Cerebellar morphology as a predictor of symptom and psychosocial outcome in schizophrenia

Cerebellar Morphology as a Predictor of Symptom and Psychosocial Outcome in Schizophrenia Thomas H. Wassink, Nancy C. Andreasen, Peg Nopoulos, and Michael Flaum Background: In this study, we examined whether brain morphology assessed early in the course of schizophrenia predicted psychosocial or symptomatic outcome. Methods: We acquired magnetic resonance images on 63 subjects with schizophrenia spectrum disorders and manually traced regions of interest, including the cerebrum, temporal lobes, ventricles, and cerebellum. Subjects were then prospectively assessed every 6 months for an average of 7 years. Outcome symptom measures were longitudinal rather than cross-sectional, and included average number of weeks per year spent in a psychotic, negative, or disorganized symptom syndrome, and average number of weeks of inpatient treatment per year. A psychosocial outcome measure summed ratings of impairment in employment, recreation, sexual activity, and interpersonal relationships. Results: Negative associations were found between cerebellar volume and three outcome measures: negative and psychotic symptom duration, and psychosocial impairment. Conclusions: These results underscore the potential role of cerebellar abnormalities in the etiology and pathophysiology of schizophrenia. Biol Psychiatry 1999;45: 41– 48 © 1999 Society of Biological Psychiatry Key Words: Schizophrenia, cerebellum, symptom dimensions, psychosocial outcome

Introduction

S

ubjects with schizophrenia have consistently been shown to have abnormal morphology of various brain structures (Gur and Pearlson 1993). Associations between these abnormalities and the signs, symptoms, and psychosocial disturbances of the illness have also been extensively examined (Andreasen and Olsen 1982; Andreasen et al 1986; Barta et al 1990; Marks and Luchins 1990;

From the Mental Health Clinical Research Center, Department of Psychiatry, University of Iowa Hospitals and Clinics, University of Iowa College of Medicine, Iowa City, Iowa. Address reprint requests to Dr. Thomas H. Wassink, University of Iowa Hospitals and Clinics, Department of Psychiatry, 2911 JPP, 200 Hawkins Dr., Iowa City, IA 52242. Received October 7, 1997; revised March 25, 1998; accepted May 7, 1998.

© 1999 Society of Biological Psychiatry

Shenton et al 1992; Flaum et al 1995a). The clinically interesting question, however, of whether initial brain morphology can predict future functioning has received scant attention. This is most likely because early-onset subjects are difficult to ascertain, and longitudinal follow-up is both labor intensive and expensive. Most previous studies addressing relationships between brain morphology and outcome have cross-sectionally assessed chronic patients later in the course of their illnesses (Nasrallah et al 1983; Owens et al 1985; Bilder et al 1988; Pandurangi et al 1988; Schroder et al 1995; Turetsky et al 1995). Frequently, however, the ventricleto-brain ratio (VBR) as assessed by computerized tomography (CT) was the only measure of brain morphology, and outcome was often evaluated by comparing current functioning with retrospective estimates of premorbid function. In addition, the effect of illness duration on the size of brain structures (i.e., whether the neuropathological process is static or active) remains quite controversial (Lieberman et al 1996; DeLisi et al 1997), bringing into question the ability of such studies to answer questions of predictive validity. Prospective studies, where brain magnetic resonance images taken near the onset of illness can be examined for their effects on longitudinal outcome, are quite rare. Vita et al, examining 18 subjects with chronic schizophrenia, assessed outcome 2 years after an initial CT scan. They found significant differences between those with and those without initial ventricular enlargement and cortical atrophy on measures of useful employment and intimacy of interpersonal contacts assessed at follow-up (Vita et al 1991). DeLisi et al, in a study of 30 first-episode subjects, assessed whether initial temporal lobe or ventricular size as measured by magnetic resonance imaging (MRI) could predict outcome, and found positive correlations between ventricular size at intake and number of hospitalizations and time spent in hospital over the following 2 years (DeLisi et al 1992). Two subsequent studies from their group examined relationships between clinical measures and changes in brain morphology as assessed by serial MRIs (DeLisi et al 1995, 1997). The first, performed on 20 patients and 5 controls, gathered information that included a neuropsychological battery and an MRI approximately 0006-3223/99/$19.00 PII S0006-3223(98)00175-9

