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Psychosis onset is characterized by white matter and electrophysiologic abnormalities. The relation between these factors in the development of illness is almost unknown. We studied the relation between white matter volumes and P300 in prodromal psychosis.
We assessed white matter volume (detected using magnetic resonance imaging) and electrophysiologic response during an oddball task (P300) in healthy controls and individuals at high clinical risk for psychosis (with an “at-risk mental state” [ARMS]).
We included 41 controls and 39 patients with an ARMS in our study. A psychotic disorder developed in 26% of the ARMS group within the follow-up period of 2 years. The P300 amplitude was significantly lower in the ARMS group than in the control group. The ARMS group showed reduced volume of white matter underlying the left superior temporal gyrus and the left superior frontal gyrus and increased volume of white matter underlying the right insula and the right angular gyrus compared with controls. Relative to individuals who did not later become psychotic, the subgroup in whom psychosis subsequently developed had a smaller volume of white matter underlying the left precuneus and the right middle temporal gyrus and increased volume in the white matter underlying the right middle frontal gyrus. We observed a significant interaction in the right middle frontal gyrus: white matter volume was negatively associated with P300 amplitude in the ARMS group and positively associated with P300 amplitude in the control group.
The voxel-based morphometry method alone cannot determine whether abnormal white matter volumes are due to an altered number of axonal connections or decreased myelination.
P300 abnormalities precede the onset of psychosis and are directly related to white matter alterations, representing a correlate of an increased vulnerability to disease.
A number of studies have shown that patients with schizophrenia display a smaller than normal auditory P300 over the midline central and parietal scalp electrode locations (for a meta-analysis, see Jeon and colleagues1). Auditory P300 abnormalities are already evident at the time of the initial onset of illness2–4 and are related to the duration of untreated psychosis.5 Despite the potential role of P300 abnormalities in the etiopathology of schizophrenia, its cerebral origin is not clear as it involves the complex summation of activity from multiple brain regions, particularly the various association areas of the cerebral cortex.6 P300 may have multiple brain generators, including the loci in the temporal, frontal and parietal lobes.4 Consistently, studies in patients with chronic schizophrenia have pinpointed an association between P300 and structural alterations in prefrontal7 and temporal4,8,9 areas. However, the relation between P300 abnormalities and brain structure in the development of the disease is still unknown. One way to address this point is to investigate the prodrome to schizophrenia. Individuals with an “at-risk mental state” (ARMS) present with prodromal symptoms of psychosis and have a very high risk for the disease developing within the next 2 years.10 The ARMS is characterized by poor psychosocial functioning11 and neurocognitive impairments.12 Interestingly, 3 recent independent studies of individuals at enhanced risk for psychosis have confirmed that P300 abnormalities are already evident in the prepsychotic phases.13–15 P300 can index a neurobiologic vulnerability to schizophrenia, in line with other studies showing P300 abnormalities in relatives of individuals with psychosis.16,17 On the other hand, neuroimaging studies have indicated that patients at high risk for psychosis show alterations in white matter18,19 volume in fronto-temporal regions. In particular, the first study exploring white matter in the prepsychotic phases found reduced temporal lobe volume in patients at increased clinical risk for psychosis.18 Another study found that the ARMS patients who later became psychotic had larger volumes of white matter in the frontal lobe.19 These alterations resemble those observed during the established phases of the illness but are less marked.20 White matter abnormalities in schizophrenia research have been interpreted as disturbed connectivity of neural networks (“disconnectivity hypothesis”21), affecting prefrontal–temporolimbic connections,22,23 cortico–cerebellar–thalamic–cortical circuits24,25 and interhemispheric connectivity.26 In line with such theories, fronto-temporal disconnectivity during cognitive functioning has been recently observed in ARMS patients.27,28 Disruption of white matter tracts may thus alter the electrophysiologic response and perturb brain connectivity during the prepsychotic phases. A combined event-related potential (ERP) and magnetic resonance imaging (MRI) study in healthy adults has confirmed significant correlations between P300 measures and white matter contractions,29 whereas a recent study involving patients presenting with a first episode of psychosis has found specific correlations between anisotropy values and P300 measures.30 Although there is independent evidence indicating both P300 and white matter alterations in patients at risk for psychosis, no formal study has properly tested the putative relation of these factors during the prepsychotic phases.
