In this paper, we have shown that OLZ and HAL differ in terms of their association with the trajectory of gray matter change in schizophrenia. The mechanisms for this difference may include altered neurotoxic or enhanced neuroprotective effects, among other interpretations. Whether this association reflects either reduced neurotoxicity or neuroprotection cannot be addressed by imaging data collected from living patients, and we emphasize that it remains speculative at this point. In addition, it is possible that the volume changes relate to glial and not neural components, as suggested by studies of these same 2 medications in monkeys’ brain (Selemon et al. 1999
; Wang et al. 2004
These trajectories of schizophrenia progression, visualized here for the first time for different treatments, are remarkable for 3 reasons. First, patients treated with HAL exhibited a parietal-to-frontal wave of gray matter loss, intensifying in scans acquired 3 and 6 months after their first psychotic episode, but attenuating by 12 months. In our adolescent-onset study, cortical deficits also spread anteriorly in the brain over a 5-year period (Thompson et al. 2001
). The trajectory is essentially the opposite to the neurodegenerative pattern in Alzheimer's disease, where cortical degeneration spreads from the medial temporal lobe entorhinal cortex in a forward wave through the limbic system, consistent with the spread of neurofibrillary tangles and amyloid pathology (Thompson et al. 2004
). Atrophic rates in Alzheimer's Disease are also roughly twice as fast as the fastest changes seen here. Frontal deficits worsened in prior longitudinal studies of schizophrenia that did not distinguish between patients receiving different neuroleptics (Ho et al. 2003
), and are consistent with the extensive literature on frontal lobe dysfunction in first-episode, at-risk, and prodromal subjects (Cannon et al. 2003
; Narr et al. 2005
; Vidal et al. 2006
). The second surprising finding of this study is that OLZ-treated patients showed significant progressive gray matter reductions, but in a more restricted anatomical pattern than in HAL-treated patients. Third, symptom measures did not correlate with the extent or rate of gray matter reduction. This may be due to lack of power, as our prior assessment of the full sample (Lieberman et al. 2003
= 161) showed that 1) in HAL-treated patients, less improvement in neurocognitive functioning was associated with greater decrease in gray matter volumes; and 2) in OLZ-treated patients, greater improvements in PANSS total and negative scores were associated with less lateral ventricular volume increase. Symptoms were reduced in both treatment groups (), and functional recovery—whose primary cause is neuroreceptor blockade—might be causally disconnected from the ongoing deterioration in brain structure, so long as patients remain on medication. If patients were to go off medication, symptoms may be unmasked with a severity related to the underlying structural deficit. Cahn et al. (2006)
found that increased gray matter loss in the first year predicted both a higher positive and negative symptom score (P
= 0.03 and P
= 0.002, respectively) and a decreased likelihood of living independently (P
= 0.001) when patients were examined 5 years later. Sometimes, mapping techniques may offer statistical advantages over volumetry in detecting correlations between clinical measures and anatomical differences that are either distributed or do not coincide well with any anatomical partition that is known a priori
. Even so, in this report it did not help perform point-wise correlations with cognition as still no significant correlations with clinical measures were found.
Our childhood-onset study mapped a dynamic wave of gray matter loss, which spread from parietal-to-frontal cortices over a 5-year period (Thompson et al. 2001
; Vidal et al. 2006
). Early-onset schizophrenia is neurobiologically continuous with the adult-onset disorder, but typically has a more severe course and poorer outcomes. The spreading wave was considered to represent the disease process interacting with normal brain development (Pantelis et al. 2003
), but here we also found a strikingly similar trajectory in adult-onset patients receiving HAL, despite these subjects being a decade older. As many developmental processes continue until middle age (Bartzokis et al. 2003
), late intracortical myelination processes that continue throughout life may be derailed in schizophrenia (Peters and Sethares 2004
). Alternatively, these gray matter volume deficits may reflect an active disease process that occurs early in the illness. Whether psychosis onset occurs in adolescence or adulthood, active pathophysiology may be combined with exaggerated or dysregulated neurodevelopment (Woods 1998
; Lieberman 1999
; Lieberman et al. 2001
). These structural differences are extremely dynamic in the first year after psychosis onset; this serves as a caveat to researchers seeking an MRI-based biological marker for genetic or diagnostic studies of schizophrenia, as the deficit level varies substantially over time and with treatment.
