013; Levitt & Campbell, 2009). NF1 can be considered a model single-gene disorder for understanding ASD symptomology, as the specific downstream effects of the RAS-MAPK disruption from NF1 can be understood in an isolated manner. Knowledge of the shared social mechanisms between children with NF1 and non-syndromic ASD will further our understanding of the association between RAS-MAPK disruptions and social challenges.

The Socio-Cognitive Integration of Abilities Model (SOCIAL) by Beauchamp and Anderson (2010) provides a key framework for understanding the underlying mechanisms of social outcomes in children with NF1 and ASD. This biopsychosocial model underscores the interplay between biological factors (such as neurodevelopment), cognitive domains (attention-executive, communication, and socio-emotional), and overall social competence (ability of child to implement social processes and behaviors to achieve social goals). Within this framework, attention and executive functioning (EF) are associated with social outcomes as they are fundamental for the processing of social information and regulating behavior and emotion in social contexts. The SOCIAL model is particularly relevant for NF1 and ASD populations due to the prevalence of increased rates of executive functioning and attention challenges in these populations.

EF and attention deficits are a core cognitive phenotype in children with NF1 and youth with ASD. These children exhibit EF impairments in behavioral regulation (i.e., inhibition, shifting, emotional control) and metacognition (i.e., initiation of tasks, working memory, organization, and monitoring behavior) across both parent-report and task-based measures (Beaussart et al., 2018; Payne et al., 2012, 2019; Plasschaert et al., 2016). Around 43–60% of children with NF1 have symptoms of Attention Deficit Hyperactivity Disorder (ADHD), with an estimated 30%−50% fulfilling criteria for diagnosis (Morris et al., 2016; Plasschaert et al., 2014; Walsh et al., 2012). In ASD samples, around 31–39% of children fulfill diagnostic criteria for ADHD, with an additional 24% exhibiting symptoms (Leyfer et al., 2006; Rong et al., 2021).

Studies applying cognitive-social frameworks such as the SOCIAL model have found associations between executive functioning and attention and social functioning. In multiple studies in children with ASD, several domains of executive functioning and social attention impairments were associated with parent-reported social skills and outcomes (Bertollo & Yerys, 2019; Gilotty et al., 2002; Greene et al., 2020; Hanley et al., 2014). For children with NF1, EF (specifically inhibition) and attention are associated with social processing and social skills across parent-report and task-based measures, with children with NF1+ADHD having the highest risk for social impairments (Barton & North, 2004; Chisholm et al., 2018; Glad et al., 2021; Hocking et al., 2024; Huijbregts & de Sonneville, 2010; Martin et al., 2012; Mautner et al., 2002; Pride et al., 2013). Attention has also been found to partially mediate the relationship between executive functioning and social outcomes in children with NF1 (Haebich et al., 2021). These findings could have implications for social interventions for these populations, as attentional control interventions have improved social competence in children with ADHD (Greenberg, 2006).

Despite shared neurodevelopmental alterations and similar social challenges and cognitive deficits in executive functioning and attention across children with NF1 and ASD, few studies have directly compared cognitive-behavioral relationships across these diagnostic groups. Multi-domain, cross-diagnostic investigations are needed to identify both shared and population-specific cognitive-behavioral relationships. Understanding whether these cognitive-behavioral mechanisms are moderated by diagnosis and population-specific can support the development of tailored interventions.

The aims of this investigation are 1) to compare profiles of executive functioning, attention, and social impairments across groups of children with NF1 (without ASD), ASD (non-NF1), and typically developing controls (TDC), and 2) to evaluate whether cognitive-social associations are moderated by diagnosis, and thus population-specific. We hypothesized that the NF1 group would have a similar profile of cognitive and social impairments to the ASD group compared to TDC, with impairments being milder in the NF1 group. We also hypothesized that executive functioning and attention would be significantly associated with social impairments in all three groups given the SOCIAL model, however, these associations would be stronger for the NF1 and ASD groups given the added influence of neurodevelopmental differences and increased variability across domains.

Methods

Procedure

This investigation is a secondary analysis, using data from two prior investigations. NF1 data was from a larger neuroimaging study investigating the neurobiological mechanisms underlying ASD in NF1, that was conducted at a large, urban pediatric medical center. ASD and TDC data were drawn from a sample who participated in an NIH-funded grant, at the same medical center, exploring electrophysiological correlates of language impairment in ASD between 2015 and 2020. All procedures were approved by the medical center’s Institutional Review Board. The medical center’s NF1 and ASD registry and medical team were used to identify potentially eligible patients. Following eligibility screening, written informed consent and child assent were obtained from all eligible participants prior to participation. Trained neuropsychologists conducted neuropsychological evaluations. Caregivers completed questionnaires reporting social, behavioral, and psychological functioning of the child. Families were compensated for the study visit and received feedback letters with the results of the evaluation.

Sample

NF1: Participants were youth ages 8–12 years old with a confirmed diagnosis of NF1. Children with premature birth (<34 weeks), serious birth complications, prior treatment for a brain tumor, any metallic implants, any other genetic conditions (aside from NF1), or severe head trauma impacting neurological functioning were excluded from the study. Additionally, children with NF1 and a diagnosis of ASD were removed from the larger study sample, to assess NF1-specific mechanisms. Out of 151 families with children with NF1 that were approached about the study, 34 families participated, and 29 children with NF1-only were included in the final sample. Fourteen children in the final sample also had a clinician concern for ADHD, identified using the Clinical Best Estimate (CBE) approach integrating behavioral ratings forms (e.g., Child Behavior Checklist), and past history (concerns of attention/hyperactivity documented in medical and IEP/educational records) (Hocking, 2024). Recruitment for the NF1 sample took place between July 2019-February 2020, July-November 2020, and February-August 2021, with pauses caused by the COVID-19 pandemic. Aside from many passive refusals, concerns about the time commitment and COVID-19 were among the top reasons for declining.

ASD and TDC: 61 participants (35 ASD, 26 TDC) who were age- and race-matched to the NF1 cohort were drawn from the original sample. All subjects in both the ASD and TD groups were native English speakers with no known genetic syndromes, neurological disorders (e.g. epilepsy, cerebral palsy, TBI) or sensory impairments (somatosensory, hearing, visual). All participants scored at or above the 2nd percentile (SS > 70) on at least one index of verbal or nonverbal intellectual functioning from the Wechsler Intelligence Scale for Children- 5th editions (Wechsler, 2014). Estimated Full Scale IQ was obtained from the WISC General Ability Index (GAI).