To our knowledge, this is the first study to address the relation between white matter volumes and P300 in prodromal psychosis. To address this, we have employed voxel-based morphometry (VBM) and electrophysiology measures (P300). Although the VBM technique was originally developed to assess grey matter abnormalities, a number of recent imaging studies have employed the method to evaluate white matter volume in healthy and clinical populations. On the basis of the evidence above, we predicted that ARMS patients would show abnormal P300 amplitude and regional white matter volume compared with controls, that such abnormalities would be directly related and that these alterations would predict later transition to psychosis.
We recruited individuals meeting Personal Assessment and Crisis Evaluation (PACE) criteria for ARMS31 from Outreach and Support in South London (OASIS).32 The diagnosis was based on assessment by 2 experienced clinicians using the Comprehensive Assessment for the ARMS (CAARMS)33 and a consensus meeting with the clinical team. An individual can meet criteria for ARMS in 1 or more of 3 ways: 1) a recent decline in function coupled with either schizotypal personality disorder or a first-degree relative with psychosis, 2) attenuated positive symptoms and 3) a brief psychotic episode of less than 1 week’s duration that resolves without antipsychotic medication. Transition to psychosis was defined according to the criteria in the CAARMS (i.e., presence of at least 1 positive psychotic symptom at high severity for more than 1 week). The ARMS group was representative of the local population of people presenting with an ARMS in terms of age, sex, race and duration and intensity of symptoms. We excluded patients with a history of neurologic disorders or if they met the DSM-IV criteria for a substance-abuse or dependence disorder.
We recruited healthy volunteers from the same geographic area as participants in the ARMS group via advertisements in the local media. Inclusion criteria were no personal history of psychiatric symptoms (as assessed by the Structured Clinical Interview for DSM-IV Axis I Disorders, nonpatient edition [SCID-NP]34), no substance dependence or abuse, no use of psychotropic medications, no medical illness and no family history of psychiatric illness (as assessed by the SCID-NP34).
We evaluated handedness using the Lateral Preferences Inventory.35 Informed consent was collected from all participants, and the protocol was approved by the local Ethical Committee (Institute of Psychiatry).
The severity of symptoms in the clinical groups was assessed at the time of scanning using the CAARMS33 and the Positive and Negative Symptom Scale (PANSS).36 Premorbid intelligence was assessed using the National Adult Reading Test (NART).37 We tested the effect of group on demographic and clinical measures using analyses of variance for parametric variables, and Mann–Whitney U tests were used to compare the ARMS and control groups for nonparametric variables after checking for equality of variance with the Levene test.
Images were acquired on a 1.5-T General Electric Signa LX system using a standard quadrature head coil at the Maudsley Hospital, London, UK. A 3-dimensional T1-weighted inversion recovery prepared spoiled gradient recalled echo (SPGR) sequence was performed with the following parameters: pure coronal orientation, 128 slices, slice thickness 1.5 mm, echo time (TE) 5.1 ms, repetition time (TR) 17.9 ms, inversion time (TI) 450 ms, flip angle 20°, matrix 256 × 144 over a field of view (FOV) of 22 × 20 cm, reconstructed to a 256 × 256 matrix over a FOV of 22 × 22cm, number of excitation (NEX) 0.75.
