Morphometric Brain Abnormalities in Schizophrenia in a Population-Based Sample: Relationship to Duration of Illness

Morphometric Brain Abnormalities in Schizophrenia in a Population-Based Sample:Relationship to Duration of Illness

Paivikki Tanskanen1,2,9, Khanum Ridler3,4,9, GrahamK. Murray4, Marianne Haapea2,5, Juha M. Veijola5,6,Erika Jaaskelainen5, Jouko Miettunen5, Peter B. Jones8,Edward T. Bullmore4, and Matti K. Isohanni5,7

2Department of Diagnostic Radiology, University of Oulu, FIN-90029 OYS, Oulu, Finland; 3GlaxoSmithKline Clinical ImagingCentre, Imperial College London, Hammersmith Hospital, DuCane Road, London W12 0NN, UK; 4Brain Mapping Unit, De-partment of Psychiatry, Addenbrooke’s Hospital, University ofCambridge,CambridgeCB22QQ,UK; 5DepartmentofPsychiatry,University of Oulu, FIN-90014 Oulu, Finland; 6Academy ofFinland, PL 99, FIN-00501Helsinki, Finland; 7University of Oulu,Department of Public Health Science and General Practice, FIN-90014 Oulu, Finland; 8Department of Psychiatry, University ofCambridge, Addenbrooke’s Hospital, Cambridge CB2 2QQ, UK

9These authors contributed equally to this work.

Biased recruitment and sample selection may cause vari-ability in neuroimaging studies. Epidemiologically princi-pled population-based magnetic resonance imaging(MRI) studies of schizophrenia are very rare. We gatheredstructural MRI data on 154 subjects from the NorthernFinland 1966 Birth Cohort, aged 33–35 (100 controls,54 schizophrenia patients). Regional differences in densityof gray matter, white matter, and cerebrospinal fluid (CSF)were identified between groups using nonparametric statis-tical analysis, and the relationship of the regional differen-ces to duration of illness was explored. Gray matterreductions were found bilaterally in the cerebellum, thala-mus, basal ganglia, middle frontal gyrus, inferior frontalgyrus, precentral gyrus, insula, superior temporal gyrus, fu-siform gyrus, parahippocampal gyrus, cuneus, and lingualgyrus; in the left posterior cingulate, superior frontal gyrus,transverse temporal gyrus, and precuneus; and in the rightpostcentral gyrus. Gray matter excesses were observedbilaterally in the basal ganglia, anterior cingulate, and me-dial orbitofrontal cortices. There were white matter deficitsin an extensive network including inter- and intrahemi-spheric tracts bilaterally in the frontal, temporal, parietal,and occipital lobes, subcortical structures, cerebellum, andbrain stem. CSF excesses were found bilaterally in the lat-

eral ventricles, third ventricle, interhemispheric, and leftSylvian fissure. We replicated the previous findings ofstructural brain abnormalities in schizophrenia on a generalpopulation level. Gray and white matter deficits were asso-ciated with duration of illness suggesting either that devel-opmental brain deficits relate to an earlier age of onset orthat brain abnormalities in schizophrenia are progressive innature.

Key words: schizophrenia/magnetic resonance imaging/birth cohort/gray matter/white matter/voxel-basedmorphometry

Introduction

A variety of structural brain abnormalities have beendocumented in schizophrenia in magnetic resonance im-aging (MRI) studies. The most consistent findings in pre-vious region of interest (ROI) studies have beenenlargement of lateral and third ventricles and corticalsulci and volume reductions in temporal and frontallobes.1–4 Consistent with these findings, newer, voxel-based morphometry (VBM) schizophrenia studies havefrequently reported regional differences in parts of thefrontal and temporal lobes.5–10 In all, 50% of studiesin the meta-analysis by Honea et al11 reported gray mat-ter deficits in schizophrenia in the left medial temporallobe; superior temporal, parahippocampal, inferior,and medial frontal gyri; and in the right superior tempo-ral gyrus. Reductions in other lobes have also beenreported, although less often.11

However, there has been considerable variability inresults of schizophrenia MRI studies. A number of fac-tors may contribute to this variability, including differen-ces in analysis methods, variability in the disorder itself,and also due to variations in sampling selection and re-cruitment biases concerning both patient and controlsamples.11,12 Most imaging studies have drawn nonran-dom samples, which can constrain generalizability of theirfindings.13,14 Many studies consist of chronic or hospital-ized patients, with a disproportionate number of severecases with long duration of illness and heavy antipsy-chotic drug exposure. Such patients may have more prom-inent cerebral abnormalities. Population-based studies are

1To whom correspondence should be addressed; tel: þ358-8-315-5367, fax: þ358-8-315-5455, e-mail: [email protected].

