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Confounders of excessive brain volume loss in schizophrenia
Neuroscience and Biobehavioral Reviews 37 (2013) 2418–2423
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Neuroscience and Biobehavioral Reviews journal homepage: www.elsevier.com/locate/neubiorev
Review
Confounders of excessive brain volume loss in schizophrenia N.E. Van Haren ∗ , W. Cahn, H.E. Hulshoff Pol, R.S. Kahn Rudolf Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Centre Utrecht, The Netherlands
a r t i c l e
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Article history: Received 25 April 2012 Received in revised form 15 August 2012 Accepted 11 September 2012 Keywords: Schizophrenia MRI Brain volumes Longitudinal Antipsychotic medication Cannabis Outcome
a b s t r a c t There is convincing evidence that schizophrenia is characterised by progressive brain volume changes during the course of the illness. In a large longitudinal study it was shown that different age-related trajectories of brain tissue loss are present in patients compared to healthy subjects, suggesting that brain maturation that occurs in the third and fourth decade of life is abnormal in schizophrenia. However, studies show that medication intake and cannabis use are important confounding factors when interpreting brain volume (change) abnormalities. Indeed, continues use of cannabis, but not cigarette smoking, is associated to a more pronounced loss of grey matter in the anterior cingulated and the prefrontal cortex. Atypical antipsychotics have been found to be related to smaller decreases in tissue loss. Moreover, independent of antipsychotic medication intake, the brain volume abnormalities appear associated to the outcome of the illness. © 2012 Elsevier Ltd. All rights reserved.
Contents 1. 2. 3. 4. 5.
Progressive brain volume loss in schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Antipsychotic medication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Smoking and cannabis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Progressive brain volume loss in schizophrenia There is substantial evidence for the presence of brain volume abnormalities in patients with schizophrenia (Wright et al., 2000; Shenton et al., 2001), and evidence for excessive tissue loss is now accumulating (Hulshoff Pol and Kahn, 2008; Pantelis et al., 2005; Kempton et al., 2010; Olabi et al., 2011). In one of the largest cross-sectional magnetic resonance imaging (MRI) study across the adult age range it was shown that with age grey matter volume decreased in patients with schizophrenia compared to healthy comparison subjects, suggesting a progressive loss of cerebral grey matter in schizophrenia patients (Hulshoff Pol et al., 2002). Focal analyses, using a voxel-based morphometry approach (VBM), it was shown that decreased grey matter density was present in the left amygdala and hippocampus, right supramarginal gyrus,
∗ Corresponding author at: Rudolf Magnus Institute of Neuroscience, Department of Psychiatry A.01.126, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Tel.: +31 30 2507130; fax: +31 30 2505443. E-mail address: [email protected] (N.E. Van Haren). 0149-7634/$ – see front matter © 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.neubiorev.2012.09.006
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thalamus, (superior) temporal, occipitotemporal, precuneus, posterior cingulate and insular gyri bilaterally. Interestingly, the left amygdala density decrease was more pronounced in the older than in the younger patients (Hulshoff Pol et al., 2001). Moreover, significant decreases in white matter density were found in the genu and truncus of the corpus callosum bilaterally, in the right anterior internal capsule and in the right anterior commissure in schizophrenia patients (Hulshoff Pol et al., 2004), suggesting aberrant inter-hemispheric connectivity in schizophrenia. Obviously, to test whether brain volume abnormalities are static or progressive one has to use a longitudinal design, i.e., serial scanning of the same subjects. At the University Medical Centre Utrecht (UMCU), the Netherlands, Magnetic Resonance Imaging (MRI) has been used to measure the structure of the brain in health and in schizophrenia using a longitudinal design. Here, we provide a non-systematic review based on studies from the UMCU, without attempting to give an extensive and complete overview of the literature. In addition, the influence of potential confounders, such as the outcome of the illness, (cumulative) intake of antipsychotic medication, smoking and cannabis use will be addressed.
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The majority of longitudinal imaging studies involved the measurements of structural brain changes in first-episode patients, providing evidence for excessive decreases in whole brain and grey matter volume (Cahn et al., 2002; DeLisi et al., 2004; Gur et al., 1998; Lieberman et al., 2001) and progressive increases in ventricular and cortical cerebrospinal fluid (CSF) volumes (Cahn et al., 2002; DeLisi et al., 2004; Ho et al., 2003; Lieberman et al., 2001) (but see (Puri et al., 2001; Wood et al., 2001)). It has been argued that the brain volume changes in patients with schizophrenia appear to be especially prominent in the first years of illness (Cahn et al., 2002; Ho et al., 2003; Kasai et al., 2003a,b) relative to change in later stages of the illness. Although considerably fewer studies have examined brain changes over time in chronically ill patients, they show similar findings as in first-episode patients, such as accelerated frontotemporal cortical grey matter decline and sulcal and ventricular expansion (Mathalon et al., 2001). Recent reviews of longitudinal MRI studies in patients with schizophrenia concluded that there is indeed evidence for accelerated loss of grey matter over time, not only in the early phases of the illness (Pantelis et al., 2005) but also in more chronic stages (Hulshoff Pol and Kahn, 2008). Findings so far are based on studies investigating first-episode patients or chronically ill patients as separate groups, which limits the possibility to test the influence of age or age-related factors, such as illness duration on brain volume change. It is important to test directly whether stage of illness is associated to the progression in brain volume decrease by including both groups in one study. This has been done in normally developing children and in children and adolescent with childhood onset schizophrenia. Evidence for differential nonlinear developmental trajectories in affected and unaffected children and young adolescents has been reported, particularly in cerebral and hippocampal volumes (showing progressive decrease in patients) and lateral ventricles (showing progressive increases in patients) (Giedd et al., 1999). Such studies, i.e. longitudinal scanning with more than two measurements in subjects across a relatively wide age range, have not been conducted in adulthood, so far. We set out to investigate age-related trajectories of brain volume change in adult onset schizophrenia and healthy individuals (Van Haren et al., 2008). We rescanned a total of 96 patients and 113 comparison subjects between the ages of 16 and 56 after an average of five years since the initial MRI scan. It was shown that the trajectory of volume change over time indeed differed between patients with schizophrenia and healthy individuals. Instead of the curved trajectory that was found for cerebral (grey) matter volume change in healthy subjects, patients showed a linear decrease over time. In addition, excessive brain volume loss in patients, particularly that of grey matter, was limited to the first two decades of the illness, i.e., before 