Brain Anomalies in Schizophrenia Arise Early, Degrade Connectivity
18 June 2013. Brain scans turn up plenty of anomalies in schizophrenia, but studies tend to look either at structure or function. Two new studies try for an integrated view by looking at both in the same people. One study, led by Su Lui and Qiyong Gong of West China Hospital of Sichuan University, Chengdu, China, and published online June 4 in the American Journal of Psychiatry, reports that early on in schizophrenia, certain brain regions are, on average, already smaller or larger than normal. However, these did not overlap with regions showing abnormal activity. As the largest brain imaging study yet of drug-naïve, first-episode people with schizophrenia, the findings argue that these differences accompany early stages of the illness.
The second study, led by Martijn Pieter van den Heuvel at the University Medical Center Utrecht in the Netherlands and published online June 5 in JAMA Psychiatry, used diffusion tensor imaging (DTI) and functional imaging to visualize structural and functional connectivity in established schizophrenia. The researchers report degraded “rich club” organization in schizophrenia, meaning that brain hub regions making many connections with other regions were less likely to connect to other highly connected hub regions than those in controls. This disrupted connectivity was specific to these elite hub regions, rather than a widespread feature across the brain, and correlations between structural and functional measures of connectivity were stronger in schizophrenia than in controls.
Both studies grapple with what structural differences might mean for the patterns of neural activity coursing through the brain. Each combines its structural measures with resting-state functional magnetic resonance imaging (fMRI), a technique that infers connectivity among different regions of the brain by monitoring simultaneously active regions while a subject rests quietly (see SRF related news story). While resting-state fMRI has come up with differences in the default-mode network in schizophrenia (see SRF related news story), how this corresponds to reported structural anomalies in the brain is unclear.
First authors Wentig Ren and Wei Deng scanned 100 people experiencing their first episode of illness but who remained treatment naïve during the brain imaging, along with 100 controls matched for age, sex, and education. The researchers detected differences in thalamic and cortical regions in schizophrenia compared to controls; for example, they found smaller volumes in the left paracentral and left inferior parietal lobules, and larger volumes in the thalamus, anterior cingulate cortex, insula, and orbital frontal gyrus in schizophrenia.
When the researchers monitored resting-state patterns of activity in the same people, they found decreased synchrony (a proxy for strength of connectivity) in a completely different set of regions: in frontal-parietal areas and in the default-mode network—a collection of regions activated while the brain rests. This disconnect is consistent with results from the group’s previous smaller study (Lui et al., 2009) and suggests that anatomical changes reflect early pathological processes underlying the disorder, whereas functional changes indicate the state of active psychosis.
These structural and functional differences did not correlate with duration of illness or with positive symptom severity, suggesting that the brain anomalies are stable and early features of illness, though there is recent evidence that such brain abnormalities may worsen with prolonged illness (see SRF related news story). Among the study participants with schizophrenia, a substantial 36 percent had severe negative symptoms, and these showed the largest differences in brain structure, particularly in the left dorsal lateral prefrontal cortex. Their resting-state activity, however, remained similar to that of people with schizophrenia with less severe negative symptoms.
Welcome to the rich club
In the second study, first author Martijn van den Heuvel and colleagues mapped the network of connections within the brain by looking at white matter structure and resting-state activity in a group of 48 people with schizophrenia and 45 healthy controls, and in a second replication group of 41 people with schizophrenia and 51 healthy controls. Both samples of patients were relatively young (approximately 30 years of age) and almost all were currently on antipsychotic medication. The researchers then derived a global picture of the network of connections based on either the structural DTI data or the functional fMRI resting-state data (see SRF related news story). Regions with many connections to and from them are defined as hub regions, much like a hub airport on an airline flight map. These hub regions typically make more connections with other hub regions than with sparsely connected regions, and this aspect of network organization is referred to as the “rich club.”
“To put it another way, the brain’s rich club has a high capacity for integrative information processing, but also a high physical cost in terms of connection distance between club hubs,” wrote Edward Bullmore and Petra Vértes of the University of Cambridge, U.K., in an accompanying editorial in JAMA Psychiatry.