All children screened for inclusion in the ASD group had a prior ASD diagnosis, typically made by an expert clinician in the outpatient autism clinic of the study’s academic medical center setting, and more rarely, by community providers or schools. Expert ASD research diagnostician licensed child psychologists provided study diagnostic evaluations, confirming the original diagnosis in the ASD group and ruling out ASD in the TD group. Study diagnostic classification of ASD was assigned when empirically-established cut-offs were exceeded on both the Autism Diagnostic Observation Schedule (ADOS-2) and parent report on the Social Communication Questionnaire (SCQ) (Lord et al., 2000; Lord et al 2012; Rutter et al., 2003). In combination with the ADOS, exceeding empirically established cut-offs by parent report on both the Social Responsiveness Scale and Autism Spectrum Rating Scale also led to ASD diagnostic confirmation if the SCQ did not corroborate diagnosis. The parent-completed Autism Diagnostic Interview-Revised (ADI-R; Rutter, LeCouteur, & Lord 2003) was administered for any participants who entered the study without a formal ASD diagnosis made by an expert clinician (e.g., ASD educational classification only) and for any child with a prior ASD diagnosis for whom a diagnostic discordance existed (e.g., a child who exceeded ADOS diagnostic cut-offs but was below SCQ and SRS-2 cut-offs). 13 children in the ASD group also had a clinician concern of ADHD, also identified using the CBE approach outlined earlier.

TD-specific inclusion criteria included scoring below the cut-off for ASD on the ADOS-2 and ASD parent questionnaires and performance above the 16th percentile (SS>85) on an index of language ability, the Clinical Evaluation of Language Fundamentals- 5th Editions (CELF-5; Semel et al 2013). Per parent report, TD subjects had no first-degree relatives with ASD and also had never been diagnosed with the following: intellectual disability, speech/language disorder, learning disability, ADHD, or psychiatric conditions including bipolar disorder, obsessive compulsive disorder, schizophrenia, conduct disorder, depression, or anxiety disorder.

Measures

The Social Responsiveness Scale 2nd Edition (SRS-2) is a parent-report questionnaire that quantifies the presence of social impairments that are associated with ASD (Constantino, 2012). The SRS-2 yields a Total social impairment T-score (m = 50, SD = 10), by aggregating the child’s challenges in social awareness, social cognition, social communication, social motivation, and the presence of restricted interests and repetitive behaviors. Higher scores indicate greater social impairments across subdomains, with T-scores > 59 indicating mild impairment, T-scores > 65 indicating moderate impairment, and T-scores > 75 indicating severe impairment and very strong evidence for ASD. The SRS-2 has been found to be related to other measures of social impairments and has a good internal consistency (Cronbach’s α = 0.95) in clinical samples (Constantino, 2012).

The Wechsler Intelligence Scale for Children, 5th edition (WISC-V) was administered to assess the child’s overall intellectual functioning (to understand group characteristics) and their attention and working memory skills. The WISC-V is a well-validated measure of cognitive functioning that is widely used in NF1 and ASD research (Wechsler, 2014). Overall intellectual functioning was reported using the Full-Scale IQ (m = 100, SD = 15). The child’s attention skills were assessed using the Digit Span Forward scaled score (m = 10, SD = 2), wherein the child was asked to repeat a sequence of numbers with increasing length. The child’s working memory skills were assessed using the Digit Span Backwards scaled score (m = 10, SD = 2), wherein the child had to repeat the sequence of numbers in reverse order.

The Behavior Rating Inventory of Executive Function (BRIEF) is a parent-report questionnaire that assesses the child’s everyday behaviors that are associated with executive functioning across the main indices: behavioral regulation and metacognition (Gioia, 2000). The behavioral regulation index (BRI) encompasses the child’s inhibition, shifting focus, and emotional control abilities, while the metacognitive index (MI) assesses initiation, working memory, planning/organizing, organization, and monitoring skills. The BRIEF yields T-scores for each subscale and index and an overall score, with scores above 65 indicating areas of concern. There is a high internal consistency for the BRIEF parent report (Cronbach’s α = 0.80–0.98) (Gioia, 2000).

The Child Behavior Checklist (CBCL) is a parent-report measure assessing the child’s emotional and behavioral symptoms across eight syndrome scales and six DSM-oriented scales (Achenbach, 2001). The attention subscale was used as a parent-report measure of attention within this analysis, with T-scores between 65–69 indicating borderline problem severity, and T-scores > 70 indicating clinical problem severity. The measure has a high test-retest reliability and internal consistency.

Analysis

Participant demographic and relevant variables were reported using descriptive statistics, and Pearson chi-square analyses and ANOVAs compared these variables across diagnostic groups. IQ was not held as a covariate in analysis to preserve group characteristics and due to its potential collinearity with cognitive measures of interest (Dennis, 2009). ANOVAs evaluated overall differences in diagnostic groups across social impairments, executive functioning, and attention measures. Games-Howell post-hoc analyses were conducted following the ANOVAs to assess specific inter-group differences and their directionalities across metrics. Preliminary associations between social impairments on the SRS-2 and executive functioning and attention across both parent-report and task-based measures was assessed using Pearson correlation analyses. These Pearson correlations were conducted on both the full sample and within group. Moderation analysis was conducted using the PROCESS macro in SPSS which uses regressions to evaluate the main effects of executive functioning and attention metrics on social impairments and assess whether these associations varied by diagnostic group (Hayes, 2018). Scatterplots were created to depict the moderation effects.

Results

Participants

After removing children with NF1+ASD from the sample and case-matching the ASD sample to the NF1 groups, the final sample included 90 children (29 children with NF1, 35 children with ASD, and 26 TDC). Across all groups, children were on average 10.3 ± 1.38 years old at the time of their study visit. There were no group differences on age, sex, or race of the participant. However, there were significant group differences in FSIQ (F[2,80]=12.9, p < .01) with a Games-Howell post-hoc test indicating that the TDC (M = 114.71 ± 14.95) had a significantly higher FSIQ than both the NF1 (M = 93.59 ± 14.36) and ASD (M = 95.23 ± 17.27) groups, with no significant differences between NF1 and ASD. See Table 1 for additional group characteristics.

Table 1.