45 years of age. From this age onwards total cerebral and grey matter volumes decreased to a similar extent in both groups. Before the age of 32 years, the progressive loss of grey matter is accompanied by a progressive increase in white matter in the patients. In the patients the increase in white matter volume diminished with increasing age while the trajectory of volume increase in the control subjects remained stable across the age range. It has been suggested that the regionally specific remodelling of grey and white matter that takes place into the third decade of life (Sowell et al., 2003) underlies some of the structural and functional changes that lead to the development of psychiatric disorders such as schizophrenia (for review see Höistad et al., 2009). The fact that the prefrontal cortex matures last and that myelination is not complete until late adolescence (Paus et al., 2001; Lenroot & Giedd, 2006) may be significant, as the timing coincides with the typical onset of symptoms in schizophrenia. This suggests that a dysfunctional myelination process could underlie the pathogenesis of schizophrenia. This is in line with previous diffusion tensor imaging (DTI) studies showing decreases in fractional anisotropy
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(FA)—which reflects microstructural directionality and to a certain extent fiber integrity—in schizophrenia (for reviews, see Kanaan et al., 2005; Kubicki et al., 2007; Konrad and Winterer, 2008). Based on the findings in this study (Van Haren et al., 2008) it was calculated, using 1150 ml as a reference brain size, that it is reasonable to state that after 20 years of illness, patients show a cumulative loss of brain tissue in the order of 34.5 ml in excess of what is expected with normal aging (for details see: Hulshoff Pol and Kahn, 2008). This cumulative loss of brain tissue results in a 3% overall brain volume loss after 20 years of illness. Interestingly, a meta-analysis of cross-sectional structural brain imaging studies also found a 3% volume loss in schizophrenia patients as compared with control subjects (Wright et al., 2000). Because 1.06 g of brain weight stands approximately for 1 ml (or 1 mm3 ) brain volume (Scharpff, 1912) the excessive brain tissue loss over 20 years that patients show equals almost 37 g. In addition to this Hulshoff Pol and Kahn (2008) calculated, based on six postmortem studies that the that the brain (weighted according the number of individuals included in the studies) weights about 38 g less in schizophrenia patients relative to controls, which is remarkably close to the 37 g found in longitudinal imaging studies.
2. Outcome An import finding in our study is that poor outcome patients, characterized by more symptoms and a lower level of social, work or school functioning (as measured with the Global Assessment of Functioning (GAF score)) showed a larger cerebral volume decrease and more extensive lateral ventricle increases over the 5 year follow-up period than good outcome patients (Van Haren et al., 2008). This is in line with studies in both chronically ill and firstepisode patients. Davis et al. (1998) showed a larger increase in lateral ventricle volume in a group of Kraepelinian patients (i.e., poor outcome patients) as compared to non-Kraepelinian patients while Lieberman et al. (2001) found an association between a larger increase in the ventricles and poorer outcome in first-episode patients. When focussing on the location of the excessive grey matter loss we showed that excessive decreases in grey matter density (using a voxelbased morphometry approach) were located in the left superior frontal gyrus (Brodmann area 9/10), left superior temporal gyrus (Brodmann area 42), right caudate nucleus, and right thalamus in patients with schizophrenia as compared to healthy subjects (Van Haren et al., 2007). In line with this are our findings on excessive cortical thinning in widespread areas on the cortical mantle, being most pronounced bilaterally in the temporal cortex and in the left frontal area (Van Haren et al., 2011). Interestingly, consistent with the excessive cerebral (grey matter) volume decrease in poor outcome patients (GAF score), the density changes in the frontal lobe were most pronounced in patients with the poorest course of the illness (expressed as number of hospitalizations during the scan-interval) (Van Haren et al., 2007). In addition, poor outcome in patients was associated with more pronounced cortical thinning (Van Haren et al., 2011). As the most rapid clinical changes, including deterioration in functioning, are seen in the first (symptomatic) years of the schizophrenic illness (Fenton and McGlashan, 1991; McGlashan, 1988) investigating the association between brain volume (change) and outcome is particularly relevant in first episode patients. In a longitudinal multi-centre study, where we investigated whether brain volume at illness onset can predict outcome in recent-onset schizophrenia after a follow-up of approximately two years, no associations were found (Van Haren et al., 2003). The lack of relationship between brain volume measures at illness onset and outcome may be a consequence of the relatively short follow-up
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period. Indeed, studies did find brain volume measures to predict outcome after seven and four years, respectively (Van Os et al., 1995; Wassink et al., 1999). Although it has been suggested that the first five years after the first psychosis are characterized by the largest decline in functioning, followed by a relatively stable clinical period (Davidson and McGlashan, 1997), this also indicates that the disease is still very active during this time period and outcome may be particularly unstable and reach a plateau only later. Alternatively, measuring brain volume at one time point might not provide sufficient information to predict prognosis. Indeed, if brain changes progress over time, one would expect the changes to be particularly pronounced during the early phase of the illness. We examined cerebral grey matter volume change after a one year interval in patients with first-episode schizophrenia (Cahn et al., 2002). Cerebral grey matter volume significantly declined and lateral ventricle volume increased over the one-year interval in patients relative to healthy subjects. Important in this respect was that these volume changes in the first year of illness appeared significantly related to functional outcome two years after the baseline MRI measurement (Cahn et al., 2002). Moreover, we clinically re-examined the same individuals five years after the initial evaluation, using various outcome measures (Cahn et al., 2006). Again, those patients who had the largest decrease in grey matter volume in the first year had the highest negative symptom scores and were less likely to live independently five years after the first evaluation. This suggests that indeed, in contrast to static brain volumes, dynamic brain measurements are more useful in predicting functional as well as symptomatic outcome in schizophrenia. However, it is important to note that there are also studies showing the opposite relationship, i.e. larger ventricles and smaller hemispheres were related to clinical improvement (DeLisi et al., 1998; Gur et al., 1998). Evidence that the volume deficits are functionally important is not only provided by associations with symptoms or impairments in daily life functioning but also by associations with cognitive function (Crespo-Facorro et al., 2007; Antonova et al., 2004). The causality of such associations is, however, is complex. Whether brain volume loss leads to poor function, worse cognitive functioning, or increased symptoms severity or vice versa remains unclear.
