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NeuroImage 36 (2007) 691–699

Sex differences in regional gray matter in healthy individuals aged44–48 years: A voxel-based morphometric study

Xiaohua Chen,a,b,⁎ Perminder S. Sachdev,a,b Wei Wen,a,b and Kaarin J. Ansteyc

aSchool of Psychiatry, University of New South Wales, AustraliabNeuropsychiatric Institute, Prince of Wales Hospital, Sydney, AustraliacCentre for Mental Health Research, Australian National University, Canberra ACT, Australia

Received 23 January 2007; revised 28 March 2007; accepted 29 March 2007Available online 12 April 2007

The study examined sex-related differences in regional gray matter(GM) in 44–48 year old healthy individuals. T1-weighted MRI scanswere acquired in 411 subjects aged 44–48 from a random communitysample and optimized voxel-based morphometry was applied to detectregional GM difference between men and women, correcting foreffects of age, years of education, handedness, and total intracranialvolume (TIV). Men had larger brain volumes and higher whitematter (WM) to TIV ratios compared with women. Women hadhigher GM to TIV ratios than men. After controlling for age, years ofeducation, handedness, and TIV, there were no significant differencesbetween men and women in the total GM volumes. Regional sex di-morphism was present, with men having more GM volume in mid-brain, left inferior temporal gyrus, right occipital lingual gyrus, rightmiddle temporal gyrus, and both cerebellar hemispheres. Womenshowed more GM in dorsal anterior, posterior and ventral cingulatecortices, and right inferior parietal lobule. Our results suggest sexdimorphism in GM in middle aged healthy individuals, which is notlikely to be explained by brain pathology. These differences mayprovide the structural brain basis for sex differences in certain cognitivefunctions.© 2007 Elsevier Inc. All rights reserved.

Introduction

Sex-related variations in human brain structure have beenstudied broadly in a number of investigations (Breedlove, 1994;Good et al., 2001a; Kruggel, 2006; Swaab and Hofman, 1984). Themost consistent observation is that men have larger brain volumesthan women (Blatter et al., 1995; Kruggel, 2006; Luders et al.,2002; Peters, 1991; Skullerud, 1985; Swaab and Hofman, 1984).There are a number of studies showing sex-related differences inbrain compartments and particular brain structures, e.g., corpus

⁎ Corresponding author. Neuropsychiatric Institute, Euroa Centre, Princeof Wales Hospital, Barker Street, Randwick NSW 2031, Australia. Fax:+612 9382 3774.

E-mail address: xiaohua.chen@student.unsw.edu.au (X. Chen).Available online on ScienceDirect (www.sciencedirect.com).

1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.neuroimage.2007.03.063

callosum (Dubb et al., 2003), cingulate gyrus (Pujol et al., 2002),and parietal lobe (Nopoulos et al., 2000), which have notnecessarily been shown by other researchers(Carne et al., 2006;Going and Dixson, 1990). The discrepancy of sexual dimorphismin regional brain volumes may be due to various methodologicalissues, which include varying sample sizes, recruitment ofconvenience samples, confounding factors such as neurologicaldiseases, and differences in neuroimaging protocols and processingtechniques.

One important factor that contributes to this inconsistency isaging, with men and women having different age-related changesin the brain (Raz et al., 2004). It may be difficult to map sex-relatedmorphological differences within a cohort with a broad age range,due to a possible nonlinear concurrent effect of aging. Forexample, age was found to be associated with smaller GM volumesin a cross-sectional study whereas this change was not replicated inone year longitudinal observation of the same group (Resnick etal., 2000). Although there is substantial evidence to show sexdifferences in ageing (Coffey et al., 1998; Xu et al., 2000), otherstudies failed to replicate this finding in subjects in the seventh andeighth decades (Lemaitre et al., 2005; Resnick et al., 2003). Also,sex difference varied in different brain regions, e.g., largerfrontomedial cortex in men (Goldstein et al., 2001) and greaterdorsolateral prefrontal cortex in women (Schlaepfer et al., 1995).Another factor associated with this discrepancy would be thedifference in methodologies applied to morphologic studies, e.g.,conventional region-of-interests (ROI) analysis or voxel-basedmorphometry (VBM). VBM is a newly developed method(Ashburner and Friston, 2000), which applies voxel-wise compar-isons throughout the brain to detect regional gray matterabnormalities objectively. Methods of optimized VBM analysishave been developed which allow comparisons of brain structurevolumes without confounding effects from non-brain tissue (Goodet al., 2001b). These have been used in brain morphometric studiesof sex difference in various populations, but with various resultsshowing sex dimorphism in the cortical mantle, parahippocampigyri, cingulate gyrus, temporal lobe, entorhinal, pararhinal gyri andcerebellum (Good et al., 2001a).

