White matter reduction in patients with schizophrenia as revealed by voxel-based morphometry: an activation likelihood estimation meta-analysis

The interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach

The current DSM-oriented diagnostic paradigm has introduced the issue of heterogeneity, as it fails to account for the identification of the neurological processes underlying mental illnesses, which affects the precision of treatment. The Research Domain Criteria (RDoC) framework serves as a recognized approach to addressing this heterogeneity, and several assessment and translation techniques have been proposed. Among these methods, transforming RDoC scores from electronic medical records (EMR) using Natural Language Processing (NLP) has emerged as a suitable technique, demonstrating clinical effectiveness. Numerous studies have sought to use RDoC to understand the Diagnostic and Statistical Manual of Mental Disorders (DSM) categories from a qualified perspective, but few studies have examined the distribution variations and interaction characteristics of RDoC within various DSM categories through retrospective analyses. Therefore, we employed unsupervised learning to translate five domains of eRDoC scores derived from electronic medical records (EMR) of patients diagnosed with Major Depressive Disorder (MDD), Schizophrenia (SCZ), and Bipolar Disorder (BD) at West China Hospital between 2008 and 2021. The distribution characteristics, interaction networks, and potential clinical effectiveness of RDoC domains were analyzed. Using non-parametric statistical tests, we found that MDD had the highest score in Negative Valence System (NVS) (4.1, p < 0.001), while BD exhibited the highest score in Positive Valence System (PVS) score (4.9, p < 0.001) and Arousal System (AS) (4.4, p < 0.001). SCZ demonstrated the highest scores in Cognitive Systems (CS) (5.8, p < 0.001) and Social Processes Systems (SPS) (4.6, p < 0.001). Through Bayesian network (BN) analysis, we identified relatively consistent interaction relationships among various RDoC domains (NVS → AS, NVS → CS, NVS → PVS, as well as CS → SPS; parameter range = 0.156 to 0.635, p < 0.001). Lastly, using logistic regression and Cox proportional hazards models, we demonstrated that AS was significantly associated with the length of hospital stay (-0.21, p < 0.05) and 30-day readmission risk (adjusted odds ratio [aOR] = 0.91, 95% confidence interval [CI] 0.91-0.99) to some extent. In conclusion, we suggest that the eRDoC characteristics varied in different DSM. By Bayesian Network, we found NVS and CS might be potential source in interacting with other system. Furthermore, CS, SPS and AS were associated with the length of stay and 30-days readmission, making them effective for predicting prognosis of psychiatric disorders.

Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders

Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.

Baseline symptom-related white matter tracts predict individualized treatment response to 12-week antipsychotic monotherapies in first-episode schizophrenia

There is significant heterogeneity in individual responses to antipsychotic drugs, but there is no reliable predictor of antipsychotics response in first-episode psychosis. This study aimed to investigate whether psychotic symptom-related alterations in fractional anisotropy (FA) and mean diffusivity (MD) of white matter (WM) at the early stage of the disorder may aid in the individualized prediction of drug response. Sixty-eight first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single atypical antipsychotic throughout the first 12 weeks. Clinical symptoms were evaluated using the eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8). Follow-up assessments were conducted at the 4th, 8th, and 12th weeks by trained psychiatrists. LASSO regression model and cross-validation were conducted to examine the performance of baseline symptom-related alterations FA and MD of WM in the prediction of individualized treatment outcome. Fifty patients completed both clinical follow-up assessments by the 8th and 12th weeks. 30 patients were classified as responders, and 20 patients were classified as nonresponders. At baseline, the altered diffusion properties of fiber tracts in the anterior thalamic radiation, corticospinal tract, callosum forceps minor, longitudinal fasciculi (ILF), inferior frontal-occipital fasciculi (IFOF) and superior longitudinal fasciculus (SLF) were related to the severity of symptoms. These abnormal fiber tracts, especially the ILF, IFOF, and SLF, significantly predicted the response to antipsychotic treatment at the individual level (AUC = 0.828, P < 0.001). These findings demonstrate that early microstructural WM changes contribute to the pathophysiology of psychosis and may serve as meaningful individualized predictors of response to antipsychotics.

A Systematic Characterization of Structural Brain Changes in Schizophrenia

A systematic characterization of the similarities and differences among different methods for detecting structural brain abnormalities in schizophrenia, such as voxel-based morphometry (VBM), tensor-based morphometry (TBM), and projection-based thickness (PBT), is important for understanding the brain pathology in schizophrenia and for developing effective biomarkers for a diagnosis of schizophrenia. However, such studies are still lacking. Here, we performed VBM, TBM, and PBT analyses on T1-weighted brain MR images acquired from 116 patients with schizophrenia and 116 healthy controls. We found that, although all methods detected wide-spread structural changes, different methods captured different information - only 10.35% of the grey matter changes in cortex were detected by all three methods, and VBM only detected 11.36% of the white matter changes detected by TBM. Further, pattern classification between patients and controls revealed that combining different measures improved the classification accuracy (81.9%), indicating that fusion of different structural measures serves as a better neuroimaging marker for the objective diagnosis of schizophrenia.

Neuroprogression across the Early Course of Psychosis

Psychotic disorders are severe, debilitating, and even fatal. The development of targeted and effective interventions for psychosis depends upon on clear understanding of the timing and nature of disease progression to target processes amenable to intervention. Strong evidence suggests early and ongoing neuroprogressive changes, but timing and inflection points remain unclear and likely differ across cognitive, clinical, and brain measures. Additionally, granular evidence across modalities is particularly sparse in the "bridging years" between first episode and established illness-years that may be especially critical for improving outcomes and during which interventions may be maximally effective. Our objective is the systematic, multimodal characterization of neuroprogression through the early course of illness in a cross-diagnostic sample of patients with psychosis. We aim to (1) interrogate neurocognition, structural brain measures, and network connectivity at multiple assessments over the first eight years of illness to map neuroprogressive trajectories, and (2) examine trajectories as predictors of clinical and functional outcomes. We will recruit 192 patients with psychosis and 36 healthy controls. Assessments will occur at baseline and 8- and 16-month follow ups using clinical, cognitive, and imaging measures. We will employ an accelerated longitudinal design (ALD), which permits ascertainment of data across a longer timeframe and at more frequent intervals than would be possible in a single cohort longitudinal study. Results from this study are expected to hasten identification of actionable treatment targets that are closely associated with clinical outcomes, and identify subgroups who share common neuroprogressive trajectories toward the development of individualized treatments.

Tractography-based classification in distinguishing patients with first-episode schizophrenia from healthy individuals

BACKGROUND

Schizophrenia has been characterized as a neurodevelopmental disorder of brain disconnectivity. However, whether disrupted integrity of white matter tracts in schizophrenia can potentially serve as individual discriminative biomarkers remains unclear.

METHODS

A random forest algorithm was applied to tractography-based diffusion properties obtained from a cohort of 65 patients with first-episode schizophrenia (FES) and 60 healthy individuals to investigate the machine-learning discriminative power of white matter disconnectivity. Recursive feature elimination was used to select the ultimate white matter features in the classification. Relationships between algorithm-predicted probabilities and clinical characteristics were also examined in the FES group.

RESULTS

The classifier was trained by 80% of the sample. Patients were distinguished from healthy individuals with an overall accuracy of 71.0% (95% confident interval: 61.1%, 79.6%), a sensitivity of 67.3%, a specificity of 75.0%, and the area under receiver operating characteristic curve (AUC) was 79.3% (χ2 p < 0.001). In validation using the held-up 20% of the sample, patients were distinguished from healthy individuals with an overall accuracy of 76.0% (95% confident interval: 54.9%, 90.6%), a sensitivity of 76.9%, a specificity of 75.0%, and an AUC of 73.1% (χ2 p = 0.012). Diffusion properties of inter-hemispheric fibres, the cerebello-thalamo-cortical circuits and the long association fibres were identified to be the most discriminative in the classification. Higher predicted probability scores were found in younger patients.