The typical parietal-to-frontal disease trajectory was not present in OLZ-treated patients although some posterior cortical changes occurred—this is consistent with the only other voxel-based MRI study that compared typical and atypical antipsychotics in schizophrenia. In this study, Dazzan et al. (2005)
compared first-episode patients cross-sectionally 8 weeks after first treatment. Their study was neither longitudinal nor randomized, but they found that compared with neuroleptic-naïve patients, those treated with typical antipsychotics showed gray matter deficits in the paracentral lobule, anterior cingulate, superior and middle frontal gyri, insula and precuneus, whereas those treated with atypicals (primarily OLZ) showed thalamic enlargement. The cortical effects they reported are highly consistent with the patterns seen here after 3 months (), and may have different mechanisms than the subcortical gray matter changes. The basal ganglia becomes hypertrophied when patients are treated with typical, but not with atypical, neuroleptics (Buchsbaum et al. 1987
; Bartlett et al. 1994
; Chakos et al. 1995
; Holcomb et al. 1996
; Heitmiller et al. 2004
), and this volume excess reverses after change in treatment to clozapine, an atypical neuroleptic (Chakos et al. 1995
). Cell processes may “sprout” or synaptogenesis may occur (Konradi and Heckers 2001
) specifically in the striatum where DR-D2 receptors are most densely concentrated, and may not account for the cortical changes. More likely, the cortical effect may be due to a glial response. In primates treated with atypical neuroleptics, prefrontal glial cells proliferate, leading to cortical hypertrophy, which may functionally deter any destructive process (Selemon et al. 1999
). OLZ stimulates glial cell division in the frontal cortex of adult rats (Wang et al. 2004
), and this may promote some form of neuroprotection, via correction of impaired myelination (Bartzokis et al. 2003
; Ho et al. 2003
; Hof et al. 2003
), and metabolic support against abnormally severe dendritic pruning and/or neurotoxic ablation of synapses. Even so, most studies do not find that neuroleptics increase neurogenesis, so the mechanism of the observed changes is not clear.
In this study, differences between the treatment arms were no longer significant by 12 months, suggesting that whatever the difference between the treatments is, the difference may be in the timing of the changes, rather than having a different anatomical trajectory. Although the HAL changes occur early, it cannot be ruled out that the OLZ group may “catch up” given enough time; further analyses of the available longitudinal scans after the 12 month time point would be useful to clarify this, although the substantial attrition of subjects in this trial makes it difficult to make inferences based on the very few scans available at all 5 time points including 2 years. Long-term studies are vital to determine whether the treatment difference is an issue of timing or if there is a real difference in the anatomical selectivity of gray matter reduction.
HAL treatment may be neurotoxic (Goff et al. 1995
; Wright et al. 1998
; Molina 2005
), which may account for some of the observable gray matter attrition. Macaque monkeys, treated for 17–27 months with high doses of HAL or OLZ (Dorph-Petersen et al. 2005
), showed a slight, but significant, brain volume decrease for both medications, with greatest reductions in frontal and parietal regions (a pattern seen here in the HAL maps, and in Lieberman et al. 2005
). In humans treated with typical antipsychotics, frontal gray matter reduction is correlated with the dose (Gur et al. 1998
), and chronic HAL, but not OLZ, administration induces oxidative damage in the rat brain (Reinke et al. 2004
). Even so, in most human histological studies, neuronal loss is not detectable in patients treated with HAL for decades (Harrison and Lewis 2003
). Medication-free prodromal subjects exhibit accelerated frontal tissue reduction relative to controls (Pantelis et al. 2003
), suggesting that the loss process is not attributable solely to medication.
OLZ may ameliorate the pathophysiological effects that cause disease progression and gray matter volume reductions in schizophrenia. In preclinical studies, clozapine and OLZ antagonize the effects of glutamate (Duncan et al. 2000
), 6-OH-dopamine lesioning (Wang et al. 2004
), oxidative stress (Wang et al. 2004
), and can stimulate the synthesis of trophic molecules (Chlan-Fourney et al. 2002
; Marx et al. 2003
; Parikh et al. 2004
; Wang et al. 2004
) and even neurogenesis (Wang et al. 2004
). These results suggest that there are pharmacologic mechanisms that go beyond symptom suppression via neuroreceptor antagonism and ameliorate the underlying pathophysiology that causes disease progression and the clinical deterioration that is the hallmark of the illness. Consistent with this, symptom normalization lags behind the dopamine and serotonin receptor blockade that occurs within hours of antipsychotic treatment (as confirmed with receptor-based positron emission tomography; Kapur and Seeman 2000
OLZ may affect brain lipids and myelination. In childhood-onset patients scanned longitudinally, white matter growth rates were silenced relative to controls (Gogtay et al. forthcoming). In adult patients, white matter volume does not increase as in healthy controls (Bartzokis et al. 2003
; Ho et al. 2003
) and its integrity may be compromised (Szeszko et al. 2005
; Kubicki et al. 2005
). A psychosis-related disruption in intracortical myelination may contribute to changes in cortical morphology (Bartzokis et al. 2003
). Some antipsychotics may positively affect the balance between myelin production and decline, perhaps by inducing oligodendrocyte proliferation and compensating for oligodendrocyte reductions (Ho et al. 2003
). Such a response, as well as associated intracellular neuronal changes, may help to ameliorate psychotic symptoms.