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every year for 4 years, and a Global Assessment of Function Scale (GAF), duration of hospitalization and medication use, and an unspecified estimate of symptom duration at the 4-year follow-up. Change over time in neuropsychological measures of left hemispheric function was found to be negatively correlated with change over time in measures of both right and left hemispheric volume, so that the greater the reduction in brain size, the smaller the improvement in left hemispheric functioning. None of these correlations, however, remained significant when corrected for multiple testing (DeLisi et al 1995). A follow-up study, performed on a larger cohort of subjects but without the neuropsychological battery, corroborated these negative results, finding no significant correlations of clinical measures with structural brain changes (DeLisi et al 1997). Lastly, Mozley et al, in a sample of 59 subjects with a duration of illness at intake of 6.8 years, found no association between brain cerebrospinal fluid (CSF) volume assessed with MRI and two psychosocial outcome scales administered 2 years later (Mozley et al 1994). Of these studies, that by Vita et al was the only one where clinical outcome was the focus of the investigation. The measures of symptom and psychosocial outcome tended to be quite limited and were almost exclusively cross-sectional. Symptoms are much more variable than brain structure, fluctuating markedly over time in an unpredictable manner (Carpenter et al 1987; Carpenter 1991; Klimke and Knecht 1992). A cross-sectional assessment, therefore, provides only a snapshot of the subject’s current symptom state rather than an accurate assessment of underlying symptom traits. This is reflected in the instability of schizophrenia subtypes, with subjects appearing primarily paranoid, disorganized, or undifferentiated at various stages of illness (Kendler et al 1985; Deister and Marneros 1993). The study presented here, therefore, attempts to extend the findings of these others by examining relationships between initial brain morphology and more substantial measures of outcome. We obtained brain MRI images from subjects with schizophrenia spectrum disorders early in the courses of their illnesses. Four regions of interest (ROIs) were examined, including the cerebrum, cerebellum, ventricular system, and temporal lobes, each of which has been shown to be associated with various psychopathological correlates of illness. Our research center has taken a special interest in the role of the cerebellum in cognition and schizophrenia. Based on data from our functional imaging studies, as well as accumulating evidence supporting the involvement of the cerebellum in higher cognition (Andreasen et al 1993, 1995b; Paradiso et al 1997a), we have proposed that the cerebellum is a primary node in a distributed neural circuit which, when dysfunctional, leads to a fundamental cognitive deficit

underlying the varied signs and symptoms of schizophrenia (Andreasen et al 1996a, in press). Subsequent to intake, subjects were assessed prospectively at regular, frequent intervals for up to 10 years (average follow-up of 6.9 years). To provide an average measure of long-term functioning, we constructed a time line that recorded week by week the severity of the full range of symptoms associated with schizophrenia. These symptoms were grouped into the psychotic, negative, and disorganized symptom groups, which have repeatedly been shown by our group and others to cluster as independent dimensions of schizophrenic psychopathology (Bilder et al 1985; Andreasen and Grove 1986; Liddle 1987). The ratings, therefore, enabled us to determine whether a subject had severe levels of one or more of three symptom groups for each week of the follow-up period. Thus, instead of volatile cross-sectional measures of current state, we were able to measure the duration of psychopathology over an extended period of time, thereby better reflecting underlying symptom traits. We also examined two other measures of outcome: time spent as an inpatient (hospitalized or institutionalized), and psychosocial outcome. Time spent as an inpatient was quantified with the time line, and psychosocial outcome was examined with measures that, while cross-sectional in nature, incorporated numerous categories of functioning into a comprehensive summary measure.