Schizophrenia Bulletindoi:10.1093/schbul/sbn141

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more robust to recruitment biases than other researchmethodologies; thus, as Lawrie and Abukmeil4 andGlahnet al15 have previously argued, there is a clear rationale forpopulation-based neuroimaging studies in schizophrenia.As far as we are aware, only one previous population-based sample, a Helsinki birth cohort, has reportedcase-control structural brain results in schizophrenia:Cannon et al16 reported significant reductions in corticalgrayandwhitemattervolumeandsignificantincreasesinsul-cal cerebrospinal fluid (CSF)volumeespecially in the frontaland temporal lobes in their ROI study in schizophrenia.

Whether structural brain abnormalities in schizophre-nia are progressive in nature or not remains unclear.Some studies suggest that there are morphometric brainabnormalities even before the illness onset17 or at the on-set in first-episode patients,6,18–21 and there is evidencethat at least some of the schizophrenic brain abnormal-ities are developmental in nature.22,23 Nevertheless, somelongitudinal studies suggest progressive changes in thedisorder,20,24–29 and increased duration of illness hasbeen associated with reduced gray matter in frontotem-poral regions.30,31

We investigated if morphometric brain abnormalitieswould exist in a truly representative sample of patientswith schizophrenia and determined the regional grayand white matter and CSF differences in schizophreniain relation to nonpsychotic general population controlsubjects using brain activation and morphological map-ping (BAMM) software to perform BAMM-VBM,a VBM style analysis. Furthermore, we investigatedthe relationship between brain structure and durationof illness within the group of patients with schizophrenia.

Materials and Methods

The Northern Finland 1966 Birth Cohort

The Northern Finland 1966 Birth Cohort of 12 058 live-born children (96% of those eligible) is an unselected, gen-eral population cohort ascertained duringmid-pregnancyin the provinces of Lapland and Oulu with an expecteddate of birth during 1966.32 The great majority of the co-hort members are Finns (white Caucasians), with lessthan 1% being Roma people and Lapps.33 The presentstudy is based on 11 017 individuals who were living inFinland at the age of 16 years. Of these, 83 denied theuse of their data, resulting in 10 934 subjects. Permissionto gather data was obtained from the Ministry of Socialand Health Affairs, and the study design has been ap-proved by and is under review of the Ethical Committeeof the Northern Ostrobothnia Hospital District. The‘‘Materials and Methods’’ section is described in detailby Isohanni et al,34 Ridler et al,23 and Tanskanen et al.35

Ascertainment and Sampling of People With Psychosis

The Finnish Hospital Discharge Register (FHDR) wasused to identify cohort members with psychosis. All co-

hortmembers over 16 years appearing on the FHDRuntil1997 for any mental disorder (ICD-8 (International Clas-sification of Diseases) 290–309, ICD-9 290–316, andICD-10 Foo-F69, F99) were identified. Case recordswere scrutinized, and diagnoses were validated using Di-agnostic and Statistical Manual of Mental Disorders,Third Edition Revised (DSM-III-R) criteria.36,37 Onehundred and forty-six living subjects (84men) were foundtohave a historyof a psychotic episode andwere invited toparticipate the present study; 92 (63%, 52 men) attendedand gavewritten informed consent. Three subjects did notfulfill the criteria of psychosis. Two subjects were ex-cluded after MRI scan due to structural lesions (hydro-cephalus). Altogether 87 participants (49 men) witha history of psychosis were sampled, of whom 61 people(36men)metDSM-III-R criteria for schizophrenia.Otherpsychoses (n = 26) consisting of bipolar disorder, schizo-affective disorder, schizophreniform psychosis, and otherforms of psychosis including delusional disorders werenot included in the sample for analysis.The control subjects without a psychotic episode were

randomly selected from the cohort members living inOulu area. In total, 187 control subjects were invited;104 (62 men) consented to participate. There was no ma-jor demographic difference between participating andnonparticipating subsets of nonpsychotic subjects.Subjects who did not consent to imaging or had images

of inadequate quality were excluded from the analysis(7 schizophrenia patients, 4 controls). Adequate MRIscans were obtained from 54 schizophrenia subjects (33men) and100 control subjects (60men). Three schizophre-nia subjectswerehospitalizedat the timeof scanning(therewasmissingdata concerninghospitalizationof2patients).

Duration of Illness

The onset of illness was ascertained frommedical recordsand defined as the age when having the first evident psy-chotic symptoms.38 Duration of illness was calculated inyears by deducting the age at onset of illness from the ageat the date of MRI.The age at onset of illness did not differ between the

participants (n = 54, mean 23.1 years [SD 4.3]) and non-participants with schizophrenia (n = 40, mean 21.8 years[SD 4.1]). The hospital treatment periods of nonpartici-pants were longer (median 378 days) than those of par-ticipants (167 days).13,35

Antipsychotic Medication and Urine Drug Screen

During the 3-month period prior to scanning, 20 subjectswith schizophrenia were taking atypical antipsychoticmedication and 26 subjects typical antipsychotic medica-tion. Seven of them had taken both atypical and typicalmedication. Fourteen subjects had not taken antipsy-chotic medication (there was missing data concerningthe medication status of 1 patient).

