MRI brain volume abnormalities in young, nonpsychotic relatives of schizophrenia probands are associated with subsequent prodromal symptoms

Disrupted-in-schizophrenia 1 overexpression disrupts hippocampal coding and oscillatory synchronization

Aberrant proteostasis of protein aggregation may lead to behavior disorders including chronic mental illnesses (CMI). Furthermore, the neuronal activity alterations that underlie CMI are not well understood. We recorded the local field potential and single‐unit activity of the hippocampal CA1 region in vivo in rats transgenically overexpressing the Disrupted‐in‐Schizophrenia 1 (DISC1) gene (tgDISC1), modeling sporadic CMI. These tgDISC1 rats have previously been shown to exhibit DISC1 protein aggregation, disturbances in the dopaminergic system and attention‐related deficits. Recordings were performed during exploration of familiar and novel open field environments and during sleep, allowing investigation of neuronal abnormalities in unconstrained behavior. Compared to controls, tgDISC1 place cells exhibited smaller place fields and decreased speed‐modulation of their firing rates, demonstrating altered spatial coding and deficits in encoding location‐independent sensory inputs. Oscillation analyses showed that tgDISC1 pyramidal neurons had higher theta phase locking strength during novelty, limiting their phase coding ability. However, their mean theta phases were more variable at the population level, reducing oscillatory network synchronization. Finally, tgDISC1 pyramidal neurons showed a lack of novelty‐induced shift in their preferred theta and gamma firing phases, indicating deficits in coding of novel environments with oscillatory firing. By combining single cell and neuronal population analyses, we link DISC1 protein pathology with abnormal hippocampal neural coding and network synchrony, and thereby gain a more comprehensive understanding of CMI mechanisms.

Impulsivity in unaffected adolescent biological relatives of schizophrenia patients

OBJECTIVE

Although schizophrenia is not a prototypic impulse-control disorder, patients report more impulsive behaviors, have higher rates of substance use, and show dysfunction in brain circuits that underlie impulsivity. We investigate impulsivity in unaffected biological relatives of schizophrenia patients to further understand the relationships between schizophrenia risk and impulse control during adolescence.

METHOD

Group differences in impulsivity (UPPS-P Impulsive Behavior Scale and delay discounting) were tested in 210 adolescents contrasting 39 first- and 53 second-degree biological relatives of schizophrenia patients, and 118 subjects with no schizophrenia family history (NSFH).

RESULTS

Compared to NSFH adolescents and to second-degree relatives, first-degree relatives of schizophrenia patients had increased impulsivity-related behaviors (higher UPPS-P Perseverance, Positive Urgency and Premeditation subscale scores) and greater preference for immediate rewards (smaller AUC and larger discounting constant). Second-degree relatives did not differ significantly from NSFH adolescents on self-report impulsive behaviors or on measures of impulsive decision-making. These group differences remained even after careful consideration of potential confounding factors.

CONCLUSION

Impulsivity is associated with schizophrenia risk, and its severity increases with greater familial relatedness to the schizophrenia proband. Additional studies are needed to understand the role impulsivity may play in mediating schizophrenia susceptibility during adolescence.

Transitive inference deficits in unaffected biological relatives of schizophrenia patients

