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REVIEW ARTICLE |
Department of Psychiatry, University of North Carolina at Chapel Hill, North Carolina, USA
Correspondence: Dr R. Grant Steen, Department of Psychiatry, University of North Carolina at Chapel Hill, Campus Box 7160, Chapel Hill, North Carolina 27599-7160, USA. Tel: +1 919 966 8382; e-mail: Grant_Steen{at}med.unc.edu
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ABSTRACT |
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Aims To determine whether patients with a first episode of schizophrenia have characteristic brain abnormalities.
Method Systematic review and meta-analysis of 66 papers comparing brain volume in patients with a first psychotic episode with volume in healthy controls.
Results A total of 52 cross-sectional studies included 1424 patients with a first psychotic episode; 16 longitudinal studies included 465 such patients. Meta-analysis suggests that whole brain and hippocampal volume are reduced (both P<0.0001) and that ventricular volume is increased (P<0.0001) in these patients relative to healthy controls.
Conclusions Average volumetric changes are close to the limit of detection by MRI methods. It remains to be determined whether schizophrenia is a neurodegenerative process that begins at about the time of symptom onset, or whether it is better characterised as a neurodevelopmental process that produces abnormal brain volumes at an early age.
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INTRODUCTION |
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METHOD |
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Studies were included in our analysis if brain MRI volumetric data were reported for both a population of patients with schizophrenia at first episode and a population of healthy controls evaluated concurrently. We excluded seven studies that did not report exclusively on patients with first-episode illness, and five studies that did not report concurrent data from healthy controls. Studies were also excluded if data from patients with first-episode psychosis were not separated from a larger population of patients with psychosis of some other type, or if results included patients with childhood-onset schizophrenia. We specifically excluded children younger than age 13 years from our analysis because there are rapid changes in brain volume among healthy children up to about age 9 years (Pfefferbaum et al, 1994; Giedd et al, 1999), and the young age of patients with childhood-onset illness would make it difficult to control adequately for the effects of normal brain growth. Studies were also excluded if data were reported in a format that did not enable us to calculate patient brain volume as a percentage of the control group volume. Thus, we excluded studies that used voxel-based morphometry, since our calculations are based on volume rather than on number of pixels. We also excluded studies that reported results from a non-volumetric analysis of the data, or from a non-quantitative analysis of the data.
Of the total of 91 articles that were originally identified, 26 were excluded for any of the above reasons. A total of 65 articles were evaluated (Table 1), including 52 cross-sectional and 16 longitudinal studies. Data from all 52 eligible cross-sectional studies were entered into a spreadsheet that tabulated study details, including a brief description of the study, demography of the study populations, patient medications and the statistical analyses used. For patients, additional data were entered summarising the percentage difference in structure volume relative to controls, and whether or not this difference was statistically significant according to the analysis presented in the original reference.
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The data entry process was then repeated for all eligible longitudinal studies. If a longitudinal study reported baseline data in a format that could be analysed as a cross-sectional study, this study was entered into both the cross-sectional and the longitudinal databases. The final database contained approximately 29 084 cells.
Data analysis
We sorted the cross-sectional database by brain structure, to determine
where brain volumetric changes had been sought. Brain volume changes in the
first-episode group were summarised, with respect to controls, on a
structure-by-structure basis (further information available from the author
upon request). We then conducted a meta-analysis of all cross-sectional
studies that measured whole-brain volume in the first-episode group relative
to controls (Table 2). For each
component study in the meta-analysis, we abstracted information about sample
properties (size, mean and standard deviation) from the original paper and
fitted a blocked analysis of variance model (with study as the blocking
factor) to examine group differences. We additionally fitted models with the
groupxtreatment interaction, to assess heterogeneity; interactions were
non-significant in all cases, so we used the models without the interaction
terms. We did similar meta-analyses of cross-sectional studies that measured
differences in hippocampal volume (Table
3) and ventricular volume
(Table 4). Finally, we
summarised all studies that reported longitudinal volumetric changes
significant at P
0.01 (further information available from the
author upon request), to address the issue of which longitudinal changes are
most robust by statistical criteria.
