Raine et al,. (2002) - 'Prefrontal Structural and Functional Deficits in Schizotypal Personality Disorder

8/12/2019 Raine et al,. (2002) - 'Prefrontal Structural and Functional Deficits in Schizotypal Personality Disorder'

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Prefrontal Structural and Functional Deficits inSchizotypal Personality Disorderby Adrian Raine, Todd Lencz, Paul ine Yaralian, Susan Bihrle, Lori LaCasse,Joseph Ventura, and Patrick Colletti

AbstractStructural prefrontal deficits have been reported inpatients with schizophrenia, but it is unclear if theyare also found in patients with schizophrenia spec-trum personality disorders. The hypothesis that aspectrum group will be characterized by prefrontalstructural deficits was tested by assessing prefrontalgray and white volumes using magnetic resonanceimaging in a community sample of 16 individualswith schizotypal/paranoid personality disorder, 27comparisons, and 26 psychiatric controls. Frontalneurocognitive functioning was also assessed usingthe Wisconsin Card Sorting Test and the ContinuousPerformance Test. The spectrum group showedreduced prefrontal gray volumes and poorer frontalfunctioning compared to both other groups.Structural deficits were independent of functionaldeficits and together correctly classified 84.2 percentof subjects. Structural but not functional deficitswere abolished after a strict control for antisocialpersonality was made. Results support the notionthat frontal deficits may be centrally involved in theetiology of schizophrenia but also suggest thatcomorbid antisocial behavior may be one factoraccounting for differences in prefrontal structuralfindings across studies.

Keywords: Schizotypal, paranoid, prefrontalgray, MRI, antisocial.chizophreni Bulletin 28 3):501-513, 2002.

Quantitative magnetic resonance imaging (MRI) studieshave found evidence for frontal structural deficits inschizophrenia (Zakzanis and Heinrichs 1999; Yaralianand Raine 2000). These imaging studies are aboutequally divided in either showing reductions in total vol-ume (gray and white) or area of the frontal/prefrontalregion (e.g., Andreasen et al. 1986, 1994; Raine et al.1992*; Nopoulos et al. 1995) or failing to find thesereductions (Andreasen et al. 1990; Bilder et al. 1994;Szeszko et al. 1999 ). Another study found prefrontal

volume deficits in schizophrenia patients compared tonormal controls, but not when compared to chronic alco-holics (Sullivan et al. 1998), while one review reportspreliminary findings failing to observe reduced pre-frontal volume in schizotypal patients (Siever et al.2002).The significance, in part, of such frontal deficits,if they truly exist, is that they may help account for thefunctional frontal deficits repeatedly observed in schizo-phrenia (Buchsbaum 1990; Cannon 1996; Weinbergerand Berman 1998).Some of these structural MRI studies have furthersegmented gray from white matter within the frontal orprefrontal region, with mixed results. Four studies foundreductions in prefrontal gray but not white matter(Zipursky et al. 1992; Lim et al. 1995; Lim et al. 1996;Sullivan et al. 1998), one study that assessed only graymatter found a reduction in the dorsolateral region(Schlaepfer et al. 1994), three studies found significantreductions in white but not gray matter (Breier et al.1992; Buchanan et al. 1993; Buchanan et al. 1998), andtwo studies failed to find differences in gray or whitematter (Suddath et al. 1989; Wible et al. 1995). In con-trast to these conflicting structural findings, at a func-tional level hypofrontality is one of the best replicatedimaging correlates of schizophrenia (Velakoulis andPantelis 1996). Compelling evidence also exists fromthe neuropsychological literature for executive functionand working memory deficits in schizophrenia patients(Park et al. 1995), with strong overall effect sizes acrossstudies of 0.88 for the Wisconsin Card Sorting Test(WCST; 43 studies) and 1.16 for the Continuous Per-formance Test (CPT; 14 studies) (Heinrichs and Zakza-nis 1998).

Further evidence for the etiologic significance of pre-frontal structural deficits comes from the study of schizo-phrenia spectrum disorders. Spectrum disorders have tra-dit ionally encompassed the DSM odd cluster of

Send reprint requests to Dr. A. Raine, Department of Psychology,University of Southern California, Los Angeles, CA 90089-1061; e-mail: [email protected].

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schizotypal, paranoid, and schizoid personality disorders(Siever et al. 1993), although the inclusion of schizoid per-sonality disorder has been questioned by some researcherson the grounds that it lacks genetic relatedness with schiz-ophren ia (Nigg and Goldsmith 1994; Torgersen 1994;Ingraham 1995) . Spect rum indiv iduals have a s tab le(schizotypal and paranoid) personality disorder with a his-tory of disturbances in cognition, perception, and behaviorthat in part mirror abnormalities found in schizophreniapatients. Research on such individuals provides a valuableadjunct to research on inst i tut ional ized schizophreniapatients. To the extent that the same neurobiological corre-lates of schizophrenia can also be observed in individualswith schizophrenia spectrum disorders who are free of theconfounds of institutionalization, medication, and label-ing, there is increased confidence that such processes maybe of etiologic significance for schizophrenia. In contrast,only one MRI s tudy appears to have tes ted whetherschizotypal personality is related to prefrontal structuraldeficits; Raine et al. (1992ft) showed that community vol-unteers with higher scores on self-report schizotypal per-sonality measures had both smaller prefrontal areas andmore perseveration errors on the WCST.