Group Characteristics

NF1 (n = 29) ASD (n = 35) TD (n = 26) Test Statistic (df) p-value
N ± SD or N (%) Range N ± SD or N (%) Range N ± SD or N (%) Range
Age (years) 10.40 ± 1.56 10.18 ± 1.27 10.35 ± 1.36 0.22 (2,87) NSa
Sex 3.62 (2) NSb
 Male 14 (48.3) 22 (62.9) 19 (73.1)
 Female 15 (51.7) 13 (37.1) 7 (26.9)
Race 7.20 (6) NSb
 Black 4 (13.8) 7 (20) 6 (23.1)
 Pacific Islander 2 (5.7)
 White 25 (86.2) 23 (65.7) 18 (69.2)
 Mixed 7 (8.6) 2 (7.7)
Clinician Concern ADHD 14 (48.3) 13 (37.1) 0
FSIQ 93.59 ± 14.36
63 – 125		 95.23 ± 17.27
69 – 125		 114.71 ± 14.95
84 – 145		 12.9 (2,80) p < .001a
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a

ANOVA

b

Pearson chi-square

NS = Not significant

Comparing Profiles of Social Impairments, Executive Functioning and Attention Across Diagnostic Groups

See Table 2 for descriptive analysis across domains and comparisons across groups.

Social Impairments:

Over a quarter of the NF1 sample (27.6%), and a majority of the ASD sample (88.6%) had parent ratings of mild-to-severe social impairments on the SRS-2. The NF1 and ASD samples yielded significantly higher SRS-2 total scores compared to the TDC (F[2,87]=85.3, p < .001). Social impairments in the ASD group were also significantly higher than the NF1 group (p < .001), with a mean difference of 22.2 T-score points (over 2 standard deviations).

Executive Functioning:

On both the BRIEF Behavioral Regulation Index and Metacognitive Index, 24.1% of children with NF1 and 60–63% of children with ASD had significant parent-reported concerns. On Digit Span Backwards, 9.5% of children with NF1 and 35.7% of children with ASD had below average performance. Children with NF1 and ASD exhibited significantly more executive functioning deficits compared to TDC on the BRIEF BRI (F[2,87]=36.4, p < .001) and MI indices (F[2,87]=38.7, p < .001). Deficits on the BRIEF BRI and MI were milder for the NF1 group compared to the ASD group (p < .001). On Digit Span Backwards, significant differences were only seen between the ASD and TDC group (F[2,65]=7.71, p < .001).

Attention:

On the CBCL Attention Problems subscale, parents rated 31% of children with NF1 and 60% of children with ASD with borderline-to-clinical attention problems. On Digit Span, 38.1% of children with NF1 and only 32.1% of children with ASD exhibited below average attention. Both children with NF1 and ASD had greater parent-reported attention problems compared to TDC (F[2,87]=25.6, p < .001). These parent-reported attention problems were milder for the NF1 group than the ASD group (p < .05). The NF1 and ASD groups also exhibited significantly lower attention skills compared to TDC on Digit Span Forward (F[2,65]=9.06, p < .001). There were no significant differences on Digit Span Forward between the NF1 and ASD group.

Preliminary Analysis: Associations between Executive Functioning, Attention, and Social Impairments

See Table 3a. for full sample correlations, and Table 3b. for group-specific correlations.

Table 3a.

Full Sample Means, Standard Deviations, and Correlations

Measure n M SD 1 2 3 4 5
1. SRS-2 Total Score 90 59.1 16.7
2. BRIEF BRI 90 55.1 13.6 0.82**
3. BRIEF MCI 90 57.7 13.7 0.75** 0.76**
4. CBCL Attention 90 60.9 10.6 0.73** 0.68** 0.85**
5. Digitspan Forward 68 9.44 3.16 −0.27* −0.20 −0.32** −0.31**
6. Digitspan Backwards 68 9.79 3.12 −0.34** −0.25* −0.42** −0.41** 0.59**
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*

p < .05

**

p < .01

Table 3b.

Means, Standard Deviations, and Correlations Across Diagnostic Groups

Group Measure n M SD 1 2 3 4 5
NF1 1. SRS-2 Total Score 29 53.3 9.78
2. BRIEF BRI 29 52.9 11.1 0.78**
3. BRIEF MCI 29 57.1 12.9 0.52** 0.58**
4. CBCL Attention 29 61.1 9.64 0.56** 0.62** 0.88**
5. Digitspan Forward 21 8.43 2.94 −0.10 −0.19 0.22 −0.09
6. Digitspan Backwards 21 9.76 2.72 −0.05 −0.08 −0.23 −0.07 0.61**
ASD 1. SRS-2 Total Score 35 75.43 12.5
2. BRIEF BRI 35 65.54 11.9 0.61**
3. BRIEF MCI 35 67.74 9.27 0.64** 0.53**
4. CBCL Attention 35 67.60 10.3 0.59** 0.39* 0.74**
5. Digitspan Forward 28 8.61 3.18 0.09 0.22 −0.09 −0.12
6. Digitspan Backwards 28 8.46 2.81 −0.04 0.07 −0.21 −0.29 0.59**
TDC 1. SRS-2 Total Score 26 43.8 3.89
2. BRIEF BRI 26 43.4 5.48 0.24
3. BRIEF MCI 26 44.8 7.18 0.04 0.66**
4. CBCL Attention 26 51.9 2.17 0.08 0.28 0.50**
5. Digitspan Forward 19 11.8 2.07 −0.4 0.19 0.17 0.25
6. Digitspan Backwards 19 11.8 3.05 0.12 0.37 −0.07 −0.18 0.24
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*

p < .05

**

p < .01

Combined Group Analysis:

Executive functioning, measured by both BRIEF indices and Digit Span Backwards, was significantly correlated to total social impairments on the SRS-2 (p < .01), and to attention problems on the CBCL (p < .01). Attention, measured by the CBCL Attention Problems scale (p < .01) and Digit Span Forward (p < .05), was also significantly associated with total social impairments on the SRS-2.

Within-Group Analysis:

Similar associations between executive functioning, attention, and social impairments were seen for the NF1 and the ASD group, while the TDC had distinct patterns of associations. For the NF1 and ASD group, executive functioning on the BRIEF indices were significantly associated with total social impairments. CBCL Attention Problems scale was also significantly correlated to social impairments for these groups. For the TDC group, there were no associations between executive functioning or attention and social impairments. Within all three groups, Digit Span Forward and Backward were not significantly associated with social impairments.

Primary Analysis: Evaluating Moderation Effects of Diagnostic Group

Separate models evaluated the main effects of executive functioning and attention on social impairments and assessed whether these associations were moderated by diagnostic group.

