Neuropsychology 2015, Vol. 29, No. 3, 473– 484

© 2014 American Psychological Association 0894-4105/15/$12.00 http://dx.doi.org/10.1037/neu0000151

Examining the Frontal Subcortical Brain Vulnerability Hypothesis in Children With Neurofibromatosis Type 1: Are T2-Weighted Hyperintensities Related to Executive Dysfunction? Arnaud Roy

Sébastien Barbarot, Valérie Charbonnier, Marie Gayet-Delacroix, and Jean-François Stalder

Angers University and Nantes University Hospital

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Nantes University Hospital

Jean-Luc Roulin

Didier Le Gall

Savoie University

Angers University

Objective: It was hypothesized that neuropsychological impairments in children with neurofibromatosis type I (NF1) are associated with brain areas of increased T2-weighted signal intensity on MRI. Systematic and extensive examination of this hypothesis remains however scarce, particularly regarding executive dysfunction whereas hyperintensities are located preferentially in frontal-subcortical networks. In this study, we compared the executive functioning profile with characteristics of brain hyperintensities in children with NF1. Method: A sample of 36 school-age children with NF1 (7–12 years) underwent a detailed examination of executive function, including performancebased tests and child’s behavior rating in daily life. Executive function measures were compared with the characteristics of the T2-weighted hyperintensities on parallel MRI scans. The presence, number, and size of hyperintensities in the whole brain were considered as well as their main cerebral locations. Results: Executive dysfunction including traditional cognitive and ecological measures in children with NF1 is not significantly influenced by T2-weighted hyperintensities, in terms of presence or not, number, size, and location, whether in the whole brain or according to involved specific brain areas. Conclusion: T2-weighted hyperintensities, as they are currently measured, cannot be used as a strong indicator of executive dysfunction in children with NF1. Based on the available NF1 cognitive impairment pathogenesis models, a critical discussion on anatomicalfunctional relationships between hyperintensities and neuropsychological profile is proposed, especially the executive dysfunction. Keywords: executive function, neurodevelopmental disorder, neurofibromatosis type 1, neuropsychology, T2-weighted hyperintensities

Neurofibromatosis type I (NF1) is a neurogenetic disorder with an estimated prevalence of 1:3500. Learning disabilities are the most common complications of NF1 in childhood, varying from 30% to 65%, according to studies (Cutting, Clements, Lightman, Yerby-Hammack, & Denckla, 2004; North et al., 1997). No consensus exists on the neuropsychological profile of children with NF1 but many research studies over the two past decades showed a slight reduction of intelligent quotient (IQ), and weaknesses in

several specific cognitive domains including visuospatial and visuomotor abilities, language, reading and spelling skills, mathematics, attention, and memory (Cutting et al., 2004; Lehtonen, Howie, Trump, & Huson, 2013; Levine, Materek, Abel, O’Donnell, & Cutting, 2006). More recently, executive function (EF) impairment was demonstrated in school-age NF1 children (Hyman, Shores, & North, 2006; Payne, Arnold, Pride, & North, 2012; Payne, Hyman, Shores, & North, 2011; Rowbotham, Pit-ten

This article was published Online First November 3, 2014. Arnaud Roy, Psychology Laboratory, LUNAM, Angers University, and Neurofibromatosis Clinic, Nantes University Hospital, and Reference Center for Learning Disabilities, Nantes University Hospital; Sébastien Barbarot, Neurofibromatosis Clinic, Nantes University Hospital; Valérie Charbonnier, Reference Center for Learning Disabilities, Nantes University Hospital; Marie Gayet-Delacroix and Jean-François Stalder, Neurofibromatosis Clinic, Nantes University Hospital; Jean-Luc Roulin, Neurocognition and Psychology Laboratory, Savoie University; Didier Le Gall, Psychology Laboratory, LUNAM, Angers University.

We are particularly grateful to the children and their parents for their precious participation in this study. We would also like to thank the French patients association “Association Neurofibromatoses & Recklinghausen” for its ongoing, generous support and the encouragement of its president Mr. Dubois. Thanks to the anonymous reviewers, for their valuable contribution to improve the manuscript. Correspondence concerning this article should be addressed to Arnaud Roy, Université d’Angers, Faculté des Lettres, Langues et Sciences Humaines, 11 boulevard Lavoisier, 49045 Angers cedex 01, France. E-mail: [email protected] 473

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ROY ET AL.

Cate, Sonuga-Barke, & Huijbregts, 2009; Roy et al., 2012; Roy et al., 2010). EF refers to a set of high-level abilities that are required to ensure goal-directed behavior, and includes a wide range of cognitive processes such as action planning, inhibition, sustained attention, and cognitive flexibility (Luria, 1966). The development of these processes is protracted and linked to the slow maturation of prefrontal cortex and its related networks from childhood into early adulthood (Dennis, 2006). The relationship between neuropsychological impairment and brain anomalies seen in NF1, especially T2-weighted hyperintensities (T2H), remains a subject of great interest. T2H are abnormally bright areas in the brain and spinal cord on MRI scans. The origin and the clinical significance of these “lesions” are unknown (“unidentified bright objects”) but they are thought to signify aberrant myelination or foci of neural dysplasia (Hyman et al., 2003). T2H are often present in individuals with NF1, ranging from 43% to 79%, and most commonly occur in the basal ganglia, cerebellum, brainstem, and thalamus. Cross-sectional and longitudinal studies suggest that MRI hyperintensities tend to disappear over time, particularly during the second and third decades of life (Feldmann, Denecke, Grenzebach, Schuierer, & Weglage, 2003; Hyman et al., 2003; Itoh et al., 1994), but in some subjects, the initial decrease of T2H is followed by a progressive increase with age (Kraut et al., 2004). The high frequency of T2H led to their potential linkage to cognition in children and to a specific model for the pathogenesis of cognitive deficits in NF1. According to this model, NF1 gene mutations result in cognitive processing impairment, through an abnormal development of neuronal circuits emerging as areas of increased T2 signal intensity on MRI (North et al., 1994; North et al., 1997). The presence of T2H was initially demonstrated by North et al. (1994) to be associated with neuropsychological impairment in children. They reported that patients with T2H had significantly lower scores on IQ, language, visuomotor, and academic achievement tests than children with NF1 without T2H. Additional cognitive measures based on this initial clinical sample indicated similar results for visuospatial, working memory, and cognitive flexibility tasks (Joy, Roberts, North, & de Silva, 1995). A longitudinal follow-up of a portion of this cohort found that the presence of T2H in childhood was the best predictor of cognitive dysfunction in adulthood, rather than current MRI hyperintensities status (Hyman et al., 2003). Similarly, a cross-sectional study indicated that children with T2H had lower performance IQ scores than NF1 children without T2H (Chabernaud et al., 2009; Feldmann et al., 2003). However, many studies found no significant relationship between NF1 cognitive performance and the presence of T2H. Some of them were limited to IQ investigation (Duffner, Cohen, Seidel, & Shucard, 1989; Dunn & Roos, 1989; Ferner, Chaudhuri, Bingham, Cox, & Hughes, 1993; Legius et al., 1995) while other works used more detailed neuropsychological assessment including visuospatial, visuomotor, language, EF, and/or academic achievement tests (Bawden et al., 1996; Goh, Khong, Leung, & Wong, 2004; Hyman, Gill, Shores, Steinberg, & North, 2007; Moore, Slopis, Schomer, Jackson, & Levy, 1996). The number of locations in the brain or their volume when T2H are present was also examined regarding the neuropsychological functioning, to go beyond the simple dichotomous “presence or absence” analysis. While no significant relationship was consis-