Although most other ima ging studies of schizotypal per-sonality have focused on ventricular size (Cannon et al.1994) or temporal lobe volumes (D ickey et al. 1999; Down-hill etal.2000), tw o additional studies of schizotypal person-ality disorder have relevance to the question of frontal struc-tural deficits. Buchsbaum et al. (1997) found that patientswith schizotypal personality disorder showed an enlarge-ment of the left anterior horn of the lateral ventricle that wasintermediate in size between that of normal controls andschizophrenia patients. Enlargement of the anterior hom ofthe lateral ventricle is suggestive of tissue loss (especially ofwhite matter) in the frontal lobe. Conversely, Siever et al.(1995) failed to find significant differences between anteriorhorn size in schizotypal patients, schizophrenia patients, andcontrols. MRI studies of frontal volume in children withschizophrenia spectrum symptoms (who may be viewed asanalogues of schizotypy) (Yeo et al. 1997) and childhood-onset schizophrenia (Frazier et al. 1996) have also found nullresults. In contrast, frontal functional deficits represent thebest replicated correlate of schizotypal personality. Specifi-cally, frontal functional deficits have been repeatedly andreplicably found on the WCST and the CPT with respect toboth schizotypal personality disorder and individual differ-ences in schizotypal personality, with at least 14 studiesobtaining significant effects (e.g. , Lyons et al . 1991;Battaglia et al. 1994; Lenzenweger and Korfune 1994; Trest-man et al. 1995; Roitman et al. 1997; Voglmaier et al. 1997;Daneluzzo et al. 1998).

An important methodological issue in the literature isthat studies of structural and functional frontal deficits in

schizotypal personality have rarely if ever included a psy-chiatric control group. Similarly, despite the imp ortance ofestablishing psychiatric specificity for structural braindeficits in schizophrenia, the majority of structural andfunctional MRI studies of schizophrenia do not employpsychiatric control groups. For example, a survey foundthat of the 28 MRI studies on schizophrenia published inth e American Journal of Psychiatry between 1996 and2000, only 3 (10.7%) employed a psychiatric controlgroup . Similarly, only 2 of 15 studies (13.3%) published inArchives of General Psychiatry in this time periodemployed a psychiatric control group, while for Schizo-phrenia Research only 2 of 14 studies (14.3%) employedpsychiatric controls. Furthermore, studies that do use psy-chiatric controls frequently control for only one experi-mental-group source of comorbidity that could confoundfindings; they do not control for the full range of com orbiddisorders that are higher in the experimental group. Itremains to be seen, therefore, whether a schizophreniaspectrum group would differ from a psychiatric controlgroup m atched on other Axis I and II disorders.

The primary goal of the current study was to test thehypothesis that individuals with schizophrenia spectrumdisorders would show a reduction in prefrontal gray vol-ume compared to both comparisons and psychiatric con-trols. It was also predicted that the spectrum group wouldshow functional n eurocognitive deficits as indicated by theWCST and the CPT and that these deficits would be predi-cated on the structural prefrontal deficits.

MethodSu bje cts . All subjects were drawn from five tempora ryemployment agencies in Los Angeles. This recruitmentsource was chosen because pilot data showed that theseindividuals had higher rates of schizotypal personality andbecause the one prior study of prefrontal structural deficitsin schizotypy had also employed a community sample.All subjects who wished to participate in the study wereallowed to do so without prior screening. Subject groupsconsisted of 27 comparisons, 26 psychiatric controls, and16 participants with a diagnosis of either schizotypal per-s ona l i t y d i s o rde r or pa rano i d pe r s ona l i t y d i s o rde r(referred to hereafter as the spectrum group). The spec-trum group consisted of 10 individuals with schizotypalpersonality disorder only, 4 individuals with paranoid per-sonality disorder only, and 2 individuals with both schizo-typal and paranoid personality disorder. Demographic,cognitive, and physical measures for the three groups areshown in table 1. Exclusion criteria were as follows: ageunder 21 or over 45, nonfluency in English, history ofepilepsy, claustrophobia, pacemaker, or metal implant.Screening of brain scans by a neuroradiologist blind to

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Table 1. Characteristics of the study groups

DemographicSex, maleAge,yrs, mean (SD)Social class, mean (SD)Ethnicity, whiteCognitive and physicalEstimated intelligence,mean (SD)Handedness, mean (SD)1Height (cm), mean (SD)Weight (kg), mean (SD)Head circumference (in.),mean (SD)History of head injury,

ComparisonC 27)85.230.9 (6.9)35.3(10.3)57.1101.7(14.9)33.8 (9.8)175.9(7.9)80.8(15.0)57.6(2.1)39.3

Psychiatriccontroln=2 6)88.529.0 (6.6)36.6(11.5)38.597.8(13.1)33.5 (10.5)179.7(9.1)80.9(15.7)57.2(1.7)38.5