Executive Functioning:

The BRIEF Behavior Regulation Index was significantly associated with SRS-2 total scores (BRIEF BRI: b = 0.69, SE = 0.13, p < .01), and this relationship was similar across groups (interaction: F (2,84), = 1.49, p > .05) (Table 4, Figure 1a). The BRIEF Metacognition index was also significantly related to SRS-2 total scores (BRIEF MI: b = 0.39, SE = 0.12, p < .01). However, this relationship was moderated by group (interaction: F (2,84), = 5.58, p < .01), with MI being significantly associated with SRS-2 total scores only for the NF1 and ASD group (p < .01), but not the TDC (p > .05) (Table 4, Figure 1b). Digit Span Backward was not associated with SRS-2 total scores for any group (DsB: b = −0.19, SE = 0.79, p > .05; interaction: F (2,62), = 0.67, p > .05) (Table 4, Figure 1c).

Table 4.

Evaluating the Moderating Effect of Diagnostic Group on Cognitive-Social Relationships

Cognitive Domain Model x-variable Term F(2,84)* Coefficient Effect SE t p-value
Executive Functioning 1 BRIEF BRI BRIEF BRI 0.69 0.13 5.37 p <.01
W1 (NF1-ASD) 16.4 9.97 1.64 p > .05
W2 (NF1-TDC) 19.4 13.8 1.4 p > .05
Interaction 1 (BRIEF BRI*W1) −0.05 0.17 −0.27 p > .05
Interaction 2 (BRIEF BRI*W2) −0.51 0.30 −1.70 p > .05
Overall Interaction (BRIEF BRI*Group) 1.49 p > .05
2 BRIEF MCI BRIEF MCI 0.39 0.12 3.30 p < .01
W1 (NF1-ASD) −13.9 12.4 −1.12 p > .05
W2 (NF1-TDC) 11.8 12.4 0.95 p > .05
Interaction 1 (BRIEF MCI*W1) 0.47 0.19 2.46 p < .05
Interaction 2 (BRIEF MCI*W2) −0.37 0.26 −1.45 p > .05
Overall Interaction (BRIEF MCI*Group) 5.58 p < .01
 NF1 0.39 0.12 3.30 p < .01
 ASD 0.86 0.15 5.77 p < .01
 TDC 0.02 0.23 0.11 p > .05
3 Digitspan Backward DsB −0.19 0.79 −0.25 p > .05
W1 (NF1-ASD) 20.4 9.91 2.06 p < .05
W2 (NF1-TDC) −12.1 12.1 −1.01 p > .05
Interaction 1 (DsB*W1) 0.04 1.03 0.04 p > .05
Interaction 2 (DsB*W2) 0.35 1.08 0.32 p > .05
Overall Interaction (DsB*Group) 0.67 p > .05
Attention 4 CBCL Attention CBCL Attention 0.57 0.16 3.55 p <.01
W1 (NF1-ASD) 8.88 13.7 0.65 p > .05
W2 (NF1-TDC) 17.9 40.7 0.44 p > .05
Interaction 1 (CBCL Attention*W1) 0.14 0.21 0.67 p > .05
Interaction 2 (CBCL Attention*W2) −0.43 0.78 −0.55 p > .05
Overall Interaction (CBCL Attention*Group) 0.44 p > .05
5 Digitspan Forward DsF −0.35 0.72 −0.48 p > .05
W1 (NF1-ASD) 15.5 8.34 1.85 p > .05
W2 (NF1-TDC) −1.86 14.5 −0.13 p > .05
Interaction 1 (DsF*W1) 0.65 0.93 0.7 p > .05
Interaction 2 (DsF*W2) −0.46 1.31 −0.35 p > .05
Overall Interaction (DsF*Group) 0.51 p > .05
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Note: Dependent Variable for all models is SRS-2 Total Score

Note: Moderator (Diagnositic Group) was a multicategorical variable analyzed using indicator coding, overall X*M interactions are shown

*

Digitspan Forward and Backward: F(2,62)

Figure 1(A-E).

Figure 1(A-E).

Figure 1(A-E).

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Scatter Plots of Social-Cognitive Relationships Across Diagnostic Groups

Attention:

The CBCL Attention Problems subscale was significantly associated with SRS-2 total scores (b = 0.57, SE = 0.16, p < .01), and this relationship was not moderated by group (interaction: (2,84), = 0.44, p > .05) (Table 4, Figure 1d). Digit Span Forward was not significantly associated with SRS-2 total scores for any group (DsF: b = −0.35, SE = 0.72, p > .05; interaction: F (2,62), = 0.51, p > .05) (Table 4, Figure 1e).

Discussion

Improving social outcomes for children with NF1 and children with ASD is imperative due to their significant impact on quality of life and health. Given the high rates of EF and attention deficits in these populations, understanding the cognitive mechanisms underlying social impairments in children with NF1 and children with ASD is critical for informing multi-domain interventions to improve social functioning. Results from this study revealed distinct profiles of executive functioning, attention, and social impairments across groups, with children with ASD and NF1 exhibiting greater challenges in these domains compared to TDC. Group specific cognitive-social associations emerged with stronger inter-domain relationships between executive functioning, attention, and social functioning observed within the NF1 and ASD groups. These findings suggest the potential utility of integrating executive functioning and attention-based training in interventions to improve social functioning in these populations.

The group-specific profiles of social and cognitive functioning observed in this study are consistent with prior studies and highlight increased challenges in these domains for children with NF1 and ASD compared to TDC. The rate of elevated SRS-2 total scores for the NF1 group in this study were lower than those reported in the current NF1 literature, as children with a co-occurring diagnosis of NF1+ASD were removed from our sample to examine NF1 specific profiles (Adviento, 2013, Payne, 2020). However, our study still found significantly higher social impairments in the NF1 group compared to TDC, in line with previous studies, with over 27% of the NF1 group exhibiting mild-severe social impairments on the SRS-2 (Payne, 2020). The higher rates of metacognitive, behavioral regulation, and attention difficulties in the NF1 and ASD groups compared to TDC are also in line with previous investigations (Beaussart, 2018, Hill, 2004, Huijbregts, 2015). Although overall IQs were similar across the NF1 and ASD groups, these executive functioning and attention difficulties were milder for the NF1 group. The group-specific profiles observed highlight the importance of screening and addressing social and cognitive functioning even in the broader NF1 population.