Based on the structural data, the regions belonging to the rich club in schizophrenia and in controls were the same: the precuneus, superior frontal cortex, superior parietal cortex, and insula. In both schizophrenia samples, however, the researchers found reduced density in rich club connections compared to controls. This seemed specific to rich club organization because “feeder” connections between rich club and non-rich club regions, and “local” connections between different non-rich club regions, were not significantly different between the schizophrenia groups and controls. Global efficiency, which reflects how well any region in the network can communicate with another region, was also down in schizophrenia, which might be related to the degraded rich club organization.
The researchers found a slightly stronger correlation between structural and functional measures of connectivity in schizophrenia than in controls. They suggest this may indicate that patterns of brain activity in schizophrenia are dictated more by the static, anatomical connections between regions.
Together, the studies start to outline an integrated view of brain structure and function in schizophrenia. Despite the complexity of this approach, it appears to be the wave of the future for imaging (see AbstractGollub et al., 2013) and may eventually help reveal the core brain disturbances in the disorder.—Michele Solis.
Ren W, Lui S, Deng W, Li F, Li M, Huang X, Wang Y, Li T, Sweeney JA, Gong Q. Anatomical and Functional Brain Abnormalities in Drug-Naive First-Episode Schizophrenia. Am J Psychiatry. 2013 Jun 4. Abstract
van den Heuvel MP, Sporns O, Collin G, Scheewe T, Mandl RC, Cahn W, Goñi J, Hulshoff Pol HE, Kahn RS. Abnormal Rich Club Organization and Functional Brain Dynamics in Schizophrenia. JAMA Psychiatry. 2013 Jun 5:1-10. Abstract
Bullmore E, Vértes P. From Lichtheim to Rich Club: Brain Networks and Psychiatry. JAMA Psychiatry. 2013 Jun 5:1-3. Abstract
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Primary Papers: Anatomical and Functional Brain Abnormalities in Drug-Naive First-Episode Schizophrenia.Comment by: Lei Wang
Submitted 17 July 2013
Posted 17 July 2013
There are two important contributions that this study brings to the field: 1) it has one of the largest samples of antipsychotic-naïve individuals at the early stages of schizophrenia—while most of the published studies on first-episode schizophrenia/psychosis are of small sample size (Radua et al., 2012), with 100 patients and 100 matched controls, this study provides good statistical power; and 2) it uses multimodal imaging. Although more and more studies have collected multimodal imaging data in an attempt to directly study relationships between brain structure and brain function (Schultz et al., 2012), there exists a dearth of information with regard to the direct relationship between structural changes and changes in resting-state functional connectivity, especially in treatment-naïve patients.
The study also invokes new questions on the neurobiology of treatment-naïve schizophrenia. For example, findings of the study suggest that in drug-naive first-episode schizophrenia patients, abnormal changes of neural structure and neural oscillation occur in different brain networks, independent of each other. The study also found, somewhat surprisingly, that a set of gray matter structures was enlarged after psychosis onset. One wonders if these brain structures, including the thalamus and anterior cingulate cortex (ACC), would also show signs of “neuronal overgrowth or a deficit in normal pruning during neurogenesis” before onset. Looking further back into prodromal periods may offer some clues. However, studies of clinically high-risk patients have found decreases in gray matter but not increases prior to psychosis onset (Pantelis et al., 2009; Wood et al., 2013).
Therefore, taking into account that recruitment, population with regard to patient subtypes, or image analysis methodology may differ across studies, multiple neural mechanisms may be at play around the period of the psychosis onset: While many gray matter regions are on a progressively decreasing trajectory, others, including the thalamus and ACC, follow a trajectory of decrease during prodrome, increase shortly after onset, and continuous decrease thereafter, and while some brain networks undergo neural structural changes, others undergo neuronal oscillation changes, both of which are fundamental to normal functioning. All of this causes us to wonder what these different models are reflections of and what the different driving forces are behind them.