Structural images were preprocessed using optimized voxel-based morphometry (VBM) implemented with Statistical Parametric Mapping software (SPM5) running under MATLAB version 7.0. Voxel-based morphometry is a whole-brain, unbiased, semiautomated technique for characterizing regional cerebral differences in structural MRI scans.38 First, structural images were segmented to extract white matter and then normalized to an asymmetric template in Montreal Neurological Institute (MNI) stereotactic space in a recursive fashion. Image segmentation incorporated an intensity nonuniformity correction to account for smooth intensity variations caused by gradient distortions and different positions of cranial structures within the MRI coil.38 We added a further step to ensure that the total amount of white matter in each voxel was conserved before and after spatial normalization.39 This modulation step involved multiplying the spatially normalized white matter by its relative volume before and after spatial normalization. The resulting white matter images were finally smoothed with an 8-mm isotropic Gaussian kernel. Smoothing is required to compensate for the inexact nature of spatial normalization and to maximize the chance that regional effects are expressed at a spatial scale where homologies in structural anatomy exist across participants. After smoothing, each voxel represents the local average amount of white matter in the region, the size of which is defined by the smoothing kernel. We performed an analysis of variance (ANOVA) to identify significant differences in white matter volume across groups; age and sex were included as covariates of no interest to reduce the potential impact of these variables on the findings.40 Inferences were made using a statistical threshold of p < 0.05, family wise error (FWE)–corrected. Significant foci were anatomically localized using the standard atlas of Talairach and Tournoux.
Voluntary and automatic attention yield distinct scalp-recorded ERPs, referred to as the P3b (target detection) and the P3a (novelty detection), respectively. The P3b is a positive- going ERP with parietal maximum amplitude and a peak latency of about 300–600 ms in young adults. It is typically elicited in tasks wherein 2 types of stimuli of unequal probability are presented, and attention is to be paid to the infrequent ones, such as the oddball tasks.41 In this study, we obtained the P300 (P3b) with a standard auditory oddball paradigm42 in a subsample of the ARMS (n = 28) and control groups (n = 13). Stimuli were 480 dB tones, with a 2-second (standard deviation [SD] 0.2 s) interstimulus interval presented through bilateral intra-aural earphones. Eighty percent of the tones were “nontargets” of 1000 Hz and 20% were “targets” of 1500 Hz in a random sequence. We instructed participants to keep their eyes open and press a button in response to target tones only. Electroencephalography (EEG) data were collected from 64 scalp sites according to the 10/20 International System and were grounded at Fpz using sintered electrodes in a cap.14 Vertical and horizontal electrooculographs monitored eye movements. Data were continuously digitized at 1000 Hz with a 0.05- to 100-Hz band-pass filter (24 dB/octave roll-off). Impedances were kept below 5 k. We employed a neuroscan linear regression procedure to minimize ocular artifacts.43 The continuous EEG recording was epoched (−100 to 700 ms), baseline-corrected using the prestimulus interval (−100 to 0 ms), band-pass filtered (0.05 to 45 Hz) and averaged for targets and nontargets separately.42 The P300 was defined as a positive waveform generated by the target tones and peaking between 280 and 500 ms poststimulus. The P300 results of a larger sample have been previously published.14 We analyzed between-group differences in P300 amplitude with independent t tests (p < 0.05).
To explore the correlation between the white matter volume and P300 amplitude, we entered P300 values as covariates in the between-group VBM analysis. Results were reported at p < 0.05, FWE-corrected. We also completed a post hoc analysis of potential interactions between white matter volumes and P300 amplitude by extracting the individual volumes and testing them in a general linear regression model (dependent variable P300 amplitude, independent variable regional grey matter volume) in SPSS (p < 0.05). We used the Cook distance test to assess the effect of potential outliers on the correlations.
We included 41 healthy controls and 39 patients with an ARMS in our study. All participants were right-handed and native English speakers. The 2 groups were matched on socio-demographic variables, including age, premorbid IQ, laterality quotient, race and years of education. The ARMS group showed higher unemployment rates than the control group. As expected, patients at clinical risk for psychosis showed higher scores on the PANSS subscales compared with controls. When subsamples of the original cohort were selected for specific imaging analysis, we carefully checked that participants in the ARMS and control groups were matched on sociodemographic characteristics. Clinical and sociodemographic characteristics of all participants are displayed in Table 1.