Distinct associations between cognitive and social domains across the clinical groups and the TDC group emerged in correlation and moderation analyses. Across all three groups, parent-reported behavioral regulation on the BRIEF and attention problems on the CBCL were significantly associated with total social impairments on the SRS-2 in moderation analyses, supporting existing literature showing similar associations in these populations (Bednarz et al., 2020, Haebich et al., 2021, Kenworthy et al., 2009, Leung et al., 2015). However, parent-reported metacognition on the BRIEF was significantly associated with SRS-2 social impairments only for the NF1 and ASD group, suggesting a distinct metacognitive-social pathway in children with neurodevelopmental disorders. These findings align with earlier work which also identified a unique relationship between metacognition and social functioning in children with ASD, not observed in TDC (Leung et al., 2015, Torske et al., 2018). Our findings of a similar metacognitive-social association in children with NF1 and children with ASD may reflect the role of shared neurodevelopmental processes that concurrently influence cognition and social functioning across both groups. The NF1 and ASD groups also had higher variability in both metacognitive and social functioning, which may have also influenced the strength of relationships across domains. Understanding these shared pathways through longitudinal imaging studies applying the SOCIAL model will offer valuable insight into the clinical and methodological factors underlying the development of cognitive and social challenges for children with neurodevelopmental disorders.

Results indicate that similar cognitive domains may underlie difficulties in social functioning across populations of children with NF1 and ASD; however, these associations appear sensitive to testing method as Digit Span scores did not account for a significant amount of unique variance in social impairments in moderation analyses. Prior work in children with ASD has also found absent-to-weak associations between cognitive performance on neuropsychological tests and social functioning (Faja & Dawson, 2013, Landa & Goldberg, 2005). As real-world social environments are more complex and dynamic, with increased distractions and unpredictable demands, broader measures of executive functioning and attention in daily life settings may have more ecological validity compared to isolated and controlled measures like Digit Span. This notion is supported by the finding that children with ASD may perform better on structured neuropsychological assessments with explicit behavioral expectations compared to real-world settings (Kenworthy et al., 2008). Thus, in the context of understanding the cognitive underpinnings of social impairments in children with neurodevelopmental disorders, executive function and social attention measures with greater ecological validity, such as ecological momentary assessments and eye-tracking measures, should be explored.

Given this study’s findings of similar associations between executive functioning and attention and social impairments in children with NF1 and children with ASD, future work should assess the utility of cognitive training in interventions to improve social functioning across these groups. For instance, Unstuck and On Target (UOT) is an executive function intervention for children that is implemented across home and school contexts and has been found to improve social functioning as well as cognition in children with ASD (Kenworthy, 2014). Additionally, improvements in metacognition for children with ASD was associated with a decrease in social impairments over time, highlighting the potential for targeted multi-domain interventions (Vogan et al., 2018). As similar cognitive-social associations were found between children with NF1 and children with ASD in this study, future work should assess the efficacy of the UOT and similar interventions on improving social functioning in children with NF1 (Kenworthy et al., 2013).

Strengths of this study include its rigorous cross-sectional design, comparing cognitive-social associations across two clinical groups and a TDC population, while matching on age, sex, and IQ, and using both parent-report and task-based measures. However, the findings of this study must be understood within the context of its limitations. The low sample sizes across diagnostic groups may have limited our power to detect significant associations between Digit Span and social functioning, as these metrics were significantly associated in the full sample correlation analysis. Given the potential collinearity between EF and attention metrics, regression analysis should be conducted to delineate if EF and attention have shared or distinct variances in social outcomes. As the study was not longitudinal, the dynamic cognitive and social developmental trajectories across these groups could not be compared. Parent-report measures of executive functioning, attention, and social impairments were also sensitive to parent bias as they were only captured by one informant and did not include child or teacher perspectives. Additionally, metrics of attention specific to social functioning, such as eye-tracking social attention, were not assessed in task-based measures, which may have offered higher ecological validity for social outcomes. These limitations should be addressed by future work assessing cognitive-social mechanisms in children with neurodevelopmental disorders using various assessment methods and multi-informant reports of functioning.

In conclusion, this study supports the consideration of attention and EF issues as key components of the social phenotype of NF1 and ASD. The emergence of similar cognitive-social associations between the NF1 and the ASD group indicate that similar neurodevelopmental pathways may underlie these relationships. Future longitudinal work exploring these shared mechanisms across groups would help inform if multi-domain cognitive-social interventions would be equally effective for both children with NF1 and children with ASD.

Table 2a.

Means, Standard Deviations, and One-Way Analyses of Variance in Social and Cognitive Domains Across Diagnostis Groups

Measure NF1 ASD TDC F(2,87)
F(2,65)		 η2
n M SD Range % ^ Cut n M SD Range % ^ Cut n M SD Range % ^ Cut
SRS-2 Total Scorea 29 53.3 9.78 39 – 74 27.6% 35 75.43 12.5 53 – 109 88.6% 26 43.8 3.89 38 – 51 0% 85.3*** 0.66
BRIEF BRIb 29 52.9 11.1 36 – 79 24.1% 35 65.54 11.9 44 – 94 60.0% 26 43.4 5.48 36 – 58 0% 36.4*** 0.46
BRIEF MCIb 29 57.1 12.9 33 – 79 24.1% 35 67.74 9.27 49 – 86 62.9% 26 44.8 7.18 33 – 62 0% 38.7*** 0.47
CBCL Attentionc 29 61.1 9.64 50 – 83 31.0% 35 67.60 10.3 51 – 97 60.0% 26 51.9 2.17 50 – 57 0% 25.6*** 0.37
Digitspan Forwardd 21 8.43 2.94 3 – 16 38.1% 28 8.61 3.18 2 – 13 32.1% 19 11.8 2.07 9 – 15 0% 9.06*** 0.22
Digitspan Backwardsd 21 9.76 2.72 5 – 17 9.5% 28 8.46 2.81 2 – 13 35.7% 19 11.8 3.05 7 – 17 10.5% 7.71*** 0.19
Open in a new tab
a

SRS-2 Cutoff: T-score ≥ 60 (Mild)

b

BRIEF Cutoff: T-score ≥ 65 (Elevated)

c

CBCL Cutoff: T-score ≥ 65 (Borderline)

d

Digitspan Cutoff: Scaled Score ≤ 7 (Low Average)

***

p < .001

Table 2b.