Methods and Materials Subjects All subjects included in these analyses were evaluated through the Mental Health Clinical Research Center (MHCRC) and were enrolled in a prospective longitudinal study of recent-onset psychosis described previously (Flaum et al 1992). Subjects were recruited if they appeared to be experiencing the early stages of a psychotic illness and were excluded if they had their first hospitalization more than 5 years prior to intake or had a history of significant neurological illness or head injury with loss of consciousness. For the analysis presented here, we selected those subjects with a schizophrenia spectrum disorder (i.e., schizophrenia, schizoaffective disorder, schizotypal personality disorder, delusional disorder, or psychotic disorder not otherwise specified) who had completed an MRI scan at intake with the sequence specified below and who had subsequently been followed prospectively for at least 4 years. Follow-up data are available for a much larger sample, but subjects enrolled after the first 3 years of the study were scanned with a different sequence that leads to different measurement characteristics, making it inappropriate to pool their data with those of the earlier subjects. All subjects gave written informed consent to participate in the study. Sixty-three subjects were appropriate for inclusion, of whom 47 (74.6%) were male and 16 (25.4%) female. The DSM-IV

Cerebellum and Outcome in Schizophrenia

breakdown of the sample, as diagnosed at most recent follow-up, was as follows: schizophrenia, n 5 53; schizoaffective disorder, n 5 6; schizotypal personality disorder, n 5 2 (primary diagnosis); psychotic disorder not otherwise specified, n 5 1; and delusional disorder, n 5 1. Their average age at onset of illness was 22.8 years (65.4), while their average age at the time they received their MRI was 25.7 years (65.7), giving an average duration of illness between onset and MRI of 2.8 years (63.3). Onset of illness was defined as onset of a full psychotic syndrome, consisting of moderate to severe hallucinations or delusions. Thirty-one subjects (49.2%) had their first hospitalization at the time of intake, and the average number of hospitalizations prior to intake was 1.3 (61.8). The average length of the follow-up period after acquisition of the MRI was 6.9 years (61.5).

Clinical Measures At intake, demographic, symptom, and psychosocial measures were gathered using the CASH (Andreasen et al 1992a) and its companion instrument, the PSYCH BASE (Andreasen 1987a). Every 6 months thereafter, subjects were assessed with follow-up versions of the CASH and PSYCH [CASH-UP and PSYCH-UP (Andreasen 1987b)]. The instruments were completed using all available sources of information by research nurses and experienced research assistants, each of whom participates in ongoing reliability and calibration checks. A weekly time line embedded in the PSYCH-UP was used to assess symptom dimension duration by measuring the number of weeks that each of three symptom dimensions was present at a clinically significant level. In this timeline, items corresponding to the SANS/SAPS (Andreasen 1983, 1984) global items were rated by the subject and an informant for every week of the interval periods, using a score ranging from 0 (none) to 5 (severe). These global ratings were then grouped into three symptom dimensions, psychotic, negative, and disorganized, which have repeatedly been shown to cluster independently (summarized in Andreasen et al 1995a). The psychotic dimension included hallucinations and delusions, the disorganized dimension included positive formal thought disorder, bizarre/ disorganized behavior, and inappropriate affect, and the negative dimension included affective flattening, alogia, avolition/apathy, and anhedonia/asociality. A subject was deemed to have experienced clinically significant psychopathology during a particular week if, for the psychotic and disorganized dimensions, he/she had at least one of the global items rated as moderately severe (score of 3 or greater) and, for the negative dimension, at least two of its items rated as moderately severe. The time line also recorded inpatient treatment (hospitalization or institutionalization) for each week of follow-up. The total number of weeks spent in each symptom syndrome and as an inpatient during the entire follow-up period was then summed and, to account for variable lengths of follow-up, converted to average number of weeks per year. To assess psychosocial outcome, we used data from the most recent follow-up evaluation for each patient. A comprehensive measure was constructed which summed four variables: quality

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of relationships, sexual activity, enjoyment of recreation, and work performance. These variables used the following scales: relationships was the average score of quality of relationship with mother, father, relatives, and friends, each rated from 1 to 5; sexual activity was rated from 0 to 3; enjoyment of recreation was rated from 1 to 5; and work performance was rated from 1 to 6. Lower scores indicated less impairment and better functioning.