Currently available treatments have limited efficacy in remediating cognitive impairment in schizophrenia. Efforts to facilitate cognition-enhancing drug discovery recommend the use of varied experimental cognitive paradigms (including relational memory) as assessment tools in clinical drug trials. Although relational memory deficits are increasingly being recognized as a reliable cognitive marker of schizophrenia, relational memory performance among unaffected biological relatives remains unknown. Therefore, we evaluated 73 adolescents or young adults (22 first- and 26 second-degree relatives of schizophrenia patients and 25 healthy controls (HC)) using a well-validated transitive inference (TI) experimental paradigm previously used to demonstrate relational memory impairment in schizophrenia. We found that TI deficits were associated with schizophrenia risk with first-degree relatives showing greater impairment than second-degree relatives. First-degree relatives had poorer TI performance with significantly lower accuracy and longer response times than HC when responding to TI probe pairs. Second-degree relatives had significantly quicker response times than first-degree relatives and were more similar to HC in TI performance. We further explored the relationships between TI performance and neurocognitive domains implicated in schizophrenia. Among HC, response times were inversely correlated with FSIQ, verbal learning, processing speed, linguistic abilities and working memory. In contrast, relatives (first-degree in particular) had a differing pattern of TI-neurocognition relationships, which suggest that different brain circuits may be used when relatives encode and retrieve relational memory. Our finding that unaffected biological relatives of schizophrenia patients have TI deficits lends further support for the use of relational memory construct in future pro-cognition drug studies.

MR image segmentation and bias field estimation based on coherent local intensity clustering with total variation regularization

Though numerous segmentation algorithms have been proposed to segment brain tissue from magnetic resonance (MR) images, few of them consider combining the tissue segmentation and bias field correction into a unified framework while simultaneously removing the noise. In this paper, we present a new unified MR image segmentation algorithm whereby tissue segmentation, bias correction and noise reduction are integrated within the same energy model. Our method is presented by a total variation term introduced to the coherent local intensity clustering criterion function. To solve the nonconvex problem with respect to membership functions, we add auxiliary variables in the energy function such as Chambolle's fast dual projection method can be used and the optimal segmentation and bias field estimation can be achieved simultaneously throughout the reciprocal iteration. Experimental results show that the proposed method has a salient advantage over the other three baseline methods on either tissue segmentation or bias correction, and the noise is significantly reduced via its applications on highly noise-corrupted images. Moreover, benefiting from the fast convergence of the proposed solution, our method is less time-consuming and robust to parameter setting.

M. Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth

BACKGROUND

Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging.

OBJECTIVE

This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regional growth.

METHODS

Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer's disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation.

RESULTS

By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively.

CONCLUSION

The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases.

The impact of metabotropic glutamate receptors into active neurodegenerative processes: A "dark side" in the development of new symptomatic treatments for neurologic and psychiatric disorders

Metabotropic glutamate (mGlu) receptor ligands are under clinical development for the treatment of CNS disorders with high social and economic burden, such as schizophrenia, major depressive disorder (MDD), and Parkinson's disease (PD), and are promising drug candidates for the treatment of Alzheimer's disease (AD). So far, clinical studies have shown symptomatic effects of mGlu receptor ligands, but it is unknown whether these drugs act as disease modifiers or, at the opposite end, they accelerate disease progression by enhancing neurodegeneration. This is a fundamental issue in the treatment of PD and AD, and is also an emerging theme in the treatment of schizophrenia and MDD, in which neurodegeneration is also present and contribute to disease progression. Moving from in vitro data and preclinical studies, we discuss the potential impact of drugs targeting mGlu2, mGlu3, mGlu4 and mGlu5 receptor ligands on active neurodegeneration associated with AD, PD, schizophrenia, and MDD. We wish to highlight that our final comments on the best drug candidates are not influenced by commercial interests or by previous or ongoing collaborations with drug companies. This article is part of the Special Issue entitled 'Metabotropic Glutamate Receptors, 5 years on'.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker

BACKGROUND

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing.

METHODS

This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri.

RESULTS

Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences.

CONCLUSIONS

CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

[Personalised medicine in psychiatry and psychotherapy. A review of the current state-of-the-art in the biomarker-based early recognition of psychoses]

The main goal of psychiatric high-risk research--the personalised early recognition and intervention of schizophrenic and affective psychoses--is one of the biggest challenges of current clinical psychiatry due to the immense socioeconomic burden of these disorders. In this regard, this review discusses the prospects and caveats of new clinical, neuropsychological, neurophysiological and imaging-based concepts aimed at optimising the current state-of-the-art of early recognition. Finally, multivariate modelling and machine learning methods are presented as a novel methodological framework facilitating the decoding of early psychosis into different intermediate phenotypes. In the future, these phenotypes could be employed for a more objective risk stratification that operates at the single-subject level. This could allow us to generate clinically applicable prognostic biomarkers for these disorders that would propel the individualised prevention of disease transition, chronification and psychopharmacological treatment resistance of psychotic disorders.