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An analysis of urine drug screen was performed on allsubjects at the time of scanning. One subject with schizo-phrenia tested positive for methadone and 1 for opiates.Two control subjects tested positive for opiates. Nopatients or controls tested positive for cannabis, cocaine,or amphetamine.

Image Acquisition, Image Analysis, and Data Processing

MRIwas conducted in 1999–2001when participants wereaged 33–35 years. Data were acquired using a GE Signasystem (General Electric, Milwaukee, WI) operating at1.5 T in Oulu University Hospital, Finland. Dual echofast spin echo (T2 and proton density (PD) weighted)images of the whole brain were acquired in the coronalplane with slice thickness = 3 mm, repetition time (TR)= 4000ms, and echo time (TE) = 24 and 96ms. All subjectswere scannedon the samescannerusing the sameprotocol.The MRI data were segmented and probabilistic maps

of gray matter, white matter, and CSF were created foreach subject by using BAMM software.39,40 Voxels rep-resenting extracerebral tissue were automatically iden-tified and set to 0 using a linear scale-space set offeatures obtained from derivatives of the Gaussian ker-nel.41 Manual editing of the segmented images was nec-essary only to remove the brain stem below a line parallelto the base of cerebellum. The probability of each intra-cerebral voxel belonging to each of 4 possible tissue clas-ses (gray matter, white matter, CSF, or dura/vasculature)was then estimated by a modified fuzzy clustering algo-rithm in the 2-dimensional feature space formed by thePD and T2 intensities.40 The coronal in-plane voxelsize was 0.86 3 0.86 mm2. Total brain, gray matter, whitematter, and CSF volumes in milliliters were calculatedfrom segmented images in native space.Tissue classification maps were resliced in the axial ori-

entation and coregistered with a customized template im-age in standard stereotactic space42 by using an affinetransformation and trilinear interpolation implementedin FSL (FMRIB Software Library) software.43–45 Theseprocedures resulted in maps of the density of gray matter,white matter, and CSF at each voxel; density is here de-fined as the probability that a voxel represents tissue ofa particular class.40,46

Transformed images were smoothed with a standard4-mm full-width half-maximum kernel.40 Voxel-level sta-tistic maps, representing group differences in density ingray matter, white matter, or CSF maps, were testedfor statistical significance by using a nonparametric per-mutation test of the mass or sum of suprathreshold voxelclusters. For whole-brain maps, the size of each cluster-wise test was set such that the expected number of false-positive tests in each map was <1: for gray and whitematter maps, clusterwise P < .003. T tests at each voxelwere performed and measured against the null distribu-tion calculated from permutations of the original data setand thresholded at P < .05 to form spatially contiguous

clusters of suprathreshold voxels. The cluster statisticswere then performed on this data such that the total t sta-tistic from each of these suprathreshold regions is calcu-lated and a new null distribution is created from thepermuted thresholded data and then statistically thresh-olded at the defined error clusters per image, based ona false discovery rate theory of statistical inference.47

We analyzed the relationship between duration of ill-ness and total brain, gray matter, white matter, and CSFvolumes in patients using correlation analysis. Further-more, having established areas where brain structure dif-fered in patients with schizophrenia and controls in thisdata set, we investigated the correlation between tissuedensity in those regions and duration of illness.

Results

Analyses of Whole-Brain Volume, Total Gray MatterVolume, Total White Matter Volume, and Total CSFVolume

In analyses without controlling for total intracranial vol-ume (ICV), there were no significant between-group dif-ferences in whole-brain volume (�2.4%: schizophrenia1266 6 120 ml, controls 1297 6 117 ml [2-sample ttest, df = 152, t = 1.55, P = .123]), gray matter volume(�2.2%: schizophrenia 682 6 58 ml, controls 697 6 57ml [t = 1.50, P = .136]), white matter volume (�2.7%:schizophrenia 584 6 67 ml, controls 600 6 66 ml [t =1.46, P = .146]), or CSF volume (þ6.5%: schizophrenia196 6 41 ml, controls 184 6 35 ml [t = �1.85, P =.066]). After controlling for ICV, between-group differ-ences in whole-brain volume (univariate analysis of var-iance, total df = 153, F = 8.20, P = .005) and total CSFvolume (F = 8.20, P = .005) were significant, and therewere trends toward significant differences in total graymatter volume (F = 3.44, P = .066) and total white mattervolume (F = 3.10, P = .080).