MRI All subjects were scanned with a 1.5-T GE Signa magnetic resonance scanner. Coronal images were obtained perpendicular to the anterior commissure–posterior commissure line using a multiecho, flow-compensated pulse sequence with a 26-cm field of view, nose to ear to xiphoid 5 1, and a 256 3 192 matrix size. The sequence spanned the cranium with 5-mm slice thickness and 2.5-mm gaps (repetition time 5 2700 msec), and produced both proton density (PD)-weighted images [echo time (TE) 5 30 msec]) and T2-weighted images (TE 5 90 msec). After acquisition, the data were archived on magnetic tape and transferred to an optical disk, and all subsequent image processing was performed on a Silicon Graphics workstation using locally developed software (Andreasen et al 1992b). Regions of interest were defined and tracing guidelines developed (Flaum et al 1995b). The tracing strategy involved tracing each ROI on the T2-weighted slices, with the technologist checking the tracing with the corresponding PD-weighted images to confirm gray/CSF and white/CSF boundaries. All tracings were performed by a single, experienced technologist blind to any clinical information about the subjects. To assess intrarater reliability, 21 randomly selected sets of MRI images were blindly retraced by the same rater. Only those ROIs for which the intraclass r was ..75 were included in the current analyses. This included the cerebrum (r 5 .99), cerebellum (r 5 .89), ventricular system (r 5 .95), and temporal lobes (r 5 .89). Interrater reliability had been previously established by having the technologist and two other trained raters, both psychiatrists here with extensive experience in tracing brain structures, trace nine arbitrarily selected brains from our data pool. Interrater reliability was .99 for the cerebrum, .70 for the cerebellum, .76 for the temporal lobes, and .98 for the ventricular system (Arndt et al 1991). After completion of tracing, ROI volumes were calculated by multiplying the number of pixels within the ROI by the slice thickness and summing this product across all slices. As the slices were noncontiguous, the pixel was assumed to be in the center of the slice.

Statistical Analyses To control against spurious findings from multiple tests, we conducted the analysis in two stages. We first tested whether there was an overall effect of the entire group of outcome variables on each ROI and, where there was, we examined the individual relationships between those ROIs and each outcome variable. The initial test was a joint omnibus test that assessed the effect

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Table 1. Medians and Interquartile Ranges of Outcome Variables Variable Psychosocial outcome Weeks per year as an inpatient Weeks per year in a psychotic syndrome Weeks per year in a negative syndrome Weeks per year in a disorganized syndrome

Median

Interquartile range

14.00 0.67 6.17 42.75 2.24

11.25–15.50 0.14 –3.00 0.33–32.57 19.27–52.00 0.33–9.69

Medians and interquartile ranges are reported, as these variables were not normally distributed.