Magnitude of Brain Changes
Any maps, such as those in , that suggest annualized rates of gray matter that reach 10% in small, restricted anatomical regions on HAL must be reconciled with prior MR and post-mortem studies showing that patients with schizophrenia have no more than a loss of about 3% of their gray matter compared with controls—in total. There are several possible reasons for this discrepancy. The first is that if the profile of deficits is not spatially homogeneous, in any spatially detailed map of atrophic rates, there will be some regions with greater average loss rates than would be reflected by a spatial average over a larger region that contains that area. This can be seen in the HAL maps at the 12 month time point ()—even though the annualized loss rate is as high as 6% in some regions, it is near zero in the central gyrus and frontal poles. If these regions were included in an overall frontal lobe region-of-interest, the apparent loss for the overall region would be much lower, around the 3% that is consistent with the pathological literature. A second hypothesis, which may or may not be plausible, is that if the region of greatest loss rate is truly small and shifts anatomically, then the total loss for the whole brain may be much less than that seen at specific locations in the maps of loss rates, as the focus of loss is shifting. Given the pathological literature, it is plausible that an annualized loss of around 3% per year persists beyond the first year. In fact, our maps tend to point to the opposite conclusion, that much of the loss on HAL has already occurred by 6 months after initial treatment. In childhood-onset schizophrenia (COS), where greater loss is reported than in adults, longitudinal studies suggest that the rate of cortical loss seen in COS during adolescence plateaus during early adulthood (Arango and Kahn 2008
Nonlinearity of Progressive Brain Changes
It is clear from the comparisons of each time point to baseline that the changes over time are not linear. In fact, we were reluctant to adopt a specific linear or nonlinear model for the trajectory over time, as it was conceivable that all changes might occur in the acute interval very soon after initial treatment (i.e., T1 to T2). As such, we did not choose to fit the effect of time using a linear or nonlinear regression through all 4 scans (using time as an explanatory variable), but instead we performed a direct t-test comparing each time point with baseline (which does not invoke any specific model of how the change occurs between the time points). As such, we are not using the model of linear regression in our analysis, we are just comparing time points in pairs. In addition, to assess group effects, we performed a group comparison at each time point (which is not affected by choices in modeling the effect of time as a continuous function).
This study included subjects who had diagnoses of schizophrenia, schizophreniform disorder, and schizoaffective disorder according to DSM-IV criteria (as assessed with the Structured Clinical Interview for DSM-IV, Research Version). As such, this heterogeneity may have influenced measures made at baseline and may be relevant to the potential effects of drug treatment. Patients with schizophrenia and schizoaffective disorder are typically combined in antipsychotic treatment trials (e.g., Kane et al. 2002
), and there is a continuing debate on whether schizoaffective disorder represents a diagnostic entity that can be biologically distinguished from schizophrenia (Kempf et al. 2005
). No studies, to our knowledge, have directly compared gray matter distribution between patients with schizoaffective disorder and schizophrenia, but studies of bipolar disorder without psychosis have shown significantly decreased cortical thickness in frontal and limbic areas (Lyoo et al. 2006
); lithium treatment also appears to have a trophic effect on gray matter (Bearden et al. 2007
). In a longitudinal comparison of schizoaffective disorder, schizophrenia, and mood disorder with and without psychosis, Harrow et al. (2000)
found that the patients with mood disorder without psychosis had the best prognosis, whereas those with schizophrenia had the worst. The patients with mood disorder with psychosis and schizoaffective disorder had progressively worsening intermediate courses, suggesting a progressive course comparable to that in schizophrenia. Further study is required to determine whether patients with schizoaffective disorder have a trajectory that is distinguishable from that the overall groups examined here.
Differences after 1 Year
A key limitation of this study is that, given the apparent intensification of the disease process, there were no differences between the treatment arms at 12 months. In that context it cannot be said that the medication alters the final pattern of brain structure at the end of the study. It may be that the trajectory of loss in time is initially drug-dependent and then significant losses have accumulated in both groups by the time they have received substantial medication. Again, we note that the technique and numbers are only sensitive to general effects between groups, and the paths for specific individuals may vary from these mean trajectories.