Regional Differences in Gray Matter

Significant gray matter density deficits were identified inpatients with schizophrenia in 7 large clusters (table 1).As several clusters span different regions, the resultsare also depicted graphically (figure 1); purple andblue regions denote areas of gray matter deficit; redand yellow regions denote areas of gray matter excessin subjects with schizophrenia relative to the controls.The left side of each panel represents the right side ofthe brain; the z coordinate for each axial slice in the stan-dard space of Talairach and Tournoux42 is given in milli-meters. Clusterwise probability of type 1 error: P = .003,at this size of test less than 1 false-positive test wasexpected over the whole map.Regional gray matter density deficits were found

bilaterally in the cerebellum, brain stem, hypothalamus,thalamus, claustrum, middle frontal gyrus, inferior fron-tal gyrus, precentral gyrus, insula, superior temporal gy-

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rus, fusiform gyrus, parahippocampal gyrus, cuneus, andlingual gyrus; in the left putamen, posterior cingulate, su-perior frontal gyrus, transverse temporal gyrus, precu-neus, and in the right caudate and postcentral gyrus.Overall within these regions, gray matter density was re-duced by 7% in subjects with schizophrenia (2-samplet test, t = 7.990, df = 152, P < .001).

Significant gray matter density excesses in subjectswith schizophrenia (figure 1) were found bilaterally inthe caudate, anterior cingulate, and medial orbitofrontalcortex and in the left putamen and pallidus; density inthese regions was increased by 10% (t = �7.385, df =152, P < .00001).

Regional Differences in White Matter

Significant white matter density deficits were identifiedin subjects with schizophrenia (figure 2) bilaterally in thecerebellum, brain stem, corpus callosum, capsula inter-

na, corona radiata, centrum semiovale, subgyral frontalwhite matter, inferior frontal gyrus, medial frontal gy-rus, middle frontal gyrus, cingulate, subgyral temporalwhite matter, superior temporal gyrus, parahippocam-pal gyrus, and subgyral parietal white matter; in theleft capsula externa and cuneus; and in the right middletemporal gyrus, transverse temporal gyrus, supramargi-nal gyrus, and inferior parietal lobule. Density in theseregions was decreased by 7% (t = 8.297, df = 152, P <.00001).

Regional Differences in CSF

Significant CSF density excesses were identified inpatients with schizophrenia, relative to control subjects(figure 3) bilaterally in the lateral ventricles, third ventri-cle, frontal interhemispheric fissure, and left Sylvian fis-sure. These regions were increased by 13% (t = �5.078,df = 152, P < .00001). A small region of significant

Table 1. Coordinates of theCenter ofMassof the 7Clusters inWhichWeDetectedDeficits inSchizophreniaRelative to theControlGroup

Region X Y Z Maximum z Minimum z Voxels

Cerebellum 9 �45 �14 �8 �24 489

Left insula (BA13) �39 4 1 16 �24 884

Right precentral gyrus (BA44) 44 9 7 35 �16 902

Thalamus 2 �13 2 20 �12 1065

Left middle frontal gyrus (BA10) �32 51 11 35 �4 446

Posterior cingulate gyrus (BA31) �4 �63 14 35 4 440

Left inferior frontal gyrus (BA45) �46 16 21 35 4 248

Note: BA, Brodmann’s area. The anatomical label of the centroid of each cluster is provided, along with BA for cortical regions. Someof the clusters are very large and extend into many different regions (displayed in figure 1 and described in the text). The maximum andminimum z values of the clusters, and size in number of voxels, are listed, in order to indicate of the extent of the clusters.

Fig. 1.RegionalGrayMatterDifferencesBetweenSubjectsWithSchizophreniaandControls.Graymatterdeficits (purple/blue):bilaterally inthe cerebellum, brain stem, hypothalamus, thalamus, claustrum, middle frontal gyrus, inferior frontal gyrus, precentral gyrus, insula,superior temporal gyrus, fusiform gyrus, parahippocampal gyrus, cuneus, and lingual gyrus; in the left putamen, superior frontal gyrus,posterior cingulate, transverse temporal gyrus, and precuneus; and in the right caudate and postcentral gyrus. Gray matter excesses (red/yellow): bilaterally in the caudate, anterior cingulate, and medial orbitofrontal cortex and in the left putamen and pallidus.

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CSF deficit was identified in the quadrigeminal cistern.This region was decreased by 10% (t = 2.566, df = 152,P < .013).