The sample of patients at risk for psychosis received standard clinical management through the OASIS service, irrespective of participation in this study. About 80% of the ARMS group received cognitive behavioural therapy, and about 46% received low-dose atypical antipsychotic medication. The sample was followed up clinically by the OASIS service, and 10 patients (26%) experienced a psychotic episode within the follow-up period of 2 years (ARMS with transition = ARMS-T; ARMS without transition = ARMS-NT; Table 2).
The P300 amplitude (PZ electrode) was significantly lower in the subsample of patients in the ARMS group (n = 28, mean 9.72, SD 7.08 μV) than in the control group (n = 13, mean 13.62, SD 4.92 μV; t39 = 2.041, p = 0.049, Fig. 1). No significant difference in P300 amplitude between ARMS-T and ARMS-NT participants was observed (mean P300 amplitude 10.22, SD 7.71 μV in the in ARMS-T group v. 7.89 μV, SD 3.98 in the ARMS-NT group; t26 = 1.09, p = 0.61).
At baseline, there were significant white matter volumetric differences between participants at high risk for psychosis (n = 39) and healthy controls (n = 41). Relative to the control group, the ARMS group showed a smaller volume of white matter underlying the left superior temporal gyrus and the left superior frontal gyrus. In addition, the ARMS group showed an increased volume of white matter underlying the right insula and the right angular gyrus compared with the control group (Table 3, Fig. 2).
At baseline, there were significant white matter volumetric differences between participants who were at high risk according to their clinical outcome at follow-up. Relative to the ARMS-NT subgroup (n = 29), the ARMS-T subgroup (n = 10) had a smaller volume of white matter underlying the left precuneus and the right middle temporal gyrus and increased volume of the white matter underlying the right middle frontal gyrus (Table 3).
There was a positive correlation (R = 0.36, F1,39 = 5.74, p = 0.023) between white matter volume of the right genu of the corpus callosum (MNI space x, y, z = 2, 24, −4; KE = 97, Z = 4.93) and P300 amplitude across the entire subsample of participants who underwent this procedure (ARMS group n = 28, control group n = 13). The correlation survived correction after the removal of potential outliers as identified with the Cook distance test (R = 0.35, F1,39 = 4.85, p = 0.031; Fig. 3). No negative correlations between white matter volume and P300 amplitude were observed.
Across the subsample of control group participants (n = 13), there was a positive correlation (R = 0.73, F1,11 = 12.75, p = 0.029) between white matter volumes underlying the right middle frontal gyrus (MNI space x, y, z = 30, 40, 22; KE = 72, Z = 4.74) and P300 amplitude. The correlation survived correction after the removal of potential outliers as identified with the Cook distance test (R = 0.83, F1,11 = 19.41, p = 0.011). No negative correlations between white matter volume and P300 amplitude were observed.
Across the subsample of participants in the ARMS group (n = 28), there was a positive correlation (R = 0.71, F1,26 = 26.41, p < 0.001) between white matter volume in a cluster underlying the right supramarginal gyrus and extending in the right arcuate fasciculus (MNI space x, y, z = 48, −46, 30; KE = 108, Z = 4.57) and P300 amplitude. The correlation survived correction after the removal of potential outliers as identified with the Cook distance test (R = 0.65, F1,26 = 16.08, p = 0.021; Fig. 3). No negative correlations between white matter volume and P300 amplitude were found.
There was a significant P300 × white matter × group interaction in a cluster underlying the right middle frontal gyrus (MNI space x, y, z = 30, 40, 22; KE = 79, Z = 4.38, p = 0.041). Post hoc analysis showed that in this region, white matter volume was positively correlated with P300 amplitude in the control group and negatively correlated in the ARMS group (Fig. 3).
