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Original Contribution |

Age-Dependent Structural Connectivity Effects in Fragile X Premutation FREE

Jun Yi Wang, PhD; David Hessl, PhD; Randi J. Hagerman, MD; Flora Tassone, PhD; Susan M. Rivera, PhD
[+] Author Affiliations

Author Affiliations: Departments of Psychiatry and Behavioral Sciences (Drs Wang and Hessl), Pediatrics (Dr Hagerman), Biochemistry and Molecular Medicine (Dr Tassone), and Psychology (Dr Rivera), Center for Mind and Brain (Drs Wang and Rivera), and Medical Investigation of Neurodevelopmental Disorders (MIND) Institute (Drs Hessl, Hagerman, Tassone, and Rivera), University of California–Davis, Sacramento.


Arch Neurol. 2012;69(4):482-489. doi:10.1001/archneurol.2011.2023.
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Objective To examine the effects of premutation alleles on major brain fiber tracts in males.

Design Cross-sectional study performed in 2007-2009.

Setting Institutional practice.

Patients Fifteen younger (18-45 years old) carriers, 11 older (>45 years old) unaffected carriers, and 15 older carriers with fragile X–associated tremor/ataxia syndrome, together with 19 younger and 15 older controls matched by age and educational level.

Main Outcome Measures Diffusion tensor imaging was performed on all study participants. Eleven fiber tracts important for motor, social, emotional, and cognitive functions were reconstructed and quantified. Complementary tract-based spatial statistical analyses were performed in core white matter.

Results In the younger carriers, premutation status was associated with a greater age-related connectivity decline in the extreme capsule. Among older carriers, unaffected individuals did not display structural alterations, whereas the affected carriers showed connectivity loss in 5 fiber tracts and exhibited greater age-related connectivity decline in all 11 tracts compared with the controls. In addition, 9 fiber tracts showed significantly higher variability relative to the controls, and symptom severity explained the variability in 6 measurements from the superior cerebellar peduncle, corpus callosum, and cingulum.

Conclusions The findings revealed widespread alterations in structural connectivity associated with fragile X–associated tremor/ataxia syndrome and preserved or subtle changes in structural connectivity in unaffected carriers. Diffusion tensor imaging is sensitive to pathologic changes in the white matter associated with this neurodegenerative disorder.

Figures in this Article

Male carriers of premutation CGG repeat expansions (55-200 CGG repeats) of the FMR1 gene are at risk for developing the late-onset neurodegenerative disorder fragile X–associated tremor/ataxia syndrome (FXTAS).1 The principal features of FXTAS are progressive intention tremor and ataxia, which typically occur after 50 years of age, primarily in males but also (less frequently) in females.2 Other features include parkinsonism, peripheral neuropathy, autonomic dysfunction, and progressive cognitive decline, including dementia and psychiatric disorders.3,4 Pathologic manifestations of FXTAS are patchy loss of axons, myelin, and astroglial cells throughout the brain and spongiosis in the middle cerebellar peduncle (MCP).5,6 In addition to the problems among the older adults, some young premutation carriers display problems in emotional, social,79 and cognitive processing.10,11

White matter integrity in male carriers older than 40 years has recently been studied using a tract-of-interest approach12 to diffusion tensor imaging (DTI).13,14 Reduced fiber directionality was found in the MCP and superior cerebellar peduncle (SCP), cerebral peduncle, fornix, and stria terminalis in carriers affected by FXTAS. In carriers without FXTAS, only the MCP and cerebral peduncle showed elevated diffusivity. The present study was intended to provide a comprehensive assessment of structural connectivity in male premutation carriers across the adult lifespan. We investigated whether 11 fiber tracts that were reconstructed using DTI tractography15,16 showed abnormal aging in carriers in a cross-sectional design. To complement the structural connectivity analysis that provides the mean values in a fiber tract, a voxel-based analysis was conducted to search for localized changes.