CONCLUSIONS

Our findings suggest that the widespread connectivity disruption observed in FES patients, especially in younger patients, might be considered potential individual discriminating biomarkers.

Substantia nigra ultrastructural pathology in schizophrenia

Schizophrenia is a severe mental illness affecting approximately 1% of the population worldwide. Despite its prevalence, the cause remains unknown, and treatment is not effective in all patients. Dopamine is thought to play a role in schizophrenia pathology, yet the substantia nigra (SN), the origin of dopaminergic pathways, has not been studied extensively in schizophrenia. In this study, electron microscopy was used to examine neurons, oligodendrocytes, and myelinated axons in the SN of normal controls (NCs, n=9) and schizophrenia subjects with varying response to antipsychotic drugs [SZ, n=14; treatment resistant (TR)=6, treatment responsive (RESP)=6, unknown=2]. Postmortem tissue was analyzed for qualitative and quantitative markers of ultrastuctural integrity. A significantly higher percentage of axons in the schizophrenia group had inclusions in the myelin sheath compared to NCs (SZ: 3.9±1.7, NC: 2.6±2.0). When considering treatment response, a significantly higher percentage of axons lacked cytoplasm (TR: 9.7±5.5, NC: 3.5±2.3), contained cellular debris (TR: 7.5±3.2, NC: 2.3±1.3) or had protrusions in the myelin sheath (TR: 0.4±0.5, NC: 0.2±0.3). The G-ratio, a measure of myelin thickness, was significantly different between treatment response groups and was greater in TR (0.72±0.02) as compared to NCs (0.68±0.03), indicating decreased myelination in TR. These findings, which suggest myelin pathology in the SN in schizophrenia, are consistent with findings elsewhere in the brain. In addition, our results suggest cytoskeletal abnormalities, which may or may not be associated with myelin pathology.

A Bayesian Spatial Model to Predict Disease Status Using Imaging Data From Various Modalities

Relating disease status to imaging data stands to increase the clinical significance of neuroimaging studies. Many neurological and psychiatric disorders involve complex, systems-level alterations that manifest in functional and structural properties of the brain and possibly other clinical and biologic measures. We propose a Bayesian hierarchical model to predict disease status, which is able to incorporate information from both functional and structural brain imaging scans. We consider a two-stage whole brain parcellation, partitioning the brain into 282 subregions, and our model accounts for correlations between voxels from different brain regions defined by the parcellations. Our approach models the imaging data and uses posterior predictive probabilities to perform prediction. The estimates of our model parameters are based on samples drawn from the joint posterior distribution using Markov Chain Monte Carlo (MCMC) methods. We evaluate our method by examining the prediction accuracy rates based on leave-one-out cross validation, and we employ an importance sampling strategy to reduce the computation time. We conduct both whole-brain and voxel-level prediction and identify the brain regions that are highly associated with the disease based on the voxel-level prediction results. We apply our model to multimodal brain imaging data from a study of Parkinson's disease. We achieve extremely high accuracy, in general, and our model identifies key regions contributing to accurate prediction including caudate, putamen, and fusiform gyrus as well as several sensory system regions.

Corpus callosum volumes in the 5 years following the first-episode of schizophrenia: Effects of antipsychotics, chronicity and maturation

Background

White matter (WM) structural changes, particularly affecting the corpus callosum (CC), seem to be critically implicated in psychosis. Whether such abnormalities are progressive or static is still a matter of debate in schizophrenia research. Aberrant maturation processes might also influence the longitudinal trajectory of age-related CC changes in schizophrenia patients. We investigated whether patients with first-episode schizophrenia-related psychoses (FESZ) would present longitudinal CC and whole WM volume changes over the 5 years after disease onset.

Method

Thirty-two FESZ patients and 34 controls recruited using a population-based design completed a 5-year assessment protocol, including structural MRI scanning at baseline and follow-up. The linear effects of disease duration, clinical outcome and antipsychotic (AP) use over time on WM and CC volumes were studied using both voxelwise and volume-based morphometry analyses. We also examined maturation/aging abnormalities through cross-sectional analyses of age-related trajectories of total WM and CC volume changes.

Results

No interaction between diagnosis and time was observed, and clinical outcome did not influence CC volumes in patients. On the other hand, FESZ patients continuously exposed to AP medication showed volume increase over time in posterior CC. Curve-estimation analyses revealed a different aging pattern in FESZ patients versus controls: while patients displayed a linear decline of total WM and anterior CC volumes with age, a non-linear trajectory of total WM and relative preservation of CC volumes were observed in controls.

Conclusions

Continuous AP exposure can influence CC morphology during the first years after schizophrenia onset. Schizophrenia is associated with an abnormal pattern of total WM and anterior CC aging during non-elderly adulthood, and this adds complexity to the discussion on the static or progressive nature of structural abnormalities in psychosis.

Disrupted focal white matter integrity in autism spectrum disorder: A voxel-based meta-analysis of diffusion tensor imaging studies

BACKGROUND

Autism spectrum disorder (ASD) is a mental disorder that has long been considered to result from brain underconnectivity. However, volumetric analysis of structural MRI data has failed to find consistent white matter alterations in patients with ASD. The present study aims to examine whether there are consistent focal white matter alterations as measured by diffusion tensor imaging (DTI) in individuals with ASD compared with typically developing (TD) individuals.

METHOD

Coordinate-based meta-analysis was performed on 14 studies that reported fractional anisotropy (FA) alterations between individuals with ASD and TD individuals. These studies have in total 297 subjects with ASD and 302 TD subjects.

RESULTS

Activation likelihood estimation (ALE) analysis identified two clusters of white matter regions that showed consistent reduction of FA in individuals with ASD compared with TD individuals: the left splenium of corpus callosum and the right cerebral peduncle.

CONCLUSIONS

Consistent focal white matter reductions in ASD could be identified by using FA, highlighting the cerebral peduncle which is usually overlooked in studies focusing on major white matter tracts. These focal reductions in the splenium and the cerebral peduncle may be associated with sensorimotor impairments seen in individuals with ASD.

Four-way multimodal fusion of 7 T imaging data using an mCCA+jICA model in first-episode schizophrenia

Acquisition of multimodal brain imaging data for the same subject has become more common leading to a growing interest in determining the intermodal relationships between imaging modalities to further elucidate the pathophysiology of schizophrenia. Multimodal data have previously been individually analyzed and subsequently integrated; however, these analysis techniques lack the ability to examine true modality inter-relationships. The utilization of a multiset canonical correlation and joint independent component analysis (mCCA + jICA) model for data fusion allows shared or distinct abnormalities between modalities to be examined. In this study, first-episode schizophrenia patients (n_SZ =19) and matched controls (n_HC =21) completed a resting-state functional magnetic resonance imaging (fMRI) scan at 7 T. Grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and amplitude of low frequency fluctuation (ALFF) maps were used as features in a mCCA + jICA model. Results of the mCCA + jICA model indicated three joint group-discriminating components (GM-CSF, WM-ALFF, GM-ALFF) and two modality-unique group-discriminating components (GM, WM). The joint component findings are highlighted by GM basal ganglia, somatosensory, parietal lobe, and thalamus abnormalities associated with ventricular CSF volume; WM occipital and frontal lobe abnormalities associated with temporal lobe function; and GM frontal, temporal, parietal, and occipital lobe abnormalities associated with caudate function. These results support and extend major findings throughout the literature using independent single modality analyses. The multimodal fusion of 7 T data in this study provides a more comprehensive illustration of the relationships between underlying neuronal abnormalities associated with schizophrenia than examination of imaging data independently.