3. Antipsychotic medication A major confounding factor in neuroimaging studies in general and in studies investigating brain volume change over time in particular is the (cumulative) intake of antipsychotic medication. It is difficult to establish whether these (changes in) structural brain abnormalities are caused by the disease or are an effect of treatment. One of the best replicated findings regarding the effect of antipsychotic medication is the increase in caudate nucleus volume in patients treated with typical antipsychotics, which is consistent with the high density of dopamine receptors in this structure (Chakos et al., 1994; Keshavan et al., 1994; Wright et al., 2000). Interestingly, typical and atypical antipsychotic medication appears to affect basal ganglia volume differently. Decreases in basal ganglia volume are generally reported in patients that shift from typical to atypical antipsychotic treatment (Chakos et al., 1995; Scheepers et al., 2001; Corson et al., 1999). Differentiating between antipsychotic-induced changes and those inherent to the disease would be most valid through randomization of antipsychotic-naive first-episode patients to treatment or placebo in comparison with healthy controls. However, this design is clearly coupled with ethical issues. One alternative design is to longitudinally study brain volumes in patients who discontinue their medication, or not (Boonstra et al., 2011). Boonstra et al.
(2011) reported volume decreases in the nucleus accumbens and putamen during a 1 year scan interval in patients who discontinued antipsychotic medication, whereas increases were found in patients who continued their antipsychotics. This might suggest that discontinuation reverses effects of atypical medication in these structures. Another approach is to carefully obtain information on cumulative antipsychotic medication intake during a period between two MRI scans. Both in our one-year follow-up of first episode patients and in our five-year follow-up of patients across the age range we showed significant associations between brain changes over time and cumulative medication intake during the interval. During the very first year of illness this association was negative, i.e. larger volume decreases were associated to higher cumulative medication intake. The majority of included patients were medication naive at baseline measurement and half of the patients used typical antipsychotics during the first year of treatment (Cahn et al., 2002). In contrast to the findings in our first episode sample, the association between brain volume change and medication intake was positive, at least for atypical antipsychotic medication intake. All patients were medicated at baseline and the majority of patients used atypical antipsychotic medication exclusively, or changed from typical to atypical medication during the interval (Van Haren et al., 2008). Moreover, in a cross-sectional VBM study Dazzan et al. (2005) showed that both typical and atypical antipsychotics are associated with brain changes. However, typical medication seemed to affect more extensively the putamen (enlargement) and cortical areas, such as lobulus paracentralis, anterior cingulate gyrus, superior and medial frontal gyri, superior and middle temporal gyri, insula, and precuneus (reductions), while atypical antipsychotics were associated with enlargement of the thalami. However, in chronically ill patients that were randomly assigned to haloperidol or clozapine for 10 weeks no difference in hippocampal, caudate, prefrontal grey or white matter volumes were observed (Arango et al., 2003). The associations between brain volume change and medication intake become even more complicated when taking outcome into account. Since patients are usually medicated continuously, it is difficult to disentangle the effects from outcome and medication on brain volume (change). Cahn et al. (2002) showed that cerebral grey matter decrease in the first year of illness was related to both outcome and antipsychotic medication intake. Larger loss of brain tissue was associated to poorer outcome and independent of that, to larger cumulative medication intake during this year. Moreover, in our longitudinal study across the adult age range we found that treatment with atypical antipsychotic medication (clozapine and olanzapine; expressed as cumulative dose per year scan during the scan interval) attenuated the loss of grey matter density in medial superior frontal gyrus. Excessive decrease in this same area was associated with an increased number of hospitalisations, which can be interpreted as an estimation of number of psychotic relapses during the scan interval. Again, these associations were independent from each other, i.e., number of hospitalisations could not explain the association between excessive grey matter density decrease and medication intake. Based on these finding it could well be that although progressive brain volume change is related to both outcome and medication intake, the two processes act independently and do not explain each other. The only MRI study so far that was set up to investigate the effects of medication on the brain, using random assignment of first episode patients to either treatment with olanzapine or haloperidol was done by Lieberman et al. (2005). In 263 randomized patients of which 161 had a baseline and at least one follow-up MRI scan they showed that haloperidol-treated patients showed significant decreases in grey matter volume, whereas olanzapine-treated patients did not relative to control subjects. Interestingly, in the
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original sample it was suggested that improvement in symptomatology was associated with less lateral ventricular volume increase, only in the olanzapine group. In contrast, more improvement in neurocognitive functioning was associated with less decrease in grey matter volumes, only in haloperidol-treated patients. Using time-lapse maps in a subgroup of patients that had at least 4 MRI scans, it was shown that intensified normal cortical maturation, i.e. a rapidly advancing parietal-to-frontal deficit trajectory was present in haloperidol-treated patients (Thompson et al., 2009). In contrast to the above findings, recent human and animal studies provide evidence of volume loss being associated with higher doses of atypical (and typical) antipsychotics. The administration of haloperidol and olanzapine to macaque monkeys during a 2-year period resulted in a significant overall brain tissue loss in both GM and WM across several brain regions (Dorph-Petersen et al., 2005; Konopaske et al., 2007). Moreover, Schmitt et al. (2004) showed that chronic haloperidol treatment (i.e., 28 days), and not clozapine treatment, in rats did increase total hippocampal volume. It was suggested that haloperidol alters neuroplastic processes or glial morphology rather than cell proliferation. Moreover, in rats, 8-week exposure to these same compounds resulted in a significant decrease in whole-brain volume (6% to 8%) compared with rats that were not treated with antipsychotics. This volume loss was driven mainly by a decrease in frontal parts of the brain (Vernon et al., 2011). Although this is work in animals and it might be that primate and rat brains react differently on these compounds, these important and remarkable findings cannot be ignored.