This study has several additional limitations. First, we did not map brain changes in a normal healthy reference population at the same ages and intervals, which may have shed light on whether normally occurring changes were intensified in either treatment group. Strictly speaking, this study did have a control group, in the sense that 2 randomized treatments were being compared, but ethical considerations prevented the treatment of normal subjects with either medication, or the use of a placebo in the patients. As such, without an absolute control condition it is difficult to be sure that the effect is either due to toxic effects of one drug versus protective effects of another (among other interpretations) and it cannot be determined what the normal trajectory of such change is in schizophrenia. Even so, even a placebo design were ethical, it would not truly distinguish medication effects from disease effects in schizophrenia, as they clearly interact and medication effects may not be distinguishable as a logically separate process, even in principle. In addition, our past studies mapping cortical change in large cohorts of healthy subjects over the lifespan (Sowell et al. 2003
= 176 subjects aged 7–87) show that changes are very subtle in normals during early adulthood, and would be extremely difficult to detect in subjects followed up with MRI after only 3, 6, and 12 months. Detecting brain changes with MRI over short follow-up intervals is the topic of significant efforts in scanner calibration and image postprocessing (Leow et al. 2006
), as it would shorten the minimum follow-up interval in a drug trial.
A second caveat is needed regarding the interpretation of gray matter changes on MRI. Gray matter density, studied here, is a surrogate measure of disease progression, and links with clinical decline and duration of illness in Alzheimer's disease, epilepsy, and HIV/AIDS (Thompson et al. 2004
; Lin et al. 2006
). Density is a derived measure, which depends, among other things, on applied smoothing, and does not represent regional volume, although it does correlate highly with cortical thickness (Narr et al. 2006
). Some caveats are therefore needed in relating any MRI structural intensity measure to presumed cellular losses in gray matter. Although there is no widely accepted cellular substrate of schizophrenia, dynamic maps such as these are valuable for generating hypotheses, especially given the shifting nature of the observed changes.
A third caveat pertains to the statistical inference used with brain maps. The permutation methods here provide an overall significance level for multiple comparisons in the maps as a whole. Here we preferred to survey the whole brain without constraining the search region, but permutation testing can be restricted to frontal or temporal regions of interest to provide better localizing power and to increase statistical power by excluding some brain regions with no hypothesized effects (as we have done in prior studies). Strictly speaking, if that were the case only observations used in those regions of interest should be used for inference in the study, so we preferred a more conservative approach that sacrificed some inferential power but avoided the potential bias of testing only brain regions that were implicated in past studies. An additional caveat was that we assessed longitudinal changes within each group, and between group differences at each time point. Because of the large numbers of multiple comparisons and the small cohort (144 scans including patients with all 4 scans), we did not have sufficient power to detect a significant group by time interaction, or a group by region by time interaction, as this would strengthen the findings of a differential change in the 2 groups.
The cortical pattern matching approach has mapped the trajectory of disease in many studies, and increases statistical power by adjusting for intersubject variation in cortical features, and localizing deficits relative to sulcal landmarks. Even so, the maps are more time-consuming to create than whole-brain or lobar volume measures—these remain the mainstay of imaging-based drug trials. Second, we restricted our analysis to data collected at one scanning site in a larger clinical trial. This reduced the risk of site-dependent differences (e.g., scanner effects). Even so, a statistical design including all scans from the trial may have offered greater power and detected site effects or site-by-treatment interactions (as in the original study, Lieberman et al. 2003
). Third, by developing a time-lapse animation of the disease trajectory, we are restricting our attention to patients compliant enough with the treatment and scanning protocols to be assessed 4 times. There was substantial subject attrition during the trial, with only around half of the participants remaining after each time point. This may have skewed our results toward representing patients with better outcomes, although this should not have biased the results in favor of one treatment versus the other (see Lieberman et al. 2003
, for discussion of attrition effects).
In summary, we created the first dynamic maps of schizophrenia progression that reveal alterations in the disease trajectory depending on treatment. The trajectory observed with older antipsychotics confirms a previously discovered spreading wave of tissue loss seen in adolescent-onset psychosis and is consistent with most findings in adult-onset schizophrenia patients undergoing various forms of treatment. Such time-lapse maps may be valuable in examining other approaches to resist or delay illness progression. These maps may also help to identify genetic or epidemiological factors that influence schizophrenia onset, when created from sequential scans of people at risk.