Schizophreniaspectrum n=16 )87.532.1 (5.4)33.9(10.9)43.894.5(13.1)35.2 (9.6)176.5(10.8)78.7(11.6)57.1 (2.3)37.5

StatisticsX2= 0.9, df=2 p = 0 . 9 5F (2,67) = 1.2, p = 0.31F (2,67) = 0.3, p = 0.72X2= 2.0,df=2 p = 0 . 3 7F (2,67) = 0.4, p = 0.68F (2,67) = 0.2, p = 0.86F (2,67) = 1.3, p = 0.27F (2,67) = 0.15, p = 0.86F (2,67) = 1.5, p = 0.39X2= 0.01,ctf=2, p = 0.99

Note.SD = standard deviation.1 High scores indicate greater degree of right-handedness.

group membership resulted in one subject being excludedfrom analyses because of encephalomalasia, consisting ofsignificant atrophy to the right temporal and frontal cor-tex. Subjects were paid $5.50 per hour for participationand were informed that the study concerned the biologicalbasis of personal i ty and behavior problems, includingcriminal behavior. After subjects were given completedescriptions of the study, written informed consent wasobtained in accordance with Institution Review Boardprocedures at the University of Southern California.

The comparison group consisted of participants with-out a diagnosis of schizophrenia, psychotic disorders,schizophrenia spectrum disorders, or substance or alcoholdepen dence . A psychiatric control group was formed froma total of63other volunteers to obtain as close a match aspossible for the comorbid conditions found in the spec-trum group. Results of this matching are shown in table 2for affective and anxiety disorders, conduct and antisocialpersonality disorders, and Cluster B and C personality dis-orders. There were no significant differences betweengroups, using 2 p>0-35 in all cases), with the only trendfor significance being the psychiatric controls havingslightly higher rates of Cluster C personality disordersthan the spectrum group. However, there was a nonsignifi-cantly higher rate of comorbidity for antisocial personalitydisorder in the spectrum group (50.0%) than in the psychi-atric controls (38.5%). Furthermore, the spectrum group(mean [M] = 9.4, standard deviation [SD] = 4.1) had sig-nificantly higher scores on a dimensional measure of anti-social personality disorder (see below) compared to bothpsychiatric controls (M = 6.7, SD = 3.5; / = 2.2, d f= 40,p

=0.033) and comparisons (M = 3.7, SD = 2.4;t= 5.7, df=41 ,p = 0.0001).Because substance and alcohol use could be a con-found in structural brain imaging correlates of schizophre-nia spectrum disorders, details of rates of alcohol and sub-stance abuse/dependence, together with past month usage,are given for the psychiatric control and spectrum groupsin table 3. Similarly, quantity and frequency of alcoholusage for these groups are given in table 4. There were nosignificant group differences.Diagnostic, Cognitive, Physical, and PsychosocialAssessment. Diagnoses were made usingDSM-IV crite-ria (American Psychiatric Association 1994) and ascer-t a i ned u s i ng t he S t ruc t u red C l i n i ca l In t e rv i ew fo rDSM-IV Axis I Disorders (First et al. 1994a) and theS t ruc t u red C l i n i ca l In t e rv i ew fo r DSM-IV Axis I IPersonal i ty Disorders (SCID-II, First et al . 1994fc).Diagnoses were made by advanced clinical psychologyPh.D. students who had undergone a standardized trainingand quality assurance program for diagnostic assessment(Ventura et al. 1998). Prior to diagnostic assessments onthe study sample, diagnostic procedures were piloted onsubjects also drawn from temporary employment agenciesand interview tapes assessed jointly by J.V., A.R., andT.L. In addition to diagnostic testing, an alcohol use ques-tionnaire to assess frequency of alcohol consumption wascompleted by participants. A dimensional measure of anti-social personal i ty disorder was created by summingscores of the seven DSM-IV criterion C symptoms of theS C ID-n .

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Table 2. Rates of psychiatric disorder in the psychiatric control and schizophrenia spectrum groups,together with 2analyses

Affective 1Anxiety2Conduct disorderAntisocial personality disorderCluster B 3Cluster C 4

Psychiatriccontroln = 26)53.819.253.838.515.415.4

Schizophreniaspectrum n = 1 6 )56.318.850.050.025.5

0.0

x20.020.000.060.540.592.70

df111111

P0.880.970.810.460.440.10

1 Major depression, bipolar depression, other depressive disorders.2 Phobia, panic, generalized anxiety.3Borderline, histrionic, obsessive-compulsive.4A voidant, dependent, narcissistic.