Pantelis C, Yücel M, Bora E, Fornito A, Testa R, Brewer WJ, Velakoulis D, Wood SJ. Neurobiological markers of illness onset in psychosis and schizophrenia: The search for a moving target. Neuropsychol Rev . 2009 Sep ; 19(3):385-98. Abstract
Radua J, Borgwardt S, Crescini A, Mataix-Cols D, Meyer-Lindenberg A, McGuire PK, Fusar-Poli P. Multimodal meta-analysis of structural and functional brain changes in first episode psychosis and the effects of antipsychotic medication. Neurosci Biobehav Rev . 2012 Nov ; 36(10):2325-33. Abstract
Schultz CC, Fusar-Poli P, Wagner G, Koch K, Schachtzabel C, Gruber O, Sauer H, Schlösser RG. Multimodal functional and structural imaging investigations in psychosis research. Eur Arch Psychiatry Clin Neurosci . 2012 Nov ; 262 Suppl 2():S97-106. Abstract
Wood SJ, Reniers RL, Heinze K. Neuroimaging findings in the at-risk mental state: a review of recent literature. Can J Psychiatry . 2013 Jan ; 58(1):13-8. Abstract
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Related News: Default Mode Network Acts Up in SchizophreniaComment by: Vince Calhoun
Submitted 27 January 2009
Posted 27 January 2009
In this work the authors test for differences in the default mode network between healthy controls, patients with schizophrenia, and first degree relatives of the patients. They look at both the degree to which the default mode is modulated by a working memory task and also examine the strength of the functional connectivity. The controls are found to show the most default mode signal decrease during a task, with relatives and patients showing much less. The controls, relatives, and patients show increasing amounts of functional connectivity within the default mode regions. In addition, signal in some of the regions correlated with positive symptoms. The findings in the chronic patients and controls are consistent with our previous work in Garrity et al., 2007, which also showed significantly more functional connectivity in the default mode of schizophrenia patients and significant correlations in certain regions of the default mode with positive symptoms, and in both cases the regions we identified are similar to those shown in the Whitfield-Gabrieli paper. Our work in Kim et al., 2009, was a large multisite study showing significantly fewer default mode signal decreases for the auditory oddball task in chronic schizophrenia patients, again consistent with the Whitfield-Gabrieli paper, but in a different task.
The most interesting contribution of the Whitfield-Gabrieli paper is their inclusion of a first-degree relative group. They found that the first-degree relatives are “in between” the healthy controls and the chronic patients in terms of both the degree to which they modulate the default mode, as well as in their degree of functional connectivity. This has interesting implications in terms of the genetic aspects of the illness and suggests that the default mode may be a potential schizophrenia endophenotype. It will be interesting in future studies to examine both the heritability of the default mode patterns and their genetic underpinnings.
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Related News: Default Mode Network Acts Up in Schizophrenia
Comment by: Edith Pomarol-Clotet
Submitted 28 January 2009
Posted 28 January 2009
The Default Mode Network and Schizophrenia
For a long time functional imaging research has focused on brain activations. However, since 2001 it has been appreciated that there is also a network of brain regions—which includes particularly two midline regions, the medial prefrontal cortex and the posterior cingulate cortex/precuneous—which deactivates during performance of a wide range of cognitive tasks. Why some brain regions should be active at rest but deactivate when tasks have to be performed is unclear, but there is intense speculation that this network is involved in functions such as self-reflection, self-monitoring, and the maintenance of one’s sense of self.
Could the default mode network be implicated in neuropsychiatric disease states? There is evidence that this is the case in autism, and a handful of studies have been also carried out in schizophrenia. Now, Whitfield-Gabrieli and colleagues report that 13 schizophrenic patients in the early phase of illness showed a failure to deactivate the anterior medial prefrontal node of the default mode network when they performed a working memory task. They also find that failure to deactivate is seen to a lesser but still significant extent in unaffected first-degree relatives of the schizophrenic patients, and that the degree of failure to deactivate is associated with both the severity of positive and negative symptoms in the patients.