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RESULTS |
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A total of 52 studies were included in the cross-sectional analysis (Table 1), these studies involving 1424 patients with first-episode schizophrenia (30.3 patients per study, s.d.=16.5) and 1315 healthy controls (28.0 controls per study, s.d.=10.7). A total of 16 studies were included in the longitudinal analysis, these studies involving 465 patients (33.2 patients per study, s.d.=26.9) and 240 healthy controls (17.1 controls per study, s.d.=8.8). The average age of patients across all studies was 26 years. Even after excluding studies that comprised only male patients (reasoning that a study with a sample composed only of men must have made an effort to exclude women), roughly two-thirds of patients were men, suggesting that males are more common among young patients with first episodes of schizophrenia.
Relatively few brain structures have been evaluated in multiple studies (further information available from the author upon request); of 14 comparisons that showed a significant volumetric decrease in grey matter of patients brains, only 6 comparisons were replicated more than three times. Most volumetric studies were small, even when the focus was a structure in which measurement error could be substantial. The total number of patients evaluated per structure, averaged across all 14 central grey matter structures, was 97.6 (s.d.=82.5), but it was only 65.5 (s.d.=47.6) if amygdala, hippocampus and the amygdala hippocampal complex were excluded. Most volumetric changes that are significant relate to grey matter, and more findings relate to central than to peripheral (cortical) grey matter. Virtually all significant volumetric differences from normal in grey matter are patient deficits in volume, compared with controls.
Cross-sectional studies that measured whole-brain volume deficits in patients with first-episode schizophrenia are summarised in Table 2. For this particular comparison there have been 21 studies, with a large number of participants (patients, n=524; controls, n=650), but only 4 studies found significance. Meta-analysis showed that the average patient brain volume was 2.7% smaller than the average control brain volume (P<0.0001). Group (patient v. control) and study differences together account for 57% of the variation in brain volume, but group differences alone were able to account for less than 1% of the variation in brain volume (P<0.0001). Thus, there was a significant variation in brain volume between studies (P<0.0001), although there was no significant study heterogeneity.
There was variation in the number (and type) of covariates used in the various studies of brain volume, suggesting that it may be problematic to pool studies in a single meta-analysis. Nevertheless, the number of statistical covariates used in analysis did not seem to be related to the level of statistical significance obtained. The 4 studies that found significance had an average of 2.0 covariates, whereas the 17 non-significant studies had an average of 2.2 covariates.
Cross-sectional studies that measured hippocampal volume deficits in patients with first-episode schizophrenia are summarised in Table 3. There have been 10 separate studies of the hippocampus, with total participant numbers of 300 patients and 287 controls. Meta-analysis shows that the volume deficit in patient hippocampus is about 8% on both right and left sides (P<0.0001). This deficit is somewhat larger than the 4% volume deficit reported in a meta-analysis of hippocampal volume in patients with chronic schizophrenia (Nelson et al, 1998). Group and study differences together accounted for 64% of the variation in hippocampal volume, but group differences alone were able to account for only 2% of this variation (P<0.0001). Study-related variation in hippocampal volume was significant (P<0.0001), without significant study heterogeneity.
Cross-sectional studies that measured the lateral or third ventricles in patients with first-episode schizophrenia are also summarised (Table 4). There have been 11 studies of ventricular volume, with total participant numbers of 204 patients and 209 controls. Meta-analysis shows that the lateral ventricle volume surplus in patients is about 34% on the left side and 25% on the right side (both P<0.0001). Group and study differences together account for 31% of the variation in ventricular volume on the left side and 26% on the right side (both P<0.0001), with group differences accounting for 6% or less of the variation in ventricular volume (both P<0.0001). For third ventricle measurements, group and study differences together accounted for 68% of the variation in third ventricle volume (P<0.0001), with group differences accounting for 4% of the variation in ventricular volume. Study-related variation in ventricular volume was significant (all P<0.0001), without significant study heterogeneity.
We summarised robustly significant (P
0.01) findings from
longitudinal studies of brain volume change in patients (further information
available from the author upon request). This compilation demonstrates that
longitudinal studies are generally of recent vintage; of eight studies
recorded, five were published within the past 5 years. Several longitudinal
changes in the volume of the brain were robustly significant after diagnosis,
including a significant decrease in volume of the whole brain after diagnosis.
No significant longitudinal change was identified in white matter or
cerebellum, so longitudinal changes in whole-brain volume may be limited to
the grey matter.
