Abstract

Turner syndrome (TS) is a genetic condition that permits direct investigation of the complex interaction among genes, hormones, behavior, and brain development. Here, we used automated segmentation and surface-based morphometry to characterize the differences in brain morphology in children (n = 30) and adolescents (n = 16) with TS relative to age- and sex-matched control groups (n = 21 and 24, respectively). Our results show that individuals with TS, young and adolescent, present widespread reduction of gray matter volume, white matter volume and surface area (SA) over both parietal and occipital cortices bilaterally, as well as enlarged amygdala. In contrast to the young cohort, adolescents with TS showed significantly larger mean cortical thickness and significantly smaller total SA compared with healthy controls. Exploratory developmental analyses suggested aberrant regional brain maturation in the parahippocampal gyrus and orbitofrontal regions from childhood to adolescence in TS. These findings show the existence of abnormal brain morphology early in development in TS, but also suggest the presence of altered neurodevelopmental trajectories in some regions, which could potentially be the consequences of estrogen deficiency, both pre- and postnatally.

Introduction

Turner syndrome (TS) is a genetic condition caused by the partial or complete absence of one X-chromosome that affects approximately 1/2000 live births in females (Sybert and McCauley 2004; Gravholt 2005). Women with TS have a distinctive cognitive profile characterized by preserved verbal abilities, but relative weaknesses in visuospatial, visuomotor, and executive functions (Kesler 2007), as well as difficulties establishing and maintaining social relationships (Burnett et al. 2010). The usual physical phenotype associated with TS includes short stature, cardiovascular malformations, and a lack of endogenous estrogen during development. Standard medical intervention consists of growth hormone (GH) to increase stature during childhood, followed by estrogen treatment to trigger puberty and the development of secondary sexual characteristics if spontaneous puberty does not occur (Sybert and McCauley 2004). Accordingly, TS provides a unique opportunity to study the effects of X-chromosome genetic influences and neurohormonal factors on brain maturation during development.

Previous magnetic resonance imaging (MRI) studies have identified a number of brain regions exhibiting aberrant morphology in adolescents and adults with TS. Using univariate structural analyses of brain MRI (e.g. volumetric studies and voxel-based morphometry), the results of these studies have consistently shown a reduction in parieto-occipital gray matter volume (GMV) (Reiss et al. 1995; Brown et al. 2004; Molko et al. 2004; Cutter et al. 2006; Marzelli et al. 2011) and enlargement of the amygdala (Good et al. 2003; Kesler, Garrett et al. 2004). These anatomical variations have putatively been linked to cognitive–behavioral difficulties in TS, including visuospatial and social functioning. Structural and functional brain abnormalities in TS have also been reported to occur in other brain regions such as the hippocampus, caudate, thalamus, prefrontal, insular, and orbitofrontal cortices, and superior temporal gyrus/sulcus (Haberecht et al. 2001; Kesler et al. 2003; Molko et al. 2004; Cutter et al. 2006; Tamnes et al. 2010; Marzelli et al. 2011).

Although a consistent picture of brain structure and function in adolescents and adults with TS has begun to emerge, little is known about the effects of TS in young, pre-pubertal girls with this condition, or how (induced) puberty affects brain development. In particular, previous studies are limited by analyses of individuals across a broad age range, often straddling the pubertal period. Recent literature (Blakemore et al. 2010) demonstrating that cortical volume undergoes dynamic changes in the adolescent period emphasizes the need to stratify cohorts of individuals with TS in this developmental period. Characterizing TS neuroanatomy before, during, and after puberty would be valuable in clarifying the early effects of X-monosomy and estrogen on brain development. Furthermore, previous studies have largely relied on analyses of cortical volume alone. These approaches may overlook underlying differences in lower-order components of cerebral development, such as surface area (SA) and cortical thickness (CT), which appear to be influenced by independent genetic effects (Panizzon et al. 2009) and may be aberrant in adult TS (Raznahan, Cutter et al. 2010; Lepage et al. 2011). These additional metrics of brain development have never been studied in young TS populations.

The overarching objective of this study was to investigate developmental neuroanatomy in TS by comparing girls with this condition with age- and sex-matched healthy controls. Two age cohorts were studied: 1) young children with TS prior to estrogen exposure (4–11 years of age, n = 30) and 2) adolescents with TS who had started estrogen treatment (14–21 years of age, n = 16). Analyses were performed using a supervised automated brain segmentation program that allows separate classification of gray and white cortical volume, area, and thickness as well as subcortical morphology.

Materials and Methods

Participants

TS participants were recruited through the national Turner Syndrome Society and Turner Syndrome Foundation, a local network of physicians, and advertisement on the Stanford University School of Medicine website. Control participants were recruited through local print media and parent networks. Prior to enrollment in this study, all participants were screened with standard forms and interviews for MRI contraindications as well as past medical history to ensure that there were no instances of neurological injury, psychiatric illness or disease (except for anxiety disorders or attention deficit hyperactivity disorder often associated with TS), or gross physical impairments. Individuals born prematurely (i.e., <34 weeks gestation) were not included, nor were those exhibiting mosaic or uncommon structural karyotypes (e.g. 45X/46XX, ring X, isochromosome, deletions). Only subjects showing a verbal intelligence quotient (VIQ) within the normal range (70–130) were included in the present study. The local Institutional Review Board at the Stanford University School of Medicine approved this study and informed written consent was obtained from the legal guardian for all participants, as well as written assent from participants over 8 years of age.

The young age sample was comprised of 30 girls with TS (X-monosomic; 20 with a single X-chromosome from maternal origin, 10 from paternal origin; mean age, 7.72 ± 2.05 years; range, 4–11) and 21 age-matched typically developing (TD) female controls (mean age, 7.06 ± 2.16 years; range 4–11), whose participation occurred between 2005 and 2011. In the TS group, 26 participants were on GH treatment and one participant had used topical estrogen cream for the treatment of labial lesions. None of the TS subjects in the young group were on systemic estrogen replacement, and none reported having a psychiatric diagnosis or taking psychotropic medication. The adolescent cohort consisted of 16 individuals with TS (X-monosomic; 5 from maternal origin, 3 from paternal origin, 8 unknown origin; mean age, 18.22 ± 2.10 years; range, 14–21) and 24 age-matched healthy adolescent females (mean age, 17.75 ± 2.18 years; range 14–22), whose participation occurred between 1999 and 2006. All TS subjects in this adolescent group were receiving exogenous estrogen, and 12 subjects had a history of GH use. Two participants in this group reported having a diagnosis of attention deficit hyperactivity disorder and took related medication (methylphenidate). The population characteristics are summarized in Table 1. There was no overlap of subjects between the 2 cohorts.