RESEARCH PARTICIPANTS

We recruited 75 research participants primarily through their family relationships with children affected by fragile X syndrome, and controls were unaffected family members or were recruited from the local community. We identified premutation alleles using FMR1 DNA testing1719 and assessed symptoms and stage of FXTAS using detailed neurologic examination.3,20 To detect early signs of FXTAS, we analyzed the younger and older participants separately using an age of 45 years as the cutoff to ensure that the carriers in the younger group were mostly free of FXTAS symptoms. Fifteen younger premutation carriers and 19 younger controls formed 2 younger groups. Fifteen premutation carriers with FXTAS, 11 older carriers without FXTAS, and 15 older controls formed 3 older groups (Table 1). Within both the younger and older groups, participants were matched for age and years of education. For the FXTAS group, FXTAS stage ranged from 2 to 4 (minor to severe tremor and/or balance problems). The appearance of white matter lesions on T2 and fluid-attenuated inversion recovery (FLAIR) images was examined by one of us (R.J.H.). Most carriers (11-14) with FXTAS had lesions in the MCP, insula, frontal lobes, and corpus callosum. Some (6-8) had lesions in the temporal lobe. In contrast, although many older carriers without FXTAS had lesions visible in the insula, frontal lobes, and temporal lobes (4-7), only a few (1-2) had lesions in the MCP and corpus callosum.

Table Graphic Jump LocationTable 1. Characteristics of the 75 Research Participants
STANDARD PROTOCOL APPROVALS, REGISTRATIONS, AND PATIENT CONSENTS

All participants signed informed consent forms according to the institutional review boards at the University of California–Davis Medical Center.

NEUROIMAGE ACQUISITION

Neuroimaging was performed on a Trio 3T magnetic resonance imaging scanner with an 8-channel head coil (Siemens Medical Solutions). Diffusion tensor images with 30 gradient directions were obtained using a single-shot diffusion-weighted EPI sequence in 72 axial sections of 1.9-mm thickness (no gap) with a 243-mm field of view and a 128 × 128 matrix. The diffusion sensitizing gradients were applied at a b -value of 700 s/mm2. Five additional images with minimum diffusion weighting were also obtained.

IMAGE PROCESSING

We used the software package FSL (www.fmrib.ox.ac.uk/fsl/, University of Oxford) for correcting eddy current and motion in DTI and skull-stripping21 and conducted DTI tractography using DTI Studio (cmrm.med.jhmi.edu; Johns Hopkins Medical Institute). Fiber tracking adopted a multiple regions-of-interest (ROIs) approach for achieving higher interrater reliability.15 We set the fractional anisotropy (FA) threshold to 0.18 and the angle threshold to 70° for fiber tracking to ensure the successful reconstruction of the uncinate fasciculus, a small curved fiber tract. We determined ROI placement based on anatomical location and functional division of the fiber tracts2226 and by referencing published methods where available.2730

We reconstructed 11 fiber tracts from 4 categories: (1) motor fiber tracts—cerebral peduncular fibers and cerebellar peduncles; (2) limbic tracts—extreme capsule fibers, cingulum, fornix, and angular bundle; (3) association fibers—arcuate fasciculus, uncinate fasciculus, inferior longitudinal fasciculus, and inferior fronto-occipital fasciculus; and (4) callosal fibers—corpus callosum (Figure 1). Only the fornix body was reconstructed because the body provides measurements with high interrater and test-retest reliability compared with the crus.31 The arcuate fasciculus was tracked separately into anterior, posterior, and direct fiber regions.30 It was possible to reconstruct the left direct arcuate (for which there were no missing data) and the right anterior arcuate (for which data were missing from 1 participant); the remaining 4 regions, however, could only be reconstructed from some of the participants (63-69 of 75) because of the high individual variability.32 For this reason, these 4 fiber regions were replaced by left and right “arcuate complex,” a combination of the 3 fiber regions at each hemisphere. See the (eAppendix) for detailed fiber tracking methods.