Relationship between prefrontal gray matter volumes and working memory performance in schizophrenia: a family study

Diffuse structural abnormalities in the prefrontal cortex have been reported in both schizophrenia patients and their nonpsychotic biological relatives. Additionally, working memory difficulties have long been documented in schizophrenia patients and have been associated with the genetic liability for the disorder. The present analysis investigated the relationship between prefrontal regional gray matter volumes and two facets of working memory in schizophrenia using a family study. Structural neuroimaging scans provided measurements of rostral middle, superior, and inferior prefrontal cortical gray matter volumes. Participants also completed a spatial working memory task that measured both short-term maintenance and manipulation of material in memory. Both schizophrenia patients and relatives had reduced superior and inferior frontal gray matter volumes. Schizophrenia patients demonstrated a spatial working memory deficit compared to both controls and relatives, with no greater impairment when required to manipulate material. Smaller prefrontal volumes in schizophrenia patients were associated with worse working memory performance. These relationships were absent in the nonpsychotic relatives and controls. Despite normative behavioral performance, nonpsychotic relatives demonstrated abnormalities in brain structure similar to those found in schizophrenia patients. Manipulation abilities were not more impaired than maintenance in schizophrenia patients. Consistent with other neuroimaging research, our results suggest that direct measures of the underlying biology may be more sensitive to the effects of the genetic liability for schizophrenia than behavioral measures.

COMT, neuropsychological function and brain structure in schizophrenia: a systematic review and neurobiological interpretation

BACKGROUND

Endophenotypes in genetic psychiatry may increase our understanding of the molecular mechanisms underlying disease risk and its manifestations. We sought to investigate the link between neuropsychological impairments and brain structural abnormalities associated with the COMT Val(158)Met polymorphism in patients with schizophrenia to improve understanding of the pathophysiology of this disorder.

METHODS

We performed a systematic review using studies identified in PubMed and MEDLINE (from the date of the first available article to July 2012). Our review examined evidence of an association between the COMT Val(158)Met polymorphism and both neuropsychological performance and brain structure in patients with psychosis, in their relatives and in healthy individuals (step 1). The review also explored whether the neuropsychological tasks and brain structures identified in step 1 met the criteria for an endophenotype (step 2). Then we evaluated evidence that the neuropsychological endophenotypes identified in step 2 are associated with the brain structure endophenotypes identified in that step (step 3). Finally, we propose a neurobiological interpretation for this evidence.

RESULTS

A poorer performance on the n-back task and the Continuous Performance Test (CPT) and smaller temporal and frontal brain areas were associated with the COMT Val allele in patients with schizophrenia and their relatives and met most of the criteria for an endophenotype. It is possible that the COMT Val(158)Met polymorphism therefore contributes to the development of these neuropsychological and brain structural endophenotypes of schizophrenia, in which the prefrontal cortex may represent the neural substrate underlying both n-back and CPT performances.

LIMITATIONS

The association between a single genetic variant and an endophenotype does not necessarily imply a causal relationship between them.

CONCLUSION

This evidence and the proposed interpretation contribute to explain, at least in part, the biological substrate of 4 important endophenotypes that characterize schizophrenia.