Estimated intelligence was based on the five subtests(vocabulary, arithmetic, digit span, digit symbol, blockdesign) of the Wechsler Adult Intelligence Scale-Revised(Wechsler 1981). Degree of right versus left hand preferencewas assessed using the abbreviated Oldfield Inventory (Bry-den 1977). History of head injury was defined as headtrauma resulting in hospitalization. Social class was mea-sured using the Hollingshead classification system (Holling-shead 1975). A physical exa mina tion w as conducted toderive measures of height, weight, and head circumference.Neurocognitive M easures of Frontal FunctioningCPT. Version 4.08 of the degraded stimulus versionof the CPT (Nuechterlein et al. 1983) was administeredaccording to author guidelines. Visually degraded num-bers ranging from 0 to 9 were flashed on a computerscreen (p laced 1 meter from the subjects in the subjects'line of vision) for 40 ms at the rate of one per second. Thesubjects' task was to press a response button on a Gravisjoy stick every time they saw the figure 0 but to notrespond to all other stimuli. Targets had a 0.25 probabilityof occurrence. After 10 presentations of the target stimu-lus only, subjects were given 120 practice trials afterwhich 480 test stimuli (lasting 8 minutes) were presented.Hits, false alarms, sensitivity, and response bias scoreswere computed.

WCST. A computerized version of the WCST (Grantand Berg 1948) was administered in which subjects sorteda pack of 64 cards according to color, shape, and number.Visual feedback (right or wrong) was provided after eachcard placement. This task reflects abstract reasoning, cog-nitive flexibility, and the ability to maintain and changeset. Total errors, percent perseverative errors, number of

categories completed, and trials to achieve the first cate-gory were computed.MRI. Full details of MR I assessments are given in Raineet al. (2000). Structural MRIs were conducted on a PhilipsS15/ACS (Selton/Conn) scanner with a magnet of 1.5Tes la f i e ld s t rength . Fol lowing an in i t i a l a l ignmentsequence of one midsagittal and four parasagittal scans(spin-echo Tl-weighted image acquisition, repetition time[TR] = 600 ms, time to echo [TE] = 20 ms) to identify theanter ior commissure-pos ter ior commissure (AC-PC)plane, 128 three-dimensional Tl-weighted gradient-echocoronal im ages (TR 34 ms, TE 12.4 ms, flip angle 35, 1.7mm over contiguous slices, 256 X 256 matrix, field ofview [FOV] = 23 cm) were taken in the plane directlyorthogonal to the AC-PC line.

Brain images were reconstructed in three dimensionsusing a SPARC workstation and semiautomated CAM RAS200 ALL EG RO sof tware used for gray/whi te /cere -brospinal fluid (CSF) segmentation. Segmentation of grayand white matter was performed using a thresholdingalgorithm, with the operator blind to group membershipapplying a cutoff va lue to the signal intensity histogram tooptimally differentiate white from gray, areas of whichwere defined using an automated seeding algorithm oneach slice. Further details of the algorithm are reported inRaine et al. (2000).

Following our earlier study (Raine et al. 1992a), thefrontal region w as defined as all cortex a nterior to the genuof the corpus callosum and divided into left and righthemispheres along the longitudinal fissure. Interrater relia-bility (intraclass correlation coefficient) based on 23 scans(raters blind to each other's ratings and group member-

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Table 3. Lifetime rates of alcohol and substance abuse/dependence in the psychiatric control andschizophrenia spectrum groups, together w ith usage in the past month

AlcoholAbuseDependencePast month

Sedatives-hypnotics-anxiolyticsAbuseDependencePast month

CannabisAbuseDependencePast month

StimulantsAbuseDependencePast monthOpioids

AbuseDependencePast monthCocaine

AbuseDependencePast monthHallucinogens/PCP

AbuseDependencePast monthPoly

AbuseDependencePast monthOther

AbuseDependencePast month

Psychiatriccontroln = 26)

23.138.57.73.83.80.0

19.231.315.411.57.70.00.03.80.07.730.80.0

23.17.70.00.00.00.07.70.00.0

Schizophreniaspectrumn = 16)

31.350.00.06.30.04.8

38.137.512.525.012.50.0

6.30.00.06.350.06.30

23.16.30.00.06.30.00.06.30.0

x1.80

1.290.74

1.30.80

0.071.76

2.25

1.6

1.670.45

1.66

2.86

df2

22

22

22

2

2

12

2

2

P0.46

0.260.69

0.260.67

0.800.41

0.32

0.45

0.190.98

0.20

0.24

Note x analyses were conducted on psychiatric disorder categorization (absent-abuse-dependence) and on substance use in pastmonth (yes/no). PCP = Phencyclidine.

ship) was as follows: left prefrontal gray 0.99, right pre-frontal gray 0.99, left prefrontal white 0.93, right pre-frontal w hite 0.94, total brain vo lume 0 .99.Statistical Analyses. Repeated measures analyses ofvariance (ANOVAs) using the mult ivariate approach(Vasey and Thayer 1987) were conducted on left and righthemisphere volume measures in a 3 (groups) X 2 (left and

right hemisphere) design for gray and white matter sepa-rately. The ability of measures to predict group member-ship independent of confounds was assessed using logisticregression and the Wald 2 statistic using a classificationcutoff of 0.5, with the Nagelkerke statistic used for vari-ance estimation. Brain and neurocognitive variables wereentered using a stepwise forward procedure (Wald) withan entry probability of 0.05 and a removal probability of

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Table 4. Mea ns standard deviations) and results of f test comparisons for alcohol usage in thepsychiatric control and schizophrenia spectrum groupsPsychiatriccontroln = 26)mean SD)