tently reported between the global size/volume of T2H and IQ or neuropsychological measures (Chabernaud et al., 2009; Denckla et al., 1996; Ferner et al., 1993; Legius et al., 1995), studies analyzing the number of locations yielded conflicting results. Denckla et al. (1996) and Hofman, Harris, Bryan, and Denckla (1994) reported a significant association between the lowering of IQ in children with NF1 and the number of brain locations occupied by T2H. However, in the study of Hofman et al. (1994), verbal IQ (VIQ) and several neuropsychological domains, with the exception of visuospatial abilities, were not related to the T2H number. In addition, several other studies did not confirm a significant association between the whole brain number of T2H and IQ or neuropsychological/academic achievement tests (Chabernaud et al., 2009; Feldmann et al., 2003; Ferner et al., 1993; Hyman et al., 2007; Moore et al., 1996). Recent reviews (Hachon, Iannuzzi, & Chaix, 2011; Levine et al., 2006) suggested that the linkage between T2H and impaired cognitive functioning is more evident when a specific location of T2H is taken into account, in accordance with the model for pathogenesis of North et al. (1997) and with the idea that specific neuropsychological disorders could depend on the cerebral networks impacted by T2H (Cutting et al., 2000). Thalamic T2H are critical to this hypothesis, since Moore and coworkers (1996) suggested that location of T2H in this cerebral area, which is involved in memory consolidation, could affect all types of information and becomes then responsible for the various cognitive deficits often reported in NF1. Goh et al. (2004) also found that children with thalamic T2H had a lower IQ compared with those without T2H in this location, and that the size of thalamic lesions correlated with cognitive impairment. Similarly, Hyman et al. (2007) showed that thalamic T2H had a significant impact on IQ, attention, and fine motor coordination. More recently, NF1 subjects exhibiting thalamo-striatal T2H were found to have lower IQ and visuospatial scores (Chabernaud et al., 2009). Specific locations of T2H in cerebellum and in basal ganglia are also discussed, since cerebellar hyperintensities were associated with a lowering of IQ (Piscitelli, Digilio, Capolino, Longo, & Di Ciommo, 2012) while right middle cerebellar peduncle T2H were associated with a lower sensorimotor performance (Goh et al., 2004). The association between attention profile and left globus pallidus hyperintensities reported by Goh et al. (2004) may be due to an impairment of the neurophysiologic pathway of the frontostriatal system. The volume of T2H involving basal ganglia was related to visuospatial deficit (Mott et al., 1994), but other studies did not confirm the relationship between cognitive performance and the specific location of T2H in basal ganglia or cerebellum in children with NF1 (Chabernaud et al., 2009; Hyman et al., 2007; Moore et al., 1996). Regarding brainstem and corpus callosum, T2H were not found to be associated with cognitive dysfunction (Hyman et al., 2007; Moore et al., 1996). Furthermore, one study demonstrated a significant correlation between impaired language on IQ tests and the extent of T2H on the left hemisphere (Goh et al., 2004), and some authors reported a specific correlation between T2H volume within the right hemisphere and visuospatial performance (Mott et al., 1995). In summary, research findings tend to support a linkage between T2H and neuropsychological status in children with NF1, especially when specific locations such as the thalamus, the cerebellum, and the basal ganglia are considered. However,

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HYPERINTENSITIES AND EXECUTIVE DYSFUNCTION IN NF1

the exact nature of this association remains highly controversial so that results need to be replicated (Cutting et al., 2004; Levine et al., 2006). Inconsistent results could be partly explained by the fact that only a few studies (e.g., Hyman et al., 2007; Moore et al., 1996) examined children with NF1 through an extensive neuropsychological assessment in order to compare them according to several indicators of T2H (i.e., presence, location, number, and size). Although hyperintensities are usually predominant in frontal subcortical networks through basal ganglia and thalamus (Chapman, Waber, Bassett, Urion, & Korf, 1996; Joy et al., 1995), only a small number of studies have examined the impact of T2H on EF in individuals with NF1. In addition, frontal networks are one of the most richly connected brain structures with a protracted development with age, so they are subject to a higher risk of impairment in case of general dysfunction (Goldberg & Bilder, 1987). This can be expected in NF1 since in this case T2H are diffusely distributed (Joy et al., 1995). Moreover, the frequent presence of T2H in the cerebellum could contribute to executive dysfunction given the implication of this region of the brain in the neuroanatomical substrates of EF (Heyder, Suchan, & Daum, 2004). Consequently, the present study aimed at analyzing, more particularly, EF in relation to indicators of T2H. Based on available data, we hypothesized that (1) the overall analysis of T2H in the whole brain (i.e., presence, number, and size) would not be associated with executive dysfunction, nor with overall cognitive impairment (as measured by IQ) in children with NF1, and (2) indicators of T2H (i.e., presence, number, and size), in a particular brain location would predict the neuropsychological profile of NF1 children. In other words, T2H in thalamus, basal ganglia, or cerebellum would be more specifically associated to EF impairment, as each of these locations is part of the neuroanatomical substrates of EF. In addition, thalamic T2H would also be related to a more overall cognitive dysfunction, according to Moore et al. (1996), who hypothesized that the location of T2H in this area could be responsible for the various cognitive deficits, which are often reported in NF1. Moreover, nonverbal IQ poor performances were expected to be in relation with right hemisphere T2H, whereas verbal IQ deficits were supposed to be associated with more extensive T2H involvement on the left hemisphere.

Methods Participants All school-age children referred to the Neurofibromatosis Clinic of our institution for medical diagnosis and follow-up in a 24-month period were offered participation in this study. The clinical sample enrolled in this research was described in detail in a previous study examining executive dysfunction in NF1 (Roy et al., 2010). All included subjects fulfilled clinical criteria for diagnosis of NF1 according to the National Institutes of Health Consensus Development Conference (1988) and were within the age range of 7 to 12 years. Exclusion criteria encompassed central nervous system pathologies or other health issues that may affect test performance (brain tumors, epilepsy/ seizures, hydrocephalus, history of psychiatric illness, premature birth), elementary visual or hearing impairment, and inad-

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equate French language skills to complete testing. Patients were not referred specifically for learning or cognitive problems to represent a relatively unbiased clinic-based sample of children with NF1. The 37 school-age children in whom the diagnosis of NF1was made accepted to participate in the study. One patient was excluded because of a history of epilepsy, so 36 patients were assessed. The mean age of children with NF1 was 9.62 years (SD ⫽ 1.74; range ⫽ 7–12.92). There were equal numbers of boys and girls; 22 patients had sporadic NF1 and 14 had the familial form of the disease (the family history of the two remaining patients could not be determined since they were adopted). The average of parents’ years of education was 11.81 (SD ⫽ 20.91; range ⫽ 7.5–20). Depending on the diagnostic criteria of the Diagnostic and Statistical Manual for Mental Disorders, 4th Edition (1996), 14 of the patients (38.89%) were classified as having attention deficit hyperactivity disorder (ADHD). The behavior rating scale adapted from Schrimsher, Billingsley, Slopis, & Moore III (2003) was used to rate each behavioral symptom of ADHD as listed in the DSM–IV, taking into account duration (at least 6 months), beginning (before 7 years old), and impact in several settings (i.e., home and school). Signed informed consent was obtained from the parents or guardians of all children and assent was granted from the patients themselves. The experimental protocol was approved by the Direction of Clinical Research of the University Hospital. This study was conducted as part of a larger study examining the neuropsychological profile of children with NF1 (BRD/05/1-K).