Table 1

Mean and standard deviation of population characteristics

 Young
 
Adolescent
 
 Control (n = 21) Turner (n = 30) Control (n = 24) Turner (n = 16) 
Age 7.03 (2.2) 7.7 (2.1) 17.8 (2.2) 18.2 (2.1) 
FSIQa 112.9 (8.9) 93.3 (12.6) 116.2 (12.8) 107.5 (14.6) 
PIQab 112.2 (12.1) 92.8 (15.5) 111.6 (13.0) 98.6 (13.9) 
VIQa 110.5 (12.0) 101.2 (12.7) 117.4 (12.1) 114.1 (16.2) 
Growth hormone – 26 (87%) – 12 (75%), 1U 
Estrogen – – 16 
Parental origin – 20M, 10P unknown – 5M, 3P, 8U unknown 
 Young
 
Adolescent
 
 Control (n = 21) Turner (n = 30) Control (n = 24) Turner (n = 16) 
Age 7.03 (2.2) 7.7 (2.1) 17.8 (2.2) 18.2 (2.1) 
FSIQa 112.9 (8.9) 93.3 (12.6) 116.2 (12.8) 107.5 (14.6) 
PIQab 112.2 (12.1) 92.8 (15.5) 111.6 (13.0) 98.6 (13.9) 
VIQa 110.5 (12.0) 101.2 (12.7) 117.4 (12.1) 114.1 (16.2) 
Growth hormone – 26 (87%) – 12 (75%), 1U 
Estrogen – – 16 
Parental origin – 20M, 10P unknown – 5M, 3P, 8U unknown 

Note: FSIQ, Full scale intelligence quotient; PIQ, Performance intelligence quotient; VIQ, Verbal intelligence quotient. Growth hormone: number of participants reporting current or past usage, U, Unknown. Parental Origin: M, Maternal, P, Paternal, U, Unknown.

aSignificant group difference in young cohort at P < 0.05.

bSignificant group difference in adolescent cohort at P < 0.05.

Cognitive Assessment

Participants were administered cognitive assessments appropriate for their age: the Wechsler Preschool and Primary Scale of Intelligence-Third Edition (WPPSI-III; Wechsler 2002) was administered for 4- to 5-year-old children; the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; Wechsler 2003) for girls aged between 6 and 16 years; and the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III; Wechsler 1997) for participants older than 16 years of age.

MR Acquisition

All subjects were introduced to a mock MRI scanner prior to their actual scan to desensitize them to the sights and sounds of an actual MRI environment, and underwent behavioral training to help reduce motion-related artifacts. All imaging data were acquired at the Stanford University Lucas Center for Medical Imaging. Magnetic resonance images of the young cohort were collected between 2006 and 2011 on a GE Signa HDxt 3.0 T whole-body MR system (GE Medical Systems, Milwaukee, WI) using a standard birdcage headcoil. A fast spoiled gradient recalled (FSPGR) echo pulse sequence was employed to obtain a high-resolution T1 anatomical brain image of each subject (124 coronal slices, repetition time [TR]/echo time [TE] = 6.4/2 ms, inversion time [TI] = 300 ms, flip angle = 15°, number of excitations (NEX) = 3, feild of view (FOV) = 22 × 22 cm, matrix = 256 × 256, 1.5 mm thickness, acquisition time = 14 min 43 s).

Imaging of the adolescent cohort was performed on 2 different scanners. Twelve TS subjects and 20 control subjects were scanned between 1999 and 2006 on a GE Signa 1.5 T whole-body MR system (GE Medical Systems, Milwaukee, WI) with a standard birdcage headcoil. A SPGR pulse sequence was employed to obtain a high-resolution T1 anatomical brain image of each subject (124 coronal slices, TR/TE = 35/6 ms, flip angle = 45°, NEX = 1, FOV = 24 × 24 cm, matrix = 256 × 256, 1.5 mm thickness, acquisition time = 14 min 24 s). In addition, 5 TS subjects and 4 control subjects were scanned between 2009 and 2010 on the GE Signa HDxt 3.0 T whole-body MR system (GE Medical Systems, Milwaukee, WI) with standard birdcage headcoil described above. A comparable SPGR pulse sequence was employed to obtain a high-resolution T1 anatomical brain image of each subject (124 coronal slices, TR/TE = 35/6 ms, flip angle = 45°, NEX = 1, FOV = 24 × 24 cm, matrix = 256 × 256, 1.5 mm thickness, acquisition time = 13 min 44 s). The SPGR pulse sequence on the 3.0 T scanner was specifically developed to optimize image calibration between the 1.5 and 3 T Signa scanners.

Morphometric Analysis

MRI data were first visually inspected to eliminate scans/subjects with significant head motion or flow artifacts. Because of the presence of bias field artifact that was not completely removed using algorithms incorporated into the Freesurfer pipeline, all 3.0 T FSPGR sequence scans were preprocessed using bias field correction methods available with SPM8 (http://www.fil.ion.ucl.ac.uk/spm) before further processing with Freesurfer. Neither the 3.0 nor 1.5 T SPGR scans required this additional processing step. Cortical reconstruction and volumetric segmentation was performed with the Freesurfer version 5.0 image analysis suite (http://surfer.nmr.mgh.harvard.edu/). The technical details of the procedures used are extensively described in prior publications (Dale et al. 1999; Fischl and Dale 2000; Fischl et al. 2002, 2004). Briefly, this processing includes removal of non-brain tissue, segmentation of subcortical white matter and deep gray matter volumetric structures (including hippocampus, amygdala, caudate, putamen, ventricles) (Fischl et al. 2002), intensity normalization (Sled et al. 1998), tessellation of the gray matter–white matter boundary, and automated topology correction (Ségonne et al. 2007). Surface definition follows intensity gradients to optimally place the gray–white and pial surfaces at the location where the greatest shift in intensity defines the transition to another tissue class (Dale et al. 1999; Fischl and Dale 2000). The gray–white and pial surfaces were visually inspected, and where needed, appropriate manual corrections were performed as per the Freesurfer Tutorial (http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial). All raters were trained to achieve inter-rater reliability of ≥0.95 (intraclass correlation coefficient) with gold-standard datasets developed in our laboratory for volumetric regions of interest. Once cortical models were complete, brain surfaces for each hemisphere were parcellated into 34 distinct regions based on gyral and sulcal structure (Supplementary material, Figure 1) (Fischl et al. 2004; Desikan et al. 2006). Freesurfer calculates GMV, SA of the gray–white boundary, mean CT, and white matter volume (WMV) for each parcellated region. Procedures for measurement of CT have been validated against histological analysis (Rosas et al. 2002) and manual measurements (Kuperberg et al. 2003; Salat et al. 2004). Mean CT for the whole brain was calculated by averaging mean thickness of each parcellated region weighted by its corresponding cortical SA.

Given that the adolescent cohort combined data collected from SPGR sequences on the 1.5 and 3.0 T scanners, 3 calibration subjects were scanned within a period of 2 weeks on each scanner. The mean CT, total SA, and total brain volume calculated by Freesurfer were within 1.3% for each subject across scanners. Further, reliability studies have shown that Freesurfer-generated subcortical volumes CT are preserved across scan platforms (Han et al. 2006; Jovicich et al. 2009). Accordingly, the structural image results from these 2 scanning platforms were combined without adjustments to the data.