Meta-analysis of regional white matter volume in bipolar disorder with replication in an independent sample using coordinates, T-maps, and individual MRI data

Converging evidence suggests that bipolar disorder (BD) is associated with white matter (WM) abnormalities. Meta-analyses of voxel based morphometry (VBM) data is commonly performed using published coordinates, however this method is limited since it ignores non-significant data. Obtaining statistical maps from studies (T-maps) as well as raw MRI datasets increases accuracy and allows for a comprehensive analysis of clinical variables. We obtained coordinate data (7-studies), T-Maps (12-studies, including unpublished data) and raw MRI datasets (5-studies) and analysed the 24 studies using Seed-based d Mapping (SDM). A VBM analysis was conducted to verify the results in an independent sample. The meta-analysis revealed decreased WM volume in the posterior corpus callosum extending to WM in the posterior cingulate cortex. This region was significantly reduced in volume in BD patients in the independent dataset (p=0.003) but there was no association with clinical variables. We identified a robust WM volume abnormality in BD patients that may represent a trait marker of the disease and used a novel methodology to validate the findings.

White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies

Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions.

Longitudinal study examining abnormal white matter integrity using a tract-specific analysis in individuals with a high risk for psychosis

AIM

Although volume reductions in the grey matter have been previously observed in individuals with an at-risk mental state (ARMS) for psychosis, the features of white matter integrity and their correlation with psychiatric symptoms remain unclear.

METHODS

Forty-six ARMS subjects were examined using magnetic resonance imaging (MRI) to acquire diffusion tensor imaging (DTI); the subjects were also evaluated using the Scale of Prodromal Symptoms at baseline and at 52 weeks. Sixteen healthy controls also underwent MRI scanning. The DTI results were longitudinally analyzed using a tract-specific analysis to measure the fractional anisotropy (FA) values of the entire corpus callosum (CC), as well as its genu, trunk, and splenium.

RESULTS

During the 52-week study period, seven patients developed psychosis (ARMS-P) and 39 did not (ARMS-NP). In the entire CC and the genu, trunk, and splenium of the CC, the FA values of the ARMS subjects were each significantly smaller than the respective values of the healthy controls at baseline. In the genu and trunk, the baseline FA values in the ARMS-NP group were, paradoxically, smaller than those of the ARMS-P group at baseline. Regarding the association between the FA values and psychiatric symptoms, a reduction in the FA value in the genu was significantly correlated with a deterioration of negative symptoms among the ARMS subjects.

CONCLUSION

Abnormal white matter integrity in the CC may predict the long-term outcome of patients with prodromal psychosis, since negative symptoms are associated with poor functioning.

Hemispheric lateralization abnormalities of the white matter microstructure in patients with schizophrenia and bipolar disorder

BACKGROUND

Hemispheric lateralization of the brain occurs during development and underpins specialized functions. It is posited that aberrant neurodevelopment leads to abnormal brain lateralization in individuals with psychotic illnesses. Here, we sought to examine whether white matter hemispheric lateralization is abnormal in individuals with the psychotic spectrum disorders of schizophrenia and bipolar disorder.

METHODS

We examined the white matter microstructure lateralization in patients with schizophrenia, bipolar disorder with psychotic features and healthy controls by measuring the laterality indices of fractional anisotropy (FA) and mean diffusivity (MD). We also correlated the laterality indices with clinical measures.

RESULTS

We included 150 patients with schizophrenia, 35 with bipolar disorder and 77 healthy controls in our analyses. Shared FA lateralization abnormalities in patients with schizophrenia and bipolar disorder were found in the cerebral peduncle and posterior limb of internal capsule, with more extensive abnormalities in patients with bipolar disorder than in those with schizophrenia. The shared MD lateralization abnormalities were more widespread, extending to the subcortical, frontal-occipital, limbic and callosal tracts, with patients with bipolar disorder showing greater abnormalities than patients with schizophrenia. While lateralization was decreased in patients with schizophrenia, the lateralization was reversed in those with bipolar disorder, underpinned by the more pronounced microstructural abnormalities in the right hemisphere. The loss of FA lateralization in patients with schizophrenia was associated with lower quality of life and psychosocial functioning.

LIMITATIONS

Owing to the cross-sectional study design, we cannot confirm whether the lateralization abnormalities are neurodevelopmental or a consequence of psychosis onset or chronicity.

CONCLUSION

Shared and distinct white matter lateralization abnormalities were found in patients with schizophrenia and bipolar disorder. In distinct regions of abnormalities, the lateralization was attenuated in patients with schizophrenia and reversed in those with bipolar disorder.

Structural neuroimaging across early-stage psychosis: Aberrations in neurobiological trajectories and implications for the staging model

OBJECTIVE

This review critically examines the structural neuroimaging evidence in psychotic illness, with a focus on longitudinal imaging across the first-episode psychosis and ultra-high-risk of psychosis illness stages.

METHODS

A thorough search of the literature involving specifically longitudinal neuroimaging in early illness stages of psychosis was conducted. The evidence supporting abnormalities in brain morphology and altered neurodevelopmental trajectories is discussed in the context of a clinical staging model.

RESULTS

In general, grey matter (and, to a lesser extent, white matter) declines across multiple frontal, temporal (especially superior regions), insular and parietal regions during the first episode of psychosis, which has a steeper trajectory than that of age-matched healthy counterparts. Although the ultra-high-risk of psychosis literature is considerably mixed, evidence indicates that certain volumetric structural aberrations predate psychotic illness onset (e.g. prefrontal cortex thinning), while other abnormalities present in ultra-high-risk of psychosis populations are potentially non-psychosis-specific (e.g. hippocampal volume reductions).

CONCLUSION

We highlight the advantages of longitudinal designs, discuss the implications such studies have on clinical staging and provide directions for future research.

Task modulated brain connectivity of the amygdala: a meta-analysis of psychophysiological interactions

Understanding functional connectivity of the amygdala with other brain regions, especially task modulated connectivity, is a critical step toward understanding the role of the amygdala in emotional processes and the interactions between emotion and cognition. The present study performed coordinate-based meta-analysis on studies of task modulated connectivity of the amygdala which used psychophysiological interaction (PPI) analysis. We first analyzed 49 PPI studies on different types of tasks using activation likelihood estimation (ALE) meta-analysis. Widespread cortical and subcortical regions showed consistent task modulated connectivity with the amygdala, including the medial frontal cortex, bilateral insula, anterior cingulate, fusiform gyrus, parahippocampal gyrus, thalamus, and basal ganglia. These regions were in general overlapped with those showed coactivations with the amygdala, suggesting that these regions and amygdala are not only activated together, but also show different levels of interactions during tasks. Further analyses with subsets of PPI studies revealed task specific functional connectivities with the amygdala that were modulated by fear processing, face processing, and emotion regulation. These results suggest a dynamic modulation of connectivity upon task demands, and provide new insights on the functions of the amygdala in different affective and cognitive processes. The meta-analytic approach on PPI studies may offer a framework toward systematical examinations of task modulated connectivity.

Occipital bending in schizophrenia

OBJECTIVE

To investigate the prevalence of occipital bending (an occipital lobe crossing or twisting across the midline) in subjects with schizophrenia and matched healthy controls.

METHOD

Occipital bending prevalence was investigated in 37 patients with schizophrenia and 44 healthy controls.