Importantly, the findings of Whitfield-Gabrieli and colleagues are closely similar to those of another recent study by our group (Pomarol-Clotet et al., 2008), which found failure to deactivate in the medial prefrontal cortex node of the default mode network in 32 chronic schizophrenic patients. This is a striking convergence in the field of functional imaging studies of schizophrenia, which has previously been marked by diverse and often conflicting findings. Additionally, in both studies the magnitude of the difference between patients and controls was large and visually striking. These findings suggest that we may be dealing with an important abnormality which could be close to the disease process in schizophrenia.
If so, what does dysfunction in the default mode network mean? On the one hand, failure to deactivate part of a network whose activity normally decreases when attention has to be turned to performance of external tasks might be expected to interfere with normal cognitive operations. Consistent with this, cognitive impairment is nowadays accepted as being an important, or even a “core” feature of schizophrenia. Perhaps more importantly, could it be that default mode network dysfunction can help us understand the symptoms of schizophrenia? As Whitfield-Gabrieli and colleagues note, if the default mode network is involved in self-reflection, self-monitoring, and maintenance of one’s sense of self, then failure of deactivation might lead to an exaggerated focus on one’s own thoughts and feelings, excessive self-reference, and/or a breakdown in the boundary between the inner self and the external world. The default mode network may thus have the potential to account for two major realms of clinical abnormality in schizophrenia—its symptoms and the cognitive impairment that is frequently associated with them.
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Related News: Default Mode Network Acts Up in Schizophrenia
Comment by: Samantha Broyd, Edmund Sonuga-Barke
Submitted 4 February 2009
Posted 4 February 2009
The surge in scientific interest in patterns of connectivity and activation of resting-state brain function and the default-mode network has recently extended to default-mode brain dysfunction in mental disorders (for a review, please see Broyd et al., 2008). Whitfield-Gabrieli et al. examine resting-state and (working-memory) task-related brain activity in 13 patients with early-phase schizophrenia, 13 unaffected first-degree relatives, and 13 healthy control participants. These authors report hyperconnectivity in the default-mode network in patients and relatives during rest, and note that this enhanced connectivity was correlated with psychopathology. Further, patients and relatives exhibited reduced task-related suppression (hyperactivation) of the medial prefrontal region of the default-mode network relative to the control group, even after controlling for task performance.
The findings from the Whitfield-Gabrieli paper are in accordance with those from a number of other research groups investigating possible default-mode network dysfunction in schizophrenia. For example, in a similar working memory task Pomarol-Clotet and colleagues (2008) have also shown reduced task-related suppression of medial frontal nodes of the default-mode network in 32 patients with chronic schizophrenia. However, the findings are at odds with research reporting widespread reductions in functional connectivity in the resting brain of this clinical group (e.g., Bluhm et al., 2007; Liang et al., 2006). As noted by Whitfield-Gabrieli et al., increased connectivity and reduced task-related suppression of default-mode activity may redirect attentional focus from task-related events to introspective and self-referential thought processes. The reduced anti-correlation between the task-positive and default-mode network in patients further supports and helps biologically ground suggestions of the possibility of an overzealous focus on internal thought. Perhaps even more interestingly, the study by Whitfield-Gabrieli and colleagues suggests that aberrant patterns of activation and connectivity in the default-mode network, and in particular the medial frontal region of this network, may be associated with genetic risk for schizophrenia. Although there are some inconsistencies in the literature regarding the role of the default-mode network in schizophrenia, the work of Whitfield-Gabrieli and others suggests that this network may well contribute to the pathophysiology of this disorder and is relevant to contemporary models of schizophrenia. Indeed, the recent flurry in empirical research investigating the clinical relevance of this network to mental disorder has highlighted a number of possible putative mechanisms that might link the default-mode network to disorder. Firstly, effective transitioning from the resting-state to task-related activity appears to be particularly vulnerable to dysfunction in mental disorders and may be characterized by deficits in attentional control. Sonuga-Barke and Castellanos (2007) have suggested that interference arising from a reduction in the task-related deactivation of the default-mode network may underlie the disruption of attentional control. The default-mode interference hypothesis proposes that spontaneous low-frequency activity in the default-mode network, normally attenuated during goal-directed tasks, can intrude on task-specific activity and create cyclical lapses in attention resulting in increased variability and a decline in task performance (Sonuga-Barke and Castellanos, 2007). Sonuga-Barke and Castellanos (2007) suggest that the efficacious transition from rest to task and the maintenance of task-specific activity may be moderated by trait factors such as disorder. Secondly, the degree of functional connectivity in the default-mode network may highlight problems of reduced connectivity, or excess functional connectivity (e.g., schizophrenia), which suggests a zealous focus on self-referential processing and introspective thought. Thirdly, the strength of the anti-correlation between the default-mode and task-positive networks may also indicate a clinical susceptibility to introspective or extrospective orienting. Finally, future research should continue to examine the etiology of the default-mode network in schizophrenia.