Statistical Analysis

For demographic and cognitive data, independent 2-tailed t-tests were used to assess differences between groups. For structural data, whole brain characteristics including total cortical GMV, subcortical GMV, total WMV, total SA, mean CT, and cerebellar volume were investigated using age and total brain volume as covariates. Total brain volume was defined as total gray and white matter tissue within the cerebrum in order to exclude the larger ventricles seen in the TS population (see below). To facilitate the interpretation of the results, we calculated the fractional difference (expressed in percentage) of TS relative to controls by computing the difference in the group means of the raw Freesurfer output divided by the mean of the control population.

Results of segmentation and parcellation processes were analyzed to compute the between-group effect for every regional GMV, WMV, SA, and CT characteristic, using age and total brain volume as covariates. Multiple comparisons were controlled using the false discovery rate (FDR; Storey 2002) available with the Matlab Bioinformatics Toolbox (www.mathworks.com). These analyses included 84 regional GMVs (including 16 subcortical regions), 73 WMVs (including 5 corpus callosum regions), 68 SAs and 68 CTs. The FDR threshold was applied separately to the results for each characteristic (GMV, WMV, SA, and CT) in order to avoid possible correlations between different characteristics for the same region. The reported regional results were considered statistically significant only if they passed both the significance threshold of P < 0.05 for the 2-tailed t-test in a single region and the FDR threshold q < 0.05 for multiple comparisons.

Within each age cohort, differences in whole brain and regional developmental trajectory of GMV, WMV, SA, and CT were evaluated using univariate models with “group” and “group × age” as factors and “total brain volume” as a covariate. In the adolescent cohort, “scanner” was also added as a covariate. In order to reduce the number of comparisons, regional analyses were only performed on a priori regions of interest (amygdala, parahippocampal gyrus, fusiform region, superior temporal region, inferior and superior parietal regions, orbitofrontal regions, caudal middle frontal, and anterior cingulate). Moreover, to measure potential developmental changes from childhood till adolescence, exploratory analyses were conducted between cohorts on the same a priori regions of interest, resulting in 80 between-cohorts comparisons where P < 0.05 uncorrected was considered significant. Differences in developmental trajectory were explored using univariate models with group, “cohort”, and “group × cohort” as factors, and total brain volume and scanner as covariates.

Results

Demographic and Cognitive Measures

There was no significant difference in age between groups in either cohort (P ≥ 0.4). In the young cohort, TD scored significantly higher than TS on all IQ measures (all P′s ≤ 0.012). In the adolescent cohort, control participants scored significantly higher than girls with TS on performance intelligence quotient (PIQ) (P = 0.005), but did not differ regarding VIQ (P = 0.35) or full scale intelligence quotient (FSIQ) (P = 0.052) (Table 1). Moreover, current or previous use of GH was similar between young (87%) and adolescent (75%) TS groups (P = 0.421, Fisher's exact test).

Whole-Brain Analyses

Total brain volume, total cortical GMV, and total WMV were not significantly different between groups in either cohort. However, in both cohorts, total subcortical GMV was significantly larger for TS than for controls (P = 0.002 for young, P = 0.004 for adolescents), and the fourth ventricle was also significantly larger for TS (P < 0.001 for young, P = 0.044 for adolescents) compared with controls. Although adolescents with TS had significantly smaller total SA (P = 0.002) and larger mean CT (P = 0.030) than controls, these differences did not reach significance in the young cohort (respectively, P < 0.065 and P < 0.160) (Table 2).

Table 2

Results of whole-brain analyses for young and adolescent age cohorts

Variable Young cohort
 
Adolescent cohort
 
Control (n = 21) Turner (n = 30) P-values Control (n = 24) Turner (n = 16) P-values 
Gray matter volume 590 970 609 347 0.108 560 408 565 959 0.097 
White matter volume 427 479 434 699 0.113 461 821 455 090 0.097 
Subcortical gray volume 55 464 58 775 0.002 58 100 60 445 0.004 
Cerebellar volume 148 012 156 762 0.056 138 632 143 211 0.120 
Fourth ventricle volume 1811 2758 <0.001 1962 2444 0.044 
Total ventricles volume 12 468 16 063 0.060 15 564 18 095 0.335 
Total brain volume 1 018 448 1 044 046 0.618 1 022 229 1 021 216 0.261 
Total surface area 170 280 170 426 0.065 166 611 160 711 0.002 
Mean cortical thickness 2.79 2.82 0.160 2.735 2.804 0.030 
Variable Young cohort
 
Adolescent cohort
 
Control (n = 21) Turner (n = 30) P-values Control (n = 24) Turner (n = 16) P-values 
Gray matter volume 590 970 609 347 0.108 560 408 565 959 0.097 
White matter volume 427 479 434 699 0.113 461 821 455 090 0.097 
Subcortical gray volume 55 464 58 775 0.002 58 100 60 445 0.004 
Cerebellar volume 148 012 156 762 0.056 138 632 143 211 0.120 
Fourth ventricle volume 1811 2758 <0.001 1962 2444 0.044 
Total ventricles volume 12 468 16 063 0.060 15 564 18 095 0.335 
Total brain volume 1 018 448 1 044 046 0.618 1 022 229 1 021 216 0.261 
Total surface area 170 280 170 426 0.065 166 611 160 711 0.002 
Mean cortical thickness 2.79 2.82 0.160 2.735 2.804 0.030 

Note: Results after controlling for total brain volume and age; volumes are expressed in mm3, surface in mm2, and thickness in mm.

Freesurfer Atlas-Based Regional Analyses

Young Cohort

Many regions showed significant structural differences between TS and controls in the young cohort (Fig. 1a; Table 3). Participants with TS showed reduced SA in the parietal (superior parietal, precuneus, postcentral) and occipital lobes (pericalcarine, cuneus, lingual gyrus) bilaterally. Differences in SA in these regions were accompanied by reductions in GMV (postcentral, cuneus, lingual gyrus, pericalcarine, superior parietal) and WMV (pericalcarine, postcentral, precuneus) in TS participants. However, results in the temporal regions show a different pattern, with increase in SA (parahippocampal, superior temporal), CT (inferior, middle and superior temporal, temporal pole, parahippocampal), GMV (bank of superior temporal sulcus (STS), inferior and superior temporal), and WMV (superior temporal) in TS compared with controls. One notable exception to this pattern was the enthorinal cortex, which showed a marked decrease in WMV bilaterally as well as a reduction in SA in the left hemisphere in TS. In the frontal lobes, young girls with TS showed increased GMV (insula, superior frontal, rostral middle frontal, lateral orbitofrontal, precentral), whereas WMV was increased in some regions (precentral, superior frontal) and decreased in others (pars opercularis, frontal pole). SA, GMV, and WMV of the rostral anterior portion of the cingulate cortex are also reduced in the right hemisphere in TS compared with controls. Regarding subcortical structures, TS participants had larger amygdala volume bilaterally, as well as increased size of the left hippocampus, and the ventral diencephalon bilaterally.