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DISCUSSION |
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Whole-brain volume deficits
Whole-brain volume differences between first-episode cases and controls are
apparently quite subtle (Harrison et
al, 2003). Cross-sectional studies that measured whole-brain
volume reported an average volume deficit in the first-episode group of less
than 3% (see Table 2), despite
a large sample size. This finding agrees well with a study of brain weight at
autopsy, in which 540 older patients with chronic schizophrenia were compared
with 794 controls (Harrison et
al, 2003). This study found that the brain weight of patients
with chronic disorder was 2% less than that of healthy controls
(P=0.04), but that disease-related differences were far less
significant than brain weight differences attributable to either age or gender
(both P<0.0001). No correlation was found between brain weight and
the duration of psychosis, which may mean that brain atrophy is not
progressive after diagnosis (Harrison
et al, 2003).
It is critically important to determine when whole-brain volume deficits in patients with schizophrenia first become significant, as this could have bearing on the aetiology of the disorder (Harrison, 1999). If whole-brain volume becomes abnormal early in childhood, this would suggest a neurodevelopmental aetiology; alternatively, if whole-brain volume becomes abnormal shortly before the onset of symptoms or even after symptoms have developed this would suggest a neurodegenerative aetiology. Population-based data suggest that head size is abnormal at birth among those who later develop schizophrenia, compared with controls (Ward et al, 1996; Harrison, 1999). Research in the offspring of people with schizophrenia, in people at high genetic risk of this disorder or in patients in its prodromal phase might help to address this aetiological question.
When does volumetric change occur?
Some brain structures in people with first-episode schizophrenia appear to
show a volumetric deficit that is significant at diagnosis and that is also
progressive over the later course of illness. For example, the lateral
ventricles are significantly larger than normal at diagnosis
(Table 4) and ventricular
volume tends to increase significantly in longitudinal studies. Volumetric
deficits at diagnosis are seen in the hippocampus
(Table 3), in cortical grey
matter, in Heschls gyrus, in the planum temporale and in temporal grey
matter, and all of these structures also show continued volumetric loss over
time (further information available from the author upon request).
Some brain tissues appear to show a volumetric deficit at diagnosis, but the deficit may not progress over time. For example, there are volumetric deficits in the thalamus at diagnosis, according to four studies, but no longitudinal change has yet been described. Similarly, volume deficits in the insula are significant at diagnosis, according to two studies, but no longitudinal change has been described. This may mean that volumetric changes in the thalamus and insula are indeed not progressive, or it may mean that there are simply too few longitudinal studies to identify a progressive volume loss that is actually present in these structures.
Imaging difficulties
There are a great many difficulties in measuring brain volumes of patients
with schizophrenia by MRI. A major problem is that the volumetric loss in
patients is no more than 4% per year (further information available upon
request), which may be close to the limit of detection by MRI, given the
precision of volumetric methods (Howard
et al, 2003; MacFall
et al, 2004). A longitudinal study of a volume phantom
found that changes of up to 5% could be introduced by changes in scanner
hardware or software (MacFall et
al, 2004). Such machine drift can have an
impact on volume measurement, as shown by a study of intracranial content in
113 healthy elderly participants (MacFall
et al, 2004). Although the intracranial content cannot
change after the cranial sutures close
(Pfefferbaum et al,
1994; Giedd et al,
1999), error in its measurement averaged ±1.5%
(MacFall et al,
2004). This error could be corrected but, in the absence of
correction, would confound any longitudinal measurement of brain volume
(MacFall et al,
2004). In studies that control for intracranial volume,
imprecision or inaccuracy may not have a major impact, but poor precision or
low accuracy in even a subset of volumetric studies would lead to a lack of
consensus among the various studies.
Imprecision or inaccuracy in the measurement of brain volume can arise in many ways. Perhaps the most likely source of error is voxel misclassification during brain segmentation (Wang & Doddrell, 2002). Voxels classified as one tissue type could, with a relatively minor change in tissue T1 or T2, be classified as another tissue type (Steen et al, 1997). A second major issue is the familiar partial volume problem; since several tissues can occur in a volume much smaller than a typical imaging voxel, this would introduce error into the volume estimate of any tissue type (Tofts et al, 1997; Ballester et al, 2000; Wang & Doddrell, 2002), and could potentially change the proportional allocation of tissue to tissue type. A third problem is the inconspicuousness of tissue edges; this type of error is really another type of partial volume error that would primarily affect the estimate of grey matter volume, since this often has poorly defined edges with cerebrospinal fluid. Error in the measurement of grey matter volume would change the estimate of total brain volume, so controlling for brain volume would not necessarily eliminate machine drift in a longitudinal study. A fourth issue is head tilt, or angulation of the imaging slab over the brain, since different volumes of brain may be interrogated in different imaging examinations. This problem can only be overcome by striving for full brain coverage during an examination. Finally, non-systematic non-systematic errors (mistakes) can be made during the complex analytic process that is required for MRI volumetry (Haller et al, 1997). In short, because error can be substantial and because brain volumetric changes from normal in patients with first-episode schizophrenia appear to be quite small, some of the differences reported between patients and controls (Tables 2, 3, 4) are probably artefactual.