Bluhm, R.L., Miller, J., Lanius, R.A., Osuch, E.A., Boksman, K., Neufeld, R.W.J., Théberge, J., Schaefer, B., & Williamson, P. (2007). Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients: Anomalies in the default network. Schizophrenia Bulletin, 33, 1004-1012. Abstract
Broyd, S.J., Demanuele, D., Debener, S., Helps, S.K., James, C.J., & Sonuga-Barke, E.J.S. (in press). Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev. 2008 Sep 9. Abstract
Liang, M., Zhou, Y., Jiang, T., Liu, Z., Tian, L., Liu, H., and Hao, Y. (2006). Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging. NeuroReport, 17, 209-213. Abstract
Pomarol-Clotet, E., Salvador, R., Sarro, S., Gomar, J., Vila, F., Martinez, A., Guerrero, A.,Ortiz-Gil, J., Sans-Sansa, B., Capdevila, A., Cebemanos, J.M., McKenna, P.J., 2008. Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default-mode network? Psychological Medicine, 38, 1185–1193. Abstract
Sonuga-Barke, E.J.S., Castellanos, F.X., 2007. Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neuroscience Biobehavioural Reviews, 31, 977–986. Abstract
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Related News: Default Mode Network Acts Up in Schizophrenia
Comment by: Yuan Zhou, Tianzi Jiang, Zhening Liu
Submitted 18 February 2009
Posted 22 February 2009
I recommend the Primary Papers
The consistent findings on default-mode network in human brain have attracted the researcher’s attention to the task-independent activity. The component regions of the default-mode network, especially medial prefrontal cortex and posterior cingulate cortex/precuneus, are related to self-reflective activities and attention. Both of these functions are observed to be impaired in schizophrenia. And thus the default-mode network has also attracted more and more attention in the schizophrenia research community. The study of Whitfield-Gabrieli et al. shows a further step along this research streamline.
The authors found hyperactivity (reduced task suppression) and hyperconnectivity of the default network in schizophrenia, and found that hyperactivity and hyperconnectivity of the default network are associated with poor work memory performance and greater psychopathology in schizophrenia. And they found less anticorrelation between the medial prefrontal cortex and the right dorsolateral prefrontal cortex, a region showing increased task-related activity in schizophrenia, whether during rest or task. Furthermore, the hyperactivity in medial prefrontal cortex is negatively related to the hyperconnectivity of the default network in schizophrenia.
There are two main contributions in this work. First, they found significant correlation between the abnormalities in the default mode network and impaired cognitive performance and psychopathology in schizophrenia. Thus they propose a new explanation for the impaired working memory and attention in schizophrenia, and propose a possibility that schizophrenic symptoms, such as delusions and hallucinations, may be due to the blurred boundary between internal thoughts and external perceptions. Secondly, they recruited the first-degree relatives of these patients in this study, and found that these healthy relatives showed abnormalities in the default network similar to that of patients but to a lesser extent. This is the first study investigating the default mode network of relatives of individuals with schizophrenia. This finding indicates that the dysfunction in the default mode network is associated with genetic risk for schizophrenia.