Table 3

Results of regional analysis between TS and controls in the young cohort

 Left hemisphere
 
Right hemisphere
 
 GMV SA CT WMV GMV SA CT WMV 
Cortical regions 
 Bankssts 9.8 4.1 3.7 4.9 13.2 5.7 6.2 10.3 
 Caudalanteriorcingulate 4.1 1.5 0.6 −1.8 1.1 0.6 −2.6 4.9 
 Caudalmiddlefrontal 9.3 5.2 2.7 −0.7 5.2 3.0 1.5 2.6 
 Cuneus 8.66.1 −2.6 0.2 −8.2 −7.2 −2.1 −2.9 
 Entorhinal 4.4 14.9** 12.8 19.2** −0.8 −9.3 6.1 15.7
 Fusiform −1.6 −4.4 3.0 −2.9 1.6 −1.0 4.0 4.4 
 Inferiorparietal 1.9 −0.9 1.8 1.1 0.6 −1.9 1.7 −0.2 
 Inferiortemporal 2.7 −0.2 1.6 5.9 11.7 2.1 6.77.2 
 Isthmuscingulate 1.9 5.5 6.14.5 6.4 −3.5 −4.0 0.5 
 Lateraloccipital 2.4 1.5 0.0 7.8 −0.5 −0.8 −0.3 3.5 
 Lateralorbitofrontal 6.5 2.4 1.6 0.7 9.2 3.2 3.3 2.1 
 Lingual 10.0 7.0 −2.0 0.8 −7.5 6.1 −1.6 −3.5 
 Medialorbitofrontal 2.4 3.2 −3.1 2.1 6.0 2.6 1.2 0.8 
 Middletemporal 9.9 7.7 1.8 8.8 6.7 0.8 5.13.1 
 Parahippocampal 4.1 12.9 −8.5 −4.2 9.6 12.3 −5.2 −3.7 
 Paracentral 3.4 5.1 −2.1 9.1 4.4 5.4 −1.3 10.5 
 Parsopercularis −2.3 −2.6 −0.8 5.8 −4.1 10.05.1 12.4** 
 Parsorbitalis 6.1 0.5 2.8 4.6 8.9 7.6 −1.5 8.8 
 Parstriangularis 2.2 0.7 0.7 −3.5 5.7 −0.1 4.4 −1.6 
 Pericalcarine 19.7** 15.3** −5.8 9.821.0** 15.2** −7.6 12.1
 Postcentral 8.89.9−1.1 8.010.18.1−2.1 6.1 
 Posteriorcingulate −3.2 0.1 −2.7 2.4 −3.3 6.2 3.0 −2.2 
 Precentral 8.1 7.4−0.2 9.7 7.1 4.1 1.3 6.5 
 Precuneus −4.6 6.90.4 5.3 −1.8 6.71.7 6.9
 Rostralanteriorcingulate 2.2 −0.4 1.3 0.0 12.312.4−0.3 10.8
 Rostralmiddlefrontal 6.1 5.7 −1.0 3.0 9.06.0 0.9 3.0 
 Superiorfrontal 6.1 4.9 0.2 5.3 10.2** 6.6 0.6 7.7 
 Superiorparietal 7.57.8** 0.0 −2.4 −5.6 6.70.3 −1.3 
 Superiortemporal 11.18.7 2.7 14.0 9.7 0.8 7.5** 5.0 
 Supramarginal 0.6 −0.6 0.7 3.6 3.0 −1.5 3.6 3.0 
 Frontalpole 2.6 −7.6 9.7 −11.8 0.7 −7.5 1.4 15.4
 Temporalpole 7.2 −4.5 11.6−1.1 −4.4 9.04.6 −6.7 
 Transversetemporal 4.5 7.2 −4.3 −1.7 7.5 6.4 −1.1 −1.2 
 Insula 10.27.6 1.9 4.8 14.6** 13.8** −0.8 7.4 
Subcortical structures 
 Amygdala 15.7– – – 16.1– –  – 
 Caudate 4.5 – – – 3.2 – – – 
 Hippocampus 9.6– – – 7.4 – – – 
 Putamen 4.7 – – – 5.7 – – – 
 Thalamus 4.5 – – – 5.2 – – – 
 Ventral DC 8.3– – – 7.9 – – – 
 Left hemisphere
 
Right hemisphere
 
 GMV SA CT WMV GMV SA CT WMV 
Cortical regions 
 Bankssts 9.8 4.1 3.7 4.9 13.2 5.7 6.2 10.3 
 Caudalanteriorcingulate 4.1 1.5 0.6 −1.8 1.1 0.6 −2.6 4.9 
 Caudalmiddlefrontal 9.3 5.2 2.7 −0.7 5.2 3.0 1.5 2.6 
 Cuneus 8.66.1 −2.6 0.2 −8.2 −7.2 −2.1 −2.9 
 Entorhinal 4.4 14.9** 12.8 19.2** −0.8 −9.3 6.1 15.7
 Fusiform −1.6 −4.4 3.0 −2.9 1.6 −1.0 4.0 4.4 
 Inferiorparietal 1.9 −0.9 1.8 1.1 0.6 −1.9 1.7 −0.2 
 Inferiortemporal 2.7 −0.2 1.6 5.9 11.7 2.1 6.77.2 
 Isthmuscingulate 1.9 5.5 6.14.5 6.4 −3.5 −4.0 0.5 
 Lateraloccipital 2.4 1.5 0.0 7.8 −0.5 −0.8 −0.3 3.5 
 Lateralorbitofrontal 6.5 2.4 1.6 0.7 9.2 3.2 3.3 2.1 
 Lingual 10.0 7.0 −2.0 0.8 −7.5 6.1 −1.6 −3.5 
 Medialorbitofrontal 2.4 3.2 −3.1 2.1 6.0 2.6 1.2 0.8 
 Middletemporal 9.9 7.7 1.8 8.8 6.7 0.8 5.13.1 
 Parahippocampal 4.1 12.9 −8.5 −4.2 9.6 12.3 −5.2 −3.7 
 Paracentral 3.4 5.1 −2.1 9.1 4.4 5.4 −1.3 10.5 
 Parsopercularis −2.3 −2.6 −0.8 5.8 −4.1 10.05.1 12.4** 
 Parsorbitalis 6.1 0.5 2.8 4.6 8.9 7.6 −1.5 8.8 
 Parstriangularis 2.2 0.7 0.7 −3.5 5.7 −0.1 4.4 −1.6 
 Pericalcarine 19.7** 15.3** −5.8 9.821.0** 15.2** −7.6 12.1
 Postcentral 8.89.9−1.1 8.010.18.1−2.1 6.1 
 Posteriorcingulate −3.2 0.1 −2.7 2.4 −3.3 6.2 3.0 −2.2 
 Precentral 8.1 7.4−0.2 9.7 7.1 4.1 1.3 6.5 
 Precuneus −4.6 6.90.4 5.3 −1.8 6.71.7 6.9
 Rostralanteriorcingulate 2.2 −0.4 1.3 0.0 12.312.4−0.3 10.8
 Rostralmiddlefrontal 6.1 5.7 −1.0 3.0 9.06.0 0.9 3.0 
 Superiorfrontal 6.1 4.9 0.2 5.3 10.2** 6.6 0.6 7.7 
 Superiorparietal 7.57.8** 0.0 −2.4 −5.6 6.70.3 −1.3 
 Superiortemporal 11.18.7 2.7 14.0 9.7 0.8 7.5** 5.0 
 Supramarginal 0.6 −0.6 0.7 3.6 3.0 −1.5 3.6 3.0 
 Frontalpole 2.6 −7.6 9.7 −11.8 0.7 −7.5 1.4 15.4
 Temporalpole 7.2 −4.5 11.6−1.1 −4.4 9.04.6 −6.7 
 Transversetemporal 4.5 7.2 −4.3 −1.7 7.5 6.4 −1.1 −1.2 
 Insula 10.27.6 1.9 4.8 14.6** 13.8** −0.8 7.4 
Subcortical structures 
 Amygdala 15.7– – – 16.1– –  – 
 Caudate 4.5 – – – 3.2 – – – 
 Hippocampus 9.6– – – 7.4 – – – 
 Putamen 4.7 – – – 5.7 – – – 
 Thalamus 4.5 – – – 5.2 – – – 
 Ventral DC 8.3– – – 7.9 – – – 