Effect of Duration of Illness

Duration of illness was not correlated with total brainvolume (r = �.003, P = .983), gray matter (r = �.096,

P = .491), white matter (r = .077, P = .580), or CSF(r = .151, P = .276) within the schizophrenia group.We also examined the association between duration ofillness and tissue density in ROIs defined by case-controldifferences. Density in gray matter–deficit areas was sig-nificantly negatively correlated with duration of illness:thus, the longer the duration of illness, the less gray mat-ter density in deficit areas (r =�.473, P< .001, figure 4a).

Fig. 2.RegionalWhiteMatterDifferencesBetweenSubjectsWithSchizophreniaandControls.Whitematter deficits (purple/blue):bilaterallyin the cerebellum, brainstem, corpus callosum, capsula interna, corona radiata, centrum semiovale, subgyral frontal white matter, inferiorfrontal gyrus, medial frontal gyrus, middle frontal gyrus, cingulate, subgyral temporal white matter, superior temporal gyrus,parahippocampal gyrus, and subgyral parietal white matter; in the left capsula externa and cuneus; and in the right middle temporal gyrus,transverse temporal gyrus, supramarginal gyrus, and inferior parietal lobule.

Fig. 3. Regional CSF Differences Between Subjects With Schizophrenia and Controls. CSF excesses (red/yellow): bilaterally in the frontalhorns and bodies of lateral ventricles, atrium of the right lateral ventricle, third ventricle, frontal interhemispheric fissure, and left Sylvianfissure. CSF deficit (blue): in the quadrigeminal cistern.

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Duration of illness was also negatively correlated with bi-lateral white matter density deficits (r = �.284, P = .038,figure 4b). Duration of illness was neither correlated withgray matter density excess (r = .223, P = .105) nor withCSF excess (r = .029, P = .834).

Discussion

Main Findings

Morphometric brain abnormalities were found in sub-jects with schizophrenia compared with controls in a gen-

eral population-based sample of the same age. In thefrontal lobe, we observed bilateral gray matter deficitsin the dorsal and lateral prefrontal cortex and in the pre-motor and motor cortices (middle, inferior, and superiorfrontal gyri and precentral gyri). There were gray matterdeficits in the insula bilaterally and in the left posteriorcingulate. In the temporal lobe, we noted some medialtemporal lobe abnormalities (reductions in gray matterdensity in the parahippocampal gyrus bilaterally) andreductions in the superior temporal gyrus and fusiformgyrus bilaterally and left transverse temporal gyrus.We also noted some deficits in the parietal (postcentralgyrus and precuneus) and occipital lobes (cuneus and lin-gual gyrus). There were reductions bilaterally in the cer-ebellum, thalamus, and basal ganglia. Relative graymatter excesses were found bilaterally in the basal gan-glia, medial orbitofrontal cortex, and anterior cingulatecortex. There were white matter deficits in an extensivenetwork including inter- and intrahemispheric tracts infrontal and temporal lobes and subcortical structures.Gray and white matter densities in ROIs defined bycase-control differences were negatively associated withduration of illness.

Comparison With Earlier Studies

The total brain, gray matter, white matter, or CSF vol-ume differences (unadjusted for ICV) were not significantin subjects with schizophrenia compared with controls inthis sample, though some differences emerged after con-trolling for ICV. We found similar trends for volumereductions as in the meta-analysis on MRI studies byWright et al,1 who reported brain volume to be 2%,gray matter 4%, and white matter 2% smaller in subjectswith schizophrenia than in control subjects. The totalCSF volume increase in our study was less than in pre-vious studies.1

Meta-analysis of VBM studies by Honea et al11

reported gray and white matter deficits in patients withschizophrenia, relative to controls, in a total of 50 brainregions; the most consistent findings were gray matterdeficits in the left medial temporal lobe, superior tempo-ral, parahippocampal, inferior, and medial frontal gyriand in the right superior temporal gyrus. A recentmeta-analysis of VBM studies in schizophrenia by Ellison-Wright et al48 detected gray matter decreases in thethalamus, the left uncus/amygdala region, the insulabilaterally, and the anterior cingulate. Morphometricbrain abnormalities especially in the frontal and temporallobes and basal ganglia have been observed even in first-episode patients.6,18–21 Meda et al7 reported similar find-ings in their recent large-scale (n = 400) multicenter study.We found gray matter deficits in several of these fron-

tal and temporal regions. In the frontal lobe, we observedbilateral deficits in the dorsal and lateral prefrontal cor-tex and premotor cortex (middle and inferior frontal gyri,

Fig. 4. (a)AssociationBetweenDurationof Illness andGrayMatterDeficits Within Schizophrenia Group. There was a significantcorrelation (r5�.473,P< .001) between the duration of illness andthe density of deficit regions identified in the case-controlcomparison (see figure 1). (b) Association between duration ofillness and white matter deficits within schizophrenia group. Therewas a significant correlation (r 5 �.284, P 5 .038) between theduration of illness and the density of deficit regions identified in thecase-control comparison (see figure 2).