The findings in schizophrenia are consistent with our previous work (Zhou et al., 2007), in which we also found hyperconnectivity of the default mode network during rest. Considering the differences in ethnicity of participants (Chinese in our study) and methodology, the consistency in the hyperconnectivity of the default mode network in schizophrenia is exciting, which supports the possibility that abnormality in the default-mode network may be a potential imaging biomarker to assist diagnosis of schizophrenia. However, this needs to be validated in future studies with a large sample size, due to other contradictory findings, for example, the reduced resting-state functional connectivities associated with the posterior cingulate cortex in chronic, medicated schizophrenic patients (Bluhm et al., 2007). In addition, further studies should focus on default-mode function in different clinical subtypes, as schizophrenia is a complicated disorder. Finally, it should be noticed that the hyperconnectivity of the default-mode network is not exclusively contradictory with hyperconnectivity in other regions, as we previously found (Liang et al., 2006). It is possible that hyperconnectivity and hyperconnectivity coexist in the brains of individuals with schizophrenia and together lead to the complicated symptoms and cognitive deficits.
Bluhm, R. L., Miller, J., Lanius, R. A., Osuch, E. A., Boksman, K., Neufeld, R. W., et al., 2007. Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients: anomalies in the default network. Schizophr Bull 33, 1004-1012. Abstract
Liang, M., Zhou, Y., Jiang, T., Liu, Z., Tian, L., Liu, H., et al., 2006. Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging. Neuroreport 17, 209-213. Abstract
Whitfield-Gabrieli, S., Thermenos, H. W., Milanovic, S., Tsuang, M. T., Faraone, S. V., McCarley, R. W., et al., 2009. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A 106, 1279-1284. Abstract
Zhou, Y., Liang, M., Tian, L., Wang, K., Hao, Y., Liu, H., et al., 2007. Functional disintegration in paranoid schizophrenia using resting-state fMRI. Schizophr Res 97, 194-205. Abstract
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Related News: Cortical Folding May Predict Antipsychotic Drug Response
Comment by: Robert B. Zipursky
Submitted 6 September 2013
Posted 6 September 2013
Palaniyappan et al. demonstrated that subjects with a first episode of psychosis (FEP) had a reduction in the extent of cortical gyrification in multiple brain areas compared to healthy comparison subjects. Notably, non-responders showed more prominent hypogyria than responders did in a number of frontal and temporal areas irrespective of whether the underlying diagnosis was of an affective or non-affective psychosis.
Previous studies using structural MRI have established that subjects with FEP have smaller cerebral gray matter volumes (Zipursky et al., 1992) but have left open the question of whether these differences reflect the result of early neurodevelopmental processes that are aberrant versus progressive degenerative losses taking place more proximal to the onset of psychosis. Palaniyappan et al. suggest that measures of cortical gyrification, which is believed to be particularly active during intrauterine growth and early infancy, are more indicative of a developmental than a degenerative process. Their finding that subjects with FEP have reductions in cortical gyrification is interpreted as supporting the neurodevelopmental origin of these differences.
The debate over whether the differences in brain structure found in FEP are developmental or degenerative in nature (Zipursky et al., 2012) is of particular relevance to the question of treatment response. If the neuropathology of schizophrenia involves a progressive degenerative process, then intervening as early as possible to halt this process and bring about a remission of symptoms becomes of critical importance. There has, therefore, been intense interest in the possibility that the duration of untreated psychosis (DUP) is an important determinant of treatment response in FEP (Perkins et al., 2004). However, it has remained unclear whether the association reported between DUP and treatment response is a causal one; it is possible that individuals with longer DUPs might have more longstanding developmental problems that result in a more insidious onset and less robust response to treatment. This report by Palaniyappan et al. reinforces the view that poor treatment response is more likely to be understood as reflecting more severe longstanding developmental differences in brain structure. These possibilities need not be mutually exclusive; early developmental changes in the brain and later progressive changes occurring closer to illness onset might both contribute to poor treatment response. Poor clinical outcomes could also relate to DUP through a range of different mechanisms that do not require that a progressive process is taking place in the brains of those with an FEP (Zipursky et al., 1992).