RESULTS

Ratings showed that prevalence was nearly three times higher among schizophrenia patients (13/37 [35.1%]) than in control subjects (6/44 [13.6%]). Furthermore, those with schizophrenia had greater normalized gray matter volume but less white matter volume and had larger brain-to-cranial ratio.

CONCLUSION

The results suggest that occipital bending is more prevalent among schizophrenia patients than healthy subjects and that schizophrenia patients have different gray matter-white matter proportions. Although the cause and clinical ramifications of occipital bending are unclear, the results infer that occipital bending may be a marker of psychiatric illness.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part II: Cognition, neuroimaging and genetics

OBJECTIVES

Schizophrenia is a group of severe psychiatric disorders with high heritability but only low odds ratios of risk genes. Despite progress in the identification of pathophysiological processes, valid biomarkers of the disease are still lacking.

METHODS

This comprehensive review summarises recent efforts to identify genetic underpinnings, clinical and cognitive endophenotypes and symptom dimensions of schizophrenia and presents findings from neuroimaging studies with structural, functional and spectroscopy magnetic resonance imaging and positron emission tomography. The potential of findings to be biomarkers of schizophrenia is discussed.

RESULTS

Recent findings have not resulted in clear biomarkers for schizophrenia. However, we identified several biomarkers that are potential candidates for future research. Among them, copy number variations and links between genetic polymorphisms derived from genome-wide analysis studies, clinical or cognitive phenotypes, multimodal neuroimaging findings including positron emission tomography and magnetic resonance imaging, and the application of multivariate pattern analyses are promising.

CONCLUSIONS

Future studies should address the effects of treatment and stage of the disease more precisely and apply combinations of biomarker candidates. Although biomarkers for schizophrenia await validation, knowledge on candidate genomic and neuroimaging biomarkers is growing rapidly and research on this topic has the potential to identify psychiatric endophenotypes and in the future increase insight on individual treatment response in schizophrenia.

Executive functions in obsessive-compulsive disorder: An activation likelihood estimate meta-analysis of fMRI studies

OBJECTIVES

To identify activation changes assessed in functional magnetic resonance imaging (fMRI) studies of obsessive-compulsive disorder (OCD) through Activation Likelihood Estimate meta-analysis.

METHODS

We included 28 peer-reviewed standard stereotactic space studies assessing adult OCD patients (OCDpts) vs. healthy controls (HCs) with fMRI during executive task performance.

RESULTS

In within-group analyses, HCs showed task-related activations in bilateral inferior frontal gyri, right middle frontal gyrus, right inferior parietal lobule, right claustrum, bilateral cingulate gyri, and left caudate body. OCDpts showed task-related left-sided activations in the superior, medial, and inferior frontal gyri, and thalamus, and bilateral activations in the middle frontal gyri, inferior parietal lobule, and insular cortices. Subtraction analysis showed increased left middle frontal gyrus activation in OCDpts. In between-groups analyses, OCDpts hypoactivated the right caudate body, left putamen, left ACC, and right medial and middle frontal gyri. Right caudate hypoactivation persisted also after applying Family-wise error algorithms.

CONCLUSIONS

This meta-analysis confirms that during executive functioning OCDpts show a functional deficit of the right caudate body, which could represent a major neural functional correlate of their illness.

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Alterations in white matter volume and its correlation with clinical characteristics in patients with generalized anxiety disorder

INTRODUCTION

Only a few morphological studies have focused on changes in white matter (WM) volume in patients with generalized anxiety disorder (GAD). We evaluated alterations in WM volume and its correlation with symptom severity and duration of illness in adults with GAD.

METHODS

The 44 subjects were comprised of 22 patients with GAD (13 males and nine females) diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) and 22 age-matched healthy controls (13 males and nine females). High-resolution magnetic resonance imaging (MRI) data were processed by voxel-based morphometry (VBM) analysis based on diffeomorphic anatomical registration using the exponentiated Lie algebra (DARTEL) algorithm in SPM8.

RESULTS

Patients with GAD showed significantly reduced WM volume, particularly in the dorsolateral prefrontal cortex (DLPFC), anterior limb of the internal capsule (ALIC), and midbrain. In addition, DLPFC volume was negatively correlated with GAD-7 score and illness duration. ALIC volume was negatively correlated with GAD-7 score. Female patients had significantly less orbitofrontal cortex volume compared to that in male patients.

CONCLUSION

The findings demonstrate localized changes in WM volume associated with cognitive and emotional dysfunction in patients with GAD. The finding will be helpful for understanding the neuropathology in patients with GAD.

White matter alterations in first episode treatment-naïve patients with deficit schizophrenia: a combined VBM and DTI study

Categorizing ‘deficit schizophrenia’ (DS) as distinct from ‘non-deficit’ schizophrenia (NDS) may help reduce heterogeneity within schizophrenia. However, it is unknown if DS has a discrete white matter signature. Here we used MRI to compare white matter volume (voxel-based morphometry) and microstructural integrity (fractional anisotropy, FA) in first-episode treatment-naïve patients with DS and NDS and their unaffected relatives to control groups of similar age. We found that white matter disruption was prominent in DS compared to controls; the DS group had lower volumes in the cerebellum, bilateral extra-nuclear and bilateral frontoparietal regions, and lower FA in the body of corpus callosum, posterior superior longitudinal fasciculus and uncinate fasciculus. The DS group also had lower volume in bilateral extra-nuclear regions compared to NDS, and the volume of these clusters was negatively correlated with deficit symptom ratings. NDS patients however, had no significant volume alterations and limited disruption of microstructural integrity compared to controls. Finally, first-degree relatives of those with DS shared volume abnormalities in right extra-nuclear white matter. Thus, white matter pathology in schizophrenia is most evident in the deficit condition, and lower extra-nuclear white matter volumes in both DS patients and their relatives may represent a brain structural ‘endophenotype’ for DS.

White matter alterations in first episode treatment-naïve patients with deficit schizophrenia: a combined VBM and DTI study

Categorizing 'deficit schizophrenia' (DS) as distinct from 'non-deficit' schizophrenia (NDS) may help reduce heterogeneity within schizophrenia. However, it is unknown if DS has a discrete white matter signature. Here we used MRI to compare white matter volume (voxel-based morphometry) and microstructural integrity (fractional anisotropy, FA) in first-episode treatment-naïve patients with DS and NDS and their unaffected relatives to control groups of similar age. We found that white matter disruption was prominent in DS compared to controls; the DS group had lower volumes in the cerebellum, bilateral extra-nuclear and bilateral frontoparietal regions, and lower FA in the body of corpus callosum, posterior superior longitudinal fasciculus and uncinate fasciculus. The DS group also had lower volume in bilateral extra-nuclear regions compared to NDS, and the volume of these clusters was negatively correlated with deficit symptom ratings. NDS patients however, had no significant volume alterations and limited disruption of microstructural integrity compared to controls. Finally, first-degree relatives of those with DS shared volume abnormalities in right extra-nuclear white matter. Thus, white matter pathology in schizophrenia is most evident in the deficit condition, and lower extra-nuclear white matter volumes in both DS patients and their relatives may represent a brain structural 'endophenotype' for DS.

Effects of a Balanced Translocation between Chromosomes 1 and 11 Disrupting the DISC1 Locus on White Matter Integrity

Objective

Individuals carrying rare, but biologically informative genetic variants provide a unique opportunity to model major mental illness and inform understanding of disease mechanisms. The rarity of such variations means that their study involves small group numbers, however they are amongst the strongest known genetic risk factors for major mental illness and are likely to have large neural effects. DISC1 (Disrupted in Schizophrenia 1) is a gene containing one such risk variant, identified in a single Scottish family through its disruption by a balanced translocation of chromosomes 1 and 11; t(1;11) (q42.1;q14.3).