Games-Howell Post-Hoc for One-Way Analyses of Variance in Social and Cognitive Domains Across Diagnostis Groups

Comparison Mean Difference 95% C.I
Group 1 Group 2 (Group 1- Group 2) SE Lower Upper
SRS-2 Total Score NF1 ASD −22.2*** 2.46 −28.0 −16.3
NF1 TD 9.51*** 2.65 3.19 15.8
ASD TD 31.7*** 2.54 25.6 37.7
BRIEF BRI NF1 ASD −12.6*** 2.56 −18.7 −6.51
NF1 TD 9.59*** 2.75 3.02 16.2
ASD TD 22.2*** 2.64 15.9 28.5
BRIEF MCI NF1 ASD −10.6*** 2.53 −16.6 −4.57
NF1 TD 12.3*** 2.72 5.84 18.8
ASD TD 22.9*** 2.61 16.7 29.2
CBCL Attention NF1 ASD −6.53* 2.14 −11.6 −1.44
NF1 TD 9.22*** 2.30 3.74 14.7
ASD TD 15.8*** 2.20 10.5 21.0
Digitspan Forward NF1 ASD −0.18 0.82 −2.14 1.79
NF1 TD −3.36*** 0.90 −5.52 −1.21
ASD TD −3.18*** 0.84 −5.20 −1.21
Digitspan Backwards NF1 ASD 1.29 0.82 −0.86 3.27
NF1 TD −2.03 0.90 −4.19 0.14
ASD TD −3.33** 0.85 −5.36 −1.29
Open in a new tab
*

p < .05

**

p < .01

***

p < .001

Funding:

National Institutes of Neurological Disorders and Stroke

Footnotes

Conflicts of Interest: Dr. Roberts discloses consulting/equity/advisory board positions with Prism Clinical Imaging, Proteus Neurodynamics, Fieldline Inc. and WestCan Proton Therapy Inc. Other authors have no relevant financial or non-financial conflicts of interest to disclose.

Ethics Approval: This study followed all Children’s Hospital of Philadelphia research policies and procedures and all applicable federal and state laws and regulations including 45 CFR 46, and the HIPAA Privacy Rule

Consent to Participate and Publish: Informed consent was obtained from all participants and legal guardians prior to any data collection, and informed consented for their deidentified data to be published was also obtained.

Data Availability Statement:

The data that support the findings of this study are available upon request from the corresponding author. The data are not publicly available due to their containing information that could compromise the privacy of the research participants.