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Figure 1. The 11 reconstructed fiber tracts (left-side only) from 3 representative research participants. A, A 53-year-old healthy control; B, a 52-year-old asymptomatic premutation carrier; and C, a 54-year-old premutation carrier with fragile X–associated tremor/ataxia syndrome stage 4. Cerebral peduncular fibers (CPF) project to the anterior frontal lobes (light green), superior frontal lobes (brown), parietal lobes (light orange), and occipital lobes (purple). The inferior cerebellar peduncle (ICP) is shown in green, the middle cerebellar peduncle (MCP) in purple, and the superior cerebellar peduncle (SCP) in dark yellow. The extreme capsule (EC) fibers contain the anterior medial projections (pink), posterior medial projections (dark red), anterior lateral projections (dark yellow), and posterior lateral projections (orange). The cingulate bundle (CB) is shown in dark purple, the anterior CB in blue, the posterior CB in dark purple, the fornix body (FB) in yellow, and the angular bundle (AB) in light blue. The arcuate fasciculus (AF) complex contains the anterior AF (light yellow), posterior AF (aqua), and direct AF (dark teal). The uncinate fasciculus (UF) is shown in lavender, the inferior longitudinal fasciculus (ILF) in teal, and the inferior fronto-occipital fasciculus (IFO) in blue. The corpus callosum (CC) contains 4 fiber regions: genu (orange), anterior body (red), posterior body (navy blue), and splenium (green).

A total of 38 fiber regions were reconstructed and quantified using FA for fiber directionality, mean diffusivity (MD) for packing density, mean length, and tract volume. To normalize the tract volume, total cranial volume was estimated from the T1-weighted MPRAGE images using the SIENAX function33 from FSL. For measurements from each fiber region, interrater reliabilities were tested by 2 raters and were above 0.9. Fiber tracking was performed with the rater masked to the status of the participants.

Because DTI tractography provides mean measurements over large areas, we also applied a voxel-based analysis, using tract-based spatial statistics (TBSS), to detect localized changes. The TBSS program possesses the advantage of assessing FA- and MD-related fiber integrity changes in core white matter, thereby being less affected by partial volume effects associated with inclusion of the gray matter and cerebrospinal fluid and inaccuracies from the normalization procedure.34 The FA threshold for generating skeleton mask was 0.2.

STATISTICAL ANALYSIS

For tractography and voxel-based analyses, group differences and group × age interactions in DTI measurements were assessed separately in the younger and older groups. Linear regression was used with age and group as independent variables and individual DTI measurements as dependent variables. An age × group interaction was included only when it was significant (P < .05). The Matlab function regstats was used for predicting individual tractography measurements (The Mathworks Inc). To correct for familywise errors, we applied a 5% false discovery rate (FDR)35 implemented in the Matlab FDR function to the combined results across all DTI outcomes and regions. The same procedures were implemented for examining the effect of T2 and FLAIR lesions on tractography measurements. We divided the older premutation carriers into groups with and without T2 and FLAIR lesions in the MCP, insula, temporal lobes, and corpus callosum and performed group comparisons of fiber tracts from these areas. Age was used as a covariate when the 2 groups differed significantly in age. For performing voxel-based comparisons of FA and MD using TBSS, the randomize tool with threshold-free cluster enhancement was used.

Thirty-two of 38 fiber regions were reconstructed successfully for all 75 participants. Fiber regions from the cerebral peduncle, inferior cerebellar peduncle, extreme capsule, and arcuate fasciculus were missing from 1 to 5 participants. All 5 groups were involved except the younger control group. The missing data points were excluded from the analysis.

eFigure 1) plots the group means and standard deviation of representative tractography measurements. Although the older asymptomatic carriers showed similar variability in tractography measurements to the controls, the carriers with FXTAS exhibited substantially high variability in many measurements. Consequently, the F test was conducted to identify tractography measurements with significantly higher variability in FXTAS carriers compared with the controls. Thirty of 152 measurements showed significantly higher variability after performing the FDR (F14,14 = 3.8-101.7, P <.001-.008). These measurements came from all fiber tracts except 2 limbic fiber tracts, the fornix body and angular bundle. Most of them (22 of 30) were MD measurements (Table 2).