Note: Statistical measures are after covariates (age, total brain volume). GMV, gray matter volume; SA, surface area; CT, cortical thickness; WMV, white matter volume.

Boldface, FDR < 0.05 and P < 0.05; *P < 0.01; **P < 0.001.

Figure 1.

(A) Significantly different regions between TS subjects and controls in the young cohort. The rows of the figure (top to bottom) correspond to cortical SA, GMV, WMV, and CT. Colors show the signed t-scores for each significant region, where a negative sign indicates that the TS subjects are significantly smaller than controls. (B) Significantly different regions between TS subjects and controls in the adolescent cohort. The rows of the figure correspond to cortical SA, GMV, WMV, and CT. Colors show the signed t-scores for each significant region, where a negative sign indicates that the TS subjects are significantly smaller than controls.

Figure 1.

(A) Significantly different regions between TS subjects and controls in the young cohort. The rows of the figure (top to bottom) correspond to cortical SA, GMV, WMV, and CT. Colors show the signed t-scores for each significant region, where a negative sign indicates that the TS subjects are significantly smaller than controls. (B) Significantly different regions between TS subjects and controls in the adolescent cohort. The rows of the figure correspond to cortical SA, GMV, WMV, and CT. Colors show the signed t-scores for each significant region, where a negative sign indicates that the TS subjects are significantly smaller than controls.

Adolescent Cohort

Like the young cohort, adolescents with TS showed widespread reduction of SA, GMV, and WMV over both parietal and occipital cortices bilaterally, namely in superior parietal, precuneus, postcentral, pericalcarine, lingual, lateroccipital, and cuneus regions (Fig. 1b; Table 4). Reductions in SA, GMV, and WMV in TS were also present in temporal regions of the left hemisphere (fusiform, parahippocampal, temporal pole). However, contiguous regions in the temporal lobe showed increases in GMV bilaterally, such as in the transverse temporal and superior temporal regions. Increases in GMV in TS were also present in many areas of the frontal lobe bilaterally (lateral orbitofrontal, medial orbitofrontal, and insular regions). Frontal regions also displayed more SA (insula, pars orbitalis, paracentral regions) and WMV (lateral orbitofrontal, bilateral pars orbitalis), although a reduction in WMV was observed in the right caudal middle frontal region in TS. Unlike the young cohort, multiple brain regions showed increased CT in adolescents with TS compared with controls, in the frontal (medial orbitofrontal, insula), temporal (inferior, middle, and superior temporal), parietal (inferior parietal), and occipital (lateral occipital) lobes. However, in sharp contrast with these results, bilateral parahippocampal CT was markedly reduced in TS compared with controls. Regarding subcortical structures, adolescents with TS showed increased volume in the amygdala bilaterally, and larger bilateral caudate, putamen, and right thalamus in comparison to controls.

Table 4

Results of regional analysis between TS and controls in the adolescent cohorts

 Left hemisphere
 
Right hemisphere
 
 GMV SA CT WMV GMV SA CT WMV 
Cortical regions 
 Bankssts 5.3 0.0 4.2 −0.1 2.2 −1.6 2.2 −1.3 
 Caudalanteriorcingulate 4.1 3.7 −0.1 4.5 −3.9 −4.2 0.6 1.8 
 Caudalmiddlefrontal 3.2 1.9 0.1 −1.9 −10.0 −8.7 −2.2 12.2 
 Cuneus 12.514.5** 1.5 13.7−6.7 9.4 2.1 10.0 
 Entorhinal −3.7 −5.3 −2.3 18.7−1.0 −1.2 −3.2 −10.8 
 Fusiform 11.19.5−1.3 −6.4 −3.0 −2.4 −1.2 3.2 
 Inferiorparietal 3.0 −2.0 3.8−0.2 0.7 −2.9 1.5 1.0 
 Inferiortemporal 4.8 −3.6 6.00.5 6.9 3.4 0.8 3.2 
 Isthmuscingulate −7.0 −3.7 −5.9 −0.3 −4.7 −2.0 −2.6 0.4 
 Lateraloccipital −1.4 7.5 4.0−5.8 8.3 11.51.1 −7.8 
 Lateralorbitofrontal 8.14.5 2.2 6.1 10.87.0 2.8 8.8
 Lingual 15.2** 17.0** 0.7 14.4** 16.6** 17.2** −0.5 16.2** 
 Medialorbitofrontal 8.6 2.7 5.7 3.8 9.44.4 4.6 5.6 
 Middletemporal 1.9 −3.6 3.4 1.9 −0.4 −5.0 2.4 −3.0 
 Parahippocampal 12.32.9 16.9** 12.79.2 4.4 13.1−6.6 
 Paracentral 11.5 7.3 1.7 1.7 1.5 −1.9 0.6 −2.0 
 Parsopercularis −5.6 7.8 1.6 −6.7 −0.8 −5.5 0.9 −9.2 
 Parsorbitalis 13.07.7 1.2 15.516.314.21.1 20.6** 
 Parstriangularis −0.9 −2.8 −0.4 −4.5 0.1 −4.1 2.6 −2.5 
 Pericalcarine 15.416.0** 0.2 14.421.4** 18.5** −4.6 16.7** 
 Postcentral 11.9** 11.5** −1.5 10.7** 13.312.9** −1.2 12.9** 
 Posteriorcingulate 0.8 0.5 −1.2 0.5 −4.0 8.95.3 −0.4 
 Precentral 9.24.2 2.7 1.5 5.3 1.7 2.7 0.8 
 Precuneus −5.1 9.50.2 12.3** −3.7 10.23.0 13.4** 
 Rostralanteriorcingulate 0.5 −2.6 2.7 −2.0 2.2 −1.3 2.5 0.9 
 Rostralmiddlefrontal 3.2 1.4 2.4 5.5 2.9 −1.8 3.2 2.3 
 Superiorfrontal 3.4 −0.8 1.9 −1.5 5.5 0.8 2.3 0.7 
 Superiorparietal 12.7** 13.9** 0.3 11.4** 5.4 6.0 −0.3 5.7 
 Superiortemporal 8.22.5 5.25.1 8.61.5 5.93.5 
 Supramarginal 7.6 1.3 3.7 3.9 4.4 −2.3 4.1 1.9 
 Frontalpole 4.7 −11.8 12.0 −14.2 9.2 −6.9 10.3 −9.1 
 Temporalpole 1.0 9.6 5.2 −14.0 6.2 2.3 1.4 3.4 
 Transversetemporal 10.6 5.5 4.6 6.4 17.4** 4.7 9.24.6 
 Insula 11.56.8 4.13.2 10.14.5 4.22.5 
Subcortical structures 
 Amygdala 7.7    7.3   
 Caudate 8.8   6.7    
 Hippocampus 2.1    0.2    
 Putamen 7.8   6.1   
 Thalamus 2.5    3.7    
 Ventral DC 1.2    0.5    
 Left hemisphere
 