Method

Within the original pedigree, we examined the effects of the t(1;11) translocation on white matter integrity, measured by fractional anisotropy (FA). This included family members with (n = 7) and without (n = 13) the translocation, along with a clinical control sample of patients with psychosis (n = 34), and a group of healthy controls (n = 33).

Results

We report decreased white matter integrity in five clusters in the genu of the corpus callosum, the right inferior fronto-occipital fasciculus, acoustic radiation and fornix. Analysis of the mixed psychosis group also demonstrated decreased white matter integrity in the above regions. FA values within the corpus callosum correlated significantly with positive psychotic symptom severity.

Conclusions

We demonstrate that the t(1;11) translocation is associated with reduced white matter integrity in frontal commissural and association fibre tracts. These findings overlap with those shown in affected patients with psychosis and in DISC1 animal models and highlight the value of rare but biologically informative mutations in modeling psychosis.

[The search of the "intact" structural and functional brain systems as a paradigm shift in schizophrenia research]

OBJECTIVE

The search of the structural and functional brain characteristics is one of the most studied directions in the modern biological psychiatry. However, in spite of the numerous studies the results are still controversial. As the necessity of the shift of the current paradigm in schizophrenia research evolves it has been suggested to discriminate not only abnormal but stable functioning neuronal circuits as well. Consequently, the aim is formulated as the search of the minimal brain damage sufficient for disease development.

MATERIAL AND METHODS

Author analyzed the auditory oddball P300 latency (as a marker of information processing speed), N-acetylaspartate level in the dorsolateral prefrontal cortex (as a marker of neuronal integrity in this brain area) and fractional anisotropy of the fasciculus uncindtus which connects the frontal and temporal lobes (as a marker of white matter bundles microstructure) in 30 patients with schizophrenia and 27 healthy people.

RESULTS AND CONCLUSION

The findings showed that all the tested characteristics are not "obligatory" for schizophrenia.

Regional white matter abnormalities in drug-naive, first-episode schizophrenia patients and their healthy unaffected siblings

OBJECTIVE

Shared neuropathological features between schizophrenia patients and their siblings may represent intermediate phenotypes of schizophrenia and can be used to investigate genetic susceptibility to the illness. This study aimed to discover regional white matter abnormalities in first-episode schizophrenia (FES) patients and their unaffected siblings compared to healthy subjects in the Chinese Han population using optimized Voxel-Based Morphometry (VBM).

METHOD

A total of 51 drug-naive, FES patients, 45 of their unaffected siblings and 59 healthy comparisons were studied with magnetic resonance imaging (MRI).

RESULTS

FES patients exhibited significant regional white matter deficits in the left inferior frontal gyrus and left joint of external capsule and internal capsule compared with healthy subjects (corrected FDR, p<0.005). The sibling group also showed significant white matter deficits in these two regions compared with the healthy comparison group (uncorrected, p<0.001). White matter deficits with a less stringent threshold for significance in the left cerebellum anterior lobe, left middle frontal gyrus, left hippocampus, right anterior cingulate and right internal capsule were observed in patients compared to their siblings.

CONCLUSIONS

Our findings extend those from previous VBM analyses showing that FES patients and their unaffected siblings may share white matter deficits in the left inferior frontal gyrus and the left joint of external capsule and internal capsule. These regional white matter deficits may be related to genetic factors related to schizophrenia susceptibility.

Neuroinflammation and white matter pathology in schizophrenia: systematic review

BACKGROUND

Neuroinflammation and white matter pathology have each been independently associated with schizophrenia, and experimental studies have revealed mechanisms by which the two can interact in vitro, but whether these abnormalities simultaneously co-occur in people with schizophrenia remains unclear.

METHOD

We searched MEDLINE, EMBASE, PsycINFO and Web of Science from inception through 12 January 2014 for studies reporting human data on the relationship between microglial or astroglial activation, or cytokines and white matter pathology in schizophrenia.

RESULTS

Fifteen studies totaling 792 subjects (350 with schizophrenia, 346 controls, 49 with bipolar disorder, 37 with major depressive disorder and 10 with Alzheimer's disease) met all eligibility criteria. Five neuropathological and two neuroimaging studies collectively yielded consistent evidence of an association between schizophrenia and microglial activation, particularly in white rather than gray matter regions. Ultrastructural analysis revealed activated microglia near dystrophic and apoptotic oligodendroglia, demyelinating and dysmyelinating axons and swollen and vacuolated astroglia in subjects with schizophrenia but not controls. Two neuroimaging studies found an association between carrier status for a functional single nucleotide polymorphism in the interleukin-1β gene and abnormal white as well as gray matter volumes in schizophrenia but not controls. A neuropathological study found that orbitofrontal white matter neuronal density was increased in schizophrenia cases exhibiting high transcription levels of pro-inflammatory cytokines relative to those exhibiting low transcription levels and to controls. Schizophrenia was associated with decreased astroglial density specifically in subgenual cingulate white matter and anterior corpus callosum, but not other gray or white matter areas. Astrogliosis was consistently absent. Data on astroglial gene expression, mRNA expression and protein concentration were inconsistent.

CONCLUSION

Neuroinflammation is associated with white matter pathology in people with schizophrenia, and may contribute to structural and functional disconnectivity, even at the first episode of psychosis.

Neuropsychology, autobiographical memory, and hippocampal volume in "younger" and "older" patients with chronic schizophrenia

Despite a wide range of studies on neuropsychology in schizophrenia, autobiographical memory (AM) has been scarcely investigated in these patients. Hence, less is known about AM in older patients and hippocampal contribution to autobiographical memories of varying remoteness. Therefore, we investigated hippocampal volume and AM along with important neuropsychological domains in patients with chronic schizophrenia and the respective relationships between these parameters. We compared 25 older patients with chronic schizophrenia to 23 younger patients and an older healthy control group (N = 21) with respect to AM, additional neuropsychological parameters, and hippocampal volume. Personal episodic and semantic memory was investigated using a semi-structured interview. Additional neuropsychological parameters were assessed by using a battery of standard neuropsychological tests. Structural magnetic resonance imaging data were analyzed with an automated region-of-interest procedure. While hippocampal volume reduction and neuropsychological impairment were more pronounced in the older than in the younger patients, both groups showed equivalent reduced AM performance for recent personal episodes. In the patient group, significant correlations between left hippocampal volume and recent autobiographical episodes as well as personal semantic memories arose. Verbal memory and working memory were significantly correlated with right hippocampal volume; executive functions, however, were associated with bilateral hippocampal volumes. These findings underline the complexity of AM and its impairments in the course of schizophrenia in comparison to rather progressive neuropsychological deficits and address the importance of hippocampal contribution.

Effects of eye dominance (left vs. right) and cannabis use on intermanual coordination and negative symptoms in schizophrenia patients

Based on the previous findings, it has been assumed that in schizophrenia patients, eye dominance and cannabis use will affect negative symptoms and intermanual coordination (IMC), an index of interhemispheric communication. But eye dominance, specifically the clinical findings for it, has been neglected in schizophrenia research. We therefore investigated its effects in 52 right-handed (36 right-eyed and 16 left-eyed) and 51 left-handed (35 left-eyed and 16 right-eyed) schizophrenia in-patients without and with drug use. Eye dominance affected IMC in all schizophrenia patients. When comparing right- and left-handers, we found that this result was only significant in the right-handed patients and in the smaller subgroup without drug use. In the right-handers, left eye dominance-like left-handedness-was associated with higher values in IMC and less pronounced manifestation of negative symptoms, right eye dominance was not. Thus, left-eyed right-handers may be more closely related to left-handers than to right-handers. In accordance with the results from the literature, we suggest that these findings are due to better interhemispheric connections and less impairment of white matter structures, especially in right-hemispheric regions. Moreover, cannabis use was related to higher scores in IMC and less pronounced negative symptoms, but only in the right-eyed and not in the left-eyed right-handers or in the left-handers. Hence, differences in eye dominance and handedness may be partially responsible for different results in interhemispheric connections among cannabis users. In conclusion, both eye dominance and use of cannabis should be taken into account when assessing clinical symptoms in schizophrenia patients.

