Cerebral cortex structure in prodromal Huntington disease

Neurobiology of Disease 40 (2010) 544–554

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Neurobiology of Disease

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Cerebral cortex structure in prodromal Huntington disease

Peggy C. Nopoulos a,b,c, Elizabeth H. Aylward f, Christopher A. Ross g,h,i, Hans J. Johnson a,Vincent A. Magnotta a,c,d, Andrew R. Juhl a, Ronald K. Pierson a, James Mills a,Douglas R. Langbehn a,e, Jane S. Paulsen a,c,⁎and the PREDICT-HD Investigators Coordinators of the Huntington Study Group (HSG)a Department of Psychiatry, University of Iowa Roy and Lucille Carver College of Medicine, Iowa City, IA 52242, USAb Department of Pediatrics, University of Iowa Roy and Lucille Carver College of Medicine, Iowa City, IA 52242, USAc Department of Neurology, University of Iowa Roy and Lucille Carver College of Medicine, Iowa City, IA 52242, USAd Department of Radiology, University of Iowa Roy and Lucille Carver College of Medicine, Iowa City, IA 52242, USAe Department of Biostatistics, University of Iowa Roy and Lucille Carver College of Medicine, Iowa City, IA 52242, USAf Department of Imaging Science and Neuroscience/Neurodevelopment, Seattle Children's Research Institute, Seattle, WA 98101, USAg Department of Psychiatry, The Johns Hopkins University, Baltimore, MD 21287, USAh Department of Neurology, The Johns Hopkins University, Baltimore, MD 21287, USAi Department of Neuroscience, The Johns Hopkins University, Baltimore, MD 21287, USA

⁎ Corresponding author. Psychiatry Research, 1-305Iowa City, IA 52242, USA. Fax: +1 319 353 3003.

E-mail addresses: [email protected] ([email protected] (E.H. Aylward),[email protected] (H.J. Johnson), vincent-magn(V.A. Magnotta), [email protected] (A.R. Juhl), ro(R.K. Pierson), [email protected] (J. Mills), d(D.R. Langbehn), [email protected] (J.S. Paulsen)

Available online on ScienceDirect (www.scienced

0969-9961/$ – see front matter © 2010 Elsevier Inc. Adoi:10.1016/j.nbd.2010.07.014

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a r t i c l e i n f o
Article history:Received 6 April 2010Revised 1 July 2010Accepted 22 July 2010Available online 2 August 2010

Keywords:Huntington diseaseMRICerebral cortexCortical thicknessSurface area

Neuroimaging studies of subjectswhoare gene-expanded forHuntingtonDisease, but not yet diagnosed (termedprodromal HD), report that the cortex is “spared,” despite the decrement in striatal and cerebral white-mattervolume.Measurement of whole-cortex volume canmaskmore subtle, but potentially clinically relevant regionalchanges in volume, thinning, or surface area. The current study addressed this limitation by evaluating corticalmorphology of 523 prodromal HD subjects. Participants included 693 individuals enrolled in the PREDICT-HDprotocol.Of theseparticipants, 523 carried theHDgenemutation (prodromalHDgroup); the remaining170werenon gene-expanded and served as the comparison group. Based on age and CAG repeat length, gene-expandedsubjects were categorized as “Far from onset,” “Midway to onset,” “Near onset,” and “already diagnosed.” MRIscans were processed using FreeSurfer. Cortical volume, thickness, and surface area were not significantlydifferent between the Far from onset group and controls. However, beginning in theMidway to onset group, thecortex showed significant volume decrement, affecting most the posterior and superior cerebral regions. Thispattern progressed when evaluating the groups further into the disease process. Areas that remained mostlyunaffected included ventral and medial regions of the frontal and temporal cortex. Morphologic changes weremostly in thinning as surface area did not substantially change in most regions. Early in the course of HD, thecortex shows changes that are manifest as cortical thinning and are most robust in the posterior and superiorregions of the cerebrum.

Medical Education Building,

Nopoulos),[email protected] (C.A. Ross),[email protected]@[email protected]).

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© 2010 Elsevier Inc. All rights reserved.

Introduction

Huntington disease (HD) is a neurodegenerative disorder thatmanifests in a triad of symptoms including cognitive, motor, andbehavioral abnormalities. The discovery of the gene in 1993 (Hunting-ngton's Disease Collaborative Research Group, 1993) provided anopportunity to study individuals who carry the mutant gene, but have

not yet manifested significant disease signs and are therefore referred toas prodromal HD.

HD is part of a family of poly-glutamine diseases inwhich themutantgene (huntingtin in the case of HD) contains a triplet CAG repeat codingfor an expanding polyglutamine repeat and resulting in an abnormal ortoxic protein. Another property of polyglutamine diseases is that despitethe fact that the mutant proteins are expressed ubiquitously, the diseasemanifestation is specific to brain tissue and also to specific regions of thebrain. For HD, the area of the brain most affected is that of the striatum.Therefore, most of the studies of HD, using either neuropathologicmethods or neuroimaging methods have focused on measuring theeffects of the disease on this brain region. However, more recently, therehave been a number of studies evaluating “extra-striatal” brain structuresuch as the morphology of the cerebral white matter and cortex insubjects with early HD or prodromal HD. As a whole, these studiessupport an interestingpattern inwhich the cerebralwhitematter volume

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545P.C. Nopoulos et al. / Neurobiology of Disease 40 (2010) 544–554

is substantially lower thannormal,while in contrast, the cerebral cortex isrelatively “spared” (Aylward et al., 1998; Beglinger et al., 2005; Ciarmielloet al., 2006; Douaud et al., 2006; Fennema-Notestine et al., 2004; Jerniganet al., 1991; Muhlau et al., 2007; Rosas et al., 2003).