Table Graphic Jump LocationTable 2. Tractography Measurements Showing Significantly High Variability in Carriers With Fragile X–Associated Tremor/Ataxia Syndromea

To investigate whether the higher variability of tractography data in the carriers with FXTAS was due to progression of FXTAS, post hoc regression analyses were performed to predict FXTAS stage using individual tractography measurements showing high variability. Six measurements demonstrated significant correlation with FXTAS stage at an FDR level of 0.05 in the premutation group after age adjustment ( t = 3.1-4.2, P <.001-.005). These were the MD of the SCP and the genu, anterior body, and posterior body of the corpus callosum, which showed positive correlation, and tract volume of the left cingulum and mean length of the corpus callosum splenium, which showed negative correlation.

The regression analyses of both the younger and older groups revealed that 41 of 1286 tractography measurements (3.2%) survived an FDR threshold of 0.05 (P < .002), showing the age effect, group effect, or age × group interaction. Lower FA, mean length, and tract volume and higher MD were designated as reduced structural connectivity. In the younger groups, the asymptomatic carriers had higher tract volume of one limbic tract (right angular bundle, t = 3.49, P = .001) and greater age-related decline (t = −3.56, P = .001) in the FA of another limbic tract relative to the controls (right posterior lateral projections of extreme capsule, Figure 2A and B). In the older groups, although no comparisons survived an FDR of 0.05 between the asymptomatic carriers and controls, when comparing the affected carriers with the controls 12 measurements showed a significant group effect and 6 exhibited a significant group × age interaction (multiple linear regression; t = 3.48-5.73, P <.001-.002). Carriers with FXTAS showed reduced structural connectivity relative to the controls in all 4 fiber tract categories (motor, limbic, association, and callosal fiber tracts) and greater age-related decline in structural connectivity in fiber tracts from limbic, association, and callosal fiber tracts. In contrast, 1 motor tract, the parietal projections of cerebral peduncle, showed increased FA in FXTAS compared with the controls (Table 3). In the analyses of FXTAS carriers vs the asymptomatic carriers, 9 tractography measurements demonstrated significant group or group × age effects (multiple linear regression; t = 3.62-7.23, P <.001-.002). The FXTAS carriers showed reduced structural connectivity relative to the controls in all 4 fiber tract categories and displayed greater age-related decline in structural connectivity in fiber tracts from 3 categories—limbic, association, and callosal fiber tracts. Figure 2C and D illustrates the representative main effect of group and group × age interaction. Because the P value corresponding to an FDR of 0.05 was so low (.002), the results obtained from using an FDR level of 0.1 (corresponding to a P value of .01) are also provided in Table 3.

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Figure 2. Aging in male carriers of the fragile X premutation. A, The younger asymptomatic carriers showed greater age-related decline in the fractional anisotropy (FA) of right posterior lateral projections (temporal lobe) of the extreme capsule compared with the controls. B, The younger asymptomatic premutation carriers showed higher tract volume (TV) of the right angular bundle relative to the controls. The fragile X–associated tremor/ataxia syndrome (FXTAS) group showed greater age-related decline in the mean length of the left cingulate bundle (C) and significant elevation and greater age-related elevation in the mean diffusivity (MD) of the posterior body of the corpus callosum (D) compared with the control and asymptomatic groups. Tract-based spatial statistics detected white matter areas with significantly lower FA (E) and higher MD in carriers with FXTAS (F) compared with the controls. Tract-based spatial statistics detected white matter areas with greater age-related decline in FA (G) and greater age-related elevation in MD in carriers with FXTAS (E) compared with the controls. AP indicates asymptomatic premutation carriers; FP, premutation carriers with FXTAS; and NC, normal controls.