References

  1. Adviento B, Corbin IL, Widjaja F, Desachy G, Enrique N, Rosser T, Risi S, Marco EJ, Hendren RL, Bearden CE, Rauen KA, & Weiss LA (2013). Autism traits in the rasopathies. Journal of Medical Genetics, 51(1), 10–20. 10.1136/jmedgenet-2013-101951 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Barton B, & North K (2004). Social skills of children with neurofibromatosis type 1. Developmental Medicine & Child Neurology, 46(08). 10.1017/s0012162204000921 [DOI] [PubMed] [Google Scholar]
  3. Beaussart M-L, Barbarot S, Mauger C, & Roy A (2018). Systematic Review and meta-analysis of executive functions in preschool and school-age children with neurofibromatosis type 1. Journal of the International Neuropsychological Society, 24(9), 977–994. 10.1017/s1355617718000383 [DOI] [PubMed] [Google Scholar]
  4. Bednarz HM, Trapani JA, & Kana RK (2020). Metacognition and behavioral regulation predict distinct aspects of social functioning in autism spectrum disorder. Child Neuropsychology, 26(7), 953–981. 10.1080/09297049.2020.1745166 [DOI] [PubMed] [Google Scholar]
  5. Bertollo JR, & Yerys BE (2019). More than IQ: Executive function explains adaptive behavior above and beyond nonverbal IQ in youth with autism and Lower IQ. American Journal on Intellectual and Developmental Disabilities, 124(3), 191–205. 10.1352/1944-7558-124.3.191 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chisholm AK, Anderson VA, Pride NA, Malarbi S, North KN, & Payne JM (2018). Social function and autism spectrum disorder in children and adults with neurofibromatosis type 1: A systematic review and meta-analysis. Neuropsychology Review, 28(3), 317–340. 10.1007/s11065-018-9380-x [DOI] [PubMed] [Google Scholar]
  7. Cui Y, Costa RM, Murphy GG, Elgersma Y, Zhu Y, Gutmann DH, Parada LF, Mody I, & Silva AJ (2008). Neurofibromin regulation of ERK signaling modulates GABA release and learning. Cell, 135(3), 549–560. 10.1016/j.cell.2008.09.060 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. DSM-V Diagnostic and statistical manual of mental disorders. (2013). American Psychiatric Association. [Google Scholar]
  9. Faja S, & Dawson G (2013). Performance on the dimensional change card sort and backward digit span by young children with autism without intellectual disability. Child Neuropsychology, 20(6), 692–699. 10.1080/09297049.2013.856395 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Friedman JM (1999). Epidemiology of neurofibromatosis type 1. American Journal of Medical Genetics, 89(1), 1–6. 10.1002/(sici)1096-8628(19990326)89:1<1::aid-ajmg3>3.0.co;2-8 [DOI] [PubMed] [Google Scholar]
  11. Gilotty L, Kenworthy L, Sirian L, Black DO, & Wagner AE (2002). Adaptive Skills and executive function in autism spectrum disorders. Child Neuropsychology, 8(4), 241–248. 10.1076/chin.8.4.241.13504 [DOI] [PubMed] [Google Scholar]
  12. Glad DM, Casnar CL, Yund BD, Lee K, & Klein-Tasman BP (2021). Parent-reported social skills in children with neurofibromatosis type 1: Longitudinal patterns and relations with attention and cognitive functioning. Journal of Developmental & Behavioral Pediatrics, 42(8), 656–665. 10.1097/dbp.0000000000000939 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Greenberg MT (2006). Promoting resilience in children and Youth. Annals of the New York Academy of Sciences, 1094(1), 139–150. 10.1196/annals.1376.013 [DOI] [PubMed] [Google Scholar]
  14. Greene RK, Parish-Morris J, Sullivan M, Kinard JL, Mosner MG, Turner-Brown LM, Penn DL, Wiesen CA, Pallathra AA, Brodkin ES, Schultz RT, & Dichter GS (2020). Dynamic Eye tracking as a predictor and outcome measure of social skills intervention in adolescents and adults with autism spectrum disorder. Journal of Autism and Developmental Disorders, 51(4), 1173–1187. 10.1007/s10803-020-04594-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hachon C, Iannuzzi S, & Chaix Y (2011). Behavioural and cognitive phenotypes in children with neurofibromatosis type 1 (NF1): The link with the neurobiological level. Brain and Development, 33(1), 52–61. 10.1016/j.braindev.2009.12.008 [DOI] [PubMed] [Google Scholar]
  16. Haebich KM, Dao DP, Pride NA, Barton B, Walsh KS, Maier A, Chisholm AK, Darke H, Catroppa C, Malarbi S, Wilkinson JC, Anderson VA, North KN, & Payne JM (2021). The mediating role of ADHD symptoms between executive function and social skills in children with neurofibromatosis type 1. Child Neuropsychology, 28(3), 318–336. 10.1080/09297049.2021.1976129 [DOI] [PubMed] [Google Scholar]
  17. Hanley M, Riby DM, McCormack T, Carty C, Coyle L, Crozier N, Robinson J, & McPhillips M (2014). Attention during social interaction in children with autism: Comparison to specific language impairment, typical development, and links to social cognition. Research in Autism Spectrum Disorders, 8(7), 908–924. 10.1016/j.rasd.2014.03.020 [DOI] [Google Scholar]
  18. Hill EL (2004). Executive dysfunction in autism☆. Trends in Cognitive Sciences, 8(1), 26–32. 10.1016/j.tics.2003.11.003 [DOI] [PubMed] [Google Scholar]
  19. Hocking MC, Albee MV, Kim M, Berman JI, Fisher MJ, Roberts TP, & Blaskey L (2024). Social challenges, autism spectrum disorder, and attention deficit/hyperactivity disorder in youth with neurofibromatosis type I. Applied Neuropsychology: Child, 1–9. 10.1080/21622965.2024.2365383 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Holland AA, Stavinoha PL, Swearer SM, Solesbee C, Patel S, & Klesse LJ (2019). Rate and frequency of bullying victimization in school-age children with neurofibromatosis type 1 (NF1). School Psychology, 34(6), 687–694. 10.1037/spq0000333 [DOI] [PubMed] [Google Scholar]
  21. Holt-Lunstad J (2021). The major health implications of Social Connection. Current Directions in Psychological Science, 30(3), 251–259. 10.1177/0963721421999630 [DOI] [Google Scholar]
  22. Huijbregts SC, & de Sonneville LM (2010). Does cognitive impairment explain behavioral and social problems of children with neurofibromatosis type 1? Behavior Genetics, 41(3), 430–436. 10.1007/s10519-010-9430-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Huijbregts SC, Loitfelder M, Rombouts SA, Swaab H, Verbist BM, Arkink EB, Van Buchem MA, & Veer IM (2015). Cerebral volumetric abnormalities in Neurofibromatosis type 1: associations with parent ratings of social and attention problems, executive dysfunction, and autistic mannerisms. Journal of neurodevelopmental disorders, 7, 32. 10.1186/s11689-015-9128-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hyman SL, Shores A, & North KN (2005). The nature and frequency of cognitive deficits in children with neurofibromatosis type 1. Neurology, 65(7), 1037–1044. 10.1212/01.wnl.0000179303.72345.ce [DOI] [PubMed] [Google Scholar]
  25. Johnson NS, Saal HM, Lovell AM, & Schorry EK (1999). Social and emotional problems in children with neurofibromatosis type 1: Evidence and proposed interventions. The Journal of Pediatrics, 134(6), 767–772. 10.1016/s0022-3476(99)70296-9 [DOI] [PubMed] [Google Scholar]
  26. Kasari C, & Rotheram-Fuller E (2007). Chapter 11. Peer relationships of children with autism: Challenges and interventions. Clinical Manual for the Treatment of Autism, 235–257. 10.1176/appi.books.9781615377633.lg11 [DOI] [Google Scholar]
  27. Kenworthy L, Anthony LG, Naiman DQ, Cannon L, Wills MC, Luong-Tran C, Werner MA, Alexander KC, Strang J, Bal E, Sokoloff JL, & Wallace GL (2013). Randomized controlled effectiveness trial of executive function intervention for children on the autism spectrum. Journal of Child Psychology and Psychiatry, 55(4), 374–383. 10.1111/jcpp.12161 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Kenworthy L, Black DO, Harrison B, della Rosa A, & Wallace GL (2009). Are executive control functions related to autism symptoms in high-functioning children? Child Neuropsychology, 15(5), 425–440. 10.1080/09297040802646983 [DOI] [PubMed] [Google Scholar]