Schizophreniaspectrum(n =16)mean SD) df

Times used, past weekTimes used, past monthNo. of drinks wh en drinkingLargest no. of drinks onone occasion

0.78(1.28)3.50 (5.03)2.70 (2.63)5.85(5.61)

1.63 (2.06)5.94 (7.02)2.56 (3.05)7.00 (8.24)

1.671.270.160.54

40404040

0.110.210.870.59

0.10. Other hypotheses were tested using ANOVA and ttests. All tests of significance are 2-tailed with an alpha of0.05.The two neuropsychological measures of frontal func-tioning (WCST and CPT) each yielded four performancescores reflecting different aspects of test performance. Toreduce the number of variables for analysis, these eightsubscores were subjected to principal component analysis,and factor scores from the first principal component werecalculated using the regression method.

ResultsPrefrontal Structure. There was a main effect for groupon prefrontal gray volumes, F(2,66) = 3.5, p = 0.037. Thespectrum group had smaller prefrontal gray volumes thanboth comparisons, t= 2.6,d f=41, p = 0.011, and psychi-atric controls, / = 2.3 ,df= 40,p =0.028 (figure 1). Th espectrum group showed a 12.4 percent reduction in thevolume of prefrontal gray matter compared to the compar-ison group, and a 13.2 percent reduction compared to psy-chiatric controls .1 Corresponding effect sizes d) were0.84 and 0.73, respectively, and are in the large range(Cohen 1988). There was no interaction between groupand hemisphere, F(2,66) = 0.1,p =0.91 , but there was amain effect for hemisphere, F(l ,88) = 94.4, p = 0.001,with the right hemisphere having higher gray volume thanthe left. In contrast, there was no group difference in pre-frontal white matter, F(2,66) = 0.14, p = 0.87 (figure 1),and no group X he misphere interaction, F(2,66) = 0.54, p= 0.58. There was a main effect for hemisphere, F(l,66)= 31 .5, p = 0.00 01, indicating a larger volume of w hitematter in the left hemisphere.

1 Groups were balanced for sex, but to assess for any interactionsbetween group and sex, sex was entered as a second factor in all analy-ses. No group x sex, F(2,62) = 0.78,p = 0.46, or group x sex x hemi-sphere, F(2,62) = 0.79,p = 0.46, interactions were observed.

Prefrontal gray was expressed as a function of wholebrain volume. A repeated measures multivariate ANOVAconfirmed the main effect for group, F(2,66) = 4.50,p =0.015. A breakdown of this effect showed that the spec-trum group had smaller prefrontal/whole brain volumesthan both comparisons,t=2.1,df= A\,p =0.044, and psy-chiatric controls,t= 2.76,d f= 39 ,p=0.009. There was nosignificant group X hemisphere interaction, F(2,66) =0.09,/?=0.91,but the main effect for hemisphere, F(l,66)= 89.0,p =0.000, again indicated relatively greater grayvolume in the right hemisphere. There was no significantgroup difference in overall brain volume, F(2,66) = 1.54, p=0.22.Frontal Neurocognitive Functioning. The principalcomponent analysis of the eight subtests from the WCSTand CPT produced a first factor that accounted for 47.9percent of the total unrotated variance. Percent persev-erative errors was the highest loading WCST variable onthis factor, while false alarm rate was the highest loadingCPT variable. Loadings on this factor for the eight sub-tests were as follows: WCST percent perseverative error0.86, total errors 0.85, number of categories -0.79, trialsto first category 0.69; CPT false alarm rate 0.75, hit rate-0 .45 , response bias -0.34, sensitivity -0.62. Given thatall the loadings were greater than 0.30 and loaded in atheoretically meaningful fashion, the factor was labeled frontal functioning, with higher scores indicating poorerfrontal functioning.

Groups differed significantly on the frontal factor score,F(2,59) =4.69,p=0.013 (table 5). The spectrum group per-formed significantly more poorly on this global factor thandid both the comparisons, t= 2.55,d f= 37 ,p =0.015, andthe psychiatric controls,t=2.51,d f= 36 ,p=0.017.With respect to specific sub tests of frontal functioning(table 5), groups differed significantly on WCST trials tocomplete first trial, F(2,62) = 5.01,p = 0.010, and CPTfalse alarms, F(2,63) = 4.85,p =0.011; and there was atrend for CPT response bias, F(2,63) = 3.09,p =0.053.