PREDICT-HD is a long-term observational study of a large populationof prodromal HD subjects (Paulsen et al., 2006). In a recent cross-sectional analysis of 657 participants, the volume of the cerebral cortexwas indeed found to be significantly reduced in volume in theprodromal HD subjects. However, the effect size for the comparison ofvolume decrement in prodromal HD subjects to controls in the cerebralcortex (0.699) was substantially smaller than the effect size of thecomparison of volumes across groups for the cerebral white matter(1.445) or striatum (2.456) (Paulsen et al., 2010). One important caveatfor this andother analyses that use the globalmeasure of cerebral cortexis that this measure is a gross one and may very well miss regionalvariation of structure within the cortex, as the cortex is divided up intomany small structurally and functionally distinct regions.

Few studies have evaluated regional morphology of the cerebralcortex in HD. Rosas, in a study of HD subjects post-diagnosis, showedthat cortical thinningwas indeedgradual in onset and regionally specific(Rosas et al., 2002). In more recent studies, cortical thickness maps ofboth small (Rosas et al., 2005) and large (Tabrizi et al., 2009) samples ofprodromal HD subjects show an interesting pattern in which corticalthinning occurs in an unexpected pattern that is heavily superior andposterior,withwhat appears to be frontal lobe sparing. This is surprisinggiven the fact that, although the striatumreceives input fromall over thecortex, the output of the striatum (via basal ganglia and thalamicconnections) is predominantly to the frontal cortex.

In regard to cerebral cortex morphology, studies have typicallyfocused on measures of volume or cortical thickness. However, volumeis a function of both thickness and surface area.Moreover, recent studieshave shown the importance of distinguishing the measures of corticalthickness and cortical surface area. For instance, two studieshave shownthat the genetic influences of cortical thickness appear to beindependent of those driving cortical surface area (Panizzon et al.,2009; Winkler et al., 2009). In addition, one of these studies (Winkleret al., 2009) showed that in a non-diseased population, measures ofcortical volume were more highly correlated to surface area than tocortical thickness. These studies highlight the importance of lookingat both thickness and surface area when evaluating corticalmorphology.

The current study is designed to extensively evaluate the morphol-ogy of the cerebral cortex in a large sample of prodromal HD subjects.This is the first study to comprehensively examine cortical morphologyin prodromal HD subjects using volume, surface area, and thicknessmeasures. Unlike previous studies that have reported only corticalthickness maps in prodromal HD, this study also measures and reportsvolumes of cortical regions.

Methods

Participants

Participants were recruited from the PREDICT-HD study, an ongoinglongitudinal study conducted at 32 sites in the United States, Canada,Australia, Germany, Spain, and the United Kingdom (Paulsen et al.,2006). The study was approved by the Institutional Review Board ateach participating institution. Study participants signed informedconsents to participate and allow their de-identified research data tobe analyzed by collaborative institutions. All participants underwentdetailed motor, cognitive, psychiatric, and functional evaluationsannually as previously described (Paulsen et al., 2006; Paulsen et al.,2008).

We use the term “prodromal HD” to describe the phase prior to themanifestation of the movement disorder clinically diagnosable as HD.Participantswere classified asprodromalHDaccording to thediagnostic

confidence level of the Unified Huntington Disease Rating Scale UHDRS(Huntington Study Group, 1996). Diagnostic confidence level is a scaleranging from0 (normal) to 4 (defined as the unequivocal presence of anotherwise unexplained movement disorder in a participant at risk forHD). Participants with ratings less than 4 were classified as prodromalHD. All subjects were prodromal at the time of study enrollment, butsome subjects converted to a diagnosis of HD at a follow-up assessment.Participants who received a rating of 4 were classified as converted andare referred to as “diagnosed.” Study participants consisted of 693individuals. Of these participants, 523 carried the HD gene mutation,and 170 carried only normal alleles; the latter were used as thecomparison group.

Proximity to Diagnosis

Estimated years to diagnosis and probability of receiving a diagnosiswithin the ensuing five years were calculated using a CAG-and-agebased predictive model developed from a worldwide sample of 2,913and validated with nearly 100 prospectively diagnosed patients fromthe PREDICT-HD study (Langbehn et al., 2004, 2009). Participants wereconsidered “Far” from diagnosis if estimated proximity to clinicaldiagnosis was greater than 15 years, “Mid” to diagnosis if theirestimated proximity was 9–15 years, and “Near” to diagnosis ifestimated proximity was less than 9 years. One group of participantswas diagnosed as havingHD. Table 1 displays the demographic and CAGrepeat-lengths of the five groups. Gender was similar across groups(from 59% to 67% female), although participants in the FAR group weresignificantly younger than participants in the other groups.

MRI procedures

All scans were obtained using a standard multi-modal protocolthat included an axial 3D volumetric spoiled-gradient echo series(~1×1×1.5 mm voxels) and a dual echo proton density/T2(~1×1×3 mm voxels) series. Thirty sites used General Electric 1.5Tesla scanners, and two sites used Siemens 1.5 Tesla scanners.

Each multi-modal scan series was processed through a standard-ized morphometric processing pipeline that corrected for commonmulti-site data differences (Magnotta et al., 2002). Briefly, outputs ofthe morphometric processing pipeline included a brain mask used forcomputing the Intracranial Volume (ICV) and a T1 weighted imagesupplied to FreeSurfer for cortical thickness processing.

The brain mask was derived from all three image intensity modes toderive robust estimates of ICV, which include tissue and surface CSF thatextends to theborder of duramater. The T1weighted imagewas createdwith isotropic (1.0 mm3) voxels. In addition, the T1 images werenormalized so that the tissue intensities across the spatial domain of asingle image and scans from different sites were placed in a consistentintensity range. Spatial intensity inhomogeneities were removed byapplyingaparametric correction (Styner et al., 2000) thatused estimatesof the tissue intensities based on tissue classes from the multi-modaltissue classification (Harris et al., 1999). Each scan's intensity range wasplaced on a consistent scale by linearly scaling tomaximize the dynamicrange inside the brain region. A reoriented, inhomogeneity and intensitycorrected T1 scan for each subject was then clipped to the brainmask tobe used as input for cortical parcellation.