4. Smoking and cannabis There are some suggestions that smoking might influence the brain. Cross-sectional brain imaging studies suggest that healthy subjects who smoke cigarettes show smaller grey matter volumes and/or densities in the prefrontal, anterior cingulate, occipital, and temporal cortices (including parahippocampal gyrus), thalamus, substantia nigra and cerebellum as compared to non-smokers (Brody et al., 2004; Gallinat et al., 2006). Moreover, a negative association has been reported between the total number of cigarettes smoked and volume of frontal and temporal lobes and cerebellum (Gallinat et al., 2006). It might be that some of the reported brain volume loss can be explained by cigarette smoking as there clearly is an overrepresentation of smokers among patients with schizophrenia (Lasser et al., 2000; Poirier et al., 2002). We showed that despite the higher prevalence of smoking behavior and the higher number of cigarettes consumed per day in the patients, cigarette smoking did not explain the excessive cerebral (grey matter) volume decreases in the patients. However, extremely heavy smoking may contribute to excessive grey matter volume loss in schizophrenia (Van Haren et al., 2011). Unfortunately, we could not compare this to the effect of heavy smoking in controls because almost 15% of the patients smoked more than 25 cigarettes per day while none of the controls did. For the continues use of cannabis after illness onset findings are different. More pronounced cerebral grey matter volume loss over time is associated with cannabis use (Rais et al., 2008). We followed up on this finding to investigate whether the grey matter volume loss is globally distributed over the entire brain or more pronounced in specific cortical brain regions (Rais et al., 2010). At inclusion, cortical thickness did not differ between cannabis-using and non-using patients but patients who continued using cannabis during the scan interval showed additional thinning in the left dorsolateral prefrontal cortex (DLPFC), left anterior cingulate cortex (ACC) and left occipital lobe as compared to those patients that did not. Interestingly, in post-mortem studies both DLPFC and ACC have
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not only been identified as being rich in cannabinoid (CB1) receptors in the brains of healthy individuals (Eggan and Lewis, 2007; Glass et al., 1997; Iversen, 2003) but also show increased density of these receptors in brain tissue of schizophrenia patients, irrespective of cannabis use (Dean et al., 2001; Zavitsanou et al., 2004). Moreover, increased cerebrospinal fluid (CSF) levels of endogenous cannabinoids have been reported in patients with schizophrenia suggesting a possible role for (changes in the) endocannabinoid signalling system in the pathogenesis of schizophrenia (Koethe et al., 2009; Leweke et al., 1999, 2007).
5. Conclusion There is sufficient evidence to suggest that schizophrenia is a progressive brain disease. Interestingly, our data suggest that during the first year of illness the largest decline of cerebral (grey matter) volume takes place. This can possibly be explained by initiation of pharmacological treatment since the majority of the patients in our longitudinal first-episode study were medication naive at inclusion in the study. In addition, after the first year, the brain changes found in the schizophrenia patients might be due to an abnormality in brain maturational processes (Van Haren et al., 2008). First, the progressive changes in schizophrenia were limited to the first 10 (for white matter) to 20 years (for cerebrum, grey matter and lateral ventricle volumes) of the illness. In addition, grey matter volume loss in the patients is mainly characterized by the absence of the normal curved trajectory of volume change with age that we observed to be present in healthy subjects. Grey matter decreased in a linear fashion in the patients, failing to show the relative diminution in grey matter loss before the age of 30 as was seen in the controls. After the age of approximately 45 years the agerelated progression in brain tissue loss, i.e. the effect of aging, was similar in patients with schizophrenia and healthy subjects. These different age-related trajectories of brain tissue loss, in our view, suggest the brain maturation that occurs in the third and fourth decade of life to be abnormal in schizophrenia. However, one has to bear in mind that prodromal and clinically high-risk individuals show structural brain changes during, and possibly before, transition into psychosis (Smieskova et al., 2010) so the exact timing of the aberrant brain changes are not yet determined. Both the presence of more symptoms as well as poorer social and daily functioning are associated with larger decreases in brain volume over time. We and others showed that medication intake is a confounding factor when interpreting brain volume (change) abnormalities. However, what has become clear is that cumulative dose of antipsychotic medication cannot cause the brain volume abnormalities. It only explains a portion of the detectable abnormalities in volume (change). Here, we discussed a variety of relevant confounders that might be important in understanding (change in) structural brain abnormalities in schizophrenia patients. It is important to note, that several other confounders have been addressed in the literature, such as diabetes and subjects’ weight (Leonard et al., 2012), and neuroinflammation (Mondelli et al., 2011). The use of multimodal imaging across neurochemical, functional, and structural imaging modalities, combined with animal modelling and postmortem studies of the cellular and molecular mechanisms of brain changes is what is required to address the issue of what is going on in the brain over time before and during the illness. Structural brain imaging by itself is limited to fully answer these questions.