A review of neuroimaging studies of young relatives of individuals with schizophrenia: a developmental perspective from schizotaxia to schizophrenia

In an effort to identify the developing abnormalities preceding psychosis, Dr. Ming T. Tsuang and colleagues at Harvard expanded Meehl's concept of "schizotaxia," and examined brain structure and function in families affected by schizophrenia (SZ). Here, we systematically review genetic (familial) high-risk (HR) studies of SZ using magnetic resonance imaging (MRI), examine how findings inform models of SZ etiology, and suggest directions for future research. Neuroimaging studies of youth at HR for SZ through the age of 30 were identified through a MEDLINE (PubMed) search. There is substantial evidence of gray matter volume abnormalities in youth at HR compared to controls, with an accelerated volume reduction over time in association with symptoms and cognitive deficits. In structural neuroimaging studies, prefrontal cortex (PFC) alterations were the most consistently reported finding in HR. There was also consistent evidence of smaller hippocampal volume. In functional studies, hyperactivity of the right PFC during performance of diverse tasks with common executive demands was consistently reported. The only longitudinal fMRI study to date revealed increasing left middle temporal activity in association with the emergence of psychotic symptoms. There was preliminary evidence of cerebellar and default mode network alterations in association with symptoms. Brain abnormalities in structure, function and neurochemistry are observed in the premorbid period in youth at HR for SZ. Future research should focus on the genetic and environmental contributions to these alterations, determine how early they emerge, and determine whether they can be partially or fully remediated by innovative treatments.

Early intervention and the treatment of prodrome in schizophrenia: a review of recent developments

OBJECTIVE

Strategies for preventing the development of schizophrenia are in their infancy but are associated with much hope and potential. The relatively long prodrome in schizophrenia allows for indicated prevention as an effective intervention. "High-risk" individuals have subtle symptoms and, without intervention, a third would develop psychosis within 1 year, and many will have poor functional outcomes, even in the absence of psychosis. Research in this area is preliminary but encouraging.

METHODS

A literature search was performed using databases including PubMed, PsychInfo, and Cochrane, as well as a search of individual journals through cross-referencing. The search used the following key words: schizophrenia, psychosis, psychotic disorders, first episode, early, prodrome, prodromal, prevention, ultra high risk, at risk, and intervention.

RESULTS

Strategies for preventing the development of schizophrenia are divided into universal, selective, and indicated levels of prevention. The common preventive methods include treatment with antipsychotic medications and psychotherapy. Early intervention helps at risk individuals with symptom reduction and appears to delay conversion to full blown psychosis. However, the criteria for identifying at risk individuals have low predictive value, which raises concerns about unnecessary and potentially harmful interventions.

CONCLUSION

Although a range of interventions appear to be effective in reducing rates of transition to psychosis, they are inadequately differentiated and require further study. Current data suggest that clinicians take an individualized approach to intervention, considering the risk-benefit ratio on a case-by-case basis.

Prefrontal deviations in function but not volume are putative endophenotypes for schizophrenia

This study sought to systematically investigate whether prefrontal cortex grey matter volume reductions are valid endophenotypes for schizophrenia, specifically investigating their presence in unaffected relatives, heritability, genetic overlap with the disorder itself and finally to contrast their performance on these criteria with putative neuropsychological indices of prefrontal functioning. We used a combined twin and family design and examined four prefrontal cortical regions of interest. Superior and inferior regions were significantly smaller in patients. However, the volumes of these same regions were normal in unaffected relatives and therefore, we could confirm that such deficits were not due to familial effects. Volumes of the prefrontal and orbital cortices were, however, moderately heritable, but neither shared a genetic overlap with schizophrenia. Total prefrontal cortical volume reductions shared a significant unique environmental overlap with the disorder, suggesting that the reductions were not familial. In contrast, prefrontal (executive) functioning deficits were present in the unaffected relatives, were moderately heritable and shared a substantial genetic overlap with liability to schizophrenia. These results suggest that the well recognized prefrontal volume reductions are not related to the same familial influences that increase schizophrenia liability and instead may be attributable to illness related biological changes or indeed confounded by illness trajectory, chronicity, medication or substance abuse, or in fact a combination of some or all of them.