Cortical reconstruction was performed with the FreeSurfer imageanalysis suite (http://surfer.nmr.mgh.harvard.edu/). Briefly, processingincludes removal of non-brain tissue using a hybrid watershed/surfacedeformation procedure (Segonne et al., 2004), tessellation of the gray-matter white-matter boundary, and automated topology correction(Fischl et al., 2001; Segonne et al., 2007). In addition, surfacedeformation, following intensity gradients, is done to optimally placethe gray/white and gray/cerebrospinal fluid borders at the locationwhere the greatest shift in intensity defines the transition to the othertissue class (Dale and Sereno, 1993; Dale et al., 1999; Fischl and Dale,

http://surfer.nmr.mgh.harvard.edu/

Table 1Demographic information.

Controls Far from onset Midway to onset Near to onset DiagnosedHD

(N15 years) (9–15 years) (b9 years)

# Females 108 (63.5) 113 (66.5) 109 (66.9) 80 (59.3) 37 (67.3)# Males 62 (36.5) 57 (33.5) 54 (33.1) 55 (40.7) 18 (32.7)Total # 170 170 163 135 55Age mean (s.d.) 44.9 (12.1) 38.1 (8.4) 44.1 (10.4) 47.1 (10.1) 47.3 (9.5)CAG length mean (s.d.) 20.1 (3.3) 41.0 (1.5) 42.3 (2.2) 43.6 (2.4) 43.7 (3.5)

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2000). Once the cortical models are complete, a number of deformableprocedures can perform further data processing and analysis includingsurface inflation (Fischl et al., 1999a), registration to a spherical atlas,which utilizes individual cortical folding patterns to match corticalgeometry across subjects (Fischl et al., 1999b), parcellation of thecerebral cortex into units based on gyral and sulcal structure (Desikanet al., 2006; Fischl et al., 2004), and creation of a variety of surface-baseddata including maps of curvature and sulcal depth. This method usesboth intensity and continuity information from the entire three-dimensional MR volume in segmentation and deformation proceduresto produce representations of cortical thickness, calculated as the closestdistance from the gray/white boundary to the gray/CSF boundary ateach vertex on the tessellated surface (Fischl and Dale, 2000). Themapsare created using spatial intensity gradients across tissue classes and aretherefore not simply reliant on absolute signal intensity. The mapsproduced are not restricted to the voxel resolution of the original dataand thus, are capable of detecting subvoxel differences between groups.Procedures for the measurement of cortical thickness have beenvalidated against histological analysis (Rosas et al., 2002) and manualmeasurements (Kuperberg et al., 2003; Salat et al., 2004). FreeSurfermorphometric procedures show good test-retest reliability acrossscanner manufacturers and field strengths (Han et al., 2006).

Table 2Analysis of regional volumes comparing all prodromal HD subjects to controls.

Region Lobe F

Lateral occipital Occipital 16Superior temporal Temporal 11Pre-cuneus Parietal 10Inferior parietal Parietal 10Cuneus Occipital 8Post-central Parietal 8Lingual Occipital 7Bank Superior Temporal Sulcus Temporal 6Pars opercularis Frontal 6Fusiform Temporal 6Rostral middle frontal Frontal 5Superior frontal Frontal 5Transverse temporal Temporal 5Supra-marginal Parietal 4Middle temporal Temporal 4Pre-central Frontal 4Superior parietal Parietal 4Para-central Parietal 4Rostral anterior cingulate Frontal 4Inferior temporal Temporal 3Entorhinal Temporal 2Peri-calcarine Occipital 2Caudal middle frontal Frontal 2Lateral orbitofrontal Frontal 2Pars orbitalis Frontal 1Pars triangularis Frontal 1Caudal anterior cingulate Frontal 1Frontal pole Frontal 1Posterior cingulate Frontal 1Isthmus cingulate Frontal 0Medial orbitofrontal Frontal 0Para-hippocampal Temporal 0Temporal pole Temporal 0

Processing was completed without manual intervention. SinceFreeSurfer uses random initiation of certain processes in the pipeline,each scan was processed five times, and a similarity index wascalculated for each run in comparison to the other runs for that scan.The run that was most similar to the other runs for a given scan waschosen to represent the best result for that scan, eliminating spuriousoutliers due to the random initialization. Visual inspection was thencompleted to review the final surfaces and parcellation.

Statistical analysis

The thickness at each vertex (brainmap analysis), the total volume ofeach region of interest, and the surface area of each region of interestwere the outcomes in a general linear-model tests of prognostic group(Control, Far, Mid, Near, or Diagnosed), whichwas the predictor variableof primary interest. Gender and age were covariates. For the region ofinterest analysis, all volumes were adjusted for ICV. To determine ifpotential groupdifferences dependedon the age or gender of individuals,the two-way interactions (age*gender, age*group, and gender*group)were tested and removed from themodel if not statistically significant, asour objective was to identify the most parsimonious model of disease

value P (FDR corrected) Direction

.47 b0.0001 Control N prHD






.14 0.0001 Control N prHD












.04 0.0055 prHD N Control


.54 0.0624 n/a

.31 0.0871 n/a

.06 0.1244 n/a

.04 0.1244 n/a

.74 0.1833 n/a

.74 0.1833 n/a

.22 0.3787 n/a

.14 0.4101 n/a

.11 0.4129 n/a

.80 0.5933 n/a

.61 0.7176 n/a

.52 0.7645 n/a

.40 0.8336 n/a

Fig. 1. Cortical regions volume. Starting from the left, each group of six maps represent the comparison of volume of separate cortical region between each prodromal HD group and the controls (Dx=diagnosed). Left hemisphere only isshown. The top row shows (from left to right) lateral and medial views, the second row shows dorsal and ventral views, the last row shows anterior and posterior views, respectively.

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Fig. 2. Cortical thickness maps. Starting from the left, each group of six maps represent the comparison of cortical thickness between each prodromal HD group and the controls (Dx=diagnosed). Left hemisphere only is shown. The top rowshows (from left to right) lateral and medial views, the second row shows dorsal and ventral views, the last row shows anterior and posterior views, respectively.

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image of Fig.�2


progression. All statistical tests were corrected for multiple comparisonsusing a false discovery rate (FDR) of 0.05 (Genovese et al., 2002).