Table 1Descriptive characteristics of men and women in the study

Variables Men (n=184) Women (n=227) Z/χ2 p value

Age (years) 46.66 (1.49) 46.73 (1.37) −0.594 0.553Education (years) 15.15 (2.17) 14.63 (2.31) −1.829 0.067Right-handed (%) 164 (89.1) 203 (89.4) 0.009 0.923Scanner A (%) 84 (45.7) 71 (31.3) 8.939 0.003*

Note. p values are for Mann–Whitney U test of age and education, chi-square tests of handedness, and scanner used between men and women,*pb0.05.

692 X. Chen et al. / NeuroImage 36 (2007) 691–699

The objective of the study was to investigate sex-related differ-ences in the brains of a large community dwelling cohort aged 44–48 years on a voxel by voxel basis. The narrow age range and mid-adulthood of the sample allow for the examination of adult brainslargely unaffected by aging or age-related pathology and thereforereflective of the sex differences in mature brains.

Materials and methods

Subjects

Subjects were sampled from the 40+ years old age group in thePATH Through Life Project, which is a longitudinal study of threecohorts aged 20–24, 40–44, and 60–64 years at first examination, allcomprising community residents recruited randomly throughelectoral rolls from the city of Canberra and the adjacent town ofQueanbeyan, Australia. Enrolment to vote is compulsory inAustralia. The cohorts are examined every 4 years, and this cohortwas in the age range 44–48 years at the time of current examination,which is Wave 2 of the study. A total of 2530 people were inter-viewed in Wave 2, of which 656 were randomly offered an MRI.Five hundred and three people accepted MRI and 431 (85.7%)eventually had an MRI scan. There were no differences in age, sex,and complete years of education between those had anMRI scan andthose who did not (pN0.05). Two scans were lost due to the technicalfault, thus giving a total number of 429 scans. The reasons for notundergoing an MRI scan after having initially agreed includedsubsequent withdrawal of consent, medical conditions contradictingMRI, and claustrophobia or other anxiety about the procedure. Age,sex, and years of education were recorded during the interview,among other variables. Handedness was assessed by EdinburghHandedness Inventory (Oldfield, 1971). The study was approved bythe ethics committees of the Australian National University,

Table 2A summary of various studies that examined sex differences in brain volumetrics

Study N Age (years) Total intracranialvolume (TIV)

Gray matter(GM)

Men Women Men

The current study 411 44–48 1.65 (0.12) 1.44 (0.11) 0.74 (0.05)Good et al. (2001a) 465 17–79 NA NA 0.829 (0.069)Luders et al. (2005) 60 24.32±4.35

(women)1.40 (0.11) 1.22 (0.09) 0.72 (0.05)

25.45±4.72(men)

Kruggel (2006) 290 18–32 1.62 (0.09) 1.49 (0.10) 0.71 (0.05)Lemaitre et al. (2005) 662 63–75 1.45 (0.10) 1.29 (0.10) 0.58 (0.04)

Note. Volumes are presented in liters for the purpose of comparison. Age is prese

Canberra and the University of New South Wales, Sydney,Australia.