Putative structural neuroimaging endophenotypes in schizophrenia: a comprehensive review of the current evidence

The genetic contribution to schizophrenia etiopathogenesis is underscored by the fact that the best predictor of developing schizophrenia is having an affected first-degree relative, which increases lifetime risk by tenfold, as well as the observation that when both parents are affected, the risk of schizophrenia increases to approximately 50%, compared with 1% in the general population. The search to elucidate the complex genetic architecture of schizophrenia has employed various approaches, including twin and family studies to examine co-aggregation of brain abnormalities, studies on genetic linkage and studies using genome-wide association to identify genetic variations associated with schizophrenia. ‘Endophenotypes’, or ‘intermediate phenotypes’, are potentially narrower constructs of genetic risk. Hypothetically, they are intermediate in the pathway between genetic variation and clinical phenotypes and can supposedly be implemented to assist in the identification of genetic diathesis for schizophrenia and, possibly, in redefining clinical phenomenology.

Abnormalities in connectivity of white-matter tracts in patients with familial and non-familial schizophrenia

BACKGROUND

Abnormalities in the connectivity of white-matter (WM) tracts in schizophrenia are supported by evidence from post-mortem investigations, functional and structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). The aims of this study were to explore the microstructural changes in first-episode schizophrenia in a Han Chinese population and to investigate whether a family history of psychiatric disorder is related to the severity of WM tract integrity abnormalities in these patients.

METHOD

T1-weighted MR and DT images were collected in 68 patients with first-episode schizophrenia [22 with a positive family history (PFH) and 46 with a negative family history (NFH)] and 100 healthy controls. Voxel-based analysis was performed and WM integrity was quantified by fractional anisotropy (FA). Cluster- and voxel-level analyses were performed by using two-sample t tests between patients and controls and/or using a full factorial model with one factor and three levels among the three sample groups (patients with PFH or NFH, and controls), as appropriate.

RESULTS

FA deficits were observed in the patient group, especially in the left temporal lobe and right corpus callosum. This effect was more severe in the non-familial schizophrenia than in the familial schizophrenia subgroup.

CONCLUSIONS

Overall, these findings support the hypothesis that loss of WM integrity may be an important pathophysiological feature of schizophrenia, with particular implications for brain dysmaturation in non-familial and familial schizophrenia.

Hypo-activation in the executive core of the sustained attention network in adolescent offspring of schizophrenia patients mediated by premorbid functional deficits

Adolescent offspring of schizophrenia patients (SCZ-Off) are vulnerable to psychiatric disorders. Assessing relationships between clinical and biological measures (such as functional magnetic resonance imaging, fMRI) may elucidate pathways of vulnerability in this group. Here we assessed the relationship between clinically assessed premorbid function, and cortico-striatal activity during sustained attention in controls (HC: with no family history of psychosis) and SCZ-Off. Subjects (n=39) were assessed using the Structured Interview for Prodromal Syndromes and the Scale of Prodromal Symptoms. Based on the Global Assessment of Functioning (GAF) score, SCZ-Off were cleaved into "high" or "low" clinically functioning sub-groups (SCZ-Off(HF), SCZ-Off(LF) respectively). During fMRI, subjects participated in a modified continuous performance task (CPT-IP). fMRI was conducted on a Bruker MedSpec 4T system (345 EPI scans; TR=2s; 24 slices; 3.8×3.8×4mm). Results show SCZ-Off(LF) evinced less activation than both HC and SCZ-Off(HF) in the executive core of the brain's attentional system (anterior cingulate, dorsal prefrontal cortex and caudate), but not visuo-spatial regions such as primary visual or superior parietal cortex. Differences were independent of behavioral performance, and reduction in activity was related to GAF score in a dose-dependent manner. Assessing the relationship between clinical measures and brain activity in domains such as attention provides a window into mechanisms of vulnerability in the developing adolescent brain.