Results

Regional cortical volume analysis of prognostic groups compared tocontrols

Table 2 displays results of the ANOVAs comparing mean corticalvolumes of 33 regions among all prodromal HD subjects combined andthe control group. Volumes in this table are ordered by group effectsizes. After correction for multiple comparisons, 20 of the 33 regionsshowed significant group differences. In all of these 20 regions, volumeswere reduced in theHDgroup compared to controls, with the exceptionof the rostral anterior cingulate region wherein volume was increased.Most of the regions that are significantly affected are in the occipital andparietal lobes aswell as lateral temporal regions. The areas affectedmostin the frontal lobes are superior frontal, paracentral (medial surface),precentral, and two small lateral regions, the rostral middle frontal andpars opercularis (Broca's area). No regions on theventral frontal lobe arestructurally different in the prodromal HDgroups compared to controls.Also spared are the temporal pole and the ventromedial areas of theentorhinal and parahippocampal cortex.

Fig. 1 displays volumes of cortical regions that significantly differedbetween the control group and each prodromal HD prognostic group.No differences between the Far and control groups were found incortical volume. However, in the Mid, Near, and Diagnosed groups,patterns of volume loss occur, starting in a few areas in themid to onsetgroup (lateral andmedial occipital and parietal, superior temporal, parstriangularis), then extending through the most of the cortex in thediagnosed groups. Consistent with the combined prodromal HD groupanalysis (Table 2), the areas with the most severe volume loss (thelightest shades of blue) include lateral and medial occipital regions

Table 3Analysis of regional cortical surface area comparing all prodromal HD subjects to controls.

Region Lobe F v

Transverse temporal Temporal 16Post-central Parietal 9Cuneus Occipital 8Pre-central Frontal 5Superior temporal Temporal 5Lateral occipital Occipital 3Lingual Occipital 2Entorhinal Temporal 2Inferior temporal Temporal 2Middle temporal Temporal 2Pre-cuneus Parietal 1Peri-calcarine Occipital 1Supra-marginal Parietal 1Para-central Frontal 1Superior frontal Frontal 1Pars opercularis Frontal 1Fusiform Temporal 1Medial orbitofrontal Frontal 1Para-hippocampal Temporal 1Inferior parietal Parietal 1Rostral anterior cingulate Frontal 1Temporal pole Temporal 1Pars triangularis Frontal 1Pars orbitalis Frontal 1Caudal middle frontal Frontal 0Lateral orbitofrontal Frontal 0Isthmus cingulate Frontal 0Frontal pole Frontal 0Posterior cingulate Frontal 0Rostral middle frontal Frontal 0Superior parietal Parietal 0Bank superior temporal sulcus Temporal 0Caudal anterior cingulate Frontal 0

along with the superior temporal gyrus while the regions not differentfrom the controls include a contiguous area of ventral andmedial frontaland temporal cortex.

Cortical thickness maps of prognostic groups compared to controls

Fig. 2 shows the cortical thickness maps of each prognostic group(Far, Mid, Near, Diagnosed) derived from comparisons with thecontrols. Each map is corrected for multiple comparisons so that onlystatistically significant differences are displayed. The pattern is similarto that of the cortical volume analysis. In the Far group, there were nosignificant differences in cortical thickness compared to controls.Going from the Mid to the Near to the Diagnosed groups, thereemerges a pattern of progressively thinner regions of the cortex.Initially, this is present predominantly in the lateral parietal andoccipital regions, but by the time of HD diagnosis, thinning is observedthroughout most of the cerebral cortex. The most affected regions(lightest shade of blue), however, remain posterior. Ventral andmedial areas of the frontal and temporal lobe are largely spared as areboth the pre and post central gyri. The exception to the widespreadthinning is in the area of the rostral anterior cingulate where thereappears to be significant thickening in the HD groups compared tocontrols, in parallel with the volumetric analysis.

One interesting exception to the similar patterns in the corticalvolume and cortical thicknessmaps are the precentral and postcentralgyri, which showed volume loss in the Near and Diagnosed groups,but relative sparing of cortical thickness, even in the diagnosed group.

Regional surface area analysis of prognostic groups compared to controls

Differences between the prodromal HD group and controls in surfacearea were significant for only five regions: transverse temporal,postcentral, precentral, cuneus, and superior temporal (see Table 3). For

alue P (FDR corrected) Direction






.96 0.0957 n/a

.94 0.1118 n/a

.77 0.1219 n/a

.65 0.1381 n/a

.51 0.3024 n/a

.91 0.3024 n/a

.91 0.3071 n/a

.85 0.3622 n/a

.68 0.3622 n/a

.65 0.3739 n/a

.58 0.3850 n/a

.52 0.3999 n/a

.44 0.3999 n/a

.42 0.3999 n/a

.39 0.4513 n/a

.27 0.4513 n/a

.21 0.4513 n/a

.20 0.4513 n/a

.15 0.4513 n/a

.21 0.5147 n/a

.98 0.5147 n/a

.96 0.5147 n/a

.93 0.5147 n/a

.91 0.5147 n/a

.87 0.5275 n/a

.81 0.5353 n/a

.80 0.5353 n/a

.71 0.5791 n/a


all of these regions, the prodromal HD group had lower surface areacompared to controls. The findings of the pre- and post-central areashaving significant smaller surface area help clarify the apparentinconsistent finding between the volume and thickness maps of theseregions. That is, although the volume is significantly lower, corticalthickness was not abnormal, yet surface area was.

With the exception of the pre- and post-central regions, the corticalthickness maps follow a pattern almost identical to the cortical volumemaps. Moreover, despite relatively widespread cortical volume decre-ments, Table 3 is impressively nonsignificant with only five of the 33regions abnormal. This is in comparison to Table 2 (volume)where 20ofthe 33 regions are abnormal, and both the figures (volumes andthickness mapped according to prognostic group) show widespread,significant volume and thickness abnormalities in the prodromal HDsubjects compared to controls. Thus, volume differences between thegroups appear to be mostly driven by changes in cortical thickness,rather than by decrements in surface area.