The goal of the present study was to address the relation between white matter alterations and P300 abnormalities in patients at high clinical risk for psychosis. Using 2 different neuroimaging protocols in the same patients is logistically difficult, and to our knowledge, no investigation has ever addressed this issue in the prodromal phases of psychosis. We found that participants in the ARMS group had abnormal white matter volumes, with temporoparietal and prefrontal alterations being associated with transition to psychosis. The ARMS group also had lower P300 amplitude than the control group. We observed significant correlations between white matter and P300 amplitude in the temporo-parietal junction and in the prefrontal cortex.
In line with our preliminary hypothesis, the ARMS group showed reduced volume of white matter underlying the left superior temporal gyrus and the left superior frontal gyrus compared with the control group. The only available VBM study of white matter volume comparing high-risk patients and controls found white matter reductions in the temporal lobe of the patient group.18 Our results further confirm that the temporal lobe plays a crucial role in the prodromal phases of psychosis. In addition, to our knowledge, we showed for the first time concurrent temporal and prefrontal white matter reductions on the left side. On the basis of the literature indicating abnormalities in brain connectivity between the superior temporal gyrus and the prefrontal cortex of the ARMS group,28 our findings may reflect an alteration of white matter volume in regions carrying fibres between the left frontal and left temporal lobes.19 Such abnormalities are consistent with structural and functional imaging studies in patients at risk for psychosis.44–46 In support of these findings, previous diffusion tensor imaging (DTI) studies in patients with schizophrenia have confirmed reduced anisotropy in the frontal cortex,47–50 the anterior cingulum51,52 and the temporal lobe.20,53
The ARMS group also showed a reduced P300 amplitude compared with controls, in line with our previous results in a larger sample14 and with other studies in patients at risk for psychosis.15,54 Functionally, the P300 reflects the summation of multiple, simultaneously occurring cognitive and brain processes that are linked to attentional resource allocation and memory-updating operations in the brain.6 Consequently, the observed P300 abnormalities in the ARMS group are consistent with data from behavioural studies indicating impaired performance on tasks that engage attention and executive processes.12 Given the cross-sectional design of the present study, it is not possible to determine whether in prodromal psychosis grey matter abnormalities lead to electrophysiologic alterations or vice versa. Nevertheless there is growing evidence from neuroimaging and postmortem studies for primary subtle changes of structural (subcortical) macrocircuit connectivity in patients with schizophrenia that may lead to secondary electrophysiologic abnormalities. For example, several studies have shown a significant reduction of oligodendroglial cells and ultrastructural alterations of myelin in patients with schizophrenia. Similarly, there is also growing evidence for abnormal expression of myelin-related genes in patients with schizophrenia (for a review, see Konrad and Winterer55).
Our finding of significant associations between white matter volume and electrophysiolgic measures during the odd-ball task is in line with our principal hypothesis. First, within the whole sample, we uncovered a positive correlation between the white matter volume of the genu of the corpus callosum and P300 amplitude: a reduction in white matter was associated with reduction in P300 amplitude. The corpus callosum is the major interhemispheric commissure between neocortical association regions; callosal transfers play a crucial role in interhemispheric communication and integration, and abnormalities of the corpus callosum can affect P300 amplitude. The corpus callosum size can reflect the myelinization of interhemispheric fibres, which would probably influence interhemispheric communication and, therefore, P300 measures. In line with these neuroanatomic considerations, 2 independent studies found that P300 amplitude and latency were positively correlated with the corpus callosum volume.29,56 There is further evidence indicating a positive correlation between anisotropy values of the genu and P300 measures during a continuous performance test.30