Putative diffusion tensor neuroimaging endophenotypes in schizophrenia: a review of the early evidence

Although schizophrenia has a high heritability, the genetic effects conferring diathesis to schizophrenia are thought to be complex and underlain by multifactorial polygenic inheritance. ‘Endophenotypes’, or ‘intermediate phenotypes’, are narrowed constructs of genetic risk that are assumed to be more proximal to the gene effects in the disease pathway than clinical phenotypes. A current aim in schizophrenia research is to identify promising putative endophenotypes for use in molecular genetics studies. Recently, much of the focus has been on neurocognitive, conventional T1-weighted structural MRI, functional MRI and electrophysiological endophenotypes. Diffusion tensor imaging has emerged as another important structural neuroimaging modality in the aim to identify abnormalities in brain connectivity and diffusivity in schizophrenia, and abnormalities detected via this method may be promising candidate endophenotypes. In this article, we present the first comprehensive review of the early evidence that qualifies diffusion tensor abnormalities as potentially appropriate endophenotypes of schizophrenia.

A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image

A modified possibilistic fuzzy c-means clustering algorithm is presented for fuzzy segmentation of magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities and noise. By introducing a novel adaptive method to compute the weights of local spatial in the objective function, the new adaptive fuzzy clustering algorithm is capable of utilizing local contextual information to impose local spatial continuity, thus allowing the suppression of noise and helping to resolve classification ambiguity. To estimate the intensity inhomogeneity, the global intensity is introduced into the coherent local intensity clustering algorithm and takes the local and global intensity information into account. The segmentation target therefore is driven by two forces to smooth the derived optimal bias field and improve the accuracy of the segmentation task. The proposed method has been successfully applied to 3 T, 7 T, synthetic and real MR images with desirable results. Comparisons with other approaches demonstrate the superior performance of the proposed algorithm. Moreover, the proposed algorithm is robust to initialization, thereby allowing fully automatic applications.

Fully automated analysis using BRAINS: AutoWorkup

The BRAINS (Brain Research: Analysis of Images, Networks, and Systems) image analysis software has been in use, and in constant development, for over 20 years. The original neuroimage analysis pipeline using BRAINS was designed as a semiautomated procedure to measure volumes of the cerebral lobes and subcortical structures, requiring manual intervention at several stages in the process. Through use of advanced image processing algorithms the need for manual intervention at stages of image realignment, tissue sampling, and mask editing have been eliminated. In addition, inhomogeneity correction, intensity normalization, and mask cleaning routines have been added to improve the accuracy and consistency of the results. The fully automated method, AutoWorkup, is shown in this study to be more reliable (ICC ≥ 0.96, Jaccard index ≥ 0.80, and Dice index ≥ 0.89 for all tissues in all regions) than the average of 18 manual raters. On a set of 1130 good quality scans, the failure rate for correct realignment was 1.1%, and manual editing of the brain mask was required on 4% of the scans. In other tests, AutoWorkup is shown to produce measures that are reliable for data acquired across scanners, scanner vendors, and across sequences. Application of AutoWorkup for the analysis of data from the 32-site, multivendor PREDICT-HD study yield estimates of reliability to be greater than or equal to 0.90 for all tissues and regions.

The psychoses: cluster 3 of the proposed meta-structure for DSM-V and ICD-11

BACKGROUND

In an effort to group mental disorders on the basis of etiology, five clusters have been proposed. Here we consider the validity of the cluster comprising selected psychotic and related disorders.

METHOD

A group of diagnostic entities classified under schizophrenia and other psychotic disorders in DSM-IV-TR were assigned to this cluster and the bordering disorders, bipolar (BD) and schizotypal personality disorders (SPD), were included. We then reviewed the literature in relation to 11 validating criteria proposed by the DSM-V Task Force Study Group.

RESULTS

Relevant comparisons on the 11 spectrum criteria are rare for the included disorders except for schizophrenia and the two border conditions, BD and SPD. The core psychosis group is congruent at the level of shared psychotic psychopathology and response to antipsychotic medication. BD and SPD are exceptions in that psychosis is not typical in BD-II disorder and frank psychosis is excluded in SPD. There is modest similarity between schizophrenia and BD relating to risk factors, neural substrates, cognition and endophenotypes, but key differences are noted. There is greater support for a spectrum relationship of SPD and schizophrenia. Antecedent temperament, an important validator for other groupings, has received little empirical study in the various psychotic disorders.