MRI acquisition

MRI data were acquired on a 1.5 Tesla Gyroscan scanner (ACS-NT, Philips Medical Systems, Best, The Netherlands). T1-weighted3-D structuralMRI images were acquired in coronal plane using FastField Echo (FFE) sequence. About mid-way through this study, forreasons outside the researchers' control, the original scanner(scanner A) was replaced with a similar Philips scanner(scanner B). The scanning parameters were kept essentially thesame. The first 163 subjects were scanned on scanner A with TR=8.84 ms, TE=3.55 ms, a flip angle of 8°, matrix size=256×256,slices 160, and the field of view (FOV) 256×256 mm. Slices werecontiguous with slice thickness of 1.5 mm. For the remaining 268subjects scanned on scanner B, the TR=8.93 ms, TE=3.57 msvalues were slightly different in order to improve image quality, butall other parameters were exactly the same. To ensure the reliabilityand compatibility of the data, we compared the subjects scanned onthe two scanners on sociodemographic and imaging parameters.There were no differences on age (p=0.377), years of education (p=0.588), but more women were inadvertently scanned on scanner Bthan A (p=0.003). The volumetric measures of total intracranialvolume (TIV), gray matter (GM) volume, white matter (WM) vo-lume, or cerebrospinal fluid (CSF) volume obtained from twoscanners did not differ significantly (see Appendix A). For mor-phometric analyses, all subjects were considered together.

Voxel-based morphometry

Optimized voxel-based morphometry (VBM) analysis (Good etal., 2001b) was applied using SPM2 (Wellcome Department ofCognitive Neurology, Institute of Neurology, London, UK) onMatlab 6.5 (Math Works, Natick, MA, USA). All imaging analyseswere performed on a Windows 2000 workstation. Before VBManalysis, all the scans were inspected and 411 scans were selectedinto the present study. Reasons for exclusion of the images werepredominant brain abnormalities (n=12), artifacts such as headmovement during the acquisition (n=1), unsatisfactory tissue seg-mentation due to insufficient gray/white tissue differentiation and/orlow signal to noise ratio (n=4), and incomplete data available forfactors being studied (n=1). Subjects included were not different inage, sex, handedness, scanners, or TIV as compared with thoseexcluded, but they had more years of education (p=0.006).

White matter(WM)

Cerebrospinal fluid(CSF)

Women Men Women Men Women

0.67 (0.05) 0.50 (0.05) 0.43 (0.04) 0.41 (0.05) 0.35 (0.05)0.747 (0.064) 0.454 (0.044) 0.395 (0.041) 0.397 (0.04) 0.401 (0.048)0.64 (0.05) 0.55 (0.06) 0.47 (0.05) 0.13 (0.02) 0.11 (0.02)

0.67 (0.05) 0.70 (0.07) 0.64 (0.07) 0.18 (0.03) 0.18 (0.03)0.53 (0.04) 0.49 (0.05) 0.43 (0.04) 0.39 (0.05) 0.33 (0.05)

nted in the forms as shown in papers.

Table 3Global volumetric measures in men and women

Men (n=184) Women (n=227) df t/F p

Total intracranial volume (TIV) 1647.16 (124.61) 1441.80 (113.76) 409 17.436 b0.001Gray matter (GM)

Raw volumes (ml) 741.35 (53.32) 666.54 (47.55) 409 15.018 b0.001Ratios to TIV 0.45 (0.02) 0.46 (0.02) 409 −6.947 b0.001Adjusted volumes a (ml) 700.32 (2.23) 699.80 (1.95) 1 0.023 0.879

White matter (WM)Raw volumes (ml) 496.20 (49.96) 425.30 (40.35) 409 15.918 b0.001Ratios to TIV 0.30 (0.01) 0.29 (0.01) 409 4.365 b0.001Adjusted volumesa (ml) 457.96 (1.92) 456.30 (1.68) 1 0.332 0.565GM/WM ratio 1.50 (0.10) 1.57 (0.10) 409 −7.370 b0.001

Cerebrospinal fluid (CSF)Raw volumes (ml) 409.61 (48.00) 349.96 (49.37) 409 12.332 b0.001Ratios to TIV 0.25 (0.02) 0.24 (0.02) 409 2.955 0.022Adjusted volumesa (ml) 375.47 (2.91) 377.64 (2.54) 1 0.247 0.619a Volumes were compared between men and women by ANCOVA, adjusting for age, handedness, years of education, scanner, and TIV.