Discussion

This study is the first comprehensive analysis of cortical morphol-ogy in a large sample of prodromal HD subjects compared to healthycontrols. Beginning in the midway to onset group (9–15 years fromdiagnosis), the cortex shows significant decrement in volume in apattern that is initially specific to superior and posterior regions of thecortex, but by onset of diagnosis represents a pattern that is quiteextensive and includes most of the entire cerebrum. Nevertheless, thesuperior and posterior regions of the cerebrum remain the mostsignificantly abnormal while regions of the ventral and medial frontaland temporal lobe remain mostly unaffected. Unique to this study inparticular is the finding that the volume loss appears to be relatedmostly to cortical thinning rather than decrements in surface area.

The current study showed that individuals far from onset had nosignificant changes in cortical thickness or volume compared tocontrols. In a previous preliminary study on prodromal HD subjectsevaluating cortexmorphology, we found a pattern in which the cortexwas enlarged in the area of gyri, but substantially thinner in the sulci(Nopoulos et al., 2007). The current study is partially supportive inthat the thinning found in the Mid and Near groups were primarilylocated in the sulci, as identified in the previous study. In addition, thecurrent study also found areas of gyral thickening in the Far fromonset group, similar to the previous study; however none of theseareas of thickening survived the more strict analysis of correction formultiple comparison. How far back the changes in the cortex areoccurring is uncertain. For instance, cortical thickening could bepresent even prior to the Far from onset group as a manifestation ofabnormal development. A recent study of a knock-in mouse model ofHD showed substantial abnormalities in brain development support-ing the notion that changes in the brain may be present decades priorto onset of disease (Molero et al., 2010).

The current findings in which substantial thinning is not presentuntil mid and near onset are consistent with the theme of relative graymatter sparing early in the course of the disease seen in our previousvolumetric analysis of a larger group of prodromal HD subjects enrolledin PREDICT-HD. In that study, the total cerebral-cortex volume wasreduced in the prodromal HD group relative to controls. However, theeffect sizeof thisfindingwas substantially smaller than the effect size forthe decrement in white-matter volume or for the effect size of thedecrement in volume of the striatum (Paulsen et al., 2010).

The observations of relative gray matter sparing in earlyprodromal HD (Far group) are interesting, given that widespreadcortical involvement is evident in later stages (Heinsen et al., 1994;Selemon et al., 2004;Wagster et al., 1994). Yet lack of cortical findingsin other neuroimaging studies of subjects who are prodromal HD ornewly diagnosed suggest that cortical degeneration is a relatively latephenomenon in the course of the illness, occurring in a slow and

patchy process. In addition, longitudinal studies of prodromal HDsubjects (Kipps et al., 2005) show very little or only regionally specificgray matter loss in prodromal HD and/or early HD subjects, while theremaining cortex is unaffected.

Recent studies of cortical thinning in prodromal HD and diagnosedsubjects have shown a similar pattern to the current study, withsubstantial thinning first in the posterior cerebrum (occipital lobe),then superior parietal, and superior frontal regions (Rosas et al., 2005;Tabrizi et al., 2009). Even as the disease progresses through diagnosisand areas of the temporal lobe and lateral frontal lobe become thin,there remains remarkable sparing of the medial and ventral aspects ofthe frontal and temporal lobe. These findings are consistent with onepathologic study in which cortical atrophy (cell count using plani-metry) was found to be greatest in the occipital lobe and least in thefrontal lobe (Lange, 1981). Given the circuitry of the basal ganglia, thecortical regions that appear spared (ventral and medial frontal andtemporal lobe) aremostly among those that receive output projectionsfrom the basal ganglia to the cortex (Middleton and Strick, 1996a,b,2000). However, given the somewhat patchy nature of change in thecortex (some parts of the frontal lobe significantly affected, other partsspared), there appears to be a relative separation between striatalatrophy and cerebral cortical changes early in the disease process.

Also similar to the two other studies evaluating the thickness ofthe cortex in prodromal HD subjects (Rosas et al., 2005; Tabrizi et al.,2009), the current study found an increase in the volume andthickness of the rostral anterior cingulate in the Near and Diagnosedgroups. As similar methods were used, one interpretation could bethat the increased volume is related to a methodologic bias. However,in individuals far from onset of motor diagnosis, functional blood flow(fMRI) studies have found both decreased blood flow (Reading et al.,2004) and increased blood flow (Paulsen et al., 2004) in the anteriorcingulate. Though these different patterns may be related to thecognitive context during neuroimaging, dysfunction in this brain areais seen early in the course of the disease. Of interest is that two recentstudies have shown the anterior cingulate to behave different thanany other region of the cortex in the context of aging (Abe et al., 2008;Salat et al., 2004). That is, whereas most cortical regions decrease involume with age, the cingulate is either unchanged or increased insize with age. Since the prodromal HD subjects in the current studywere compared against healthy controls, it suggests that thisphenomenon of increased volume in the prodromal HD subjects asdisease onset approached was above and beyond what is seen in thecontext of aging within the normal healthy group. Themechanisms bywhich this brain region, in contrast to other regions, would thickensubstantially as the disease progresses are unclear.

Our study is the first to comprehensively examine corticalmorphology in prodromal HD using volume, surface area, andthickness measures. Since volume is the product of surface area andthickness, these measures can have unique and independentcontributions. Consistent with this notion are studies reportingcortical thickness and cortical surface area measures to be geneticallyindependent (Panizzon et al., 2009; Winkler et al., 2009). In thecurrent study, most of the brain regions that show significant volumedecrement compared to controls seem to be lower due to a thinning ofthe cortex rather than a reduction in surface area. This is in contrast tothe Winkler et al. study (2009), who measured cortical thickness andsurface area in a large sample of randomly ascertained extendedpedigrees of families and found that cortical volume was more closelyrelated to surface area than cortical thickness (Winkler et al., 2009).The difference between our study and the Winkler study may be thatthe current study was an assessment of a disease process whereas theWinkler study was, in general, a sample of related subjects, notrepresentative of a disease, but more representative of a healthycontrol sample.