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Contents lists available at ScienceDirect
Neuroscience and Biobehavioral Reviews journal homepage: www.elsevier.com/locate/neubiorev
Review
Confounders of excessive brain volume loss in schizophrenia N.E. Van Haren ∗ , W. Cahn, H.E. Hulshoff Pol, R.S. Kahn Rudolf Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Centre Utrecht, The Netherlands
a r t i c l e
i n f o
Article history: Received 25 April 2012 Received in revised form 15 August 2012 Accepted 11 September 2012 Keywords: Schizophrenia MRI Brain volumes Longitudinal Antipsychotic medication Cannabis Outcome
a b s t r a c t There is convincing evidence that schizophrenia is characterised by progressive brain volume changes during the course of the illness. In a large longitudinal study it was shown that different age-related trajectories of brain tissue loss are present in patients compared to healthy subjects, suggesting that brain maturation that occurs in the third and fourth decade of life is abnormal in schizophrenia. However, studies show that medication intake and cannabis use are important confounding factors when interpreting brain volume (change) abnormalities. Indeed, continues use of cannabis, but not cigarette smoking, is associated to a more pronounced loss of grey matter in the anterior cingulated and the prefrontal cortex. Atypical antipsychotics have been found to be related to smaller decreases in tissue loss. Moreover, independent of antipsychotic medication intake, the brain volume abnormalities appear associated to the outcome of the illness. © 2012 Elsevier Ltd. All rights reserved.
Contents 1. 2. 3. 4. 5.
Progressive brain volume loss in schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Antipsychotic medication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Smoking and cannabis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Progressive brain volume loss in schizophrenia There is substantial evidence for the presence of brain volume abnormalities in patients with schizophrenia (Wright et al., 2000; Shenton et al., 2001), and evidence for excessive tissue loss is now accumulating (Hulshoff Pol and Kahn, 2008; Pantelis et al., 2005; Kempton et al., 2010; Olabi et al., 2011). In one of the largest cross-sectional magnetic resonance imaging (MRI) study across the adult age range it was shown that with age grey matter volume decreased in patients with schizophrenia compared to healthy comparison subjects, suggesting a progressive loss of cerebral grey matter in schizophrenia patients (Hulshoff Pol et al., 2002). Focal analyses, using a voxel-based morphometry approach (VBM), it was shown that decreased grey matter density was present in the left amygdala and hippocampus, right supramarginal gyrus,
∗ Corresponding author at: Rudolf Magnus Institute of Neuroscience, Department of Psychiatry A.01.126, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Tel.: +31 30 2507130; fax: +31 30 2505443. E-mail address: [email protected] (N.E. Van Haren). 0149-7634/$ – see front matter © 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.neubiorev.2012.09.006
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thalamus, (superior) temporal, occipitotemporal, precuneus, posterior cingulate and insular gyri bilaterally. Interestingly, the left amygdala density decrease was more pronounced in the older than in the younger patients (Hulshoff Pol et al., 2001). Moreover, significant decreases in white matter density were found in the genu and truncus of the corpus callosum bilaterally, in the right anterior internal capsule and in the right anterior commissure in schizophrenia patients (Hulshoff Pol et al., 2004), suggesting aberrant inter-hemispheric connectivity in schizophrenia. Obviously, to test whether brain volume abnormalities are static or progressive one has to use a longitudinal design, i.e., serial scanning of the same subjects. At the University Medical Centre Utrecht (UMCU), the Netherlands, Magnetic Resonance Imaging (MRI) has been used to measure the structure of the brain in health and in schizophrenia using a longitudinal design. Here, we provide a non-systematic review based on studies from the UMCU, without attempting to give an extensive and complete overview of the literature. In addition, the influence of potential confounders, such as the outcome of the illness, (cumulative) intake of antipsychotic medication, smoking and cannabis use will be addressed.
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The majority of longitudinal imaging studies involved the measurements of structural brain changes in first-episode patients, providing evidence for excessive decreases in whole brain and grey matter volume (Cahn et al., 2002; DeLisi et al., 2004; Gur et al., 1998; Lieberman et al., 2001) and progressive increases in ventricular and cortical cerebrospinal fluid (CSF) volumes (Cahn et al., 2002; DeLisi et al., 2004; Ho et al., 2003; Lieberman et al., 2001) (but see (Puri et al., 2001; Wood et al., 2001)). It has been argued that the brain volume changes in patients with schizophrenia appear to be especially prominent in the first years of illness (Cahn et al., 2002; Ho et al., 2003; Kasai et al., 2003a,b) relative to change in later stages of the illness. Although considerably fewer studies have examined brain changes over time in chronically ill patients, they show similar findings as in first-episode patients, such as accelerated frontotemporal cortical grey matter decline and sulcal and ventricular expansion (Mathalon et al., 2001). Recent reviews of longitudinal MRI studies in patients with schizophrenia concluded that there is indeed evidence for accelerated loss of grey matter over time, not only in the early phases of the illness (Pantelis et al., 2005) but also in more chronic stages (Hulshoff Pol and Kahn, 2008). Findings so far are based on studies investigating first-episode patients or chronically ill patients as separate groups, which limits the possibility to test the influence of age or age-related factors, such as illness duration on brain volume change. It is important to test directly whether stage of illness is associated to the progression in brain volume decrease by including both groups in one study. This has been done in normally developing children and in children and adolescent with childhood onset schizophrenia. Evidence for differential nonlinear developmental trajectories in affected and unaffected children and young adolescents has been reported, particularly in cerebral and hippocampal volumes (showing progressive decrease in patients) and lateral ventricles (showing progressive increases in patients) (Giedd et al., 1999). Such studies, i.e. longitudinal scanning with more than two measurements in subjects across a relatively wide age range, have not been conducted in adulthood, so far. We set out to investigate age-related trajectories of brain volume change in adult onset schizophrenia and healthy individuals (Van Haren et al., 2008). We rescanned a total of 96 patients and 113 comparison subjects between the ages of 16 and 56 after an average of five years since the initial MRI scan. It was shown that the trajectory of volume change over time indeed differed between patients with schizophrenia and healthy individuals. Instead of the curved trajectory that was found for cerebral (grey) matter volume change in healthy subjects, patients showed a linear decrease over time. In addition, excessive brain volume loss in patients, particularly that of grey matter, was limited to the first two decades of the illness, i.e., before 45 years of age. From this age onwards total cerebral and grey matter volumes decreased to a similar extent in both groups. Before the age of 32 years, the progressive loss of grey matter is accompanied by a progressive increase in white matter in the patients. In the patients the increase in white matter volume diminished with increasing age while the trajectory of volume increase in the control subjects remained stable across the age range. It has been suggested that the regionally specific remodelling of grey and white matter that takes place into the third decade of life (Sowell et al., 2003) underlies some of the structural and functional changes that lead to the development of psychiatric disorders such as schizophrenia (for review see Höistad et al., 2009). The fact that the prefrontal cortex matures last and that myelination is not complete until late adolescence (Paus et al., 2001; Lenroot & Giedd, 2006) may be significant, as the timing coincides with the typical onset of symptoms in schizophrenia. This suggests that a dysfunctional myelination process could underlie the pathogenesis of schizophrenia. This is in line with previous diffusion tensor imaging (DTI) studies showing decreases in fractional anisotropy