Table Graphic Jump LocationTable 3. Group Effect and Group × Age Interaction on Diffusion Tensor Imaging Measurements in the Older Groupsa

The TBSS program did not detect any group effect or group × age interaction when comparing younger or older asymptomatic carriers with the corresponding control group. When comparing the FXTAS carriers with the controls, TBSS detected lower FA in one association fiber tract (inferior longitudinal fasciculus) and higher MD and lower FA in all corpus callosum regions in the FXTAS carriers. The age and group interaction affected all 11 fiber tracts in the 4 categories, showing greater age-related elevation in MD in the FXTAS carriers compared with that of the controls. Three fiber tracts—the cingulum, inferior fronto-occipital fasciculus, and corpus callosum—also exhibited greater age-related decline in FA in the FXTAS carriers (Table 3 and Figure 2E-H). When the FXTAS carriers were compared with the asymptomatic carriers, only the corpus callosum showed lower FA and higher MD in the FXTAS carriers. The greater age-related MD elevation and FA decline in the FXTAS compared with the asymptomatic carriers affected all 11 fiber tracts except the cerebellar peduncles for MD and affected only the corpus callosum splenium for FA (Table 3).

We also examined how the occurrence of macroscopic T2 and FLAIR lesions affected tractography by superimposing fiber tracts on images without diffusion weighting (b =  0 s/mm2). Although no fibers were observed in areas with bright lesions, DTI fibers penetrated areas with less bright lesions. The comparisons of the groups with and without lesions revealed that only the groups with lesions in the MCP and corpus callosum exhibited significantly reduced structural connectivity relative to the groups without lesions at an FDR level of 0.05 (eTable).

To our knowledge, the current study has provided the first DTI tractography analysis to assess structural connectivity in male fragile X premutation carriers (Figure 1). Tractography with DTI has the advantages of examining structural connectivity more directly than TBSS- and ROI-based analyses. The anatomical locations of fiber tracts are determined by performing tractography in which fibers connecting predefined areas are visualized. In contrast, the anatomical locations in voxel- and ROI-based analyses are determined by looking up the brain atlas. In areas where more than 1 fiber tract exists and that have similar fiber orientations, fiber tracts cannot be distinguished from one another by simply looking at the DTI maps. In addition, DTI tractography provides tract-based measurements that are averaged across the voxels containing the fiber tract and thus may not be sensitive to localized changes. Therefore, we added TBSS analysis for the detection of localized changes. The analyses were conducted in both carriers younger than 45 years who did not have the clinical symptoms of FXTAS and older carriers with and without FXTAS. Structural connectivity changes were detected not only in the carriers affected by FXTAS but also in the younger, asymptomatic carriers. The premutation carriers tended to show higher MD and lower FA, mean length, and fiber volume compared with the controls, as well as greater age-related elevation in MD and greater age-related decline in the remaining 3 fiber variables. These patterns of change are consistent with our common understanding of the effect of weaker structural connectivity or more rapid aging on DTI measurements.

In the younger carriers, the FA of extreme capsule (right posterior lateral projections) showed significantly accelerated age-related decline compared with the controls (Figure 2A). The volume elevation of right angular bundle in the younger carriers (Figure 2B) may be related to the effect of FMR1 premutation on white matter development and can be further tested in children with fragile X premutation. In the older groups, although the asymptomatic carriers maintained structural connectivity similar to the controls, the structural connectivity in the carriers with FXTAS was substantially different from that of the controls and showed accelerated aging. Both DTI tractography and TBSS detected lower structural connectivity and integrity in carriers with FXTAS relative to the controls in 5 of the 11 fiber tracts from all 4 fiber tracts categories. The carriers with FXTAS also showed greater age-related decline in structural connectivity and integrity in all 11 fiber tracts (Table 3).