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left superior frontal gyrus), and motor cortex (precentralgyri). There were gray matter deficits in the insula bilat-erally. Our findings of reductions in frontal lobe gyriconverge mostly with previous large VBM studies,5,7

meta-analysis of ROI-based MRI studies,3 and recentVBM meta-analyses.11,48 Hulshoff Pol et al5 found defi-cits in inferior, middle, and superior frontal gyri, in ad-dition to orbitofrontal deficits. Shenton et al3 reportedfrontal reductions in 60% of the reviewed 50MRI studies,andHonea et al11 reported that 50% of studies found graymatter deficits in left inferior andmedial frontal lobe gyri.Honea et al11 also reported that 40% of the studies hadfound insular gray matter deficits, in accordance with ourbilateral finding.In the temporal lobe, we noted bilateral superior tem-

poral gyrus reductions, which is in accordance with meta-analyses byHonea et al11 and Shenton et al.3 Additionally,we noted fusiform gyrus and left transverse temporalgyrus reductions and some medial temporal lobe abnor-malities. We observed gray matter reduction in one me-dial temporal lobe structure—the parahippocampalgyrus, where we found bilateral gray matter reduction,in accordance with previous studies.1,3 However, wedid not find reductions in the hippocampus or amygdala,although volume reductions in these regions have beenfrequently reported previously in ROI-based studies.1–3

The result of our prior, ROI study of hippocampuswas a borderline case: hippocampal volume was reduced2%, but adjustment for total brain volume diminished theeffect.35 In that study, we did not find amygdalar volumechanges either. Even though many VBM studies andsome meta-analyses have reported volume reductionsin hippocampus or amygdala,5,6,11,18,48–50 it is not a uni-versally reported finding: eg, the largest study publishedto date, an international multicenter study, consisting of200 patients, did not find hippocampal reductions.7

Surprisingly, besides the deficits in the prefrontal, pre-motor, and motor cortices and posterior cingulate, weobserved gray matter excesses in the medial orbitofrontalcortex and anterior cingulate, whereas many previousstudies have found deficits in these regions.11,48,51 The in-terpretation of these results is challenging. One implica-tion of this anatomical distinction is that these parts ofthe frontal cortex have rather different cognitive func-tions, with dorsal and lateral prefrontal cortex beingstrongly associated with executive, attentional, andworking memory function, and the orbitofrontal cortexplaying amore critical role in affective decisionmaking.52

Likewise, the anterior cingulate cortex has different func-tions according to anatomical subdivisions, with morerostral sections subtending emotional processing andmore caudal sections subserving attentional and cogni-tive control functions.53 Our finding of subgenual ante-rior cingulate gray matter excess is not in directdiscrepancy with meta-analysis by Ellison-Wright et al,48

who reported deficits mostly in pregenual and dorsal

anterior cingulate. Additionally, anterior cingulateincreases in schizophrenia are not entirely unprece-dented, as at least 2 previous studies have reported similarfindings, which have been interpreted as possibly stem-ming from medication effects.54,55 Finally, there is 1more possible explanation for our anterior cingulateresults; interindividual variability in sulcal and gyralanatomy of this region has been shown in control pop-ulations as well as in schizophrenia patients.56–58 Ourfinding of gray matter density excess in the anterior cin-gulate may present true density difference, or differencein shape, which may cause the apparent density differ-ences in this sample.In addition to the deficits in frontal and temporal cor-

tices described above, we observed widespread gray mat-ter deficits, which extended into parietal lobe (postcentralgyri or sensory cortex and precuneus), the occipital lobe(cuneus and lingual gyri), and the cerebellum. While pa-rietal or occipital lobes have perhaps been somewhatneglected in schizophrenia research in comparison withstudies focusing on frontal and temporal pathology, infact 60% of the MRI studies of the parietal and 44%of studies of the occipital lobe have reported volumereductions.3 Some of the more recent VBM studies andmeta-analyses report volume reductions in parietal or oc-cipital lobes.5,7,8,11,48,59

Similarly, the cerebellum has rarely been a focus inschizophrenia studies, although there is ample evidencesuggesting both that cerebellum plays a critical role inhigher cognitive function and that it is implicated inschizophrenia pathology.23,60–62 Cerebellar reductionsin schizophrenia have been reported by several stud-ies,11,17,48,59,63 although cerebellar increase has alsobeen reported.10,50

Most of the subcortical findings in our study arein agreement with previous studies. We observed bilat-eral thalamic volume reduction, which has also beenreported in meta-analyses by Wright et al,1 Konick andFriedman,64 Honea et al,11 and Ellison-Wright et al.48