Manifest HD pathological studies (Hedreen et al., 1991; Selemonet al., 2004; Sotrel et al., 1991) have indicated relatively selective loss


of neurons in deep cortical layers (especially layers V and VI, and someloss in layer III as well). These changes would be consistent with thethinning that we see. However cortical thinning could also representmorphologic changes in cell size, dendritic number and shape, andvolume of glial components (DiProspero et al., 2004). Thus earlychanges might represent cellular abnormalities with or withoutsubstantial cell death. These early changes would be more likely to bereversible with therapeutics. Thus therapeutics begun during theprodromal HD period might be able to forestall further irreversiblepathologic changes in cortex. Though these changes could in factmanifest in cognitive changes and other symptoms, they would morelikely represent the earliest stages of dysfunction in a process thateventually leads to cell death.

Another important aspect to investigate further is the relationshipbetween clinical symptoms and regions of cortex abnormality. In arecent pathologic study, cell loss in the primary motor strip wasassociated with movement abnormalities, while cell loss in theanterior cingulated was associated with significant mood symptomsin subjects with manifest disease (Thu et al, 2010). These are findingsthat, at first glance, may seem inconsistent with the current findingssince the motor strip and the anterior cingulated appear “spared” insome aspects compared to other regions of the brain that are affected.However, although the primary motor strip was normal in thickness,it had substantial reduction in surface area (and therefore volume),which could be correlated with cell loss. Moreover, although theanterior cingulate is enlarged, there is still possibility that this couldrepresent morphology such as cell loss with accompanying gliosis.Finally, the Thu study was done on patients with manifest disease andtherefore represent morphology that is most likely years advancedbeyond the current study. Future work in which neuropathologicchanges and neuroimaging changes can be assessed on patients incomparable time frames of disease would help shed light on whetherMRI findings truly mirror that of histopathologic findings.

Cerebral white matter changes may potentially be considered as“secondary” to either striatal or cortical abnormality (functionaldeterioration or frank degeneration). Yet some have suggested thatthe white matter abnormalities reported in HD may be the result of aprimary pathology in white matter rather than a secondary one(Bartzokis et al., 2007, 2006). Findings from the current study maysupport the theory of a primaryproblemwithwhitematter pathology. Ifthe white matter changes in prodromal HD are seen as secondarycortical change, there should be a clear association between the regionsof cortical change and the white matter associated with those regions.However in the current study, there is a lack of connection between theregions of the cortex that are abnormal and the regions of white matterthat are abnormal. FromthePREDICT-HDsample, a longitudinal analysisof brainmorphology in prodromalHDsubjects shows thatwhite-mattervolumes significantly decrease far from onset (greater than 15 yearsfrom diagnosis), and although the changes are throughout thecerebrum, they are most prominent in the frontal lobes (Aylwardet al., forthcoming). This is in contrast to the current analysis that showscortical thinning mostly in the posterior regions with no appreciablechange in relatively large parts of the frontal lobes (ventral andmedial).This further supports the notion that the changes in cerebral whitematter may be a primary process rather than secondary to structuralchanges in the cortex or striatum (Bartzokis et al., 2007, 2006).

In summary, the current study evaluates extensively the corticalmorphology of prodromal HD subjects. Changes in the cortex ofprodromal HD subjects appear to occur much later in the diseaseprocess (within a decade or nearer to onset) compared to changes inthe striatum or white matter (seen as far out as greater than 15 yearsfrom onset). When changes are apparent, they appear as corticalthinning (rather than decrement in surface area) in mostly superiorand posterior regions. Ventral and medial aspects of the frontal andtemporal lobes remain largely unchanged even throughout theprogression to formal clinical diagnosis of the cortical changes early

in the course of the disease may be amenable to therapeuticintervention and seem to be unrelated to changes in white matter.

Acknowledgments

This research is supported by the National Institutes for Health,National Institute of Neurological Disorders and Stroke (NS40068)and CHDI Foundation, Inc. We thank the PREDICT-HD sites, the studyparticipants, and the National Research Roster for Huntington DiseasePatients and Families.

Appendix

PREDICT-HD Investigators, Coordinators, Motor Raters, CognitiveRaters

January 5, 2010Peg Nopoulos, MD, Robert Rodnitzky, MD, Ergun Uc, MD, BA, Leigh

J. Beglinger, PhD, Vincent A. Magnotta, PhD, Stephen Cross, BA,Nicholas Doucette, BA, Andrew Juhl, BS, Jessica Schumacher, BA,Mycah Kimble, BA, Pat Ryan, MS, MA, Jessica Wood, MD, PhD, EricEpping, MD, PhD, Thomas Wassink, MD, and Teri Thomsen, MD(University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA);

David Ames, MD, Edmond Chiu, MD, Phyllis Chua, MD, OlgaYastrubetskaya, PhD, Joy Preston, Anita Goh, D. Psych, and AngelaKomiti, BS, MA (The University of Melbourne, Kew, Victoria,Australia);

Lynn Raymond, MD, PhD, Rachelle Dar Santos, BSc, Joji Decolon-gon, MSC, and David Weir, BSc (University of British Columbia,Vancouver, British Columbia, Canada);

Adam Rosenblatt, MD, Christopher A. Ross, MD, PhD, BarnettShpritz, BS, MA, OD, and Claire Welsh (Johns Hopkins University,Baltimore, Maryland, USA);

William M. Mallonee, MD and Greg Suter, BA (HereditaryNeurological Disease Centre, Wichita, Kansas, USA);

Ali Samii, MD, Hillary Lipe, ARNP, and Kurt Weaver, PhD (Universityof Washington and VA Puget Sound Health Care System, Seattle,Washington, USA);

Randi Jones, PhD, Cathy Wood-Siverio, MS, Stewart A. Factor, DO,and Claudia Testa, MD, PhD (Emory University School of Medicine,Atlanta, Georgia, USA);