The widespread effect of FXTAS on white matter structural connectivity and integrity was in concordance with previous findings of generalized brain atrophy, widespread low gray matter density, and T2 hyperintensity in the MCP and subcortical white matter in the carriers with FXTAS.3638 However, we did not replicate previous findings of increased diffusivity in the MCP and cerebral peduncle in the older asymptomatic carriers relative to the controls,12 although the FXTAS carriers showed reduced structural connectivity in the MCP and cerebral peduncle significant at an FDR level of 0.1 (P = .01) and in the SCP significant at an FDR level of 0.05 (P = .002). The subsequent assessment of the effect of T2 and FLAIR lesions on DTI revealed significantly lower structural connectivity in the group with MCP lesions compared with the group without MCP lesions, providing the direct link between MCP lesions and reduced structural connectivity.

Tractography with DTI also showed a pattern of change contradictory to our common understanding of the effect of neurodegeneration on DTI measurements. The FA values of the parietal projections of cerebral peduncle were higher in the carriers with FXTAS compared with the corresponding control group. Although this may at first glance seem counterintuitive, the FA elevation can be explained by the well-known crossing fiber issue in DTI tractography.39 The parietal projections of the cerebral peduncle overlapped at the centrum semiovale with the corpus callosum, which sustained a significant amount of neurodegeneration in FXTAS. As shown in the histogram of sectionwise FA, the degeneration of the corpus callosum caused the FA of the cerebral peduncle to increase artificially in the carriers with FXTAS at the axial sections where the 2 fiber tracts intersect (eFigure 2A and B).

In addition to the diverging age effect on structural connectivity between the older carriers with and without FXTAS, the variability of structural connectivity increased significantly among the carriers with FXTAS compared with age-matched controls for 30 tractography measurements from 9 of 11 fiber tracts (except 2 limbic tracts). The tractography measurement that showed the most variability was the MD (22 of 30). Regression analyses using age as a nuisance covariate revealed FXTAS stage as a possible explanation for the higher variability in 6 of the tractography measurements from the SCP, corpus callosum, and cingulum. Typically, FXTAS carriers showed abnormally low MD values in these areas at initial stages of FXTAS but elevated MD at the advanced stages, indicating the high sensitivity of tractography measurements to white matter pathologic changes associated with FXTAS.

The current study was limited by using a cross-sectional rather than a longitudinal design to examine aging in male carriers of the premutation, which is a common problem in the aging literature because of the difficulties of following up the participants for a long period. The sample size was also relatively small, especially for the older asymptomatic carriers. The correlation of DTI measurements with molecular data and cognitive functions was unexplored because of the small sample size.

In conclusion, the present study detected subtle white matter structural changes in the young premutation carriers without FXTAS and widespread age-related deterioration in structural connectivity in carriers with FXTAS. The strength of structural connectivity diverged as the carriers aged. Although the unaffected carriers maintained healthy structural connectivity, the affected carriers showed radical structural deterioration. Even within the group of carriers with FXTAS, the variability of structural connectivity increased significantly in 9 fiber tracts compared with age-matched controls, and FXTAS severity explained the variability for measurements from the SCP, corpus callosum, and cingulum. The DTI structural connectivity analyses were sensitive to pathologic changes associated with FXTAS.

Correspondence: Susan M. Rivera, PhD, Center for Mind and Brain, 202 Cousteau Pl, Ste 250, Davis, CA 95618 (srivera@ucdavis.edu).

Accepted for Publication: September 14, 2011.

Author Contributions:Study concept and design: Wang and Rivera. Acquisition of data: Wang, Hessl, Hagerman, and Tassone. Analysis and interpretation of data: Wang, Hessl, Hagerman, and Rivera. Drafting of the manuscript: Wang and Hessl. Critical revision of the manuscript for important intellectual content: Wang, Hessl, Hagerman, Tassone, and Rivera. Statistical analysis: Wang. Obtained funding: Hessl, Hagerman, and Rivera. Administrative, technical, and material support: Hagerman and Rivera. Study supervision: Hessl and Rivera.