of all outcome variables simultaneously. One joint test was done for each ROI. The test included all five outcome variables and controlled for cranial volume, age at MRI, and duration of illness between onset and MRI. A multiple regression was performed that first forced in these three covariates and then added the five outcome variables. The combined analysis with the five outcome measures offered the omnibus test with 5 df, with the resulting p value for the F statistic estimating the significance of any increase in the amount of variance in the ROI accounted for by the inclusion of the outcome measures. To control for multiple testing, the p value threshold for this F statistic was set at p 5 .05/4 5 .0125 (four omnibus tests were performed, one for each ROI). For those ROIs meeting this level of significance, relationships between the ROI volumes and outcome measures were assessed independently. Analyses of covariance were performed using the same covariates, ROI volume as the dependent variable, and the outcome measures as independent variables. Analyses were conducted separately for time spent hospitalized/institutionalized and psychosocial outcome, while the three symptom dimension measures were placed in the same model. Thus, the relationships between the ROI volumes and each symptom dimension were also controlled for the severity of the other two dimensions. Two other statistical items were noteworthy. First, as the symptom dimension variables were summary measures of time (i.e., number of weeks per year), they were not normally distributed. The distributions of the covariates measuring age at onset and duration of illness were also not normal. Ranked values were therefore used for these measures in all analyses. Second, the choice of covariates to use when analyzing brain ROIs remains controversial (Arndt et al 1991). For larger structures, the degree of intercorrelation with cranial volume may be so great as to dissipate any meaningful variance in the size of those structures when cranial volume is the covariate. Some have advocated, therefore, covarying for height instead of cranial volume in these instances. Thus, while we covaried for cranial volume in all analyses, we also reperformed the analyses using height to guard against this.

Results Median and interquartile range values are shown for the outcome variables in Table 1. The negative symptom syndrome was the most persistent of the three, whereas

Table 2. Omnibus Tests for Significance of Variance (R2) Accounted for by Independent Variables Region Cerebrum Cerebellum Temporal lobes Ventricles

R2 added

F

df

p

.003 .15 .053 .104

0.67 3.36 1.61 1.40

5,54 5,54 5,54 5,54

.65 .01 .17 .24

subjects spent the least amount of time in a disorganized state. Results for the omnibus tests are shown in Table 2. The only test to achieve the threshold level of significance was the cerebellum (F 5 3.36, df 5 5,54, p 5 .01). The outcome variables did not account for a significant amount of the variance in any of the other three ROIs. Thus, the cerebellum was the only ROI examined for specific relationships with the outcome variables. The results of these tests are shown in Table 3. Cerebellar volume was shown to be related to level of psychosocial impairment and also to duration of the negative and psychotic syndromes. Partial correlation analyses demonstrated that smaller cerebellar volume was associated with greater psychopathology in all three cases (see Table 3). Also, as the symptom syndromes were examined in the same model, their effects were shown to be independent of each other. As noted above in the Methods section, all analyses were also performed using height as a covariate in place of cranial volume. In no instance did this produce significantly different results (data not shown).

Discussion This study is one of only a few, to our knowledge, to prospectively examine relationships between initial brain morphology, duration of symptoms, and psychosocial outcome. The primary brain region implicated, of the four that were studied, was the cerebellum, with cerebellar size early in the course of illness found to be negatively correlated with persistence of both more severe psychotic Table 3. Analyses of Covariance Relating Cerebellar Volume to Outcome Variables Variable a

Weeks per year in a negative syndrome Weeks per year in a psychotic syndromea Weeks per year in a disorganized syndromea Weeks per year as an inpatient Psychosocial impairment

F

p

Partial r

7.21 6.26 0.14 0.49 5.35

.01 .02 .71 .49 .02

2.29 2.32 2.29

df 5 1,61. a Symptom syndrome variables were analyzed together to assure the independence of their effects.

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Table 4. Medians and Interquartile Ranges of Outcome Measures for Subjects in the Upper and Lower Thirds of Cerebellar Size Lower tertile group

Upper tertile group

Outcome measure

Med

IQ range

Med

IQ range

Weeks per year in a negative syndrome Weeks per year in a psychotic syndrome Weeks per year in a disorganized syndrome Weeks per year as an inpatient Psychosocial impairment

50.2

(39.8 –52.0)

26.3

(10.1– 46.9)

11.1

(4.8 – 49.3)

2.8

(0.3–26.9)

2.7

(0.2– 8.9)

1.4

(0.4–10.3)