Roger A. Barker, BA,MBBS,MRCP, SarahMason, BSC, AnnaGoodman,PhD, and Anna DiPietro (Cambridge Centre for Brain Repair, Cambridge,UK);

Elizabeth McCusker, MD, Jane Griffith, RN, and Kylie Richardson,PhD (Westmead Hospital, Sydney, Australia);

Bernhard G. Landwehrmeyer, MD, Daniel Ecker, MD, PatrickWeydt,MD, Michael Orth MD, PhD, Sigurd Süβmuth, MD, RN, Katrin Barth, RN,and Sonja Trautmann, RN (University of Ulm, Ulm, Germany);

Kimberly Quaid, PhD, MelissaWesson, MS, and JoanneWojcieszek,MD (Indiana University School of Medicine, Indianapolis, IN);

Mark Guttman,MD, Alanna Sheinberg, BA, Adam Singer, and JaniceStober, BA, BSW (Centre for Addiction and Mental Health, Universityof Toronto, Markham, Ontario, Canada);

Susan Perlman, MD and Arik Johnson, PsyD (University ofCalifornia, Los Angeles Medical Center, Los Angeles, California, USA);

Michael D. Geschwind, MD, PhD and Jon Gooblar, BA (University ofCalifornia San Francisco, California, USA);

Tom Warner, MD, PhD, Stefan Kloppel, MD, Maggie Burrows, RN,BA, Marianne Novak, MD, Thomasin Andrews, MD, BSC, MRCP,Elisabeth Rosser, MBBS, FRCP, and Sarah Tabrizi, BSC, PhD (NationalHospital for Neurology and Neurosurgery, London, UK);

Anne Rosser, MD, PhD, MRCP and Kathy Price, RN (CardiffUniversity, Cardiff, Wales, UK);

Amy Chesire, LCSW-R, MSG, Frederick Marshall, MD, and MaryWodarski, BA (University of Rochester, Rochester, New York, USA);


Oksana Suchowersky,MD, FRCPC, Sarah Furtado,MD, PhD, FRCPC, andMary Lou Klimek, RN, BN, MA (University of Calgary, Calgary, Alberta,Canada);

Peter Panegyres, MB, BS, PhD, Carmela Connor, BP, MP, DP, andElizabeth Vuletich, BSC (Neurosciences Unit, Graylands, Selby-Lemnos& Special Care Health Services, Perth, Australia);

Joel Perlmutter, MD and Stacey Barton, MSW, LCSW (WashingtonUniversity, St. Louis, Missouri, USA);

Sheila A. Simpson, MD and Daniela Rae, RN (Clinical GeneticsCentre, Aberdeen, Scotland, UK);

David Craufurd, MD, Ruth Fullam, BSC, and Elizabeth Howard, MD(University of Manchester, Manchester, UK)

Pietro Mazzoni, MD, PhD, Karen Marder, MD, MPH, CarolMoskowitz, MS, and Paula Wasserman, MA (Columbia UniversityMedical Center, New York, New York, USA);

Diane Erickson, RN, Dawn Miracle, BS, MS, and Rajeev Kumar, MD(Colorado Neurological Institute, Englewood, Colorado, USA);

Vicki Wheelock, MD, Terry Tempkin, RNC, MSN, Nicole Mans, BA,MS, and Kathleen Baynes, PhD (University of California Davis,Sacramento, California, USA);

Joseph Jankovic, MD, Christine Hunter, RN, CCRC, and WilliamOndo, MD (Baylor College of Medicine, Houston, Texas, USA);

Justo Garcia de Yebenes, MD, Monica Bascunana Garde, MartaFatas, BA, and Jose Luis Lópenz Sendon, MD (Hospital Ramón y Cajal,Madrid, Spain);

Martha Nance, MD, Dawn Radtke, RN, and David Tupper, PhD(Hennepin County Medical Center, Minneapolis, Minnesota, USA);

Wayne Martin, MD, Pamela King, BScN, RN, and Satwinder Sran,BSC (University of Alberta, Edmonton, Alberta, Canada);

Anwar Ahmed, PhD, Stephen Rao, PhD, Christine Reece, BS, JaniceZimbelman, PhD, PT, Alexandra Bea, BA, and Emily Newman, BA(Cleveland Clinic Foundation, Cleveland, Ohio, USA);

Steering Committee

Jane Paulsen, PhD, Principal Investigator, Eric Epping, MD, PhD,Douglas Langbehn, MD, PhD, Hans Johnson, PhD, Megan Smith, PhD,Janet Williams, PhD, RN, FAAN (University of Iowa Hospitals andClinics, Iowa City, IA); Elizabeth Aylward, PhD (Seattle Children'sResearch Institute, WA); Kevin Biglan, MD (University of Rochester,Rochester, NY); Blair Leavitt, MD (University of British Columbia,Vancouver, BC, Canada); Marcy MacDonald, PhD (MassachusettsGeneral Hospital); Martha Nance, MD (Hennepin County MedicalCenter, Minneapolis, MN); Jean Paul Vonsattel, PhD (ColumbiaUniversity Medical Center, New York, NY).

Scientific Sections

Bio Markers: Blair Leavitt, MDCM, FRCPC (Chair) and MichaelHayden, PhD (University of British Columbia); Stefano DiDonato, MD(Neurological Insitute “C. Besta,” Italy); Ken Evans, PhD (OntarioCancer Biomarker Network);WayneMatson, PhD (VAMedical Center,Bedford, MA); Asa Peterson, MD, PhD (Lund University, Sweden),Sarah Tabrizi, PhD (National Hospital for Neurology and Neurologyand Neurosurgery, London).