Assessment The study protocol included a relatively comprehensive neuropsychological assessment of EF, and a brain MRI examination. Executive functioning was examined through various wellstandardized neuropsychological classical tests including NEPSY subtests (tower, verbal and design fluencies, knock-tap, and statue; Korkman, Kirk, & Kemp, 2008), a French adaptation of the matching familiar figure test (MFFT; Marquet-Doléac, Albaret, & Bénesteau, 1999), the Wechsler Intelligence Scale for Children (3rd ed.; WISC-III) mazes (Wechsler, 1996), the Rey complex figure test (RCFT; Rey, 1959), and the test of two barrages (T2B; with two conditions, T2B1 -selective attention-, and T2B2 -divided attention; Zazzo, 1969). To provide ecological assessment of EF, we used the parent form of the French Behavior Rating Inventory of Executive Function (BRIEF; Roy, Fournet, Roulin, & Le Gall, 2013). The WISC–III was also completed to assess intellectual functioning, with all subtests administered (Wechsler, 1996). This set was not the entire test battery, but those tasks for which French normative data were available and then retained for data analysis within the context of this study. The MRI examinations of the brain were performed using a © Signa 1.5 Tesla imager (Siemens-Magnetom ) and reviewed by a pediatric radiologist expert in NF1’s disease. If any doubts existed about T2H measures, other study investigators were questioned to reach consensus after discussion. Sequences were performed in axial and sagittal orientation, with T2-weighted images and protons. The images were obtained with 4 to 5 mm thick sections. Most of the MRIs were carried out without any medication or

ROY ET AL.

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anesthetic; a trivial oral premedication (i.e., hydroxyzine syrup) was sometimes required. A standard method for analysis was used: sequences and parameters were identical from one patient to another. All identifiable T2H were systematically recorded according to their number, size, and site of occurrence. The crosssectional area of each T2H was manually traced to obtain its size; in case of shape heterogeneity, the largest hyperintensity diameter (in millimeters) was considered. On the basis of previous research on this domain (e.g., Goh et al., 2004; Hyman et al., 2007), the anatomical sites of T2 hyperintensities occurrence were categorized into the thalamus, basal ganglia (pallidum and/or striatum), cerebellum (cerebellar peduncle and/or dentate nucleus), thalamus, brain stem, left versus right hemispheres, and others (corpus callosum and frontal, temporal, occipital or parietal white matter). We easily identified the localization of T2H on precise neuroanatomical atlases by the difference of signal intensity between them and adjacent anatomical structures. In the current study, image localization in a given structure was achieved with no difficulties. This can be explained by the fact that T2H are of small size and can be easily linked to a specific region.

Procedure The neuropsychological assessment was conducted individually over three half-day sessions in a 1-month period by two experienced child neuropsychologists. MRI imaging was carried out up to 6 months before the neuropsychological evaluation. The MRI scan took about 20 minutes. MR images were independently analyzed by the experienced radiologist of the Neurofibromatosis Clinic, who was unaware of the patient’s clinical history, except for the diagnosis of NF1. Equally, results of the MRI examination were not known at the moment of the neuropsychological assessment.

Statistical Analyses ©

All statistical analyses were performed using Statistica , version 9.0. In a preliminary step, the neuropsychological profile of the clinical study sample as a whole was studied. Some tests results have been described in our previous study with healthy controls matched by age, gender, and parental education outperforming NF1 patients, especially on intellectual composite and EF scores (Roy et al., 2010). To further describe the cognitive phenotype of our sample within the larger context of this study, all neuropsychological measures of patients were compared with normative means of the tests, using one-sample t tests (on the basis of theoretical Z scores) or chi-square when appropriate (for categorical measures, the proportion of patients with limit to impaired performance derived from age-referenced norms was compared to the corresponding normative sample percentage, i.e., 25%). To be compared with scarce published data on T2H and NF1 neuropsychological profile, we adopted the same statistical methodology as recent studies that considered the presence, location, number, and size of T2H (i.e., Goh et al., 2004; Hyman et al., 2007). Two different data sets were constructed and then analyzed to test our hypotheses. In a first global analysis step, patients’ samples were divided into two subgroups: with T2H on MRI scans (T2H⫹), and without (T2H⫺).

Independent t tests and chi-square analysis were used to control for demographic equivalence between the two patients subgroups (i.e., age, gender, parents’ education level, and family history of NF1). The effect of the presence of hyperintensities was analyzed by comparing IQ and EF measures between T2H ⫹ and T2H⫺ groups. Given the small sample size, Mann– Whitney nonparametric tests were used for continuous variables with standardized scores by age (WISC–III, NEPSY) or raw scores when standardized scores were not available (T2B, MFFT, RCFT). Chi-square analysis was used for categorical measures (knock-tap, statue, and tower rule breaks) to compare groups for the number of children with limit to impaired performance derived from age-referenced norms (i.e., cumulative percentage of 25%). The total number and size of brain hyperintensities were correlated with each neuropsychological test score using Spearman’s coefficients. As multiple comparisons and correlations were conducted, a more conservative significance level of p ⬍ .01 was required to limit the probability of type I errors. In a second local analysis step, the same statistics were performed to study the differences between children with T2H in a specific brain site and both children without T2H and having T2H elsewhere in terms of EF and intellectual measures (after the control for demographic equivalence between each subgroups). The presence, number, and size of T2H as a function of their particular anatomical location were then systematically taken into account. To study dominant left and right hemisphere functions in relation to T2H location, we adopted the methodology proposed by Goh et al. (2004): we examined the relationship between the number (and size) of T2H in the left hemisphere minus the number of T2H in the right’s one and the difference between VIQ and Performance IQ (PIQ) using Spearman correlations. As previously, a significance level of p ⬍ .01 was chosen to reduce type I errors.