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Figure 1. Prefrontal gray and white matter volumes in the three groups

Prefrontal VolumeC on tro ls Psy chiatric ControlsSchizotypals

cc

85

75

65

55

45 GRAY WHITETable 5. Group comparisons on the frontal factor first principal component) and subtests of the WCSTand CPT

Frontal factorWCST

Trials to first category perseverative errorsTotal errorsNo.of categoriesCP T

False alarmsResponse biasHit rateSensitivity

Comparisonn = 27),mean SD)

-0.27 (0.89)17.68(8.53)13.40(9.04)22.12(9.64)2.65 (1.44)0 035(0.065)0.58 (0.39)0.78 (0.26)0.91 (0.14)

Psychiatriccontrol n = 26),mean SD)

-0 .16 (0 .64 )19.36(10.21)15.21 (10.96)24.62 (9.52)2.27(1.25)0.019(0.020)0.66 (0.25)0.78 (0.25)0.93 (0.08)

Schizophreniaspectrumn = 16),mean SD)

0.60 (1.22)31.47(23.80)20.80(12.09)28.69(10.69)1.81 (1.33)0.071 (0.062)0.39 (0.40)0.70 (0.29)0.87(0.18)

F4.695.012.372.211.964.853.090.561.25

at2,592,622,652,652,652,632,632,632,63

0.0130.0100.1020.1180.1490.0110 0530 5720 294

Note CPT= Continuous Performance Test;SD= standarddeviation;WCST=W isconsin Card Sorting Test.The spectrum group had a significantly higher percentageof perseveration errors on the WCST than did both com-parisons, / = 2.65,df= 38 ,p = 0.012, and psychiatric con-trols, t= 2.23,df= 38 ,p =0.031.The spectrum group alsohad a higher CPT false alarm rate than did psychiatric con-trols, / = 3.86, df=38 ,p = 0.000, but the contrast with

comparisons was only marginally significant in the pre-dicted direction, /=1.77,d f= 40,p = 0.084. The spectrumgroup had a poorer response bias compared to psychiatriccontrols, / = 2.69,d f= 38 ,p= 0.01, but the contrast withcomparisons, while in the predicted direction, was statisti-cally nonsignificant, t=1.57, df= 40,p=0.125.

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Independence of Structural and Functional PrefrontalDeficits. The spectrum group was characterized by bothstructural and functional prefrontal deficits. It has beenhypothesized that structural deficits to the prefrontal cor-tex give rise to the frontal functional deficits in this group.If this were the case, then equating the three groups onprefrontal gray volume would abolish the frontal func-tional deficits in the spectrum group. This hypothesis wastested by entering prefrontal gray volumes in the firstblock predicting spectrum grou p versus comparison groupmembership in the logistic regression, and then enteringthe frontal functional factor in a second block. Afterequating the differences in prefrontal structure, group dif-ferences in frontal functional deficits remained significant,X2=6.86, df=\,p = 0.0088, indicating independence ofstructural and functional deficits. Independence of struc-tural and functional deficits was confirmed by the lack ofsignificant correlations between the frontal functional fac-tor and prefrontal gray volumes in the entire sample andin each of the three samples (all r 0.21).

Th i s i ndependence o f s t ruc t u ra l and func t i ona ldeficits suggests that these factors account for independentproportions of variance in the group difference betweenthe spectrum and com parison groups. This hypothesis wastested in a logist ic regression analysis with spectrumgroup versus comparison group as the grouping variableand prefrontal gray and the frontal factor as two predictorvariables entered on the same block. Results are shown intable 6. Prefrontal gray h ad the strong est relation to groupsand was entered first, accounting for 21.8 percent of thevariance in group membership. After entry of prefrontalgray, the frontal functioning factor still significantly pre-dicted group membership, almost doubling the percentageof variance accounted for, from about 22 percent to about41 percent. The variables together correctly classified 84.2percent of subjects.Further Control for Substance Use. Although psychi-atric controls and the spectrum group were matched onsubstance abuse, the spectrum group had nonsignificantlyhigher rates of cocaine, cannabis, stimulant, and sedativeuse than did psychiatric controls. To further control for

the possible effects of these confounds on structural andfunctional brain differences, these four variables weresimultaneously entered as covariates and the above analy-ses were repeated. After this control, group differencesstill remained for prefrontal gray volume, F(2,62) = 4.29,p= 0.018 . For frontal functioning, group differences weremarginally significant, F(2,61) = 2.34, p = 0.066. Theabsolute group difference between spectrum and compari-son groups was reduced only 9.7 percent after the sub-stance abuse control, and this difference still remainedsignificant, F(l,33) = 4.46,p=0.042.Possible C onfounding Effect of Antisocial B ehavior.The significantly higher scores on antisocial person ality inthe spectrum group relative to the two other groups raisedthe question of whether prefrontal structural deficits arean artifact of the increased antisocial behavior in the spec-trum group. To test this possibility, a logistic regressionanalysis was conducted in which prefrontal gray volumewas used to predict spectrum versus comparison groupmembership after controlling for the dimensional measureof antisocial personality disorder. The schizotypy-pre-frontal gray relationship was abolished, 2=0.001,d f= 1,p= 0.98, after controlling for antisocial personality disor-der.2 In contrast, group differences on frontal neurocogni-tive functioning remained after controlling for antisocialpersonality, 2=7-23,df=\,p =0.007.

Because the spectrum group had nonsignificant lyhigher rates of antisocial personality disorder and signifi-cantly higher scores on the dimensional measure of antiso-cial personality than psychiatric controls did, a completestatistical control was made on the dimensional measureof antisocial personality disorder in logistic regressions

2 Our previous findings of reductions in prefrontal gray volume inindividuals with antisocial personality disorder (Raine et al. 2000) arenot a function of increased schizotypai personality in this group because(1) the antisocial personality disorder group showed reduced prefrontalvolume compared to a psychiatric control group matched on schizophre-nia spectrum disorder, and (2) reduced prefrontal gray differentiated theantisocial personality disorder group from the control group after initialentry of schizotypai personality in a logistic regression, x2 = 5.08,d f= 1,p=0.024.