Cognitive: Deborah Harrington, PhD (Chair, University of Califor-nia, San Diego), Tamara Hershey, PhD and Desiree White, PhD(Washington University Cognitive Science Battery Development);Holly Westervelt, PhD, Jennifer Davis, PhD, Pete Snyder, PhD, andGeoff Tremont, PhD, MS (Chair, Quality Control and Training, BrownUniversity); Megan Smith, PhD (Chair, Administration), David J.Moser, PhD, Leigh J. Beglinger, PhD (University of Iowa); LucetteCysique, PhD (St. Vincent's/University of Melbourne, Australia);Carissa Gehl, PhD (VA Medical Center, Iowa City, IA); Robert K.Heaton, PhD, David Moore, PhD, Joanne Hamilton, PhD, and DavidSalmon, PhD (University of California, San Diego); Kirsty Matheson

(University of Aberdeen); Paula Shear, PhD (University of Cincinnati);Karen Siedlecki, PhD (Fordham University); Glenn Smith, PhD (MayoClinic); and Marleen Van Walsem (EHDN).

Functional Assessment: Janet Williams, PhD (Co-Chair), Leigh J.Beglinger, PhD, Anne Leserman, MSW, LISW, Justin O'Rourke, MA,Bradley Brossman, MA, Eunyoe Ro, MA (University of Iowa); RebeccaReady, PhD (University of Massachusetts); Anthony Vaccarino, PhD(Ontario Cancer Biomarker Network); Sarah Farias, PhD (University ofCalifornia, Davis); Noelle Carlozzi, PhD (Kessler Medical Rehabilita-tion Research & Education Center); and Carissa Gehl, PhD (VAMedicalCenter, Iowa City, IA).

Genetics:MarcyMacDonald, PhD (Co-Chair), Jim Gusella, PhD, andRick Myers, PhD (Massachusetts General Hospital); Michael Hayden,PhD (University of British Columbia); Tom Wassink, MD (Co-Chair)and Eric Epping, MD, PhD (University of Iowa).

Imaging

Administrative: Ron Pierson, PhD (Chair), Kathy Jones, BS, JacquieMarietta, BS, William McDowell, AA, Steve Dunn, BA, Greg Harris, BS,Eun Young Kim, MS, and Yong Qiang Zhao, PhD (University of Iowa);John Ashburner, PhD (Functional Imaging Lab, London); Vince Calhoun,PhD (University of New Mexico); Steve Potkin, MD (University ofCalifornia, Irvine); Klaas Stephan, MD, PhD (University College ofLondon); and Arthur Toga, PhD (University of California, Los Angeles).

Striatal: Elizabeth Aylward, PhD (Chair, Seattle Children's Re-search Institute) and Kurt Weaver, PhD (University of Washingtonand VA Puget Sound Health Care System, Seattle, Washington).

Surface Analysis: Peg Nopoulos, MD (Chair), Eric Axelson, BSE,and Jeremy Bockholt, BS (University of Iowa).

Shape Analysis: Christopher A. Ross (Chair), MD, PhD, MichaelMiller, PhD, and Sarah Reading, MD (Johns Hopkins University); MirzaFaisal Beg, PhD (Simon Fraser University).

DTI: Vincent A. Magnotta, PhD (Chair, University of Iowa); KarlHelmer, PhD (Massachusetts General Hospital); Kelvin Lim, MD(University of Ulm, Germany); Mark Lowe, PhD (Cleveland Clinic);SasumuMori, PhD (Johns Hopkins University); Allen Song, PhD (DukeUniversity); and Jessica Turner, PhD (University of California, Irvine).

fMRI: Steve Rao, PhD (Chair), Erik Beall, PhD, Katherine Koenig,PhD, Mark Lowe, PhD, Michael Phillips, MD, Christine Reece, BS, andJan Zimbelman, PhD, PT (Cleveland Clinic).

Motor: Kevin Biglan, MD (University of Rochester), Karen Marder,MD (Columbia University), and Jody Corey-Bloom, MD, PhD (Univer-sity of California, San Diego) all Co-Chairs; Michael Geschwind, MD,PhD (University of California, San Francisco); and Ralf Reilmann, MD(Muenster, Germany).

Psychiatric: Eric Epping, MD, PhD (Chair), Nancy Downing, RN,MSN, Jess Fedorowicz, MD, Robert Robinson, MD, and Megan Smith,PhD (University of Iowa); Karen Anderson, MD (University ofMaryland); David Craufurd, MD (Manchester University); MarkGroves, MD (Columbia University); Anthony Vaccarino, PhD andKen Evans, PhD (Ontario Cancer Biomarker Network); Hugh Rickards,MD (Queen Elizabeth Psychiatric Hospital); and Eric van Duijn, MD(Leiden University Medical Center, Netherlands).

Core Sections

Statistics: Douglas Langbehn, MD, PhD (Chair) and James Mills,MEd, MS (University of Iowa); and David Oakes, PhD (University ofRochester).

Recruitment/Retention: Martha Nance, MD (Chair, University ofMinnesota); Anne Leserman, MSW, LISW, Stacie Vik, BA, ChristineAnderson, BA, Nick Doucette, BA, Kelly Herwig, BA, MS, Mycah Kimble,BA, Pat Ryan, MSW, LISW, MA, Jessica Schumacher, BA, Kelli Thumma,BA, and Elijah Waterman, BA (University of Iowa); and NormReynolds, MD (University of Wisconsin, Milwaukee).


Ethics: Cheryl Erwin, JD, PhD, (Chair, McGovern Center for Health,Humanities and the Human Spirit); Eric Epping, MD, PhD and JanetWilliams, PhD (University of Iowa); and Martha Nance, MD(University of Minnesota).

IT/Management: Hans Johnson, PhD (Chair), R.J. Connell, BS, PaulAllen, AASC, Sudharshan Reddy Bommu, MS, Karen Pease, BS, BenRogers, BA, BSCS, Jim Smith, AS, Kent Williams, BSA, MCS, MS, ShuhuaWu, MCS, and Roland Zschiegner (University of Iowa).

Program Management

Administrative: Chris Werling-Witkoske (Chair), Karla Anderson,BS, Kristine Bjork, BA, Ann Dudler, Stacey Jones, BS, Jamy Schumacher,Sean Thompson, BA (University of Iowa).

Financial: Steve Blanchard, MSHA (Co-Chair), Machelle Henne-berry, and Kelsey Montross, BA (University of Iowa).

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Cerebral cortex structure in prodromal Huntington disease