Results Clinical Sample Characteristics Of the 36 patients, 28 (77.8%) had T2H whereas eight had no evidence of increased T2 signal intensity on MRI examinations. The two groups did not differ significantly in terms of age, t ⫽ 0.29, p ⫽ .770, parents’ education level, t ⫽ ⫺0.38, p ⫽ .704, and gender (␹2 ⫽ 2.57, p ⫽ .109). Likewise, there were equal frequencies between the two groups for family history of NF1 (␹2 ⫽ 1.70, p ⫽ .192). Among the 28 children with hyperintensities, the total number of hyperintensities across the brain ranged from 1 to 10 (M ⫽ 4.28, SD ⫽ 2.10), and the cumulative size of T2H ranged from a diameter of 10.5 to 119.5 mm (M ⫽ 47.60, SD ⫽ 26.11). The number and size of T2H were not correlated with age in months (both, p ⬎ .05). The locations of T2H, together with the number and size of hyperintensities by location, are shown in Table 1. The areas of increased T2 signal most commonly occurred in the basal ganglia (more than 85% of patients with T2H). The cerebellum (68%) and brainstem (64%) were also frequently involved, whereas the thalamus (21%), cortex white matter (14%), and corpus callosum (7%) were rarely involved. In 93% of children, hyperintensities were present in more than one of these sites (two locations, n ⫽ 13;

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HYPERINTENSITIES AND EXECUTIVE DYSFUNCTION IN NF1

three or more locations, n ⫽ 13) while they were present in a single site in only two patients. In the first patient, the only site concerned was the pallidum (one T2H in each hemisphere), while in the second patient one T2H was identified in the left cerebellar hemisphere. It is of interest to note that this patient is the only one who did not have T2H in both hemispheres. All subgroups of children with main specific T2H location (i.e., basal ganglia, cerebellar, brain stem, or thalamic T2H) did not significantly differ for age, parents’ education level, or sporadic/ familial NF1 when respectively compared with both children without hyperintensities and having hyperintensities elsewhere (all, p ⬎ .05). Gender repartition was also equivalent across these subgroups, except for children with and without cerebellar T2H (␹2 ⫽ 5.46, p ⫽ .019). The proportion of girls in the subgroup of children with cerebellar T2H (68.42%) was higher than in the subgroup without T2H (29.41%). In addition, age (in months) was not correlated with the number and size of T2H within each location (all, p ⬎ .05). Children with NF1 had lower scores compared with normative data across numerous neuropsychological tests including composite IQ scores (VIQ, PIQ, and FIQ) and most EF performance based-tests: mazes, RCFT, tower score, MFFT, T2B1 and T2B2 speed and accuracy (see Table 2). BRIEF ratings showed significant increase in children with NF1, both for global executive composite (GEC), behavior regulation index (BRI), and metacognition index (MI). Performances of patients were not significantly different from normative data on verbal and design fluencies, tower broken rules, statue, and knock tap (all, p ⬎ .08).

Global Analysis of T2H and Cognitive Profile Global analysis of neuropsychological performances and parents’ ratings according to the overall presence of T2H in the brain showed no statistically significant difference between the mean tests scores of the T2H ⫹ and T2H⫺ groups (all, p ⬎ .04; see Table 2). All EF tests and IQ measures were concerned by this result. A marginal effect was found for MFFT (p ⬍ .05), with a tendency of the T2H ⫹ group to outperform the T2H⫺ group.

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Similarly, the total brain number and size of hyperintensities were not significantly correlated with performance on any cognitive test or rating scale (all, p ⬎ .13; see Table 2 for details).

Location Analysis of T2H and Cognitive Profile As illustrated in Table 3, no significant differences were found in the cognitive profile of NF1 children with or without T2H independently from brain location. This was particularly true for children with versus without basal ganglia T2H (all, p ⬎ .13). Neuropsychological performances were also closely equivalent between patients with and without cerebellar T2H; except for a small trend toward significance in the latter subgroup on one executive score (tower, score: p ⬍ .09), all other comparisons did not differ significantly (all, p ⬎ .11). When contrasting children with T2H in thalamus with other patients, one significant effect and trends toward significance were observed for sporadic measures, however, not necessarily as expected. Patients with thalamic T2H tended to have lower performance on design fluency compared with those without lesions and those having lesions elsewhere (U ⫽ 30.50, Z ⫽ 2.50, p ⫽ .012) whereas the opposite pattern was found on MFFT (U ⫽ 39.00, Z ⫽ ⫺2.14, p ⫽ .032), and tower broken rules (␹2 ⫽ 2.77, p ⫽ .096). All other differences as a function of thalamic T2H were largely not significant (all, p ⬎ .12). Globally, there were no significant correlations between the number and size of T2H in each of the main locations (i.e., basal ganglia, cerebellum, and thalamus) and neuropsychological scores. Only one significant negative correlation was found between the number of thalamic T2H and design fluency (p ⬍ .01). A number of trends were identified between cognitive outcomes and location of T2H (p value range between .01-.09); however, the direction of the correlations was inconsistent (either positive or negative correlations; see Table 4). On the basis of the methodology used in previous work (Goh et al., 2004), we failed to find any significant correlation between (i) the number of T2H in the left hemisphere minus the number of T2H in the right one, and (ii) the VIQ minus PIQ mean score

Table 1 Number and Size of Unidentified Bright Objects Depending on Brain Anatomical Locations in NF1 Children With Hyperintensities (N ⫽ 28) Number of T2H

Cumulative size of T2H (in millimeters)

T2H locationa

Number of patients (%)

Mean (SD)

Range

Mean (SD)

Range

Basal ganglia Cerebellum Brain stem Thalamus Cortex WMb Corpus callosum LHc RHc

24 (85.7) 19 (67.9) 18 (64.3) 6 (21.4) 4 (14.3) 2 (7.1) 28 (100) 27 (96.4)

1.83 (0.38) 1.36 (0.49) 1.77 (1.21) 1.66 (0.81) 1.50 (1.00) 1.00 (0.00) 2.07 (1.15) 1.92 (0.87)

1–2 1–2 1–6 1–3 1–3 — 1–6 1–4

19.20 (9.53) 21.23 (11.40) 15.83 (7.58) 18.00 (8.53) 14.12 (13.93) 9.50 (9.19) 24.41 (16.08) 22.46 (13.98)

8–48 6–42 2.5–32.5 5–26 3–34.5 3–16 3–73 5–52

a

Abbreviations: T2H, T2-weighted hyperintensities; WM, white matter; LH, left hemisphere; RH, right hemisphere. b T2H location within cortex WM: frontal (n ⫽ 1), occipital (n ⫽ 1), parietal (n ⫽ 1) or frontal and occipital lobes (n ⫽ 1). c Data provided are based on 110 out of the 120 total identified T2H, as 10 T2H were not clearly lateralized (e.g., corpus callosum, median areas of brain stem).

t ⫽ ⫺3.33 (.002) t ⫽ ⫺3.12 (.003) t ⫽ ⫺2.54 (.015) t ⫽ ⫺0.40 (.684) t ⫽ ⫺1.73 (.092) t ⫽ ⫺8.59 (⬍.001) t ⫽ ⫺3.74 (⬍.001) t ⫽ ⫺2.68 (.010) t ⫽ ⫺2.88 (.006) t ⫽ ⫺6.36 (⬍.001) t ⫽ ⫺3.76 (⬍.001) ␹2 ⫽ 0.11 (.743) ␹2 ⫽ 3.04 (.081) ... t ⫽ ⫺5.10 (⬍.001) t ⫽ ⫺2.99 (.005) t ⫽ ⫺5.27 (⬍.001) t ⫽ ⫺4.57 (⬍.001) t ⫽ ⫺5.14 (⬍.001)