  29. Kenworthy L, Yerys BE, Anthony LG, & Wallace GL (2008). Understanding executive control in Autism Spectrum Disorders in the lab and in the real world. Neuropsychology Review, 18(4), 320–338. 10.1007/s11065-008-9077-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Landa RJ, & Goldberg MC (2005). Language, social, and executive functions in high functioning autism: A continuum of performance. Journal of Autism and Developmental Disorders, 35(5), 557–573. 10.1007/s10803-005-0001-1 [DOI] [PubMed] [Google Scholar]
  31. Leung RC, Vogan VM, Powell TL, Anagnostou E, & Taylor MJ (2015). The role of executive functions in social impairment in autism spectrum disorder. Child Neuropsychology, 22(3), 336–344. 10.1080/09297049.2015.1005066 [DOI] [PubMed] [Google Scholar]
  32. Levitt P, & Campbell DB (2009). The genetic and neurobiologic compass points toward common signaling dysfunctions in autism spectrum disorders. Journal of Clinical Investigation, 119(4), 747–754. 10.1172/jci37934 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Leyfer OT, Folstein SE, Bacalman S, Davis NO, Dinh E, Morgan J, Tager-Flusberg H, & Lainhart JE (2006). Comorbid psychiatric disorders in children with autism: Interview Development and rates of disorders. Journal of Autism and Developmental Disorders, 36(7), 849–861. 10.1007/s10803-006-0123-0 [DOI] [PubMed] [Google Scholar]
  34. Martin S, Wolters P, Baldwin A, Gillespie A, Dombi E, Walker K, & Widemann B (2012). Social-emotional functioning of children and adolescents with neurofibromatosis type 1 and plexiform neurofibromas: Relationships with cognitive, disease, and environmental variables. Journal of Pediatric Psychology, 37(7), 713–724. 10.1093/jpepsy/jsr124 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Mautner V-F, Kluwe L, Thakker SD, & Leark RA (2002). Treatment of ADHD in neurofibromatosis type 1. Developmental Medicine and Child Neurology, 44(03), 164. 10.1017/s0012162201001876 [DOI] [PubMed] [Google Scholar]
  36. Mayes DA, Rizvi TA, Titus-Mitchell H, Oberst R, Ciraolo GM, Vorhees CV, Robinson AP, Miller SD, Cancelas JA, Stemmer-Rachamimov AO, & Ratner N (2013). NF1 loss and Ras hyperactivation in oligodendrocytes induce nos-driven defects in myelin and vasculature. Cell Reports, 4(6), 1197–1212. 10.1016/j.celrep.2013.08.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Morris SM, Acosta MT, Garg S, Green J, Huson S, Legius E, North KN, Payne JM, Plasschaert E, Frazier TW, Weiss LA, Zhang Y, Gutmann DH, & Constantino JN (2016). Disease burden and symptom structure of autism in neurofibromatosis type 1. JAMA Psychiatry, 73(12), 1276. 10.1001/jamapsychiatry.2016.2600 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Noll RB, Reiter-Purtill J, Moore BD, Schorry EK, Lovell AM, Vannatta K, & Gerhardt CA (2007). Social, emotional, and behavioral functioning of children with NF1. American Journal of Medical Genetics Part A, 143A(19), 2261–2273. 10.1002/ajmg.a.31923 [DOI] [PubMed] [Google Scholar]
  39. Office of the Surgeon General (OSG). (2023). Our Epidemic of Loneliness and Isolation: The U.S. Surgeon General’s Advisory on the Healing Effects of Social Connection and Community. [PubMed] [Google Scholar]
  40. Orsmond GI, Krauss MW, & Seltzer MM (2004). Peer relationships and social and recreational activities among adolescents and adults with autism. Journal of Autism and Developmental Disorders, 34(3), 245–256. 10.1023/b:jadd.0000029547.96610.df [DOI] [PubMed] [Google Scholar]
  41. Payne JM, Walsh KS, Pride NA, Haebich KM, Maier A, Chisholm A, Glad DM, Casnar CL, Rouel M, Lorenzo J, Del Castillo A, North KN, & Klein-Tasman B (2020). Social skills and autism spectrum disorder symptoms in children with neurofibromatosis type 1: Evidence for clinical trial outcomes. Developmental Medicine & Child Neurology, 62(7), 813–819. 10.1111/dmcn.14517 [DOI] [PubMed] [Google Scholar]
  42. Torske T, Nærland T, Øie MG, Stenberg N, & Andreassen OA (2018). Metacognitive aspects of executive function are highly associated with social functioning on parent-rated measures in children with autism spectrum disorder. Frontiers in Behavioral Neuroscience, 11. 10.3389/fnbeh.2017.00258 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Payne JM, Moharir MD, Webster R, & North KN (2010). Brain structure and function in neurofibromatosis type 1: Current concepts and Future Directions. Journal of Neurology, Neurosurgery & Psychiatry, 81(3), 304–309. 10.1136/jnnp.2009.179630 [DOI] [PubMed] [Google Scholar]
  44. Payne JM, Arnold SS, Pride NA, & North KN (2012). Does attention-deficit–hyperactivity disorder exacerbate executive dysfunction in children with neurofibromatosis type 1? Developmental Medicine & Child Neurology, 54(10), 898–904. 10.1111/j.1469-8749.2012.04357.x [DOI] [PubMed] [Google Scholar]
  45. Payne Jonathan M., Hearps SJ, Walsh KS, Paltin I, Barton B, Ullrich NJ, Haebich KM, Coghill D, Gioia GA, Cantor A, Cutter G, Tonsgard JH, Viskochil D, Rey-Casserly C, Schorry EK, Ackerson JD, Klesse L, Fisher MJ, Gutmann DH, North KN (2019). Reproducibility of cognitive endpoints in clinical trials: Lessons from neurofibromatosis type 1. Annals of Clinical and Translational Neurology, 6(12), 2555–2565. 10.1002/acn3.50952 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Plasschaert E, Descheemaeker M, Van Eylen L, Noens I, Steyaert J, & Legius E (2014). Prevalence of autism spectrum disorder symptoms in children with neurofibromatosis type 1. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 168(1), 72–80. 10.1002/ajmg.b.32280 [DOI] [PubMed] [Google Scholar]
  47. Plasschaert E, Van Eylen L, Descheemaeker M, Noens I, Legius E, & Steyaert J (2016). Executive functioning deficits in children with neurofibromatosis type 1: The influence of intellectual and social functioning. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 171(3), 348–362. 10.1002/ajmg.b.32414 [DOI] [PubMed] [Google Scholar]
  48. Pride NA, Crawford H, Payne Jonathan. M., & North KN (2013). Social functioning in adults with neurofibromatosis type 1. Research in Developmental Disabilities, 34(10), 3393–3399. 10.1016/j.ridd.2013.07.011 [DOI] [PubMed] [Google Scholar]
  49. Rong Y, Yang C-J, Jin Y, & Wang Y (2021). Prevalence of attention-deficit/hyperactivity disorder in individuals with autism spectrum disorder: A meta-analysis. Research in Autism Spectrum Disorders, 83, 101759. 10.1016/j.rasd.2021.101759 [DOI] [Google Scholar]
  50. Schroeder JH, Cappadocia MC, Bebko JM, Pepler DJ, & Weiss JA (2014). Shedding light on a pervasive problem: A review of research on bullying experiences among children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 44(7), 1520–1534. 10.1007/s10803-013-2011-8 [DOI] [PubMed] [Google Scholar]
  51. Violante IR, Patricio M, Bernardino I, Rebola J, Abrunhosa AJ, Ferreira N, & Castelo-Branco M (2016). GABA deficiency in NF1. Neurology, 87(9), 897–904. 10.1212/wnl.0000000000003044 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Vogan VM, Leung RC, Safar K, Martinussen R, Smith ML, & Taylor MJ (2018). Longitudinal examination of everyday executive functioning in children with ASD: Relations with social, emotional, and behavioral functioning over time. Frontiers in Psychology, 9. 10.3389/fpsyg.2018.01774 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Walsh KS, Velez JI, Kardel PG, Imas DM, Muenke M, Packer RJ, Castellanos FX, & Acosta MT (2012). Symptomatology of Autism Spectrum Disorder in a population with neurofibromatosis type 1. Developmental Medicine & Child Neurology, 55(2), 131–138. 10.1111/dmcn.12038 [DOI] [PubMed] [Google Scholar]
  54. Wang Y, Kim E, Wang X, Novitch BG, Yoshikawa K, Chang L-S, & Zhu Y (2012). ERK inhibition rescues defects in fate specification of NF1-deficient neural progenitors and brain abnormalities. Cell, 150(4), 816–830. 10.1016/j.cell.2012.06.034 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available upon request from the corresponding author. The data are not publicly available due to their containing information that could compromise the privacy of the research participants.

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