Right hemisphere
 
 GMV SA CT WMV GMV SA CT WMV 
Cortical regions 
 Bankssts 5.3 0.0 4.2 −0.1 2.2 −1.6 2.2 −1.3 
 Caudalanteriorcingulate 4.1 3.7 −0.1 4.5 −3.9 −4.2 0.6 1.8 
 Caudalmiddlefrontal 3.2 1.9 0.1 −1.9 −10.0 −8.7 −2.2 12.2 
 Cuneus 12.514.5** 1.5 13.7−6.7 9.4 2.1 10.0 
 Entorhinal −3.7 −5.3 −2.3 18.7−1.0 −1.2 −3.2 −10.8 
 Fusiform 11.19.5−1.3 −6.4 −3.0 −2.4 −1.2 3.2 
 Inferiorparietal 3.0 −2.0 3.8−0.2 0.7 −2.9 1.5 1.0 
 Inferiortemporal 4.8 −3.6 6.00.5 6.9 3.4 0.8 3.2 
 Isthmuscingulate −7.0 −3.7 −5.9 −0.3 −4.7 −2.0 −2.6 0.4 
 Lateraloccipital −1.4 7.5 4.0−5.8 8.3 11.51.1 −7.8 
 Lateralorbitofrontal 8.14.5 2.2 6.1 10.87.0 2.8 8.8
 Lingual 15.2** 17.0** 0.7 14.4** 16.6** 17.2** −0.5 16.2** 
 Medialorbitofrontal 8.6 2.7 5.7 3.8 9.44.4 4.6 5.6 
 Middletemporal 1.9 −3.6 3.4 1.9 −0.4 −5.0 2.4 −3.0 
 Parahippocampal 12.32.9 16.9** 12.79.2 4.4 13.1−6.6 
 Paracentral 11.5 7.3 1.7 1.7 1.5 −1.9 0.6 −2.0 
 Parsopercularis −5.6 7.8 1.6 −6.7 −0.8 −5.5 0.9 −9.2 
 Parsorbitalis 13.07.7 1.2 15.516.314.21.1 20.6** 
 Parstriangularis −0.9 −2.8 −0.4 −4.5 0.1 −4.1 2.6 −2.5 
 Pericalcarine 15.416.0** 0.2 14.421.4** 18.5** −4.6 16.7** 
 Postcentral 11.9** 11.5** −1.5 10.7** 13.312.9** −1.2 12.9** 
 Posteriorcingulate 0.8 0.5 −1.2 0.5 −4.0 8.95.3 −0.4 
 Precentral 9.24.2 2.7 1.5 5.3 1.7 2.7 0.8 
 Precuneus −5.1 9.50.2 12.3** −3.7 10.23.0 13.4** 
 Rostralanteriorcingulate 0.5 −2.6 2.7 −2.0 2.2 −1.3 2.5 0.9 
 Rostralmiddlefrontal 3.2 1.4 2.4 5.5 2.9 −1.8 3.2 2.3 
 Superiorfrontal 3.4 −0.8 1.9 −1.5 5.5 0.8 2.3 0.7 
 Superiorparietal 12.7** 13.9** 0.3 11.4** 5.4 6.0 −0.3 5.7 
 Superiortemporal 8.22.5 5.25.1 8.61.5 5.93.5 
 Supramarginal 7.6 1.3 3.7 3.9 4.4 −2.3 4.1 1.9 
 Frontalpole 4.7 −11.8 12.0 −14.2 9.2 −6.9 10.3 −9.1 
 Temporalpole 1.0 9.6 5.2 −14.0 6.2 2.3 1.4 3.4 
 Transversetemporal 10.6 5.5 4.6 6.4 17.4** 4.7 9.24.6 
 Insula 11.56.8 4.13.2 10.14.5 4.22.5 
Subcortical structures 
 Amygdala 7.7    7.3   
 Caudate 8.8   6.7    
 Hippocampus 2.1    0.2    
 Putamen 7.8   6.1   
 Thalamus 2.5    3.7    
 Ventral DC 1.2    0.5    

Note: Statistical measures are after covariates (age, total brain volume). GMV, gray matter volume; SA, surface area; CT, cortical thickness; WMV, white matter volume.

Boldface, FDR < 0.05 and P < 0.05; *P < 0.01; **P < 0.001.

Exploratory Developmental Analyses

In the young cohort, whole-brain analyses were performed on total SA, mean CT, total GMV, and total WMV. These analyses showed a significant main effect of age on total GMV (F = 5.557; P = 0.023), which decreased with age, and on total WMV (F = 5.407; P = 0.025), which increased with age. In these models, there was no effect for group or group × age factors; and no effect was found for models pertaining to SA and CT. With respect to regional analyses in the young cohort, the group × age interaction term was significant for both GMV (F = 4.481; P = 0.040) and WMV (F = 5.889; P = 0.019) in the right fusiform region, indicating different developmental trends in TS versus controls (both models P < 0.001). Specifically, for this region, both WMV (R = 0.465) and GMV (R = 0.173) increased in TS with age, while decreasing in controls (R = −0.155; R = −0.392, respectively).

In the adolescent cohort, whole-brain measures analyses showed a main effect of age on mean CT (F = 6.436; P = 0.016) and total GMV (F = 8.815; P = 0.007), both of which decreased with age, while total WMV (F = 13.757; P = 0.001) increased with maturation. Regional analyses revealed different developmental trajectories for GMV and WMV in the left caudal middle frontal region, as the interaction term group × age was significant (F = 10.535; P = 0.003). In this region, corresponding approximately to the dorsolateral prefrontal cortex, adolescents with TS showed increased WMV with age (R = 0.328), in comparison to controls who had decreased WMV (R = −0.077). In contrast, TD adolescents displayed a reduction in GMV with age (R = −0.257), whereas TS adolescents showed a slight increase (R = 0.054) in this prefrontal region (interaction term; F = 4.541; P = 0.040). No other model revealed significant interaction effects between age and group in this cohort.