0.7

(0.0 –2.3)

0.7

(0.3–3.2)

15.3

(13.5–16.5)

12.1

(10.6–14.6)

Medians (Med) and interquartile (IQ) ranges are reported, as these variables were not normally distributed.

and negative symptoms. Cerebellar size was also negatively associated with psychosocial impairment at outcome. Thus, a larger cerebellum, in terms of the outcome measures we assessed, was a good prognostic indicator. This is further demonstrated in Table 4, which displays the actual values for these outcome variables for subjects with larger cerebella (upper tertile) versus those with smaller cerebella (lower tertile). Those with smaller cerebella clearly had a longer duration of severe psychotic and negative symptoms and had greater psychosocial impairment at outcome than those with larger cerebella. Evidence has been accumulating in recent years identifying a cerebellar contribution to higher cognitive processes. Cerebellar lesions have produced impairment in language abilities (Silveri et al 1994; Van Dongen et al 1994), learning (Akshoomoff and Courchesne 1992; Akshoomoff et al 1992; Pascual-Leone et al 1993), memory (Appollonio 1993), and planning (Grafman et al 1992), sometimes in the absence of gross motor deficits. Our group has found, in normal controls, a positive association between cerebellar size and various measures of intelligence (Andreasen et al 1993; Paradiso et al 1997a). Functional imaging studies of normal subjects have demonstrated cerebellar activation during cognitive tasks such as memory (Grasby et al 1993; Raichle 1994; Raichle et al 1994; Andreasen et al 1995b, 1995c; 1995d; Nyberg et al 1995), mood induction (Mayberg and Solomon 1995; Paradiso et al 1997b), time perception (Jueptner et al 1995), facial recognition (Andreasen et al 1996a), and problem solving (Kim et al 1994). Complementary evidence, to which the current study is a contribution, has increasingly implicated cerebellar involvement in schizophrenic psychopathology. Postmortem studies have found abnormalities in Purkinje and granule cell number and morphology in subjects with schizophre-

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nia (Weinberger et al 1980; Reyes and Gordon 1981; Stevens 1982). A number of early CT studies found gross morphological abnormalities of the cerebellum (Weinberger et al 1979; Coffman et al 1981; Nasrallah et al 1981; Lippmann et al 1982; Sandyk et al 1991), and structural MRI studies, though less consistent in their findings, have also shown differences between subjects with schizophrenia and controls (Nasrallah et al 1991; Rossi et al 1993). In addition, a small number of functional imaging studies have examined cerebellar metabolism in subjects with schizophrenia. Volkow et al, using positronemission tomography (PET) and carbon-11-2-deoxyglucose, found subjects with schizophrenia to have lower metabolism in the cerebellum than normal controls (Volkow et al 1992). In O15H2O PET studies from our lab, subjects with schizophrenia were found to have decreased cerebellar blood flow, in comparison to controls, when performing tasks testing various aspects of short- and long-term memory (Andreasen et al 1995b, 1996b). These same subjects also had prominent blood flow abnormalities in thalamic and prefrontal regions. Therefore, we have recently proposed a model of schizophrenia as being due to a disturbance in a distributed neural circuit, producing a fundamental cognitive deficit that underlies the varied signs and symptoms of schizophrenia. The circuit hypothesized to be dysfunctional is the cortical– cerebellar thalamic– cortical circuit (CCTCC), a well-established anatomical entity in which the cerebellum, thalamus, and cortical regions interact as a feedback loop that permits coordination of both motor and cognitive activities (Leiner et al 1989; Middleton and Strick 1994; Schmahmann and Pandya 1997). The cerebellum, as part of this circuit, is felt to act as a cognitive “metron,” guiding the fine-tuning of mental activities much as it does for physical activities. Dysfunction of this circuit, therefore, leads to a specific cognitive deficit, termed “cognitive dysmetria,” which is characterized by incoordination in the processing, prioritization, retrieval, and expression of information. This type of cognitive abnormality could potentially produce the full spectrum of manifestations of schizophrenia (for a full summary of this model, see (Andreasen et al 1996a, in press). A neural circuit model such as this, rather than viewing structure–function relationships as isolated, one-to-one associations, predicts a broad range of manifestations when the circuit is dysfunctional. The data from the current study, where cerebellar dysmorphology is associated with increased duration of two independent symptom dimensions and with greater psychosocial impairment, fit such a model. If examined from a one-structure– onefunction perspective, the finding would seem muddled and nonspecific. When placed within a neural circuit model, however, the findings support the idea that a functional