Distribution of tract deficits in schizophrenia

BACKGROUND

Gray and white matter brain changes have been found in schizophrenia but the anatomical organizing process underlying these changes remains unknown. We aimed to identify gray and white matter volumetric changes in a group of patients with schizophrenia and to quantify the distribution of white matter tract changes using a novel approach which applied three complementary analyses to diffusion imaging data.

METHODS

21 patients with schizophrenia and 21 matched control subjects underwent brain magnetic resonance imaging. Gray and white matter volume differences were investigated using Voxel-based Morphometry (VBM). White matter diffusion changes were located using Tract Based Spatial Statistics (TBSS) and quantified within a standard atlas. Tracts where significant regional differences were located were examined using fiber tractography.

RESULTS

No significant differences in gray or white matter volumetry were found between the two groups. Using TBSS the schizophrenia group showed significantly lower fractional anisotropy (FA) compared to the controls in regions (false discovery rate <0.05) including the genu, body and splenium of the corpus callosum and the left anterior limb of the internal capsule (ALIC). Using fiber tractography, FA was significantly lower in schizophrenia in the corpus callosum genu (p = 0.003).

CONCLUSIONS

In schizophrenia, white matter diffusion deficits are prominent in medial frontal regions. These changes are consistent with the results of previous studies which have detected white matter changes in these areas. The pathology of schizophrenia may preferentially affect the prefrontal-thalamic white matter circuits traversing these regions.

Altered interhemispheric and temporal lobe white matter microstructural organization in severe chronic schizophrenia

Diffusion MRI investigations in schizophrenia provide evidence of abnormal white matter (WM) microstructural organization as indicated by reduced fractional anisotropy (FA) primarily in interhemispheric, left frontal and temporal WM. Using tract-based spatial statistics (TBSS), we examined diffusion parameters in a sample of patients with severe chronic schizophrenia. Diffusion MRI data were acquired on 19 patients with chronic severe schizophrenia and 19 age- and gender-matched healthy controls using a 64 gradient direction sequence, (b=1300 s/mm(2)) collected on a Siemens 1.5T MRI scanner. Diagnosis of schizophrenia was determined by Diagnostic and Statistical Manual for Mental Disorders 4th Edition (DSM-IV) Structured Clinical Interview for DSM disorder (SCID). Patients were treatment resistance, having failed to respond to at least two antipsychotic medications, and had prolonged periods of moderate to severe positive or negative symptoms. Analysis of diffusion parameters was carried out using TBSS. Individuals with chronic severe schizophrenia had significantly reduced FA with corresponding increased radial diffusivity in the genu, body, and splenium of the corpus callosum, the right posterior limb of the internal capsule, right external capsule, and the right temporal inferior longitudinal fasciculus. There were no voxels of significantly increased FA in patients compared with controls. A decrease in splenium FA was shown to be related to a longer illness duration. We detected widespread abnormal diffusivity properties in the callosal and temporal lobe WM regions in individuals with severe chronic schizophrenia who have not previously been exposed to clozapine. These deficits can be driven by a number of factors that are indistinguishable using in vivo diffusion-weighted imaging, but may be related to reduced axonal number or packing density, abnormal glial cell arrangement or function, and reduced myelin.

Correspondence of executive function related functional and anatomical alterations in aging brain

Neurocognitive aging studies have focused on age-related changes in neural activity or neural structure but few studies have focused on relationships between the two. The present study quantitatively reviewed 24 studies of age-related changes in fMRI activation across a broad spectrum of executive function tasks using activation likelihood estimation (ALE) and 22 separate studies of age-related changes in gray matter using voxel-based morphometry (VBM). Conjunction analyses between functional and structural alteration maps were constructed. Overlaps were only observed in the conjunction of dorsolateral prefrontal cortex (DLPFC) gray matter reduction and functional hyperactivation but not hypoactivation. It was not evident that the conjunctions between gray matter and activation were related to task performance. Theoretical implications of these results are discussed.

Functional and white matter abnormalities in the language network in patients with schizophrenia: a combined study with diffusion tensor imaging and functional magnetic resonance imaging

BACKGROUND

Schizophrenia is a mental disorder characterized by functional abnormalities in the language network. Anatomical white matter (WM) abnormalities (volume and integrity) have also been reported for this pathology. Nevertheless, few studies have investigated anatomo-functional relationships in schizophrenia, and none has focused on the language comprehension network in relation to various diffusion parameters. We hypothesized that the WM abnormalities that are reflected by several diffusion parameters underlie functional deficits in the language network.

METHODS

Eighteen DSM-IV patients with schizophrenia and 18 healthy controls without any significant differences in sex, age, or level of education were included. First, functional brain activation within the language network was estimated. Then, using diffusion tensor imaging, fractional anisotropy (FA), radial diffusivity (RD), and mean diffusivity (MD) values were extracted within WM regions adjacent to this network and their anatomo-functional relationships were investigated.

RESULTS

Compared with healthy participants, both functional and diffusion deficits were observed in patients with schizophrenia. Primarily, an altered diffusion-functional relationship was observed in patients in the left middle temporal region: functional activations were positively correlated with FA, but were negatively correlated with RD.

CONCLUSIONS

Our findings indicate a close relationship between diffusion and functional deficits in patients with schizophrenia, suggesting that WM integrity disturbance might be one cause of functional alterations in the language network in patients with schizophrenia. Thus, the present multimodal study improves our understanding of the pathophysiology of schizophrenia.

Clinical utility of machine-learning approaches in schizophrenia: improving diagnostic confidence for translational neuroimaging

Machine-learning approaches are becoming commonplace in the neuroimaging literature as potential diagnostic and prognostic tools for the study of clinical populations. However, very few studies provide clinically informative measures to aid in decision-making and resource allocation. Head-to-head comparison of neuroimaging-based multivariate classifiers is an essential first step to promote translation of these tools to clinical practice. We systematically evaluated the classifier performance using back-to-back structural MRI in two field strengths (3- and 7-T) to discriminate patients with schizophrenia (n = 19) from healthy controls (n = 20). Gray matter (GM) and white matter images were used as inputs into a support vector machine to classify patients and control subjects. Seven Tesla classifiers outperformed the 3-T classifiers with accuracy reaching as high as 77% for the 7-T GM classifier compared to 66.6% for the 3-T GM classifier. Furthermore, diagnostic odds ratio (a measure that is not affected by variations in sample characteristics) and number needed to predict (a measure based on Bayesian certainty of a test result) indicated superior performance of the 7-T classifiers, whereby for each correct diagnosis made, the number of patients that need to be examined using the 7-T GM classifier was one less than the number that need to be examined if a different classifier was used. Using a hypothetical example, we highlight how these findings could have significant implications for clinical decision-making. We encourage the reporting of measures proposed here in future studies utilizing machine-learning approaches. This will not only promote the search for an optimum diagnostic tool but also aid in the translation of neuroimaging to clinical use.