Exploratory developmental analyses performed across age cohorts on whole-brain measures showed a main effect of group on mean CT (F = 6.183; P = 0.015), which is larger in TS, and total SA (F = 18.359, P < 0.001) and total WMV (F = 8.050, P = 0.006), which are reduced in TS compared with controls. The interaction term did not reach P < 0.05 threshold in any of these analyses. However, between-age cohort regional analyses showed a contribution of the group × age cohort interaction term in 7 of the 80 comparisons conducted in the 10 a priori defined regions of interest (Table 5), with distinctive trajectories depending on the region. Notably, divergent developmental trends were observed in the left (F = 4.269; P = 0.042) and right (F = 12.008; P = 0.001) orbitofrontal regions, where WMV increased significantly from childhood to adulthood in TS compared with controls, and also in the parahippocampal gyrus bilaterally (left, F = 7.375; P = 0.008; right, F = 5.175, P = 0.025), where controls showed increased cortical thickening with maturation compared with TS. Controls also showed larger increases than girls with TS for WMV in the left superior parietal region (F = 4.010, P = 0.048) and in the right caudal middle frontal region (F = 4.217, P = 0.043).

Table 5

Significant results for regional developmental analysis

 Within cohort
 
Region of interest Model
 
Group × age interaction
 
F P F P 
Young cohort Right fusiform 
 GMV 7.069 <0.001 4.481 0.040 
 WMV 29.079 <0.001 5.889 0.019 
Adolescent cohort 
Left caudal middle frontal 
 GMV 3.961 0.006 4.541 0.040 
 WMV 10.561 <0.001 10.535 0.003 
 Between cohort
 
 F P F P 
Left superior parietal 
 WMV 24.886 <0.001 4.010 0.048 
Right caudal middle frontal 
 WMV 13.467 <0.001 4.217 0.043 
Right parahippocampal 
 CT 5.238 <0.001 5.175 0.025 
Left parahippocampal 
 CT 4.973 <0.001 7.375 0.008 
Left orbitofrontal 
 WMV 27.325 <0.001 4.269 0.042 
Right orbitofrontal 
 WMV 45.998 <0.001 12.008 0.001 
 SA 29.191 <0.001 4.600 0.035 
 Within cohort
 
Region of interest Model
 
Group × age interaction
 
F P F P 
Young cohort Right fusiform 
 GMV 7.069 <0.001 4.481 0.040 
 WMV 29.079 <0.001 5.889 0.019 
Adolescent cohort 
Left caudal middle frontal 
 GMV 3.961 0.006 4.541 0.040 
 WMV 10.561 <0.001 10.535 0.003 
 Between cohort
 
 F P F P 
Left superior parietal 
 WMV 24.886 <0.001 4.010 0.048 
Right caudal middle frontal 
 WMV 13.467 <0.001 4.217 0.043 
Right parahippocampal 
 CT 5.238 <0.001 5.175 0.025 
Left parahippocampal 
 CT 4.973 <0.001 7.375 0.008 
Left orbitofrontal 
 WMV 27.325 <0.001 4.269 0.042 
Right orbitofrontal 
 WMV 45.998 <0.001 12.008 0.001 
 SA 29.191 <0.001 4.600 0.035 

Note: Only models in which the interaction term was significant are shown. For within cohort analyses, univariate models were used, with group, and group × age as factors and total brain volume as a covariate. In the adolescent cohort, scanner was also added as covariate. For between cohorts, developmental trajectory were explored using univariate models with group, cohort, and group x cohort as factors, and total brain volume and scanner as covariates.

Discussion

This is the first study of its kind to simultaneously investigate GMV, WMV, SA, and CT in specific age cohorts of individuals with TS who are differentiated by virtue of being exposed to estrogen therapy. Our results show that aberrant brain morphology is present in individuals with TS from early childhood, and that many of these differences persist through adolescence into early adulthood. Indeed, a large number of between-group differences in regional SA, WMV, and GMV were consistent across age cohorts, especially in the occipital and parietal lobes. Importantly, we also demonstrate significant differences between young and adolescent cohorts in the development of a number of brain regions, which suggest distinct developmental trajectories in girls with TS relative to TD controls spanning the pubertal period.

Many of the morphological findings in this study replicate the most commonly reported neuroanatomical findings in TS. For example, reduced GMV in parietal and occipital lobes are in line with results from previous studies in adolescent and adult subjects with TS (Brown et al. 2002; Cutter et al. 2006; Mullaney and Murphy 2009; Raznahan, Cutter et al. 2010) and bilateral reductions in GMV and WMV in the postcentral gyrus have been observed in adult and child populations with TS (Molko et al. 2004; Marzelli et al. 2011). Similarly, enlargement of amygdala bilaterally (Good et al. 2003; Kesler, Garrett et al. 2004), the orbitofrontal cortex (Good et al. 2003; Molko et al. 2004), superior temporal gyri, and insula (Molko et al. 2004; Marzelli et al. 2011) have also been reported. The overlap between current findings and previous studies provides further evidence that there are pervasive structural brain differences across the lifespan in individuals with TS. Accordingly, it is not surprising that these anatomic regions are also those that are associated most closely with cognitive–behavioral domains most impaired in TS (Kesler, Haberecht et al. 2004; Hart et al. 2006).

Overall, the consistency of our findings with previous literature provides convergent validity for the automated segmentation technique used in this study. Furthermore, this method provides novel surface-based morphometric findings in previously unstudied cohorts of young and adolescent girls with TS. Prior research has underscored the importance of studying CT and SA separately from cortical volume, as neurodevelopmental outcomes for these factors are presumed to be differentially influenced by genetic and environmental factors (Panizzon et al. 2009; Winkler et al. 2010). This premise is in line with our finding that few cortical regions displayed significant differences on both measures. For example, we found large regional differences in SA between TS and controls in both age cohorts in the pericalcarine region, postcentral gyri, and the entire posterior medial surface of the brain, whereas no such differences were observed regarding CT. These are core cortical regions associated with visuospatial and visuomotor abilities, particularly the postcentral gyrus, superior parietal cortex, precuneus, and parahippocampal region (Corbetta and Shulman 2002; Grefkes et al. 2004; Kesler, Haberecht et al. 2004; Cavanna and Trimble 2006). SA abnormalities in these regions are consistent with results of cognitive–behavioral studies of TS that have shown impairments in visuomotor function (Nijhuis-van der Sanden et al. 2003) and the immediate and delayed recall of spatial and verbal memory in TS (Murphy et al. 1994; Ross, Roeltgen et al. 2000).