Most patients with FEP will have a robust response to antipsychotic medication. We were able to demonstrate a number of years ago that FEP patients who did not respond to low doses of haloperidol had smaller cortical gray matter volumes than responders did (Zipursky et al., 1998) and that even with higher doses of haloperidol, these individuals had less improvement than the low-dose responders (Zhang-Wong et al., 1999).
The results of Palaniyappan et al. are in keeping with these findings. The focus of much research on treatment response has been to understand the determinants of antipsychotic response. As most FEP patients will have a robust response, it may be of greater interest to ask what factors underlie poor response. The 20-30 percent of individuals with FEP who do not have a remission of symptoms are likely to have a poor outcome in the longer run as well. Understanding that poor response may reflect the result of longstanding neurodevelopmental differences, as suggested by this study by Palaniyappan et al., may lead to more specialized approaches to identifying and treating poor responders earlier in their illness course (Agid et al., 2007). The development of more sophisticated, stratified approaches to the management of schizophrenia would be enhanced if neuroimaging markers could be proven to be valuable in predicting treatment response. The study by Palaniyappan is an important step in this direction. Further research will be required to ensure that medication effects are not confounding the measurement of cortical gyrification and that measures of gyrification are clinically meaningful determinants of treatment response.
Agid O, Remington G, Kapur S, Arenovich T, Zipursky RB. Early use of clozapine for poorly responding first-episode psychosis. J Clin Psychopharmacol. 2007;27(4):369-73. Abstract
Perkins D, Lieberman J, Gu H, Tohen M, McEvoy J, Green A, et al. Predictors of antipsychotic treatment response in patients with first-episode schizophrenia, schizoaffective and schizophreniform disorders. Br J Psychiatry. 2004;185:18-24. Abstract
Zhang-Wong J, Zipursky RB, Beiser M, Bean G. Optimal haloperidol dosage in first-episode psychosis. Can J Psychiatry. 1999;44(2):164-7. Abstract
Zipursky RB, Lim KO, Sullivan EV, Brown BW, Pfefferbaum A. Widespread cerebral gray matter volume deficits in schizophrenia. Arch Gen Psychiatry. 1992;49(3):195-205. Abstract
Zipursky RB, Zhang-Wong J, Lambe EK, Bean G, Beiser M. MRI correlates of treatment response in first episode psychosis. Schizophr Res. 1998;30(1):81-90. Abstract
Zipursky RB, Reilly TJ, Murray RM. The myth of schizophrenia as a progressive brain disease. Schizophr Bull. 2012. Abstract
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Related News: Cortical Folding May Predict Antipsychotic Drug Response
Comment by: S. Charles Schulz (Disclosure)
Submitted 6 September 2013
Posted 6 September 2013
This study by Palaniyappan et al. is an excellent step in using neuroscience measures—in this case MRI imaging—to address the important issue of treatment outcomes. As noted by the authors, this is a new way to address outcome in the early phase of psychotic disorders and may be related to the issue of poorer outcome with increased duration of untreated psychosis (DUP). In other words, the literature does show that approximately 25 percent of young people with schizophrenia are not responsive to first-line antipsychotic medication (Agid et al., 2011). Therefore, ways to provide the best treatments sooner can be very helpful in improving outcome.
The authors use an excellent test and examine more than just a single brain area. This newer strategy can lead to much better assessments than earlier work with a single measure. Further, by using MRI measures in the first episode of psychotic illness, they are adding to the initial evaluation of psychotic illness—making sure that there is not some other cause of psychosis.
In addition, it is very useful that they examined a range of psychotic disorders and note that the assessment is useful across these illnesses; therefore, the findings are not limited to schizophrenia alone. Some clinicians will be aware that this may lead to a broader assessment of treatment initiation and moving along on algorithms for a broader range of patients.
In summary, this is a very good contribution and can lead to new care pathways in the early stages of psychosis.
Agid O, Arenovich T, Sajeev G, Zipursky RB, Kapur S, Foussias G, Remington G. An algorithm-based approach to first-episode schizophrenia: response rates over 3 prospective antipsychotic trials with a retrospective data analysis. J Clin Psychiatry. 2011 Nov;72(11):1439-44. Abstract
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