Red blood cell polyunsaturated fatty acids measured in red blood cells and schizophrenia: a meta-analysis

Alterations of polyunsaturated fatty acids (PUFA) in schizophrenia have been reported, but there is substantial variation in the findings. We performed a systematic review and meta-analysis for docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), linoleic acid (LA), and arachidonic acid (AA). We identified 18 studies which compared PUFA in the erythrocyte cell membrane between patients with schizophrenia and controls. A total of 642 patients (169 were antipsychotic-naïve) and 574 controls participated in these studies. We found suggestive evidence that the levels of DPA (C22:5n3) and DHA (C22:6n3) are decreased both in patients currently being treated with antipsychotic medication and antipsychotic-naïve patients. Our findings furthermore suggest that the levels of LA (C18:2n6) are decreased in the medicated subgroup, but not in the antipsychotic-naive group. Finally, we found decreased levels of AA (C20:4n6), most convincingly in antipsychotic-naive patients. Taken together, there is substantial evidence that decreased levels of DPA (C22:5n3), DHA (C22:6n3), and AA (C20:4n6) are associated with the schizophrenia syndrome, apart from a possible influence of antipsychotic medication. Given the large heterogeneity in results, these conclusions should be interpreted cautiously.

Anatomical abnormalities in gray and white matter of the cortical surface in persons with schizophrenia

BACKGROUND

Although schizophrenia has been associated with abnormalities in brain anatomy, imaging studies have not fully determined the nature and relative contributions of gray matter (GM) and white matter (WM) disturbances underlying these findings. We sought to determine the pattern and distribution of these GM and WM abnormalities. Furthermore, we aimed to clarify the contribution of abnormalities in cortical thickness and cortical surface area to the reduced GM volumes reported in schizophrenia.

METHODS

We recruited 76 persons with schizophrenia and 57 healthy controls from the community and obtained measures of cortical and WM surface areas, of local volumes along the brain and WM surfaces, and of cortical thickness.

RESULTS

We detected reduced local volumes in patients along corresponding locations of the brain and WM surfaces in addition to bilateral greater thickness of perisylvian cortices and thinner cortex in the superior frontal and cingulate gyri. Total cortical and WM surface areas were reduced. Patients with worse performance on the serial-position task, a measure of working memory, had a higher burden of WM abnormalities.

CONCLUSIONS

Reduced local volumes along the surface of the brain mirrored the locations of abnormalities along the surface of the underlying WM, rather than of abnormalities of cortical thickness. Moreover, anatomical features of white matter, but not cortical thickness, correlated with measures of working memory. We propose that reductions in WM and smaller total cortical surface area could be central anatomical abnormalities in schizophrenia, driving, at least partially, the reduced regional GM volumes often observed in this illness.

Alterations in the cerebral white matter of genetic high risk offspring of patients with schizophrenia spectrum disorder

Alterations in white matter (WM) may be seen in young relatives at risk and may underlie vulnerability to schizophrenia. We were interested in exploring which of the WM regions were altered in adolescent offspring at familial risk for schizophrenia. We examined structural alterations in the offspring of subjects with schizophrenia or schizoaffective disorder (HR; n=65; 36 males) and healthy controls (HC; n=80: 37 males) matched for age and education. MRI images were collected using a GE 1.5 T scanner at the University of Pittsburgh Medical Center. Image processing was done using FreeSurfer (MGH) by an experienced rater blind to clinical data. We used multivariate analysis of covariance, with intracranial volume (p>0.05) and age as covariates. High Risk offspring had significant reductions in total WM, hemispheric WM and WM within left parietal and left cingulate cortices. Male offspring had more pronounced right hemisphere WM reductions than females.

Functional and structural MR imaging in neuropsychiatric disorders, part 2: application in schizophrenia and autism

SUMMARY

During the past decade, the application of advanced MR imaging techniques in neuropsychiatric disorders has seen a rapid increase. Disease-specific alterations in brain function can be assessed by fMRI. Structural GM and WM properties are increasingly investigated by DTI and voxel-based approaches like VBM. These methods provide neurobiologic correlates for brain architecture and function, evaluation tools for therapeutic approaches, and potential early markers for diagnosis. Having provided insight into principles of functional and structural imaging and delineated common findings in mild cognitive impairment and Alzheimer disease in Part 1 of this review, we will now focus on autism and schizophrenia as common psychiatric disorders covering different stages of the life span. This review concludes by summarizing current applications, limitations, and future prospects in the field of MR imaging-based neuroimaging.

Anterior limb of the internal capsule in schizotypal personality disorder: fiber-tract counting, volume, and anisotropy

Mounting evidence suggests that white matter abnormalities and altered subcortical-cortical connectivity may be central to the pathology of schizophrenia (SZ). The anterior limb of the internal capsule (ALIC) is an important thalamo-frontal white-matter tract shown to have volume reductions in SZ and to a lesser degree in schizotypal personality disorder (SPD). While fractional anisotropy (FA) and connectivity abnormalities in the ALIC have been reported in SZ, they have not been examined in SPD. In the current study, magnetic resonance (MRI) and diffusion tensor imaging (DTI) were obtained in age- and sex-matched individuals with SPD (n=33) and healthy controls (HCs; n=38). The ALIC was traced bilaterally on five equally spaced dorsal-to-ventral axial slices from each participant's MRI scan and co-registered to DTI for the calculation of FA. Tractography was used to examine tracts between the ALIC and two key Brodmann areas (BAs; BA10, BA45) within the dorsolateral prefrontal cortex (DLPFC). Compared with HCs, the SPD participants exhibited (a) smaller relative volume at the mid-ventral ALIC slice level but not the other levels; (b) normal FA within the ALIC; (c) fewer relative number of tracts between the most-dorsal ALIC levels and BA10 but not BA45 and (d) fewer dorsal ALIC-DLPFC tracts were associated with greater symptom severity in SPD. In contrast to prior SZ studies that report lower FA, individuals with SPD show sparing. Our findings are consistent with a pattern of milder thalamo-frontal dysconnectivity in SPD than schizophrenia.

White matter tract abnormalities in first-episode psychosis

Fibers connecting fronto-temporal and fronto-medial structures that pass through the anterior limb of the internal capsule (ALIC) subserve executive and psychomotor functioning. Both of these functions are adversely affected in schizophrenia, and may be abnormal at illness onset. In a study of first-episode psychosis, we used diffusion tensor imaging (DTI) and cognitive testing to examine ALIC integrity. Fourteen early psychosis patients and 29 healthy volunteers were included. Symptoms were assessed with the Positive and Negative Syndromes Scale (PANSS). All structural and diffusion scans were acquired on a GE Signa 1.5T scanner. A T1-weighted 3D FSPGR Inversion Recovery imaging series was acquired for manual seeding in structural space. Diffusion tensor imaging (DTI) was performed, and all DTI images were co-registered to structural space. Seeds were manually drawn bilaterally on the coronal plane at a specified location. Diffusion images were post-processed for subsequent Tract-based Spatial Statistics (TBSS) analysis. First-episode psychosis patients had significantly smaller fronto-medial and fronto-temporal AIC tract volumes compared to healthy volunteers on the left and the right (p-values<0.04). No differences in mean fractional anisotropy (FA) were seen within either left or right tracts (p-values>0.05), nor did TBSS reveal any other differences in FA values between groups in other regions. Relationships between tract volumes and symptom severity were not observed in this study.