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cerebellum is involved in a circuit that maintains a primary cognitive process which, when disrupted, can give rise to a broad diversity of symptoms.

Limitations Interpretation of this study is subject to a number of limitations. First, within the context of the proposed model of cognitive dysmetria, we were only able to examine one of the proposed nodes of activity, as neither the thalamus nor the prefrontal cortex were able to be traced with adequate reliability. Thus, though multiple associations were found with the cerebellum, our inability to examine these other regions limits our ability to cite the current findings as clear support for the model. At best, we can say that these findings conform to or are compatible with cognitive dysmetria. A second limitation is that the imaging protocol used in this study has become somewhat outdated. This, unfortunately, is one of the consequences of performing longitudinal analyses, especially in the current study where the average follow-up period was almost 7 years. By the time analyses are performed, the original technology, which at the time was state of the art, has been significantly improved. Nonetheless, our use of 5-mm MR slices with 2.5-mm interslice gaps is as good as or better than virtually all previous imaging studies of either the cerebellum in schizophrenia or of long-term symptom and psychosocial outcome in relationship to initial brain morphology. A third potential limitation stems from the retrospective nature of the time line information, where every 6 months symptom severity and treatment status were rated for each week of that follow-up period. Ratings for the early weeks in each period could, presumably, have been less reliable than for the weeks closer to the times of assessment. Subjects could also have had a global sense of psychopathology but have had difficulty discriminating specific symptoms from one another. A number of factors, however, mitigate against these potential biases. First, ratings incorporated interviews with both probands and informants (usually a parent), as well as information from medical records, to guard against bias or lack of insight from proband-only ratings. Second, though the time line does not use the SANS/SAPS instrument per se, it is intimately related, consisting of all the global SANS/SAPS items rated on the same 5-point rating scale, with all raters here being extremely familiar with these items. Third, a previous publication from these data has demonstrated that the three symptom dimensions fluctuated independently over time (Arndt et al 1995), indicating that the raters were able to discriminate the various symptoms instead of making global, covarying estimates of symptom severity. The methods of the current study also contribute to its

reliability. First, instead of using the actual rating numbers, the scales were dichotomized to either none/mild or moderate/severe symptomatology. Thus, rather than comparing values along a continuum, we measured whether subjects were in a syndrome or not. Second, as the values of the outcome measures were not normally distributed, we used their ranked values in all analyses. Thus, the relative duration of the symptom syndromes was examined in place of the exact number of weeks spent in a particular symptom syndrome.

Conclusion Support is gathering for the hypothesis that cerebellar dysfunction contributes to the psychopathology of schizophrenia, with the current study providing further evidence for this notion. The findings are interpreted in the context of a model of illness positing cerebellar involvement in a neural circuit, dysfunction of which produces a primary cognitive deficit that underlies the varied signs and symptoms of schizophrenia. Future studies using more advanced imaging protocols and neurocognitive measures more attuned to the cerebellum will be required to replicate these findings and delineate them in finer detail.

This research was supported in part by NIMH grants MG-31593 and MH-40856; MHCRC grant MH-43271; the Nellie Ball Trust Research Fund, Iowa State Bank and Trust Company, Trustee; and NIMH Research Scientist Award MH-00625.

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