⫺0.06 (0.94) ⫺0.33 (1.15) ⫺2.33 (1.62) ⫺0.74 (1.19) ⫺0.75 (1.69) ⫺0.68 (1.42) ⫺2.25 (2.12) ⫺0.41 (0.66) 10 (27.7%) 4 (11.1%) 9 (25%) ⫺2.31 (2.71) ⫺0.57 (1.15) ⫺1.22 (1.39) ⫺1.03 (1.35) ⫺1.15 (1.34)

One-sample t test or ␹2 (p)

⫺0.51 (0.92) ⫺0.47 (0.90) ⫺0.41 (0.97)

Whole NF1 sample (n ⫽ 36)

0.01 (0.96) ⫺0.36 (1.21) ⫺2.28 (1.72) ⫺0.74 (1.20) ⫺0.79 (1.48) ⫺0.51 (1.55) ⫺2.08 (2.14) ⫺0.34 (0.61) 8 (28.6%) 3 (10.7%) 7 (25%) ⫺1.89 (2.64) ⫺0.42 (1.13) ⫺1.08 (1.35) ⫺0.96 (1.33) ⫺1.00 (1.33)

⫺0.50 (0.86) ⫺0.46 (0.86) ⫺0.38 (0.95)

T2H⫹ (n ⫽ 28)

⫺0.33 (0.89) ⫺0.20 (0.95) ⫺2.49 (1.31) ⫺0.73 (1.21) ⫺0.60 (2.39) ⫺1.25 (0.57) ⫺2.86 (2.09) ⫺0.66 (0.79) 2 (25%) 1 (12.5%) 2 (25%) ⫺3.76 (2.57) ⫺1.08 (1.13) ⫺1.70 (1.50) ⫺1.28 (1.51) ⫺1.70 (1.34)

⫺0.56 (1.16) ⫺0.48 (1.08) ⫺0.51 (1.10)

T2H- (n ⫽ 8)

U ⫽ 89.5, Z ⫽ 0.83 (.402) U ⫽ 92.0, Z ⫽ ⫺0.74 (.458) U ⫽ 95.0, Z ⫽ 0.62 (.530) U ⫽ 109.0, Z ⫽ 0.09 (.924) U ⫽ 90.0, Z ⫽ ⫺0.81 (.413) U ⫽ 70.0, Z ⫽ 1.57 (.114) U ⫽ 84.0, Z ⫽ 1.04 (.295) U ⫽ 74.5, Z ⫽ 1.40 (.159) ␹2 ⫽ 0.04 (.842) ␹2 ⫽ 0.02 (.887) ... U ⫽ 59.0, Z ⫽ 1.99 (.045) U ⫽ 75.5, Z ⫽ 1.36 (.170) U ⫽ 82.5, Z ⫽ 1.10 (.269) U ⫽ 100.5, Z ⫽ 0.41 (.675) U ⫽ 75.0, Z ⫽ 1.38 (.164)

U ⫽ 105.5, Z ⫽ 0.22 (.819) U ⫽ 109.5, Z ⫽ 0.07 (.939) U ⫽ 106.0, Z ⫽ 0.20 (.834)

U, Z or ␹2 (p)

.12 (.457) ⫺.01 (.947) ⫺.09 (.587) .04 (.787) ⫺.25 (.131) .25 (.135) .01 (.950) .23 (.169) .07 (.679) .17 (.300) ⫺.00 (.985) .19 (.247) .10 (.523) .09 (.565) .13 (.444) .05 (.754)

⫺.13 (.431) ⫺.07 (.652) ⫺.14 (.406)

Correlation (r) with total number of T2H (p)

.06 (.702) ⫺.04 (.777) ⫺.05 (.764) .01 (.928) ⫺.20 (.233) .23 (.162) .06 (.708) .18 (.169) ⫺.08 (.623) .14 (.385) .02 (.867) .17 (.307) .15 (.362) .09 (.574) .14 (.387) .08 (.623)

⫺.15 (.374) ⫺.05 (.732) ⫺.21 (.215)

Correlation (r) with cumulative size of T2H (p)

Abbreviations: IQ, intelligence quotient; T2H⫹, children with T2-weighted hyperintensities; T2H⫺, children without T2-weighted hyperintensities; RCFT, Rey Complex Figure Test; T2B1, test of two barrages--selective attention; T2B2, test of two barrages--divided attention; MFFT, matching familiar figure test; BRIEF, Behavior Rating Inventory of Executive Function; GEC, global executive composite; BRI, behavior regulation index; MI, metacognition index. b All scores reported are mean Z scores (deviation from the mean of a normal population with negative Z scores corresponding to worse performance) with SD in parenthesis, except for categorical measures (knock tap, statue, and tower rule breaks: number of children with limit to impaired performance derived from age-referenced norms is reported, with correspondent proportion in parenthesis).

a

Intelligence Full scale IQ Verbal IQ Performance IQ Executive function Verbal fluency Design fluency RCFT T2B1, speed T2B1, accuracy T2B2, speed T2B2, accuracy Tower, score Tower, rules compliance Knock-tap Statue MFFT Mazes BRIEF GEC BRIEF BRI BRIEF MI

Neuropsychological testsa,b

Table 2 Neuropsychological Performances of Children With NF1 As A Function of T2H: Global presence, Number and Size (N ⫽ 36)

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478 ROY ET AL.

HYPERINTENSITIES AND EXECUTIVE DYSFUNCTION IN NF1

479

Table 3 Neuropsychological Performances of Children With NF1 Depending on the Presence or Absence of Unidentified Bright Objects in Specific Brain Locations (N ⫽ 36)

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Neuropsychological testsa,b Intelligence Full scale IQ Verbal IQ Performance IQ Executive function Verbal fluency Design fluency RCFT T2B1, speed T2B1, accuracy T2B2, speed T2B2, accuracy Tower, score Tower, rules compliance Knock tap Statue MFFT Mazes BRIEF GEC BRIEF BRI BRIEF MI

BG T2H⫹ (n ⫽ 24)

BG T2H⫺ (n ⫽ 12)

Cer T2H⫹ (n ⫽ 19)

Cer T2H⫺ (n ⫽ 17)

Thal T2H⫹ (n ⫽ 6)

Thal T2H⫺ (n ⫽ 30)

⫺0.51 (0.90) ⫺0.53 (0.90) ⫺0.35 (0.96)

⫺0.50 (0.99) ⫺0.34 (0.93) ⫺0.52 (1.01)

⫺0.60 (0.91) ⫺0.56 (0.93) ⫺0.48 (0.94)

⫺0.41 (0.95) ⫺0.36 (0.88) ⫺0.32 (1.02)

⫺0.72 (0.67) ⫺0.67 (0.77) ⫺0.62 (0.56)

⫺0.47 (0.97) ⫺0.42 (0.93) ⫺0.37 (1.03)

0.02 (0.92) ⫺0.25 (1.26) ⫺2.32 (1.72) ⫺0.70 (1.16) ⫺0.92 (1.55) ⫺0.51 (1.55) ⫺2.15 (2.08) ⫺0.31 (0.64) 8 (33.3%) 3 (12.5%) 6 (25%) ⫺2.07 (2.79) ⫺0.40 (1.18) ⫺0.97 (1.39) ⫺0.82 (1.30) ⫺0.91 (1.40)