Table 4Regions of sex differences in gray matter volume using VBM analysis

Comparisons Regions Coordinates(mm)

p(corrected)

tvalue

x y z

MenNwomen Midbrain −3 −13 −10 0.000 6.71Left inferiortemporal gyrus

−34 −1 −45 0.000 6.62

Right lingual gyrus 14 −81 −1 0.000 6.42Right middletemporal gyrus

39 4 −44 0.000 6.07

Right cerebellum 17 −60 −52 0.000 6.70Left cerebellum −32 −42 −47 0.000 5.96

−21 −54 −65 0.000 5.94WomenNmen Posterior cingulate,

dorsal part−2 −15 45 0.000 6.48

anterior cingulate,dorsal part

−1 4 46 0.000 5.81

Left cingulate gyrus −6 −2 41 0.000 5.76Right inferiorparietal lobule

43 −50 54 0.000 5.65

Note. x, y, z are the coordinates of significant voxels in stereotactic space.t-values were significant values set at pb0.001, corrected for multiplecomparison, testing for greater or smaller grey matter volume within avoxel.

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The detailed procedures for optimized VBM have beenpreviously reported (Good et al., 2001b) and there is a specialtoolbox available (http://dbm.neuro.uni-jena.de/vbm/vbm2-for-spm2). Images were corrected for intensity inhomogeneities byfunctions implemented in SPM. In brief, a customized template wasfirstly created from all included images, during which T1-weightedimages were spatially normalized by applying a 12-parameter affinetransformation to a SPM T1 template, then averaged and smoothedwith an 8-mm full-width half maximum (FWHM) smoothing kernel.Secondly, the T1-weighted MRI images were spatially normalizedwith a 12-parameter affine linear transformation into the newtemplate and subsequently priors of gray matter were obtained.Thirdly, raw structural images were segmented into gray matter,white matter, and cerebrospinal fluid partitions in original space. Thetotal GM volumes, WM volumes, and CSF volumes were computedby adding the GM, WM, and CSF segments of images in nativespace for each participant's image. TIV was sum of total GM, WM,and CSF volumes. The gray matter template previously generatedwas used in original gray matter partitions to normalize them bothlinearly and nonlinearly, with optimal normalization parametersestimated, which were reapplied back to the original raw images tomake whole brain images in stereotactic space. These optimallynormalized images were segmented again to make gray matterpartitions, which were modulated, i.e., by multiplying voxel valueswith the Jacobian determinants derived from spatial normalization,to obtain absolute volume of gray matter (Good et al., 2001b).Finally, to satisfy the Gaussian distribution assumption for statisticalanalysis to test regional differences, gray matter images weresmoothed with a 12-mm FWHM Gaussian kernel.

Statistical analysis

In order to compare our results with others, total raw gray mattervolumes as well as their ratios to total intracranial volumes werecompared between men and women by independent t tests.Compartmental volumes were also compared, after controlling foreffects of handedness, age, education years, and by using ANCOVAmodels. Although different scanners appeared to have no effect onbrain volumes, it was included in the model as a covariate.

Regional gray matter volume differences were detected byapplying a general linear model to form statistical parametricmaps, in which statistical significances were tested on a voxel

by voxel basis. Specifically, an ANCOVA analysis was per-formed for men and women, with age, handedness, years ofeducation, scanner difference, and total intracranial volume(TIV) included as covariates. To locate significant regions,statistical threshold was set at pb0.001 with family-wise cor-rection for multiple comparisons. Significant coordinates weretransferred to Talairach coordinates (http://imaging.mrc-cbu.cam.ac.uk/imaging/MniTalairach) and anatomical localizations weredetermined by the Talairach Daemon (Lancaster et al., 2000).

Result

Global volumetric measures

Demographic characteristics of the study sample are presentedin Table 1. Global measures were compared between our sample

694 X. Chen et al. / NeuroImage 36 (2007) 691–699

and comparable studies in Table 2. Comparisons of global volu-metric measures between men and women are shown in Table 3.Men had larger raw volumes of GM, WM, and CSF than women

Fig. 1. SPM (T) map showing regions in which more gray matter volumes in m+23 mm, with 5 mm interval, in a single male subject's normalized T1-weighted imfrom z=+ 26 mm to z=+62 mm, with 2 mm interval, in a single female subject'years of education, scanner difference, and total intracranial volume (TIV). Thecorrected.

while women had higher ratio of GM and smaller ratios of WMand CSF to TIV. However, there were no significant differencewhen comparing volumes adjusted by age, handedness, and total

en than in women superimposed on coronal slices from y=87 mm to y=age (A) and more gray matter volumes in women than in men on axial slicess normalized T1-weighted image (B), after controlling for age, handedness,color bar represents the t value thresholded at pb0.001, family-wise error

Fig. 1 (continued).