Table 6. Logistic reg ression predicting schizotypai versus com parison group m embership using pre-frontal gray and frontal functioning as predictor variablesWald x 2entryStep 1: prefrontal grayStep 2: frontal functioning

X26.606.86

df11

P0.0100.009

Nagelkerke R20.2180.408

Correct classification73.688 4 .2 1

Note.Nagelkerke R2 refers to total variance account for; correct classification refers to the percentage of cases correctly classified intogroups.

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predicting group differences on structural and functionalfrontal measures. Full control for antisocial personalityrendered the previously significant group difference non-significant, x 2= 3.0,df= 1,p=0.08 3, but the group differ-ence in frontal neurocognitive functioning remained sig-nificant, X2= 5.56,df=\,p =0.018.

DiscussionFindings support the hypothesis that schizotypal/paranoidpersonality disorder is characterized by structural andfunctional prefrontal deficits. The spectrum group showeda 12.4 percent reduction in the volume of prefrontal graymatter compared to the comparison group, and a 13.2 per-cent reduction compared to psychiatric controls. Corre-sponding effect sizes d)were 0.84 and 0.73, respectively,and are in the large range (Cohen 1988). These findingscould not be accounted for by differences in whole brainvolume, alcohol and drug use, history of head injury, orcomorbidity for affective and anxiety disorders. Similargroup differences in functional frontal deficits were found,with effect sizes of 0.80 for both comparisons and psychi-atric controls. These functional frontal findings are consis-tent with the previous literature showing robust WCSTand CPT deficits in schizotypals, as noted earlier. Giventhat the spectrum group also showed poorer prefrontalfunctioning compared to matched psychiatric controls, thecurrent findings provide support for the centrality offrontal structural and functional deficits in schizophreniaspectrum disorders.

Structural prefrontal deficits were independent offunctional deficits in schizophrenia spectrum patients.Though not predicted, this result is consistent with the fail-ure of all three prior cross-sectional studies that comparedschizophrenia patients to controls and assessed prefrontalstructural deficits together with frontal neurocognitivefunctioning (Andreasen et al. 1986; DeMyer et al. 1988;DeLisi et al. 1991). Set against these three failures, onelongitudinal study observed that frontal volume reductionspredicted decline in executive functions over a 31-monthperiod (Gur et al. 1998), while one cross-sectional study ofonly chronic schizophrenia patients showed that reduceddorsolateral prefrontal area was associated with impairedperformance on both the WCST and the CPT (Seidman etal .1994). There are at least two possible explanations forthis lack of structure-function association. First, if thestructural deficit was localized to the orbitofrontal cortex,such damage might be less likely to affect frontal neu-rocognitive measures, which have been traditionally asso-ciated with dorsolateral prefrontal regions. In support ofthis explanation, frontal neurocognitive measures havebeen found within schizophrenia patients to correlate with

the dorsolateral but not the orbitofrontal area (Seidman etal . 1994). Second, it must be remembered that the neu-rocognitive measures of frontal functioning used in thisstudy are complex measures of executive/attentional func-tions that involve neural networks outside of this brainregion. For example, the CPT is known to activate bilat-eral frontal and occipital regions, together with right tem-poral and parietal regions (Buchsbaum et al. 1990). Fur-thermore, damage to subcortical structuresincluding thet h a l a m u s , h i p p o c a m p u s , a n d a m y g d a l a w o u l d b eexpected to interfere with tasks, such as the CPT andWCST, that are dependent on the integrity of these pre-frontal-subcortical circuits (Bilder et al. 1995). Futureimaging studies that both segment prefrontal gray volumeinto structural subregions and assess prefrontal and sub-cortical functioning using imaging techniques with highspatial resolution (e.g., fMRI) are needed to elucidate thecomplex interplay between prefrontal structure and func-tion.As noted above, only 10.7-14.9 percent of structuralMRI studies of schizophrenia have employed a psychi-atric control group. A strength of the present study is theuse of a psychiatric control group that controls for all AxisI and II disorders, unlike the few studies that employ apsychiatric control group but control for only one comor-bid disorder. As such , the structural and functional deficitsfound in the spectrum group cannot be readily attributed tomost comorbidity. Specifically, although rates of drug andalcohol abuse/dependence in the spectrum group werequite high (possibly reflecting self-medication for symp-toms in this noninstitutionalized sample), we have previ-ously shown for this sample that individuals dependent ondrugs or alcohol have prefrontal gray volumes identical tocontrols (Raine et al. 2000). Furthermore, the spectrumgroup was reasonably well matched to psychiatric controlson substance use, and ad ditional control for nonsignificantgroup differences on cannabis, sedatives, cocaine, andstimulant use left resu lts essentially unchanged.