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(FA)—which reflects microstructural directionality and to a certain extent fiber integrity—in schizophrenia (for reviews, see Kanaan et al., 2005; Kubicki et al., 2007; Konrad and Winterer, 2008). Based on the findings in this study (Van Haren et al., 2008) it was calculated, using 1150 ml as a reference brain size, that it is reasonable to state that after 20 years of illness, patients show a cumulative loss of brain tissue in the order of 34.5 ml in excess of what is expected with normal aging (for details see: Hulshoff Pol and Kahn, 2008). This cumulative loss of brain tissue results in a 3% overall brain volume loss after 20 years of illness. Interestingly, a meta-analysis of cross-sectional structural brain imaging studies also found a 3% volume loss in schizophrenia patients as compared with control subjects (Wright et al., 2000). Because 1.06 g of brain weight stands approximately for 1 ml (or 1 mm3 ) brain volume (Scharpff, 1912) the excessive brain tissue loss over 20 years that patients show equals almost 37 g. In addition to this Hulshoff Pol and Kahn (2008) calculated, based on six postmortem studies that the that the brain (weighted according the number of individuals included in the studies) weights about 38 g less in schizophrenia patients relative to controls, which is remarkably close to the 37 g found in longitudinal imaging studies.
2. Outcome An import finding in our study is that poor outcome patients, characterized by more symptoms and a lower level of social, work or school functioning (as measured with the Global Assessment of Functioning (GAF score)) showed a larger cerebral volume decrease and more extensive lateral ventricle increases over the 5 year follow-up period than good outcome patients (Van Haren et al., 2008). This is in line with studies in both chronically ill and firstepisode patients. Davis et al. (1998) showed a larger increase in lateral ventricle volume in a group of Kraepelinian patients (i.e., poor outcome patients) as compared to non-Kraepelinian patients while Lieberman et al. (2001) found an association between a larger increase in the ventricles and poorer outcome in first-episode patients. When focussing on the location of the excessive grey matter loss we showed that excessive decreases in grey matter density (using a voxelbased morphometry approach) were located in the left superior frontal gyrus (Brodmann area 9/10), left superior temporal gyrus (Brodmann area 42), right caudate nucleus, and right thalamus in patients with schizophrenia as compared to healthy subjects (Van Haren et al., 2007). In line with this are our findings on excessive cortical thinning in widespread areas on the cortical mantle, being most pronounced bilaterally in the temporal cortex and in the left frontal area (Van Haren et al., 2011). Interestingly, consistent with the excessive cerebral (grey matter) volume decrease in poor outcome patients (GAF score), the density changes in the frontal lobe were most pronounced in patients with the poorest course of the illness (expressed as number of hospitalizations during the scan-interval) (Van Haren et al., 2007). In addition, poor outcome in patients was associated with more pronounced cortical thinning (Van Haren et al., 2011). As the most rapid clinical changes, including deterioration in functioning, are seen in the first (symptomatic) years of the schizophrenic illness (Fenton and McGlashan, 1991; McGlashan, 1988) investigating the association between brain volume (change) and outcome is particularly relevant in first episode patients. In a longitudinal multi-centre study, where we investigated whether brain volume at illness onset can predict outcome in recent-onset schizophrenia after a follow-up of approximately two years, no associations were found (Van Haren et al., 2003). The lack of relationship between brain volume measures at illness onset and outcome may be a consequence of the relatively short follow-up
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period. Indeed, studies did find brain volume measures to predict outcome after seven and four years, respectively (Van Os et al., 1995; Wassink et al., 1999). Although it has been suggested that the first five years after the first psychosis are characterized by the largest decline in functioning, followed by a relatively stable clinical period (Davidson and McGlashan, 1997), this also indicates that the disease is still very active during this time period and outcome may be particularly unstable and reach a plateau only later. Alternatively, measuring brain volume at one time point might not provide sufficient information to predict prognosis. Indeed, if brain changes progress over time, one would expect the changes to be particularly pronounced during the early phase of the illness. We examined cerebral grey matter volume change after a one year interval in patients with first-episode schizophrenia (Cahn et al., 2002). Cerebral grey matter volume significantly declined and lateral ventricle volume increased over the one-year interval in patients relative to healthy subjects. Important in this respect was that these volume changes in the first year of illness appeared significantly related to functional outcome two years after the baseline MRI measurement (Cahn et al., 2002). Moreover, we clinically re-examined the same individuals five years after the initial evaluation, using various outcome measures (Cahn et al., 2006). Again, those patients who had the largest decrease in grey matter volume in the first year had the highest negative symptom scores and were less likely to live independently five years after the first evaluation. This suggests that indeed, in contrast to static brain volumes, dynamic brain measurements are more useful in predicting functional as well as symptomatic outcome in schizophrenia. However, it is important to note that there are also studies showing the opposite relationship, i.e. larger ventricles and smaller hemispheres were related to clinical improvement (DeLisi et al., 1998; Gur et al., 1998). Evidence that the volume deficits are functionally important is not only provided by associations with symptoms or impairments in daily life functioning but also by associations with cognitive function (Crespo-Facorro et al., 2007; Antonova et al., 2004). The causality of such associations is, however, is complex. Whether brain volume loss leads to poor function, worse cognitive functioning, or increased symptoms severity or vice versa remains unclear.