Financial Disclosure: Dr Wang receives support as a postdoctoral fellow from the National Institutes of Health. Dr Hessl receives grant support from Roche, Novartis, and Seaside Therapeutics for treatment trials in fragile X syndrome and research support from the National Institutes of Health. Dr Hagerman receives grant support from Roche, Novartis, Seaside Therapeutics, Forest, Johnson and Johnson, and Curemark for treatment trials in fragile X or autism and research support from the National Institutes of Health and the National Fragile X Foundation. Dr Tassone receives research support from the National Fragile X Foundation, UC Davis Health System Research Award, and the National Institutes of Health. Dr Rivera receives research support from the National Institutes of Health.

Funding/Support: This work was supported by National Institutes of Health grants HD036071, MH078041, MH077554, NS062412, UL1DE019583, RL1AG032119, RL1AG032115, and TL1DA024854.

Additional Contributions: We are grateful to the research participants and their families; to Jenny Tram, BS, Jose Fon, BS, and John Shell, BS, for performing fiber tracking; Jim Grigsby, PhD, John Wang, BS, and Patrick Adams, BS, for image and data collection; and Danielle Harvey, PhD, for statistical support.

This article was corrected for errors on May 4, 2012.

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Wang JY, Abdi H, Bakhadirov K, Diaz-Arrastia R, Devous MD Sr. A comprehensive reliability assessment of quantitative diffusion tensor tractography [published online ahead of print December 29, 2011].  Neuroimage
PubMed  |  Link to Article
Catani M, Allin MP, Husain M,  et al.  Symmetries in human brain language pathways correlate with verbal recall.  Proc Natl Acad Sci U S A. 2007;104(43):17163-17168
PubMed   |  Link to Article
Smith SM, Zhang Y, Jenkinson M,  et al.  Accurate, robust, and automated longitudinal and cross-sectional brain change analysis.  Neuroimage. 2002;17(1):479-489
PubMed   |  Link to Article
Smith SM, Jenkinson M, Johansen-Berg H,  et al.  Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.  Neuroimage. 2006;31(4):1487-1505
PubMed   |  Link to Article
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing.  J R Stat Soc B. 1995;57(1):289-300
Brunberg JA, Jacquemont S, Hagerman RJ,  et al.  Fragile X premutation carriers: characteristic MR imaging findings of adult male patients with progressive cerebellar and cognitive dysfunction.  AJNR Am J Neuroradiol. 2002;23(10):1757-1766
PubMed
Cohen S, Masyn K, Adams J,  et al.  Molecular and imaging correlates of the fragile X–associated tremor/ataxia syndrome.  Neurology. 2006;67(8):1426-1431
PubMed   |  Link to Article
Hashimoto R, Javan AK, Tassone F, Hagerman RJ, Rivera SM. A voxel-based morphometry study of grey matter loss in fragile X–associated tremor/ataxia syndrome.  Brain. 2011;134(Pt 3):863-878
PubMed   |  Link to Article
Mori S, van Zijl PC. Fiber tracking: principles and strategies - a technical review.  NMR Biomed. 2002;15(7-8):468-480
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. The 11 reconstructed fiber tracts (left-side only) from 3 representative research participants. A, A 53-year-old healthy control; B, a 52-year-old asymptomatic premutation carrier; and C, a 54-year-old premutation carrier with fragile X–associated tremor/ataxia syndrome stage 4. Cerebral peduncular fibers (CPF) project to the anterior frontal lobes (light green), superior frontal lobes (brown), parietal lobes (light orange), and occipital lobes (purple). The inferior cerebellar peduncle (ICP) is shown in green, the middle cerebellar peduncle (MCP) in purple, and the superior cerebellar peduncle (SCP) in dark yellow. The extreme capsule (EC) fibers contain the anterior medial projections (pink), posterior medial projections (dark red), anterior lateral projections (dark yellow), and posterior lateral projections (orange). The cingulate bundle (CB) is shown in dark purple, the anterior CB in blue, the posterior CB in dark purple, the fornix body (FB) in yellow, and the angular bundle (AB) in light blue. The arcuate fasciculus (AF) complex contains the anterior AF (light yellow), posterior AF (aqua), and direct AF (dark teal). The uncinate fasciculus (UF) is shown in lavender, the inferior longitudinal fasciculus (ILF) in teal, and the inferior fronto-occipital fasciculus (IFO) in blue. The corpus callosum (CC) contains 4 fiber regions: genu (orange), anterior body (red), posterior body (navy blue), and splenium (green).