Findings on prefrontal structural deficits are consis-tent with one prior community study showing an associa-tion between reduced prefrontal volume and increasedschizotypy (Raine et al. 1992fc), but the findings conflictwith those of a recent study by Downhill et al. (2001)showing prefrontal volumes in schizotypal personality dis-order that do not differ statistically from controls'. Fur-thermore, Buchsbaum et al. (2002) have found higher, notlower, glucose metabolic rates in Brodmann area 10 in 13patients with schizotypy personality disorder, while areview by Siever et al. (2002) similarly argues that schizo-typal patients may be spared prefrontal structural deficitsand have greater prefrontal reserves compared to schizo-phrenia patients. One possible explanation for the contra-diction is that samples may differ in comorbidity with anti-

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social personality. In the present community-derived spec-trum sample with relatively high base rates of antisocialbehavior, controlling for group differences in antisocialpersonality disorder abolished the prefrontal gray volumedifference between the spectrum and comparison groupsp = 0.98) and reduced the difference between the spec-trum and psychiatric control groups to a nonsignificantlevel p =0.083). Although significan t co morbidity hasbeen reported between schizophrenia and violent criminalbehavior (Belfrage 1998; Raesaenen et al. 1998; Volavka1999), control for antisocial behavior has rarely, if ever,been included in studies of schizophrenia and spectrumdisorders. On the other hand, group differences in frontalfunctioning remained intact after controlling for antisocialpersonal i ty and at test to the robustness of functionalfrontal deficits in spectrum disorders. Ultimately, patientswith both schizotypal and antisocial/impulsive featuresmay have a somewhat different et iology compared toschizotypal patients lacking these features. Consequently,controlling for antisocial comorbidity in future studies ofschizophrenia and schizophrenia spectrum disorders mayhelp clarify conflicting findings and produce a clearer pic-ture of the unique risk factors for spectrum disorders.

The effect size d) of 0.84 for the structural prefrontalgray volume reduction in the spectrum group compared tothe comparison group is relatively large (Cohen 1988).Although one limitation of the current study is that aschizophrenia patient group with which to compare effectsizes was not included, a recent meta-analysis (Yaralianand Ra ine 2000) observe d an overall effect size of 0.42 forfrontal gray loss in schizophrenia patients compared tocontrols. In comparison, the doubling of the effect size inspectrum individuals could be interpreted as highlightingthe advantage of studying noninstitutionalized spectrumindividuals from the community who do not share themethodological confounds that apply to institutionalizedschizophrenia patients. Alternatively, comorbid antisocialbeha vior m ay contribute to the effect size obtained for pre-frontal structure, although this argument cannot explainthe large effect size of 0.8 found for functional prefrontaldeficits.

In conclusion, schizophrenia spectrum disorder ischaracterized by reduced prefrontal gray volumes andreduced frontal functioning compared to both comparisonand psychiatric control groups. Though these results sup-port the potential etiologic significance of prefrontal struc-tural deficits in schizophrenia, the possibility exists thatthese effects are abolished by careful control for antisocialpersonality, comorbidity that may account for discrepantfindings in the literature. In contrast, in the spectrum groupwe observed functional deficits of equal magnitude thatcannot be accounted for by either structural deficits orcomorbid antisocial behavior.

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Zakzanis, K.K., and Heinrichs, R.W. Schizophrenia andthe frontal brain: A quantitative review. Journal of theInternational Neurological Society, 5:556-566, 1999.Zipursky, R.B.; Lim, K.O.; Sullivan, E.V.; Brown, B.W.;and Pfefferbaum, A. Widespread cerebral gray matter vol-ume deficits in schizophrenia.Archives of General Psychi-atry,49:195-205, 1992.AcknowledgmentsThe authors wish to thank Jennifer Bobier, Nicole Diamond,Kevin H o, Blane Horvath, Shari Mills, and K risten Taylor forassistance in data collection and sco ring, and Keith N uechter-lein for providing the Continuous Performance Test. Thisstudy was supported by grants to the first author from theNational Institute of Mental Health (RO3 MH50940-O1A2,and an Independent Scientist Award K02 M H01 114-0 1).The AuthorsAdrian R aine, D.Phil., is Robert G. W right Professor of Psy-chology, Department of Psychology, University of SouthernCalifornia (USC), Los Angeles, CA. Todd Lencz, Ph.D., isResearch Psychologist, Department of Research, HillsideHospital (North Shore-Long Island Jewish Health System),Glen Oaks, New York. Pauline Yaralian, M.A., is ResearchAssistant; Susan Bihrle, Ph.D., is Research Associate; andLori LaCasse, B.A., is Research Coordinator, Department ofPsychology, USC. Joseph Ventura, Ph.D., is Assistant Pro-fessor, Department of Psychiatry and Biobehavioral Sci-ences, University of California Los Angeles, Los Angeles,CA. Patrick Colletti, M.D., is Chief of Magnetic ResonanceImaging and Professor of Radiology, Department of Radiol-ogy, USC School of Medicine.

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Raine et al,. (2002) - 'Prefrontal Structural and Functional Deficits in Schizotypal Personality Disorder