Second, we uncovered a positive association between P300 amplitude and the white matter volume underlying the right supramarginal gyrus extending into the right arcuate fasciculus. Such correlation was observed in the ARMS group but not in the control group. Although the intracerebral origins of the P300 (and its components P3a and P3b) are not clear, the main regions consistently implicated include the temporal– parietal junction, medial temporal complex and lateral pre-frontal cortex.57,58 In particular, the P3b-like potential (as the one employed in this study) engages the multimodal association cortex, including the supramarginal gyrus, which constitutes an associative area that receives auditory, visual and somatosensory imputs.57 Previous auditory oddball fMRI–ERP studies clearly indicated the supramarginal gyrus is the main generator of the scalp-recorded P3b.59 Lesion studies confirmed that discrete damage in the temporoparietal junction, including the supramarginal gyrus, results in severe reduction of P3b activity at posterior scalp sites in both the auditory60 and somatosensory modalities.61 Animal studies further support the notion that the posterior scalp P3b component marks activity in the supramarginal gyrus during engagement of early attention and memory processes.57 Previous MRI–EEG studies have shown that superior temporal gyrus volume is associated with smaller P300 in patients with chronic8 or first-episode4 schizophrenia. To our knowledge, our study is the first to demonstrate that a significant correlation between supramarginal white matter volume and P300 is already evident during the prodromal phases of psychosis. This finding is in line with recent theories suggesting that P300 amplitude alterations in patients with schizophrenia are associated with early temporo-parietal maturation abnormalities followed by further functional impairments later in life.15
Third, we found a significant group × white matter × P300 interaction in the right middle frontal gyrus, with white matter volume being correlated with P300 in the control group (positive correlation) and in the ARMS group (negative correlation). Previous functional imaging studies support the involvement of the dorsolateral prefrontal cortex during the oddball task62 and in the generation of P300 amplitude.63 A recent EEG–fMRI study investigating the localization and activities of the P300 generators further confirmed the engagement of the middle frontal gyrus in P300.64 Consequently, it is possible that the integrity of this region is fundamental to the physiologic generation of P300. There is also consistent neuroimaging evidence indicating that the prefrontal cortex is already altered in the ARMS group.44
Finally, we have attempted to identify the core abnormalities underlying transition to psychosis.65 Thus, we have compared the ARMS-T and the ARMS-NT subgroups. The ARMS-T subgroup showed robust volumetric white matter differences compared with the ARMS-NT subgroup, with white matter reductions in the parietal lobule and in the middle temporal gyrus and white matter increases in the right middle frontal gyrus. Previous MRI studies of ARMS groups have found grey matter reductions in parietal and temporal areas in cohorts of individuals at high risk for psychosis (for a review, see Wood and colleagues46). These structural abnormalities can be interpreted as reflecting an active pathologic process underlying the transition to psychosis. Given the interaction that we observed in the middle frontal gyrus, it is possible to speculate that the white matter increases in the ARMS-T group are associated with reduced P300 amplitude. Although we did not find P300 differences between the ARMS-T and ARMS-NT subgroups, we cannot exclude that in a larger sample size we would have been able to detect significant amplitude differences underlying transition to psychosis. White matter increases in ARMS-T groups have been previously reported to be a compensatory response to an abnormal reduction in grey matter volume.19 Such increases could also be considered reflective of increased pre-frontal cortical folding, as measured by the gyrification index, which can be seen as an indirect measure of axonal connectivity.66 Increased prefrontal gyrification has been demonstrated in patients with schizophrenia67 and has been shown to be predictive of transition to psychosis in high-risk cohorts.68
Limitations of the present study are well acknowledged. Voxel-wise structural image analysis is a method of looking for anatomic variations without prior hypotheses about the location and extent of those variations. However, using the VBM method alone, we could not tell if the abnormal white matter volumes were due to an altered number of axonal connections or decreased myelination. In fact, the amplitude and scalp topography of P300 is related to the number, size, location and orientation of the neural generators and to the strength and synchrony of the neural response of each generator. Disease can reduce P300 amplitude by weakening the neural generator response or by altering the connectivity between different generators. Diffusion tensor imaging or the application of tractography to the abnormal white matter regions identified in the present study can provide more detailed information about the tracts and the connectivity within white matter.
P300 abnormalities precede the psychosis onset and are directly related to white matter alterations, representing a correlate of an increased vulnerability to disease.
Competing interests: None declared.
Contributors: Dr. Fusar-Poli designed the study and wrote the article; all other authors reviewed the article. All authors acquired the data, which Drs. Fusar-Poli and Crossley analyzed. All authors approved publication of the article.