CONCLUSIONS

The DSM-IV-TR grouping of psychotic disorders is supported by tradition and shared psychopathology, but few data exist across these diagnoses relating to the 11 spectrum criteria. The case for including BD is modest, and the relationship of BD to other mood disorders is addressed elsewhere. Evidence is stronger for inclusion of SPD, but the relationship with other personality disorders along the 11 criteria is not addressed and the absence of psychosis presents a conceptual problem. There are no data along the 11 spectrum criteria that are decisive for a cluster based on etiology, and inclusion of BD and SPD is questionable.

Progressive temporal lobe grey matter loss in adolescents with schizotypal traits and mild intellectual impairment

Adolescents with mild intellectual impairment are known to have an increased risk of schizophrenia compared to the general population. However, little is known regarding the association between potential risk markers for later schizophrenia within this population. We therefore set out to examine the association between schizotypal traits and progressive grey matter loss in adolescents with mild intellectual impairment. Ninety-eight adolescents receiving educational assistance were divided into two groups based on their degree of schizotypal features, measured using the Structured Interview for Schizotypy (SIS). Each participant received two structural magnetic resonance imaging scans approximately 16 months apart. Changes over time in the voxel-wise presentation of tissue were evaluated using tensor based morphometry. Those with marked schizotypal features exhibited significantly greater grey matter losses in the left medial temporal lobe than those without. Three focal locations were identified, two within the left amygdala and one in the left parahippocampal gyrus. Thus, adolescents with cognitive impairment and schizotypal features show changes in brain structure over time, changes that are consistent with those identified in other high risk populations. Medial temporal grey matter loss may therefore represent a common neuroanatomical substrate of risk for schizophrenia, common to familial, prodromal and cognitive high risk groups.

Hippocampal volume deficits and shape deformities in young biological relatives of schizophrenia probands

Hippocampal volume decrement may be one of the changes that most closely pre-date schizophrenia onset. Studying hippocampal developmental morphology in adolescent or young adult biological relatives of schizophrenia probands has the potential to further our understanding of the neurodevelopmental etiology of schizophrenia and to discover biomarkers that may aid its early identification. We utilized an artificial neural network segmentation algorithm to automatically define and reliably measure MRI hippocampus volumes. We compared 46 young, nonpsychotic biological relatives of probands against 46 healthy controls without family history of schizophrenia and 46 schizophrenia probands (age range=13 to 28 years). We further contrasted hippocampal shape differences using spherical harmonic functions and assessed how obstetric complications (a trigger for aberrant in utero neurodevelopment) may contribute to hippocampal abnormalities. Similar to schizophrenia probands, unaffected biological relatives of probands had significantly smaller hippocampus volumes than controls; which correspond to inward displacements in shape deformities principally in the anterior hippocampal subregions. Examination of hippocampus volume-age relationships indicate that hippocampus volume normally decreases with age during late adolescence through early adulthood. In contrast, relatives of probands did not show these age-expected changes. Deviant hippocampus volume-age relationships suggest aberrant hippocampal neurodevelopment among biological relatives. Relatives with a history of obstetric complications had significantly smaller left and right hippocampi than relatives without obstetrics complications, including a dose relationship such that greater number of birth complications correlated with smaller hippocampus. Similar hippocampal volume deficits-obstetric complications relationships were observed among schizophrenia probands. Hippocampal abnormalities in schizophrenia are likely to be mediated by different neurobiological mechanisms, including factors associated with obstetric complications which occur during early neurodevelopment. Other brain maturational anomalies affecting the hippocampus in schizophrenia may manifest closer to illness onset in adolescence/early adulthood.