⫺0.25 (1.01) ⫺0.50 (0.92) ⫺2.34 (1.49) ⫺0.82 (1.29) ⫺0.42 (1.96) ⫺1.02 (1.08) ⫺2.46 (2.29) ⫺0.61 (0.67) 2 (16.6%) 1 (8.3%) 3 (25%) ⫺2.77 (2.59) ⫺0.91 (1.03) ⫺1.71 (1.30) ⫺1.46 (1.41) ⫺1.63 (1.14)

⫺0.15 (0.89) ⫺0.38 (1.20) ⫺2.29 (1.47) ⫺0.73 (1.17) ⫺0.89 (1.30) ⫺0.29 (1.36) ⫺2.21 (2.21) ⫺0.24 (0.63) 5 (26.3%) 2 (10.5%) 5 (26.3%) ⫺2.55 (2.88) ⫺0.64 (0.95) ⫺1.26 (1.47) ⫺0.99 (1.54) ⫺1.23 (1.38)

0.03 (1.01) ⫺0.27 (1.13) ⫺2.37 (1.82) ⫺-0.75 (1.24) ⫺0.59 (2.07) ⫺1.11 (1.39) ⫺2.30 (2.10) ⫺0.60 (0.65) 5 (29.4%) 2 (11.7%) 4 (23.5%) ⫺2.04 (2.57) ⫺0.49 (1.35) ⫺1.17 (1.33) ⫺1.08 (1.16) ⫺1.06 (1.34)

⫺0.00 (0.63) ⫺1.38 (0.90) ⫺3.14 (1.38) ⫺0.82 (0.51) ⫺1.50 (1.73) ⫺0.59 (1.45) ⫺2.92 (1.96) ⫺0.11 (0.75) 0 (0%) 0 (0%) 0 (0%) ⫺0.48 (1.21) ⫺1.11 (0.62) ⫺1.50 (1.47) ⫺1.28 (1.61) ⫺1.45 (1.42)

⫺0.07 (1.00) ⫺0.12 (1.09) ⫺2.16 (1.64) ⫺0.72 (1.29) ⫺0.60 (1.66) ⫺0.70 (1.43) ⫺2.12 (2.16) ⫺0.47 (0.64) 10 (33.3%) 4 (13.3%) 9 (30%) ⫺2.67 (2.79) ⫺0.46 (1.20) ⫺1.16 (1.39) ⫺0.98 (1.32) ⫺1.09 (1.34)

a

IQ, intelligence quotient; T2H⫹, children with T2-weighted hyperintensities; T2H⫺, children without T2-weighted hyperintensities; BG, basal ganglia; Cer, Cerebellum; Thal, thalamus; BS, brain stem; IQ, intellectual quotient; RCFT, Rey Complex Figure Test; T2B1, test of two barrages--selective attention; T2B2, test of two barrages--divided attention; MFFT, matching familiar figure test; BRIEF, Behavior Rating Inventory of Executive Function; GEC, global executive composite; BRI, behavior regulation index; MI, metacognition index. b All scores reported are mean Z scores (deviation from the mean of a normal population, with negative Z scores corresponding to worse performance) with SD in parenthesis, except for categorical measures (route finding, knock tap, statue, and tower rule breaks: number of children with limit to impaired performance derived from age-referenced norms is reported, with correspondent proportion in parenthesis).

(r ⫽ ⫺.01, p ⫽ .920). Similar result was observed regarding T2H size (r ⫽ ⫺.01, p ⫽ .929).

Discussion The objective of the present study was to examine possible associations between the cognitive phenotype of children with NF1 and T2H characteristics. To date, only few studies used an extended neuropsychological assessment for analyzing EF to compare patients with NF1 according to different specific T2H indicators (presence vs. absence, number, size, and specific location). The study also controlled for the demographic equivalence (i.e., age, sex, parental level of education, form of the disease) of the different T2H subgroups. We assumed, in accordance with the majority of the available data, that (1) the presence, number, and size of the T2H in the whole brain would be independent from executive functioning and intelligence scores, and (2) taking into account the specific and preferential location of T2H (i.e., in thalamus, basal ganglia, cerebellum) could more accurately predict the cognitive phenotype (Hachon et al., 2011; Levine et al., 2006), especially executive dysfunction, in reference to the NF1 typical pathogenesis model (North et al., 1997). The frequency of the T2H found in our clinical sample (77.8%) complies with the classically described percentage (43–79%) in earlier reviews on NF1 (Cutting et al., 2004; Levine et al., 2006). The majority of children with NF1 in our study had T2H, in accordance with the relatively high rates reported in recent studies (Barbier et al., 2011: 60%; Hyman et al., 2007: 89.5%). Moreover, the locations of

the T2H appear to be close to that usually observed in the literature (e.g., Barbier et al., 2011; Goh et al., 2004; Hyman et al., 2007), with predominant involvement of basal ganglia, cerebellum, and brain stem in more than half of patients with hyperintensities. On the contrary, the less frequent locations were corpus callosum and hemispheric white matter (less than 15% of patients). Thalamic hyperintensities were found in approximately 20% of patients with T2H. This moderate frequency is lower than that observed in some studies (Hyman et al., 2007), but consistent with others showing that the number of T2H in the thalamus is lower than that observed in most of other main brain areas (Barbier et al., 2011; Goh et al., 2004). Furthermore, more than 90% of patients had several hyperintensity lesions that were widely distributed throughout the brain (almost one out of two NF1 children with T2H had three or more locations), with an involvement of both hemispheres in nearly all patients. Finally, T2H (presence, location, number, and size) seemed to be independent of the form of the disease (sporadic vs. familial) and demographic variables (age, gender, and parental level of education). So, the distribution of T2H within the study sample was relatively close to conventional observations, with a sociodemographic subgroups equivalence limiting the risk of bias, unlike several previous studies. The overall analysis of neuropsychological performance in NF1 children demonstrated a significant decline, as compared to normative data, in all composite scores of intelligence, and almost all EF performance-based tests and parental ratings, in accordance with previous data (see Lehtonen et al., 2013). By contrast, the presence of the T2H in the whole brain of children with NF1 was

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480

Table 4 Correlations Between T2H in Main Brain Locations and Neuropsychological Scores in the NF1 Sample (N ⫽ 36)

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Neuropsychological testsa,b Intelligence Full scale IQ Verbal IQ Performance IQ Executive function Verbal fluency Design fluency Rey complex figure test T2B1, speed T2B1, accuracy T2B2, speed T2B2, accuracy Tower, score Tower, rules compliance Knock tap Statue MFFT Mazes BRIEF GEC BRIEF BRI BRIEF MI