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Aging in male carriers of the fragile X premutation. A, The younger asymptomatic carriers showed greater age-related decline in the fractional anisotropy (FA) of right posterior lateral projections (temporal lobe) of the extreme capsule compared with the controls. B, The younger asymptomatic premutation carriers showed higher tract volume (TV) of the right angular bundle relative to the controls. The fragile X–associated tremor/ataxia syndrome (FXTAS) group showed greater age-related decline in the mean length of the left cingulate bundle (C) and significant elevation and greater age-related elevation in the mean diffusivity (MD) of the posterior body of the corpus callosum (D) compared with the control and asymptomatic groups. Tract-based spatial statistics detected white matter areas with significantly lower FA (E) and higher MD in carriers with FXTAS (F) compared with the controls. Tract-based spatial statistics detected white matter areas with greater age-related decline in FA (G) and greater age-related elevation in MD in carriers with FXTAS (E) compared with the controls. AP indicates asymptomatic premutation carriers; FP, premutation carriers with FXTAS; and NC, normal controls.

Tables

Table Graphic Jump LocationTable 1. Characteristics of the 75 Research Participants
Table Graphic Jump LocationTable 2. Tractography Measurements Showing Significantly High Variability in Carriers With Fragile X–Associated Tremor/Ataxia Syndromea
Table Graphic Jump LocationTable 3. Group Effect and Group × Age Interaction on Diffusion Tensor Imaging Measurements in the Older Groupsa

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Wang JY, Abdi H, Bakhadirov K, Diaz-Arrastia R, Devous MD Sr. A comprehensive reliability assessment of quantitative diffusion tensor tractography [published online ahead of print December 29, 2011].  Neuroimage
PubMed  |  Link to Article
Catani M, Allin MP, Husain M,  et al.  Symmetries in human brain language pathways correlate with verbal recall.  Proc Natl Acad Sci U S A. 2007;104(43):17163-17168
PubMed   |  Link to Article
Smith SM, Zhang Y, Jenkinson M,  et al.  Accurate, robust, and automated longitudinal and cross-sectional brain change analysis.  Neuroimage. 2002;17(1):479-489
PubMed   |  Link to Article
Smith SM, Jenkinson M, Johansen-Berg H,  et al.  Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.  Neuroimage. 2006;31(4):1487-1505
PubMed   |  Link to Article
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing.  J R Stat Soc B. 1995;57(1):289-300
Brunberg JA, Jacquemont S, Hagerman RJ,  et al.  Fragile X premutation carriers: characteristic MR imaging findings of adult male patients with progressive cerebellar and cognitive dysfunction.  AJNR Am J Neuroradiol. 2002;23(10):1757-1766
PubMed
Cohen S, Masyn K, Adams J,  et al.  Molecular and imaging correlates of the fragile X–associated tremor/ataxia syndrome.  Neurology. 2006;67(8):1426-1431
PubMed   |  Link to Article
Hashimoto R, Javan AK, Tassone F, Hagerman RJ, Rivera SM. A voxel-based morphometry study of grey matter loss in fragile X–associated tremor/ataxia syndrome.  Brain. 2011;134(Pt 3):863-878
PubMed   |  Link to Article
Mori S, van Zijl PC. Fiber tracking: principles and strategies - a technical review.  NMR Biomed. 2002;15(7-8):468-480
PubMed   |  Link to Article

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