3. Antipsychotic medication A major confounding factor in neuroimaging studies in general and in studies investigating brain volume change over time in particular is the (cumulative) intake of antipsychotic medication. It is difficult to establish whether these (changes in) structural brain abnormalities are caused by the disease or are an effect of treatment. One of the best replicated findings regarding the effect of antipsychotic medication is the increase in caudate nucleus volume in patients treated with typical antipsychotics, which is consistent with the high density of dopamine receptors in this structure (Chakos et al., 1994; Keshavan et al., 1994; Wright et al., 2000). Interestingly, typical and atypical antipsychotic medication appears to affect basal ganglia volume differently. Decreases in basal ganglia volume are generally reported in patients that shift from typical to atypical antipsychotic treatment (Chakos et al., 1995; Scheepers et al., 2001; Corson et al., 1999). Differentiating between antipsychotic-induced changes and those inherent to the disease would be most valid through randomization of antipsychotic-naive first-episode patients to treatment or placebo in comparison with healthy controls. However, this design is clearly coupled with ethical issues. One alternative design is to longitudinally study brain volumes in patients who discontinue their medication, or not (Boonstra et al., 2011). Boonstra et al.
(2011) reported volume decreases in the nucleus accumbens and putamen during a 1 year scan interval in patients who discontinued antipsychotic medication, whereas increases were found in patients who continued their antipsychotics. This might suggest that discontinuation reverses effects of atypical medication in these structures. Another approach is to carefully obtain information on cumulative antipsychotic medication intake during a period between two MRI scans. Both in our one-year follow-up of first episode patients and in our five-year follow-up of patients across the age range we showed significant associations between brain changes over time and cumulative medication intake during the interval. During the very first year of illness this association was negative, i.e. larger volume decreases were associated to higher cumulative medication intake. The majority of included patients were medication naive at baseline measurement and half of the patients used typical antipsychotics during the first year of treatment (Cahn et al., 2002). In contrast to the findings in our first episode sample, the association between brain volume change and medication intake was positive, at least for atypical antipsychotic medication intake. All patients were medicated at baseline and the majority of patients used atypical antipsychotic medication exclusively, or changed from typical to atypical medication during the interval (Van Haren et al., 2008). Moreover, in a cross-sectional VBM study Dazzan et al. (2005) showed that both typical and atypical antipsychotics are associated with brain changes. However, typical medication seemed to affect more extensively the putamen (enlargement) and cortical areas, such as lobulus paracentralis, anterior cingulate gyrus, superior and medial frontal gyri, superior and middle temporal gyri, insula, and precuneus (reductions), while atypical antipsychotics were associated with enlargement of the thalami. However, in chronically ill patients that were randomly assigned to haloperidol or clozapine for 10 weeks no difference in hippocampal, caudate, prefrontal grey or white matter volumes were observed (Arango et al., 2003). The associations between brain volume change and medication intake become even more complicated when taking outcome into account. Since patients are usually medicated continuously, it is difficult to disentangle the effects from outcome and medication on brain volume (change). Cahn et al. (2002) showed that cerebral grey matter decrease in the first year of illness was related to both outcome and antipsychotic medication intake. Larger loss of brain tissue was associated to poorer outcome and independent of that, to larger cumulative medication intake during this year. Moreover, in our longitudinal study across the adult age range we found that treatment with atypical antipsychotic medication (clozapine and olanzapine; expressed as cumulative dose per year scan during the scan interval) attenuated the loss of grey matter density in medial superior frontal gyrus. Excessive decrease in this same area was associated with an increased number of hospitalisations, which can be interpreted as an estimation of number of psychotic relapses during the scan interval. Again, these associations were independent from each other, i.e., number of hospitalisations could not explain the association between excessive grey matter density decrease and medication intake. Based on these finding it could well be that although progressive brain volume change is related to both outcome and medication intake, the two processes act independently and do not explain each other. The only MRI study so far that was set up to investigate the effects of medication on the brain, using random assignment of first episode patients to either treatment with olanzapine or haloperidol was done by Lieberman et al. (2005). In 263 randomized patients of which 161 had a baseline and at least one follow-up MRI scan they showed that haloperidol-treated patients showed significant decreases in grey matter volume, whereas olanzapine-treated patients did not relative to control subjects. Interestingly, in the
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original sample it was suggested that improvement in symptomatology was associated with less lateral ventricular volume increase, only in the olanzapine group. In contrast, more improvement in neurocognitive functioning was associated with less decrease in grey matter volumes, only in haloperidol-treated patients. Using time-lapse maps in a subgroup of patients that had at least 4 MRI scans, it was shown that intensified normal cortical maturation, i.e. a rapidly advancing parietal-to-frontal deficit trajectory was present in haloperidol-treated patients (Thompson et al., 2009). In contrast to the above findings, recent human and animal studies provide evidence of volume loss being associated with higher doses of atypical (and typical) antipsychotics. The administration of haloperidol and olanzapine to macaque monkeys during a 2-year period resulted in a significant overall brain tissue loss in both GM and WM across several brain regions (Dorph-Petersen et al., 2005; Konopaske et al., 2007). Moreover, Schmitt et al. (2004) showed that chronic haloperidol treatment (i.e., 28 days), and not clozapine treatment, in rats did increase total hippocampal volume. It was suggested that haloperidol alters neuroplastic processes or glial morphology rather than cell proliferation. Moreover, in rats, 8-week exposure to these same compounds resulted in a significant decrease in whole-brain volume (6% to 8%) compared with rats that were not treated with antipsychotics. This volume loss was driven mainly by a decrease in frontal parts of the brain (Vernon et al., 2011). Although this is work in animals and it might be that primate and rat brains react differently on these compounds, these important and remarkable findings cannot be ignored.