Clinical difficulties
A great many clinical difficulties complicate a volumetric search for the
causes of schizophrenia. An enormous problem is that patients are typically
treated with antipsychotic medications as soon as possible after diagnosis.
Different patients may receive different medications at different dosages, and
such treatment heterogeneity is almost impossible to eliminate. This makes it
essential to determine whether there are acute effects of medication on total
brain volume (DeLisi et al,
1991; Chakos et al,
1994; Gur et al,
1998). If brain volumetric changes in response to medication are
rapid, then the length of time between first medication and imaging evaluation
could be a major confounder. Antipsychotic medication has been postulated to
have an effect on basal ganglia volume in as little as 6 months
(Chakos et al, 1994),
and it is possible that brain volumetric change in response to medication
occurs even more rapidly. A further difficulty inherent to studying
first-episode cases is that some patients may have been symptomatic, but
undiagnosed, for a long time. If progressive brain volume changes are rapid in
the period surrounding diagnosis, then the duration of undiagnosed illness
would be a serious confounder. However, since no consistent relationship has
been found between duration of illness and brain volume loss
(Harrison et al,
2003), this may be less likely.
Recruiting patients with schizophrenia can be time-consuming, difficult and expensive, since many are unable or unwilling to comply with study requirements. Another problem is that brain structure may be weakly correlated with brain function, so that substantial variation in brain volume could be found in the absence of any variation in brain function (Uttal, 2001). These two problems together probably account for why so many studies of brain volume appear to be underpowered (Table 2). Many studies lack a sample size sufficient to test hypotheses that relate to what may be an inherently weak relationship, especially given the limitations of the methods (Haller et al, 1997; Howard et al, 2003; MacFall et al, 2004). To complicate the picture further, there may be genetic heterogeneity within the diagnosis, such that patients in a single study might actually have different diseases that converge in causing psychotic symptoms.
Concluding remarks
The most robust volumetric findings in patients with schizophrenia are
those of grey matter volume loss (Table
3) and ventricular volume increase
(Table 4), and these findings
are probably linked. In monozygotic twins discordant for schizophrenia, there
is a correlation between reduced left temporal grey matter volume and
increased volume of cerebrospinal fluid in the left temporal horn, suggesting
that loss of grey matter leads to an increase in ventricular volume
(Suddath et al,
1989). Many more longitudinal studies of brain volume change in
patients with first psychotic episodes are needed to determine which tissues
are prone to the atrophy that manifests as ventricular volume increase.
This review confirms that grey matter deficits are present in patients with first-episode psychosis (Hulshoff-Pol et al, 2001), whereas white matter changes have seldom been described (Sanfilipo et al, 2000; Hulshoff-Pol et al, 2004). Yet it is still not known whether changes in grey matter volume at first episode are associated with disease progression itself or with the many correlates of disease, including antipsychotic medication, alcoholism, drug misuse, malnutrition or even social deprivation. Both alcoholism (Joyce, 1996) and malnutrition (Swayze et al, 1996) are associated with acutely reversible changes in brain volume. Such volumetric changes are postulated to result from changes in brain water content, secondary to systemic hydration or serum protein content (Joyce, 1996; Swayze et al, 1996). Similar hydration mechanisms could be important in schizophrenia, since many patients suffer from malnutrition, dehydration and exposure (Shenton et al, 2001), so it is important to control for such environmental effects in studies.
It remains to be determined whether schizophrenia is a neurodegenerative process that begins at about the time of symptom onset and manifests as progressive volumetric loss thereafter, or whether it is better characterised as a neurodevelopmental process that results in abnormal brain volume beginning at an early age (Maynard et al, 2001).
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ACKNOWLEDGMENTS |
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Received for publication November 16, 2004. Revision received July 12, 2005. Accepted for publication August 18, 2005.
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