In addition, we found gray matter excesses in parts ofthe basal ganglia (bilaterally in the caudate and left puta-men) in accordance with meta-analyses by Shenton et al3

and by Wright et al.1 It has been suggested that thesebasal ganglia excesses could be secondary to neurolepticmedication.65–67

White matter reductions were bilateral and widespreadin this study; deficits were observed in frontal, temporal,occipital, and parietal lobes, cerebellum, and brain stem.Some studies concentrate on gray matter findings, eg, 7studies included in themeta-analysis byHonea et al11 hadstudied only gray matter, whereas 7 studies had exploredboth tissues, and only one was restricted to white matter.Hence, the literature supporting white matter loss is notyet as strong that documenting gray matter deficit.1,4

However, our findings suggest that there are significantdeficits in regional white matter tissue in schizophrenia,

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and thus, white matter should not be overlooked in futuremorphometric studies.

Our data suggest an effect of duration of illness onbrain structure because the duration of illness correlatedwith the gray and white matter deficits in the areas iden-tified in the case-control comparison. Increased durationof illness has previously been associated with reducedgray matter volumes in temporal or frontal cortices.30,31

Longitudinal studies have shown progressive total brainand gray matter volume loss, lateral ventricle enlarge-ment, as well as progressive regional gray or white mattervolume decreases and sulcal CSF enlargement in fronto-temporal regions,20,24–29 though negative results havealso been reported.68 The combination of evidence ofprogressive effects and the reports of gray or white matterreductions in first-episode patients6,18–20,69 suggest a dualprocess model of psychosis: the pathological process ofschizophrenia effects brain structure at various neurode-velopmental stages and may continue as neurodegenera-tive gray matter loss over time.26,70–72

However, there is another possible explanation for ourresults relating duration of illness to increased gray andwhite matter deficits. Given that all our participants wereof the same age, duration of illness is inversely correlatedwith age at onset in this cohort, so that patients who hadthe longest duration of illness also were younger whenthey first became unwell. Thus, an important alternativeinterpretation of our findings is that patients with a youngage of onset are characterized by greater brain structuraldeficits. This could be interpreted as secondary to neuro-developmental processes, namely that the putative path-ological process which causes an early age of onset alsocauses more marked neuropathology in terms of abnor-mal gray and white matter density.

Finally, an additional reason contributing to the cor-relation of deficits with duration of illness could be thechronic effect of antipsychotic drugs because as prelim-inary evidence suggests that chronic exposure to haloper-idol and olanzapine may decrease brain weight andvolume in monkeys.73,74 Despite preliminary studies inhumans,75 it remains unclear how antipsychotic drugs ef-fect brain morphology in schizophrenia. The effect ofdrug treatment is not easy to disentangle in an observa-tional study, and only a randomized placebo-controlledtreatment study, which could be unethical, could finallyresolve this issue.

Strengths and Limitations of the Study

The major strength of the study is the epidemiologicallyrepresentative general population sample. Large effectsizes from initial studies in a field often disappear in sub-sequent work with larger, more representative samples.35

The present study has these features and yet yields signif-icant results. The epidemiological nature of the samplemakes it more representative than most imaging studies

and support generalization of the findings to the popula-tion of patients with schizophrenia. Our study is the firstVBM study of schizophrenia where cases and controls aresampled in a population-based manner. This study is thesecond case-control study of brain morphology in schizo-phrenia where all participants are drawn from a popula-tion-based birth cohort. To our knowledge, only onepopulation-based birth cohort sample has previouslyreported structural brain abnormalities in schizophre-nia, that is the study by Cannon et al.16 Their studywas ROI based, and most analyses from that samplehave focused on genetics (sibling and twin studies)and fetal hypoxia.16,22,76–78

As age has previously been shown to be related to brainmorphology (quite possibly differently in cases and con-trols),79 the fact that all our subjects, being drawn froma birth cohort, are of the same age is an additional advan-tage, which eliminates the possibility of confounding bythis factor. We were also able to exclude the effect of eth-nic differences in brain structure because the subjectswere the same ethnic background representing the gen-eral population of the whole Finland. Additionally, wehad approximately 2 control subjects in both gendersfor each schizophrenia subject to strengthen the statisti-cal power. In contrast to a number of previous schizo-phrenia studies, our cases are not overrepresented bymen: we had a representative sample of women with psy-chosis (39%), a group often neglected.4 The sample ofsubjects is not overrepresented by severe cases of psycho-sis: at the time of scanning, there were only 3 hospitalizedpatients.The population-based nature of the research means

that our study is less susceptible to sampling biasesthan most schizophrenia neuroimaging research. Thecontrols are representative of the population from whichthe cases arise and are not ‘‘supernormal,’’ as previousevidence suggests that selection of supernormal controlparticipants may have enormous influence on resultsof neuroimaging studies,12 which is why we selectedour control participants from the Oulu region generalpopulation truly at random (constrained only by genderstratification). The lifetime absence of a clinical diagnosisof any psychotic disorder in the nonpsychotic group wasconfirmed, but because they were drawn truly randomlyfrom the population, there were some cases of other psy-chiatric or somatic diseases.13,35