4. Smoking and cannabis There are some suggestions that smoking might influence the brain. Cross-sectional brain imaging studies suggest that healthy subjects who smoke cigarettes show smaller grey matter volumes and/or densities in the prefrontal, anterior cingulate, occipital, and temporal cortices (including parahippocampal gyrus), thalamus, substantia nigra and cerebellum as compared to non-smokers (Brody et al., 2004; Gallinat et al., 2006). Moreover, a negative association has been reported between the total number of cigarettes smoked and volume of frontal and temporal lobes and cerebellum (Gallinat et al., 2006). It might be that some of the reported brain volume loss can be explained by cigarette smoking as there clearly is an overrepresentation of smokers among patients with schizophrenia (Lasser et al., 2000; Poirier et al., 2002). We showed that despite the higher prevalence of smoking behavior and the higher number of cigarettes consumed per day in the patients, cigarette smoking did not explain the excessive cerebral (grey matter) volume decreases in the patients. However, extremely heavy smoking may contribute to excessive grey matter volume loss in schizophrenia (Van Haren et al., 2011). Unfortunately, we could not compare this to the effect of heavy smoking in controls because almost 15% of the patients smoked more than 25 cigarettes per day while none of the controls did. For the continues use of cannabis after illness onset findings are different. More pronounced cerebral grey matter volume loss over time is associated with cannabis use (Rais et al., 2008). We followed up on this finding to investigate whether the grey matter volume loss is globally distributed over the entire brain or more pronounced in specific cortical brain regions (Rais et al., 2010). At inclusion, cortical thickness did not differ between cannabis-using and non-using patients but patients who continued using cannabis during the scan interval showed additional thinning in the left dorsolateral prefrontal cortex (DLPFC), left anterior cingulate cortex (ACC) and left occipital lobe as compared to those patients that did not. Interestingly, in post-mortem studies both DLPFC and ACC have
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not only been identified as being rich in cannabinoid (CB1) receptors in the brains of healthy individuals (Eggan and Lewis, 2007; Glass et al., 1997; Iversen, 2003) but also show increased density of these receptors in brain tissue of schizophrenia patients, irrespective of cannabis use (Dean et al., 2001; Zavitsanou et al., 2004). Moreover, increased cerebrospinal fluid (CSF) levels of endogenous cannabinoids have been reported in patients with schizophrenia suggesting a possible role for (changes in the) endocannabinoid signalling system in the pathogenesis of schizophrenia (Koethe et al., 2009; Leweke et al., 1999, 2007).
5. Conclusion There is sufficient evidence to suggest that schizophrenia is a progressive brain disease. Interestingly, our data suggest that during the first year of illness the largest decline of cerebral (grey matter) volume takes place. This can possibly be explained by initiation of pharmacological treatment since the majority of the patients in our longitudinal first-episode study were medication naive at inclusion in the study. In addition, after the first year, the brain changes found in the schizophrenia patients might be due to an abnormality in brain maturational processes (Van Haren et al., 2008). First, the progressive changes in schizophrenia were limited to the first 10 (for white matter) to 20 years (for cerebrum, grey matter and lateral ventricle volumes) of the illness. In addition, grey matter volume loss in the patients is mainly characterized by the absence of the normal curved trajectory of volume change with age that we observed to be present in healthy subjects. Grey matter decreased in a linear fashion in the patients, failing to show the relative diminution in grey matter loss before the age of 30 as was seen in the controls. After the age of approximately 45 years the agerelated progression in brain tissue loss, i.e. the effect of aging, was similar in patients with schizophrenia and healthy subjects. These different age-related trajectories of brain tissue loss, in our view, suggest the brain maturation that occurs in the third and fourth decade of life to be abnormal in schizophrenia. However, one has to bear in mind that prodromal and clinically high-risk individuals show structural brain changes during, and possibly before, transition into psychosis (Smieskova et al., 2010) so the exact timing of the aberrant brain changes are not yet determined. Both the presence of more symptoms as well as poorer social and daily functioning are associated with larger decreases in brain volume over time. We and others showed that medication intake is a confounding factor when interpreting brain volume (change) abnormalities. However, what has become clear is that cumulative dose of antipsychotic medication cannot cause the brain volume abnormalities. It only explains a portion of the detectable abnormalities in volume (change). Here, we discussed a variety of relevant confounders that might be important in understanding (change in) structural brain abnormalities in schizophrenia patients. It is important to note, that several other confounders have been addressed in the literature, such as diabetes and subjects’ weight (Leonard et al., 2012), and neuroinflammation (Mondelli et al., 2011). The use of multimodal imaging across neurochemical, functional, and structural imaging modalities, combined with animal modelling and postmortem studies of the cellular and molecular mechanisms of brain changes is what is required to address the issue of what is going on in the brain over time before and during the illness. Structural brain imaging by itself is limited to fully answer these questions.
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