BG T2H

Cer T2H Number

Thal T2H

Number

size

Size

Number

Size

⫺.08 ⫺.17 .07

⫺.11 ⫺.07 ⫺.04

⫺.08 ⫺.06 ⫺.01

⫺.08 ⫺.06 ⫺.05

⫺.11 ⫺.15 ⫺.11

⫺.10 ⫺.13 ⫺.11

.13 .04 .05 .07 ⫺.22 .20 ⫺.00 .23 ⫺.22 .06 ⫺.10 .11 .04 .24 .14 .22

.11 .12 .01 .00 ⫺.09 .24 .03 .14 ⫺.37ⴱ .03 ⫺.09 .00 .12 .26 .21 .22

⫺.06 .02 .08 .10 ⫺.24 .38ⴱ ⫺.02 .30 (ⴱ) ⫺.00 .03 ⫺.09 ⫺.04 .00 .04 .15 ⫺.01

⫺.07 ⫺.03 .11 .06 ⫺.17 .28 (ⴱ) .03 .31 (ⴱ) ⫺.06 .05 .00 .03 .00 ⫺.00 .08 ⫺.03

.06 ⫺.43ⴱⴱ ⫺.23 ⫺.01 ⫺.20 .03 ⫺.21 .23 .07 .23 .06 .36ⴱ ⫺.24 ⫺.07 ⫺.03 ⫺.09

.05 ⫺.41ⴱ ⫺.23 ⫺.01 ⫺.20 .03 ⫺.19 .20 .07 .23 .05 .34ⴱ ⫺.24 ⫺.08 ⫺.02 ⫺.10

a

IQ, intelligence quotient; T2H⫹, children with T2-weighted hyperintensities; T2H-, children without T2weighted hyperintensities; BG, basal ganglia; Cer, cerebellum; Thal, thalamus; BS, brain stem; IQ, intellectual quotient; RCFT, Rey Complex Figure Test; T2B1, test of two barrages--selective attention; T2B2, test of two barrages--divided attention; MFFT, matching familiar figure test; BRIEF, Behavior Rating Inventory of Executive Function; GEC, global executive composite; BRI, behavior regulation index; MI, metacognition index. b All scores reported are Spearman’s correlation coefficients. (ⴱ) p ⬍ .10. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

not specifically associated with lower neuropsychological scores. This result is consistent with that of many studies examining different aspects of cognition in NF1 (Bawden et al., 1996; Duffner et al., 1989; Dunn & Roos, 1989; Ferner et al., 1993; Goh et al., 2004; Hyman et al., 2007; Legius et al., 1995; Moore et al., 1996), but not all (Chabernaud et al., 2009; Feldmann et al., 2003; North et al., 1994). It is worth noting that Chabernaud et al. (2009) reported mixed results and their interpretation is unclear (uncontrolled multiple comparisons and conflicting data between the text and the table regarding the RCFT). Moreover, the whole brain T2H mean size was not significantly related to neuropsychological test performances. This finding is in agreement with results of the few studies that considered this variable (Chabernaud et al., 2009; Denckla et al., 1996; Ferner et al., 1993; Legius et al., 1995). Given that results of prior studies were only based on IQ assessment, our findings further support the nondiscriminating nature of the global T2H size regarding NF1 children’s cognitive profile. Likewise, our results confirm the absence of any significant link between the total number of brain T2H and the cognitive phenotype (Chabernaud et al., 2009; Feldmann et al., 2003; Ferner et al., 1993; Hyman et al., 2007; Moore et al., 1996; North et al., 1994). So, the presence of T2H as well as their number and size in the whole brain of children with NF1 appear to be independent from intellectual and EF profiles. This finding, which is consistent with almost all available data, validates our first hypothesis and reduces the relevance of considering

the whole presence of T2H when analyzing the neuropsychological profile of children with NF1. Contrary to what we expected in our second hypothesis, there was no significant correlation between the presence, number, and size of T2H in each of the classic locations (i.e., basal ganglia, thalamus, and cerebellum) and EF performance-based tests and parents’ ratings of NF1 children. Likewise, there was no evidence suggesting a lateralization effect of T2H on cognitive phenotype. While some studies (Ferner et al., 1993; Legius et al., 1995) support our finding that thalamic T2H have no impact on EF or the overall cognitive functioning, others (Chabernaud et al., 2009; Goh et al., 2004; Hyman et al., 2007; Moore et al., 1996) failed to show this finding. This could be explained by the fact that most of these works, except for Moore et al. (1996), were limited to some neuropsychological measures. Only VIQ (and FIQ), as well as two sporadic indexes of episodic memory, were moderately associated to thalamic T2H size (but neither presence nor number) in Goh et al.’s (2004) study; on the contrary, PIQ and all other cognitive domains including memory, motor speed, attention, and sensorimotor and manual dexterity were not significantly associated with location of T2H in the thalamus. Also, in Hyman et al.’s (2007) study, only 4 out of 20 neuropsychological tests were significantly associated with thalamic T2H, when patients were compared with their sibling controls; only IQ scores and, more particularly, nonverbal ones were concerned by this relationship (unlike the previously cited study) whereas this was not the case for memory,

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HYPERINTENSITIES AND EXECUTIVE DYSFUNCTION IN NF1

language, visuospatial abilities, academic achievement, EF, or attention. When these patients were compared with normative data, a significant effect was found for thalamic T2H on only attentional switching and fine motor coordination, which is inconsistent with results reported by Goh et al. (2004). Results reported by Chabernaud et al. (2009) reveal additional inconsistencies, with an effect of the thalamic-striatal T2H on both verbal and nonverbal IQ (as partially opposed to the previous two studies) and on visuospatial processing (with opposite results from Moore et al. (1996) and Hyman et al. (2007)), however, without specific visuospatial task and statistical control for multiple comparisons. The fact that basal ganglia and cerebellum T2H are not associated with preferential executive dysfunction (and global cognitive impairment) tends to confirm some preliminary data (Hyman et al., 2007; Moore et al., 1996) but contradicts other ones that show an association between hyperintensities in the left globus pallidus and attentional difficulties (Goh et al., 2004). Inconsistencies also emerge in another study (Piscitelli et al., 2012) that showed a decline in IQ among NF1 children with cerebellar T2H, but not in other cognitive measures, including attention (this latter aspect being consistent with our results). Further inconsistencies come from other results showing a main decrease of IQ in the case of T2H in basal ganglia by contrast to cerebellar T2H over time (Feldmann, Schuierer, Wessel, Neveling, & Weglage, 2010). Finally, no significant link was observed between T2H in the right hemisphere and fluid intelligence as well as between T2H in the left hemisphere and verbal intelligence, contrary to previously published data based on the same methodology (Goh et al., 2004). So, findings of the present study contribute to further contradiction in literature data regarding the potential correlation between neuropsychological profile and brain hyperintensities in children with NF1, even when specific T2H locations are considered. This contradiction could be partially explained by the fact that studies generally focused on small samples of patients (30 to 40 patients for most studies), except for Hyman et al.’s study (2007) that included a larger sample but also failed to demonstrate a clear impact of T2H location on cognitive profile. Furthermore, the sociodemographic equivalence of subgroups of patients (with and without T2H, overall and for each of the locations) was rarely controlled, in particular, with respect to mean age (e.g., patients with T2H are younger than patients without T2H in the samples studied by Goh et al. (2004) or Hyman et al. (2007). Similarly, there is no study that controlled for the equivalence of the parental education level between these subgroups (except for Piscitelli et al.’s (2012) study), while this factor is likely to influence cognitive performance. Moreover, apart from some few studies (Hyman et al., 2007; Moore et al., 1996), neuropsychological examination was often restricted and conclusions were sometimes drawn from a few isolated clues that did not accurately reflect the targeted process, which were sometimes not clearly defined. For example, the correlation between hyperintensities in the left globus pallidus and attentional difficulties in the study of Goh et al. (2004) was only based on an undetermined measure derived from the trail making test, not allowing the specific assessment of attentional abilities. Even after considering many methodological limitations (i.e., equivalence of subgroups in terms of age, gender distribution, and parental education level, detailed examination of EF through several direct measures, and by an everyday life questionnaire), the