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years of education, scanner A or B, and TIV. In the multipleregression analysis, age, handedness, years of education, andscanner A or B were all non-significant contributors to the varianceof GM across all subjects. There were no interaction effectsbetween sex and age, and sex and years of education.

Regional abnormalities in GM

VBM results of GM are presented in Table 4 and Fig. 1. Thevoxel-wise difference in GM could not be explained by educationalyears, handedness, or age. The effect of global volumes was re-

696 X. Chen et al. / NeuroImage 36 (2007) 691–699

moved by including TIVas a covariate in the general linear model forVBM analysis. Scanner effect was controlled in the same way. Menshowed more GM in midbrain, left inferior temporal gyrus (BA 20),right occipital lingual gyrus (BA 18), right middle temporal gyrus(BA 20), and bilateral cerebellar hemispheres. Women showedmoreGM in posterior cingulate cortex, dorsal part (BA 31), anteriorcingulate cortex, dorsal part (BA 32), left cingulate gyrus (BA 24),and right inferior parietal lobule (BA 40). The effect of age and itsinteraction with sex on brain MRI measures were also examined.There were no significant relationships with volumetric measures orregional GMvariations in relation to age or any sex–age interactions.

Discussion

The study explored sex difference in global and regional brainvolumes in a healthy community cohort within a limited range ofage. Men had higher values than women in all raw volume cal-culations. They differed in compartmental ratios, for which men hadhigher WM to TIV ratios and women had higher GM to TIV ratios.Our results demonstrated a sex dimorphism in regional GM, withmen showing more GM in multiple brain regions, in particular thetemporal and occipital gyri, midbrain, and cerebellum. Womenshowed more GM than men mostly in the cingulate cortex and rightinferior parietal lobule.

Global volumes

The volumetric measures of GM and WM in the study arecompatible with other studies as shown in Table 2, with the exceptionof CSF, which was higher in this study and one VBM study (Good etal., 2001a). Brain tissue volumes, including GM and WM, wererelatively consistent while CSF varied across different studies. Thismay be mostly due to differences in methodology relating to theprocedure of segmentation of brain tissue. Our study and that ofGood et al. (2001a) applied SPM for segmentation of GM,WM, andCSF, in which CSF might be overestimated. Although using SPM,Lemaitre et al. (2005) applied an extra step to optimize segmentationof CSF by adding information derived from T2-weighted images,giving smaller values compared to CSF volumes obtained by T1-weighted images only. It should be noted that comparisons of threealgorisms of automatic segmentation suggested that SPM2 providesbest result for CSF segmentation in terms of misclassification rate(Zaidi et al., 2006). Also, differences in defining CSFmay contributeto the variation of CSF data from the literature. Luders et al. (2005)excluded extra-cortical CSF in calculating imaging volumes, whichmay partly explain the discrepancies of the data. Another factorshould be borne in mind for the variance of global measures is theage of study population. For example, Kruggel (2006) comparedglobal volumes between young men and women aged 18–32, whohad relatively less CSF than participants, all of whom aged 44–48 years, in our study. This is consistent with the evidence thatabsolute CSF volume is increasing with age not only in later life butalso in early adulthood (Courchesne et al., 2000).

As was shown in Table 3, global measures in our study replicatedprevious findings of sex differences in brain compartments (Allen etal., 2003; Filipek et al., 1994; Kruggel, 2006; Passe et al., 1997),although conflicting reports exist (Nopoulos et al., 2000; Schlaepferet al., 1995). It is well established that men have larger brains thanwomen, as seen in MRI studies (Gur et al., 2002a) as well as apostmortem reports (Dekaban, 1978). GM/WM ratio is also higher inwomen than in men (Allen et al., 2003), which is consistent with the

result of higher relative GM in women andWM in men in this study.Previous research of sex differences in fractional volumes has notbeen consistent, e.g., fractional GMwas reported to be higher in men(Good et al., 2001a; Sullivan et al., 2004) or women (Gur et al., 1999;Kruggel, 2006) by different authors. Brain tissue volume ratios varywith age. It is known that GM and WM grow in an asynchronousmanner in adolescence (Courchesne et al., 2000), and decrease by adifferent slope with aging in the two sexes (Jernigan et al., 2001).The hypothesis for sex dimorphism is that in women, a smaller skullsize is compensated during development by a relative increase in thesomatodentritic tissue necessary for processing of information,rather than connecting axons for transportation of information (Guret al., 1999).