Illicit drug use is high in samples of schizophrenia inmany countries,80 and chronic use is known to affectbrain structure.81 Patients with schizophrenia who con-tinue to use cannabis after illness onset show largerincreases in ventricular volume than schizophreniapatients who abstain from cannabis after illness onset.82

Anadvantageofour cohort, due to its location inNorthernFinland and the time the study was conducted, is thatvery few patients were exposed to illicit drugs: on analysisof urine drug screens performed on all subjects, none

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tested positive for cannabis, cocaine, or amphetamine atthe time of scanning.An advantage of our methodology is that we employ

permutation-based methods of statistical testing, whichrequire less assumptions than parametric analyses andalso allow for the use of a smaller amount of smoothingof the original data (parametric statistics may often re-quire greater smoothing to meet the assumptions ofGaussian random field theory). This is important asthe amount of smoothing has been shown to be impor-tant in determining the results of morphological studiesin schizophrenia research.11

With a total of 154 participants (combined cases andcontrols), our sample is larger than most schizophrenianeuroimaging studies, which typically include under 50participants,7 though it is considerably smaller thanthe very largest studies to date, such as Hulshoff Polet al5 and Meda et al7; therefore, the possibility of type2 error remains.Another limitation was the moderate nonparticipation

in the psychosis group. Even though we were able to iden-tify a total of 146 subjects with psychosis who were bornin Northern Finland in 1966, our final sample of schizo-phrenia patients whose imaging data passed quality con-trol standards consisted of 54 individuals. The rationalefor inviting all cohort subjects with previously identifiedpsychosis on national registers (as opposed to identifyingall subjects with previously identified schizophrenia) wasin order to capture individuals who had been previouslymisdiagnosed or who had recently converted to meet cri-teria for schizophrenia. This approach was successful inidentifying a number of additional cases of schizophreniawho would otherwise have been missed. However, it isa limitation of our study that there were a number ofschizophrenia patients who we could identify from na-tional records, but who did not agree to participate inthe study, or who could not be contacted. The clinicalcourse of the participants was more advantageous thanamong the nonparticipants with psychosis.13,35 Our sam-ple may, therefore, be slightly biased toward the lesssevere cases of psychosis with a consequent reductionin power to detect brain changes related to severity ofillness.A technical limitation of our study relates to our scan-

ning parameters. Although an advantage of our study isthat all participants were scanned in the same magnet us-ing the same software, a limitation is that we collected 3-mm thick slices, which is less than optimal and whichcould limit our sensitivity to detect small differences be-tween groups.A limitation in investigating the relationship of brain

structure to illness duration is that, in our study, allpatients are of the same age and, in an early middleage, typical to birth cohort studies.83 As age has beenshown to be a predictor of brain abnormality in schizo-phrenia,79 this confers the advantage that age is not a con-

founder as regards the case-control analysis, but for thewithin-patients analysis, it is a limitation because there isa reciprocal relationship between illness duration and ageat onset of illness. Thus, the longer the duration of illness,the earlier the age of onset; it is impossible to separatethese issues in this study. Moreover, the only way to trulystudy the course of brain structure changes in the illness isto perform repeated measurements of brain structureover time.

Conclusion

Morphometric brain abnormalities in frontotemporalregions and basal ganglia were confirmed in this epidemi-ological sample. Furthermore, gray matter density defi-cits were observed in brain regions which have previouslyreceived less scrutiny in schizophrenia research. Whitematter reductions were bilateral and widespread. Sub-jects with longer duration of illness, and younger ageat onset, showed more prominent brain abnormalitiessuggesting either that developmental brain deficits relateto an earlier age of onset or that brain abnormalities inschizophrenia are progressive in nature.

Funding

The Academy of Finland (grant numbers: 110 143, 120479, 214 273); Sigrid Juselius Foundation; The StanleyMedical Research Institute; The Radiological Societyof Finland; The Lundbeck Foundation; AstraZenecaOy. Software development (BAMM) was supported bya Human Brain Project grant from the National Instituteof Mental Health and the National Institute of Biomed-ical Imaging and Bioengineering.

Acknowledgments

The authors wish to thank Xavier Chitnis and AriKarttunen for their help in analyzing the data andJohn Suckling, Anna Barnes, and Alex Fornito fortheir comments in preparing the manuscript.

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Morphometric Brain Abnormalities in Schizophrenia in a Population-Based Sample: Relationship to Duration of Illness