In contrast to SA findings, there were no regions that showed consistent differences in CT across age cohorts in the TS group. However, we did find that individuals with TS in the adolescent cohort had significantly greater overall CT than controls, particularly in the superior temporal and medial orbitofrontal regions bilaterally. In agreement with historical clinical guidelines (Knickmeyer and Davenport 2011), none of the adolescents with TS in our study initiated estrogen treatment prior to 14.5 years of age. Given that the mean onset of puberty for TD females is 12.5 years (Anderson et al. 2003), individuals with TS are exposed to the effects of estrogen at an age that is considerably later than physiologically expected. Taken together with previous literature describing an inverted U-shaped trajectory of GMV in frontal and parietal lobes peaking at ∼11 years of age in TD females (Giedd et al. 1999), a plausible explanation for the greater frontal CT seen in our adolescent TS subjects is that ‘typical’ maturational volume reductions in these regions are delayed or abnormal in TS. Recent studies also suggest that these reductions in whole brain, prefrontal, and parietal GMVs during puberty may at least, in part, be driven by estrogen (Peper et al. 2009; Bramen et al. 2011), providing a framework that links sex hormone deficiencies in TS with the observed morphometric findings during adolescence.

Regional SA differences have not been previously studied in the TS population, although lobar SAs have been reported for adults with TS (Raznahan, Cutter et al. 2010; Raznahan, Lee et al. 2010). When the regional results were assembled on a lobar basis, we found that the bilateral parietal lobe and occipital lobe SAs were significantly smaller for both cohorts with TS (all P < 0.0001), similar to the results seen for adults (Raznahan, Cutter et al. 2010; Raznahan, Lee et al. 2010). In terms of CT, TS subjects in the adolescent cohort had significant cortical thickening in the left temporal and occipital lobes, which is also similar to findings in adults with TS (Raznahan, Cutter et al. 2010; Raznahan, Lee et al. 2010). However, regions showing the most significant thickness increases in TS adolescents were bilateral superior temporal gyri and insula, findings which were not reported for adults. These differences may be due to the different ages or developmental trajectories of these populations, or different analysis methods (Freesurfer vs CIVET; http://wiki.bic.mni.mcgill.ca/index.php/CIVET).

Interestingly, the only regions showing significantly reduced CT in the TS cohort were the bilateral parahippocampal gyri, a finding that is similar to a previous report describing CT in adult women with TS (Raznahan, Cutter et al. 2010). Primate studies have shown that limbic regions, including the parahippocampal gyrus, are rich in estrogen receptors (Morse et al. 1986; Sholl and Kim 1989), while imaging studies in humans have demonstrated that the structure of the parahippocampal region is particularly sensitive to circulating estrogen levels with the level of estrogen being positively associated with parahippocampal GMV (Neufang et al. 2009; Lord et al. 2010). Therefore, our findings of increased parahippocampal CT between age cohorts in the TD group, compared with a relatively smaller increase in CT in the TS group across this same span, suggest that differences in estrogen status may significantly impact developmental changes in this region. Previous studies of hormone replacement in TS have demonstrated positive effects of estrogen on cognition, and memory in particular (Ross et al. 1998; Ross, Zinn et al. 2000). Taken together with the prominent role of the parahippocampus in memory processes (van Strien et al. 2009), our findings suggest a functional link between this anatomical region, estrogen status, and cognitive differences. In order to test this hypothesis, we conducted exploratory post hoc analyses assessing the relationship between surface morphometry in the parahippocampal region and cognitive performance (PIQ, VIQ) in each group. These analyses revealed positive correlations between VIQ and WMV (r = 0.327; P = 0.028) and CT (r = 0.358; P = 0.016) in the left parahippocampal region across all TS participants (n = 46). Significant positive associations were also present between the right parahippocampal CT, VIQ (r = 0.326; P = 0.029), and PIQ (r = 0.368; P = 0.013) in TS. Interestingly, CT of the left parahippocampal region was negatively associated with PIQ within the combined control group (n = 45, r = −0.358, P = 0.017). These results suggest that parahippocampal regions, which display marked developmental abnormalities in TS and are known to be sensitive to estrogen, might be related to the cognitive profile typical of this condition.

Limitations

One of the main strengths of this study is the use of more homogenous cohorts with respect to age, karyotype, and estrogen treatment. However, limitations include lack of comprehensive cognitive–behavioral data, absence of information regarding onset or pubertal status for control adolescents, heterogeneity with regard to GH status, as well as length and dosage of estrogen replacement therapies. Also, the regional results observed in this study do not necessarily map to single functional brain circuits, thus limiting our ability to interpret their behavioral significance. Finally, the cross-sectional study design using 2 age cohorts and scanners may have limited our ability to detect other developmental changes between youth and adolescence. Moreover, the design used here does not permit delineation of the relative contribution of age, estrogen, or other confounding cohort effects, to the neurodevelopmental trajectories associated with TS. These limitations underscore the need for longitudinal studies in this developmental period in future studies.

Conclusion

Our results demonstrate prominent differences between TS and TD across age cohorts, and the emergence of dynamic changes in estrogen-sensitive regions during adolescence. The underlying mechanism for these differences is likely sex hormone deficiency and/or haploinsufficiency of X-linked genes, which are characteristic features of TS. Interestingly, sex hormone and chromosome effects are also thought to drive the organization of sexually dimorphic brain differences in typical development (Davies and Wilkinson 2006; Lombardo et al. 2012). Therefore, it is interesting to note that cortical volume differences between young girls and boys are primarily driven by changes in SA rather than CT (Raznahan et al. 2011), which is in line with findings in our young cohort where morphometric differences predominately occur in SA. Although these findings suggest that neurodevelopmental differences are already established early in TS, our findings in the adolescent cohort suggest a more complex process. We found that individuals with TS did not undergo expected neuroanatomical changes during adolescence, implying that activational effects of pubertal sex hormones during adolescence are either reduced or absent, and that neurodevelopment in TS occurs in a time-sensitive fashion similar to other genetic conditions (Hoeft et al. 2010). However, our parahippocampal findings and previous data regarding hormone replacement effects on cognitive function in TS (Ross et al. 1998; Ross, Zinn et al. 2000), suggest the possibility that these changes may, at least in part, be ‘normalized’ with sex hormone therapy, particularly in regions that are sensitive to sex hormone influence. In order to explicitly address these issues, prospective, longitudinal studies are needed to examine the effects and interaction of neuroanatomy and hormone replacement before, during and after puberty.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org/.

Funding

This work was supported by grants from the NICHD (HD049653), NIMH (MH050047), and the Chain of Love Foundation to ALR. J.F.L. was supported by a Post-Doctoral Fellowship from the Fonds de la Recherche en Santé du Québec, D.S.H. was supported by an American Psychiatric Institute for Research and Education/Lilly Psychiatric Research Fellowship. A.R. received grants from NICHD and Genentech, and is an unpaid medical advisor for the Turner Syndrome Society and Turner Syndrome Foundation.

Notes

Conflict of Interest: J.F.L., P.M., D.H. and M.R. have nothing to declare.

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