481

current study does not support a clear link between T2H brain location and executive dysfunction, and more globally between T2H and cognitive impairment in children with NF1. However, it is possible that the way we measure the T2H on structural MRI does not allow the identification of this link, given their inherently evolving nature (Hyman et al., 2003; Itoh et al., 1994). Indeed, the decline or change in the T2H incidence with age, in terms of presence, number, size, and location, contributes to cloud the issue and supposes that abnormal MRI signals may vary, depending on the time they are measured. In other words, the absence of T2H does not mean that they have not previously existed, and that the potential consequences of their previous occurrence are not yet perceptible at the time of the MRI. Their tendency to disappear as children grow up may lead to errors in T2H measurement and therefore interferes with the subgrouping, according to the presence or not of T2H. Based on this point, we realized a longitudinal imaging study of data available for our sample. This analysis showed that two of the patients classified as having no T2H at the time of the study have had hyperintensities lesions in the past, preferentially in frontal subcortical circuits. These children were therefore classified as “without T2H” while they previously have had hyperintensity lesions so that the impact of these, becoming now, invisible lesions, is potentially similar to that in children identified as “with T2H.” The fact that in some studies patients without T2H were older than children with T2H (Goh et al., 2004; Hyman et al., 2007), could also be a sort of artifact in relation to the trend of T2H to disappear with age. Consequently, longitudinal examination of the growing up children in terms of T2H and cognitive performance represents relevant areas for research. All the same, it is important to note that this does not mean that T2H location is not critical for determining the neuropsychological profile of children with NF1, but that their significance at the time of their examination is of limited value, at least regarding the cognitive phenotype. Their high frequency of occurrence in some brain areas (basal ganglia, cerebellum, and thalamus) at some time during the patients’ life suggests that disruption of these structures is probably responsible for the neuropsychological symptomatology, as this was recently modeled through an etiological approach involving neuroanatomical substrates and cognitive/behavioral disturbances in NF1 (see Hachon et al., 2011). If impairment of these different cerebral areas helps to explain several neuropsychological manifestations (especially visuospatial and motor abilities and phonological processing), it is becoming increasingly evident that EF and its anatomicalfunctional substrates could represent a basic feature. Indeed, each of the brain structures preferentially affected by T2H is an integral part of cortico-sub-cortical circuits underlying EF, which are connecting to the prefrontal cortex, the basal ganglia, and the cerebellum via the thalamus (Heyder et al., 2004). In the current study, almost all NF1 children with T2H are concerned with a disruption of one or more levels of this frontostriatal system; besides, it is likely that those without T2H at the time of the investigation could have had hyperintensities in this location in the past (as described above for two patients). Growing arguments supporting the idea that EF impairment is prominent in children with NF1 (Hyman et al., 2006; Payne et al., 2012; Payne et al., 2011; Rowbotham et al., 2009; Roy et al., 2012; Roy et al., 2010) tend to confirm this proposal, together with diffuse EF disorders observed in our patients’ sample as compared with

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482

available norms. The high prevalence of ADHD in NF1 further strengthens the critical role of fronto-sub-cortical networks and their link with EF disorder in NF1, which has already been discussed within the broader context of ADHD (Barkley, 1997). Similarly, functional imaging data (see Hachon et al., 2011; Payne, Moharir, Webster, & North, 2010 for a review) contribute to suggest a disruption of the connection between the anterior and posterior brain regions in NF1, leading to potential weakening of executive control abilities over the overall cognitive functioning. NF1 morphological abnormalities in fronto-sub-cortical networks, such as the thalamus and basal ganglia (Duarte et al., 2014; Violante, Ribeiro, Silva, & Castelo Branco, 2013) are additional arguments supporting executive dysfunction as a key component of neuropsychological phenotype in NF1. Limitations to the present study include the small sample size, which could lead to relativize the generalizability of the results. It remains possible that lack of significant correlations in different comparisons is corresponding to the small sample size, and that larger samples allow for obtaining significant positive results. One can note, however, that most prior studies were based on similar sample size, and that sociodemographic equivalence between T2H subgroups was generally not controlled for, in contrast with our study. In addition, a comprehensive assessment of cognitive functioning would have been necessary, in particular, visuospatial, visuomotor, and language abilities, in order to specifically study the T2H effect on these domains. Similarly, although learning disabilities are common in NF1, they were not investigated, which could also limit the scope of our results.

Conclusion The analysis of T2H (presence, number, and size) throughout the whole brain or according to their preferential locations does not seem to constitute a robust and systematic differentiating criterion for NF1 children in terms of cognitive phenotype, especially EF. More fundamentally, given the possible errors in T2H measurement due to their evolving nature on MRI, caution is required in considering the results of the present study, as well as conflicting evidence from the literature. So, first, one should refrain from drawing oversimplistic conclusions like that only or mainly children having NF1 with T2H (or those with T2H in certain locations) are at increased risk of having neuropsychological and learning disorders. The follow-up of children should not be exclusively reserved to those having NF1 with T2H (at the expense of children without T2H), given the high risk of false negatives. Second, the current method of T2H measurement does not guarantee direct anatomical-functional matching with neuropsychological disorders in NF1 patients. These issues are not inconsistent with the idea that T2H represent crucial markers of cognitive dysfunction in NF1. Specifically, the presence of diffuse T2H and their preponderance in frontosub-cortical networks, together with other neurophysiologic markers (i.e., morphologic and functional imaging data), could be cumulative risk factors for executive dysfunction. Moreover, early onset of these congenital brain anomalies can be related to the early brain vulnerability hypothesis, which is particularly pronounced for EF in the context of early brain injury (e.g., Anderson et al., 2010). This idea echoes that of Chapman et al. (1996) who suggested that the neurobehavioral profile of their NF1 sample was

consistent with a compromise of frontal subcortical brain system. This also fits well with the historical pathogenesis model of North et al. (1994) and with further recent modeling (Hachon et al., 2010), including specific brain structures. This view is also supported by the persistent neuropsychological impairment found in adults with NF1 suggesting that the NF1 child’s brain would adapt partly to early wide neuronal abnormalities without, however, being able to overcome them completely (Pavol et al., 2006). This partial compensation during development would explain that various cognitive areas are often disrupted in NF1, and preferentially when multiple cognitive abilities including coordination, regulation, and control skills, in other words EF, are required.

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Received March 11, 2014 Revision received September 12, 2014 Accepted September 12, 2014 䡲

Examining the frontal subcortical brain vulnerability hypothesis in children with neurofibromatosis type 1: Are T2-weighted hyperintensities related to executive dysfunction?

It was hypothesized that neuropsychological impairments in children with neurofibromatosis type I (NF1) are associated with brain areas of increased T...
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