Neuroanatomical Dissections of Unilateral Visual Neglect Symptoms: ALE Meta-Analysis of Lesion-Symptom Mapping

Unilateral visual neglect is commonly defined as impaired ability to attend to stimuli presented on the side of visual space contralateral to the brain lesion. However, behavioral analyses indicate that different neglect symptoms can dissociate. The neuroanatomy of the syndrome has been hotly debated. Some groups have argued that the syndrome is linked to posterior parietal cortex lesions, while others report damage within regions including the superior temporal gyrus, insula, and basal ganglia. Several recent neuroimaging studies provide evidence that heterogeneity in the behavioral symptoms of neglect can be matched by variations in the brain lesions, and that some of the discrepancies across earlier findings might have resulted from the use of different neuropsychological tests and/or varied measures within the same task for diagnosing neglect. In this paper, we review the evidence for dissociations between both the symptoms and the neural substrates of unilateral visual neglect, drawing on ALE (anatomic likelihood estimation) meta-analyses of lesion-symptom mapping studies. Specifically, we examine dissociations between neglect symptoms associated with impaired control of attention across space (in an egocentric frame of reference) and within objects (in an allocentric frame of reference). Results of ALE meta-analyses indicated that, while egocentric symptoms are associated with damage within perisylvian network (pre- and postcentral, supramarginal, and superior temporal gyri) and damage within sub-cortical structures, more posterior lesions including the angular, middle temporal, and middle occipital gyri are associated with allocentric symptoms. Furthermore, there was high concurrence in deficits associated with white matter lesions within long association (superior longitudinal, inferior fronto-occipital, and inferior longitudinal fasciculi) and projection (corona radiata and thalamic radiation) pathways, supporting a disconnection account of the syndrome. Using this evidence we argue that different forms of neglect link to both distinct and common patterns of gray and white matter lesions. The findings are discussed in terms of functional accounts of neglect and theoretical models based on computational studies of both normal and impaired attention functions.

Systematic meta-review and quality assessment of the structural brain alterations in schizophrenia

BACKGROUND

The large quantity of systematic reviews of magnetic resonance imaging studies in schizophrenia challenges their meaningful interpretation. This meta-review synthesises the available information from systematic reviews of structural alteration in both chronic and first-episode schizophrenia.

METHODS

Systematic reviews were identified using electronic databases. Review methodological quality was assessed according to the Assessment of Multiple Systematic Reviews checklist. Data were extracted in duplicate and quality assessed for consistency and precision, guided by Grading of Recommendations Assessment, Development and Evaluation recommendations.

RESULTS

Integration of volumetric and voxel-based estimates allowed critical assessment of the magnitude and location of anatomical differences. There is evidence for grey matter reductions of anterior cingulate, frontal (particularly medial and inferior) and temporal lobes, hippocampus/amygdala, thalamus, and insula that may be magnified over time. Other regional alterations appear specific to illness stage or medication status.

CONCLUSIONS

There is limited high quality evidence supporting grey or white matter changes in schizophrenia, which has previously been obscured by a large volume of conflicting lower quality evidence.

Impact of the genome wide supported NRGN gene on anterior cingulate morphology in schizophrenia

Background

The rs12807809 single-nucleotide polymorphism in NRGN is a genetic risk variant with genome-wide significance for schizophrenia. The frequency of the T allele of rs12807809 is higher in individuals with schizophrenia than in those without the disorder. Reduced immunoreactivity of NRGN, which is expressed exclusively in the brain, has been observed in Brodmann areas (BA) 9 and 32 of the prefrontal cortex in postmortem brains from patients with schizophrenia compared with those in controls.

Methods

Genotype effects of rs12807809 were investigated on gray matter (GM) and white matter (WM) volumes using magnetic resonance imaging (MRI) with a voxel-based morphometry (VBM) technique in a sample of 99 Japanese patients with schizophrenia and 263 healthy controls.

Results

Although significant genotype-diagnosis interaction either on GM or WM volume was not observed, there was a trend of genotype-diagnosis interaction on GM volume in the left anterior cingulate cortex (ACC). Thus, the effects of NRGN genotype on GM volume of patients with schizophrenia and healthy controls were separately investigated. In patients with schizophrenia, carriers of the risk T allele had a smaller GM volume in the left ACC (BA32) than did carriers of the non-risk C allele. Significant genotype effect on other regions of the GM or WM was not observed for either the patients or controls.

Conclusions

Our findings suggest that the genome-wide associated genetic risk variant in the NRGN gene may be related to a small GM volume in the ACC in the left hemisphere in patients with schizophrenia.

Association of the ZNF804A gene polymorphism rs1344706 with white matter density changes in Chinese schizophrenia

BACKGROUND

ZNF804A gene polymorphism rs1344706, the first genetic risk variant to achieve genome wide significance for schizophrenia, has been linked to neural functional connectivity. Dysconnectivity of WM may be the primary pathological mechanism of schizophrenia. Association of this variant with regional WM density has not been investigated in schizophrenic patients.

METHODS

69 healthy controls and 80 patients with schizophrenia underwent genotyping of rs1344706 SNPs, and were examined for WM density (T1-weighted MRI). The association of rs1344706 with WM changes in schizophrenia patients and healthy controls was analyzed using a full-factorial 2×2 analysis of variance.

RESULTS

1. There was an interaction on WM density in the left prefrontal lobe between the rs1344706 genotype and schizophrenic diagnosis, where the risk T allele carriers presented higher WM density in the schizophrenia patients and lower WM density in healthy controls in comparison with the non-risk allele carriers. 2. The risk allele was associated with an increased WM density of the bilateral hippocampus in both the patients and the healthy group.

LIMITATION

The influence of antipsychotics to the white matter in schizophrenic patients was not fully eliminated.

CONCLUSIONS

The ZNF804A variant may confer risk for schizophrenia by exerting its effects on the WM in the left prefrontal lobe together with other risk factors for schizophrenia.

Reduction of cerebellar grey matter in Crus I and II in schizophrenia

Structural deficiencies within the cerebellum have been associated with schizophrenia. Whereas several region-of-interest-based studies have shown deviations in cerebellar volume, meta-analyses on conventional whole-brain voxel-based morphometry (VBM) studies do not implicate abnormalities in the cerebellum. Since this discrepancy could be due to methodological problems of VBM, we used a cerebellum-optimized VBM procedure. We acquired high-resolution MRI scans from 29 schizophrenia patients and 45 healthy controls and used a VBM approach utilizing the Spatially Unbiased Infratentorial toolbox (Diedrichsen in Neuroimage 33:127-138, 2006). Relative to healthy controls, schizophrenia patients showed reductions of grey matter volume in the left cerebellum Crus I/II that were correlated with thought disorder (p < 0.05; one-sided) and performance in the Trail-making test B (p < 0.01). No cerebellar group differences were detected employing conventional whole-brain VBM. The results derived from the cerebellum analysis provide evidence for distinct grey matter deficits in schizophrenia located in Crus I/II. The association of this area with thought disorder and Trail-making performance supports the previously suggested role of the cerebellum in coordination of mental processes including disordered thought in schizophrenia. The failure of conventional VBM to detect such effects suggests that previous studies might have underestimated the importance of cerebellar structural deficits in schizophrenia.

Understanding aberrant white matter development in schizophrenia: an avenue for therapy?

Although historically gray matter changes have been the focus of neuropathological and neuroradiological studies in schizophrenia, in recent years an increasing body of research has implicated white matter structures and its constituent components (axons, their myelin sheaths and supporting oligodendrocytes). This article summarizes this body of literature, examining neuropathological, neurogenetic and neuroradiological evidence for white matter pathology in schizophrenia. We then look at the possible role that antipsychotic medication may play in these studies, examining both its role as a potential confounder in studies examining neuronal density and brain volume, but also the possible role that these medications may play in promoting myelination through their effects on oligodendrocytes. Finally, the role of potential novel therapies is discussed.