Regional GM volumes

Sex differences in certain brain regions have been reported inprevious volumetric studies. Men were shown as having largerabsolute regional GM volumes, e.g., bilateral frontal, temporal, orleft parietal lobes (Carne et al., 2006).Men have also been reported tohave larger hippocampal formation (Raz et al., 1997), frontomedialcortex, amygdala, and angular gyrus (Goldstein et al., 2001) thanwomen. While taking skull size into account, sex differences werenot shown in several regions including dorsolateral prefrontal cortex,somatosensory cortex, and hippocampal formation. In a volumetricstudy of hippocampus in adults aged 60–64, hippocampus volumewas found larger in men thanwomen, but the opposite was true whentotal intracranial volume was controlled for (Maller et al., 2006).Regional higher GM volumes, e.g., amygdala, hippocampi,entorhinal perirhinal cortex, left anterior temporal gyrus, were foundin men by another VBM study as well (Good et al., 2001a). Previousstudies, either ROI-based or VBM-based, jointly presented evidenceof sex dimorphism, while giving different details.

In our study, regional sex dimorphism was seen bilaterally in thetemporal lobes, with men having more GM than women. Results ofprevious volumetric ROI studies of temporo-limbic structures havenot been consistent. Men had larger inferior temporal cortex,hippocampus, and parahippocampal gyrus (Raz et al., 2004), but nodifference in amygdala and hippocampus volumes in another study(Gur et al., 2002a). Inferior temporal cortex, however, was reportedto be more vulnerable to shrinkage with aging in men than inwomen (Raz et al., 2004), suggesting effects of sex–age interactionin this region. Therefore, studies of sex difference in this region maygive inconsistent results if aging effects are not appropriately con-trolled for. Our results, however, strengthened by the large studypopulation younger than 50 years old and correcting for the smallage range, largely overcomes the error introduced by aging. Al-though the exact biological explanation for these findings is unclear,genetics may be one important factor that affects human temporallobe morphometry. Volumetric studies in patients with Turner syn-drome (46, X) showed enlarged temporal lobe (Rae et al., 2004) anddecreased GM in temporal gyri in Klinefelter syndrome (47, XXY)(Patwardhan et al., 2000), suggesting effects of X chromosome ontemporal volume, which might allude to the mechanism of sexdimorphism in temporal cortex.

It has been widely documented that women have higher regionalGM volumes than men in various structures. Our study replicatedprevious findings in cingulate (Paus et al., 1996) and inferiorparietal lobe (Nopoulos et al., 2000), but not in the superior tem-poral cortex (Harasty et al., 1997), caudate and thalamic nuclei(Murphy et al., 1996), or dorsolateral prefrontal cortex (Schlaepfer

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et al., 1995), which are believed to be related to sex dimorphism inlanguage and visuospatial function (Schlaepfer et al., 1995). How-ever, a positron emission topography (PET) study showed higherglucose metabolism in temporo-limbic region and lower in cingu-late regions in men than in women, suggesting functional correlatesof sex dimorphism that are consistent with our results. In addition,more GM was demonstrated in women than men in the perisylvianright temporal cortices (Van Laere and Dierckx, 2001), orbitalfrontal cortices (Gur et al., 2002a) and even wider area in temporal,frontal and parietal lobes in another VBM study (Good et al.,2001a). Women showed widespread increased regional corticalthickness of GM and larger quantity of gyrification and fissurationof the brain surface than men in a young cohort (Luders et al., 2004,2006).

Sex dimorphism, aging, and other factors

Brain volume changes over time, with about 50% of its variancebeing explained by age. Given that aging probably affects the brainin a nonlinear fashion (Allen et al., 2005; Walhovd et al., 2005), thiswill confound the sex differences in a cohort with a wide age range.If examined in the elderly, sexual difference in volumetric measuresof the brain is prone to be affected by lesions that are prevalent in oldage, e.g., lacunes and white matter hyperintensities. In the currentstudy, we performed the investigations in a community-dwellingcohort within a narrow age band. Besides, in our study global as wellas voxel wise comparisons of brain volumes did not show anydifferences in association with age or any age-sex interactions,unlike what has been reported by some researches (Cowell et al.,1994; Gur et al., 1999; Murphy et al., 1996). Furthermore, the cohortis in the forties, which is widely believed to be earlier than the age ofconsiderable decline in brain volume. Previous studies suggestedthat total brain volumes change slightly before age 50 butsubstantially afterwards (DeCarli et al., 2005; Pfefferbaum et al.,1994). We therefore consider this to be a suitable sample to examinesex differences and as far as we know, this is the first studyaddressing sex differences in brain morphometry in a middle-agedpopulation using the VBM method.

Sex dimorphism in GM is subject to the influence of variousfactors. There is substantial evidence showing that age-relatedbrain decline is sex- and region-specific, although the results areinconsistent. Sex differences of brain volumes loss with ageingwere not detected in a longitudinal study (Tang et al., 2001), aswell as a cross-sectional study (Raz et al., 2003). When regionalbrain volumes were examined, men showed a steeper volume lossin frontal and temporal lobes (Murphy et al., 1996), and the globuspallidus (Gunning-Dixon et al., 1998), with relatively stablehippocampus and parietal lobes volumes (Murphy et al., 1996), butnot all reports were consistent with these findings (Raz et al., 2004;Xu et al., 2000). Also, men had a stronger correlation between ageand decrease in GM of dorsolateral prefrontal cortices than women(Gur et al., 2002b). Contrastingly, women showed steeper age-related decline in the caudate and the effect was stronger in theright rather than the left hemisphere, a finding opposite to that inmen (Gunning-Dixon et al., 1998). No significant sex differencewas found in other regions longitudinally (Raz et al., 2005). Also,higher education was found to be associated with ageing-relatedincreasing peripheral CSF in an elderly community population(Coffey et al., 1999). When these factors were controlled in ourstudy, men and women had significant difference in regional butnot global GM, WM, and CSF volumes. It is not yet known if sex

affects brain volumes through its interactions with other factors,which was not examined in the present study. Vascular risk factorsmay also play a role in sex dimorphism of regional GM in brain, ashas previously been reported (Chen et al., 2006; Taki et al., 2004).

Limitations

There are some limitations to our study which need to beconsidered when interpreting the results. First, effects of vascularfactors were not controlled in the study, although confoundingeffects due to these factors were minimal in this relatively youngcohort. Second, two different scanners were used in the study, eventhough the same scanning parameters were used and there were nodifferences between subjects in age, education, handedness, orglobal volumetric measures when the results from the two scannerswere compared. There is evidence to show that the reliability ofMRI across centers with different scanners, hardware, andparameters is relatively good, especially for large sample size(Ewers et al., 2006). Additionally, scanner effect was controlledstatistically in the study. Therefore, scanner effect seems not likelyto have affected the current results. Third, VBM analysis offers anapproximation of the biological structural changes in brainstructure. Further details in microstructure, as well as its relationto behavioral characteristics in men and women, are needed for theultimate understanding of sex dimorphism.

Conclusion

This study explored sex-related differences in global as well asregional GM in a representative middle-aged population within alimited range of age by applying a voxel-wise morphometricanalysis. Sex dimorphism in GM was observed regionally but notglobally if controlling for age, handedness, education, and TIV.Menshowed more GM in many discrete regions distributed in temporal,occipital, brain stem, and cerebellum, while women showed moreGM mainly in limbic associated regions, e.g., cingulate cortex. Ourresults suggest that sex dimorphism appears to exist independent ofaging or age-related pathology. However, the causes of thesevariations are not well understood and await further research.

Acknowledgments

This study was supported by Project Grant ID 157125 andProgram Grant 179805 from the National Health and MedicalResearch Council (NHMRC) of Australia. We wish to thank thefollowing for their contribution to the PATH Through Life Project:Helen Christensen, Anthony F Jorm, June Cullen, Trish Jacomb,Rajeev Kumar, Jerome Maller, Karen Maxwell, Chantal Meslin,Jeremy Price, Bryan Rodgers, and the PATH Interviewing Team.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.neuroimage.2007.03.063.

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