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Dubiety exists over whether clinical symptoms of schizophrenia can be distinguished from affective psychosis, the assumption being that absence of a "point of rarity" indicates lack of nosological distinction, based on prior group-level analyses. Advanced machine learning techniques, using unsupervised (hierarchical clustering) and supervised (regularized logistic regression algorithm and nested-cross-validation) were applied to a dataset of 202 patients with functional psychosis (schizophrenia n = 120, affective psychosis, n = 82). Patients were initially assessed with the Present State Examination (PSE), and followed up 2.5 years later, when DSM III diagnoses were applied (independent of initial PSE). Based on PSE syndromes, unsupervised learning discriminated depressive (approximately unbiased probability, AUP = 0.92) and mania/psychosis (AUP = 0.94) clusters. The mania/psychosis cluster further split into two groups - a mania (AUP = 0.84) and a psychosis cluster (AUP = 0.88). Supervised machine learning classified schizophrenia or affective psychosis with 83.66% (95% CI = 77.83% to 88.48%) accuracy. Area under the ROC curve (AUROC) was 89.14%. True positive rate for schizophrenia was 88.24% (95%CI = 81.05-93.42%) and affective psychosis 77.11% (95%CI = 66.58-85.62). Classification accuracy and AUROC remained high when PSE syndromes corresponding to affective symptoms (those that corresponded to the depressive and mania clusters) were removed. PSE syndromes, based on clinical symptoms, therefore discriminated between schizophrenia and affective psychosis, suggesting validity to these diagnostic constructs., (Copyright © 2018. Published by Elsevier B.V.)

To date, there are no reliable markers for predicting onset of schizophrenia in individuals at high risk (HR). Substantial promise is, however, shown by a variety of pattern classification approaches to neuroimaging data. Here, we examined the predictive accuracy of support vector machine (SVM) in later diagnosing schizophrenia, at a single-subject level, using a cohort of HR individuals drawn from multiply affected families and a combination of neuroanatomical, schizotypal and neurocognitive variables. Baseline structural magnetic resonance imaging (MRI), schizotypal and neurocognitive data from 17 HR subjects, who subsequently developed schizophrenia and a matched group of 17 HR subjects who did not make the transition, yet had psychotic symptoms, were included in the analysis. We employed recursive feature elimination (RFE), in a nested cross-validation scheme to identify the most significant predictors of disease transition and enhance diagnostic performance. Classification accuracy was 94% when a self-completed measure of schizotypy, a declarative memory test and structural MRI data were combined into a single learning algorithm; higher than when either quantitative measure was used alone. The discriminative neuroanatomical pattern involved gray matter volume differences in frontal, orbito-frontal and occipital lobe regions bilaterally as well as parts of the superior, medial temporal lobe and cerebellar regions. Our findings suggest that an early SVM-based prediction of schizophrenia is possible and can be improved by combining schizotypal and neurocognitive features with neuroanatomical variables. However, our predictive model needs to be tested by classifying a new, independent HR cohort in order to estimate its validity., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background: There is an established link between childhood adversity (CA) and schizophrenia. Hippocampus and amygdala abnormalities pre-date onset in those at high familial risk (fHR) of schizophrenia, but it is not clear whether these alterations are associated with CA in those at elevated risk of schizophrenia., Methods: We examined hippocampal and amygdala volumes in those at fHR who had been referred to a social worker or the Children's Panel compared to those who had not., Results: The right hippocampus and left amygdala were significantly smaller in those that had been referred to social work and Children's Panel., Conclusions: Our findings suggest that CA can influence structural changes in the brain in a cohort at fHR of schizophrenia. These findings provide further evidence that while genetic factors contribute to the structural changes found in schizophrenia, environmental factors such as CA can have a lasting impact on specific brain regions., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Schizophrenia is associated with structural brain abnormalities that are likely to be present before disease onset. It remains unclear to what extent these represent general vulnerability indicators or are associated with the developing clinical state itself. It also remains unclear whether such state or trait alterations may be evident at any given time-point, or whether they progress over time. To investigate this, structural brain scans were acquired at two time-points (mean scan-interval 1.87years) in a cohort of young unaffected individuals at high familial risk of schizophrenia (baseline, n=142; follow-up, n=64) and healthy controls (baseline, n=36; follow-up, n=18). Sub-cortical reconstructions of the hippocampus and amygdala were generated using the longitudinal pipeline available with Freesurfer. The high risk cohort was subdivided into individuals that remained well during the study (HR[well], baseline, n=68; follow-up, n=30), transient and/or partial symptoms that were insufficient to support a formal diagnosis (HR[symp], baseline, n=57; follow-up, n=26) and individuals that subsequently developed schizophrenia according to ICD-10 criteria (HR[ill], baseline, n=17; follow-up, n=8). Longitudinal change in the hippocampus and amygdala was compared, focusing first on overall differences between high-risk individuals and controls and then on sub-group differences within the high-risk cohort. We found a significantly altered developmental trajectory for all high risk individuals compared to controls, with controls showing a significant increase in hippocampal volume over time compared to those at high risk. We did not find evidence of altered longitudinal trajectories based on clinical outcome within the high risk cohort. These results suggest that an altered developmental trajectory of hippocampal volume is associated with a general familial predisposition to develop schizophrenia, as this alteration was not related to subsequent clinical outcome., (Copyright © 2014. Published by Elsevier B.V.)

Grey matter brain networks are disrupted in schizophrenia, but it is still unclear at which point during the development of the illness these disruptions arise and whether these can be associated with behavioural predictors of schizophrenia. We investigated if single-subject grey matter networks were disrupted in a sample of people at familial risk of schizophrenia. Single-subject grey matter networks were extracted from structural MRI scans of 144 high risk subjects, 32 recent-onset patients and 36 healthy controls. The following network properties were calculated: size, connectivity density, degree, path length, clustering coefficient, betweenness centrality and small world properties. People at risk of schizophrenia showed decreased path length and clustering in mostly prefrontal and temporal areas. Within the high risk sample, the path length of the posterior cingulate cortex and the betweenness centrality of the left inferior frontal operculum explained 81% of the variance in schizotypal cognitions, which was previously shown to be the strongest behavioural predictor of schizophrenia in the study. In contrast, local grey matter volume measurements explained 48% of variance in schizotypy. The present results suggest that single-subject grey matter networks can quantify behaviourally relevant biological alterations in people at increased risk for schizophrenia before disease onset., (Copyright © 2015 Elsevier B.V. All rights reserved.)

It is unknown whether brain changes occur prior to onset of schizophrenia or after it develops. Prospective familial high risk studies provide a good method to investigate this. In the Edinburgh High Risk Study, structural MRI scans of 150 young individuals at familial high risk of schizophrenia, 34 patients with first-episode schizophrenia and 36 matched controls were obtained. Of the high risk participants with scans suitable for analysis, 17 developed schizophrenia after the scans were taken, whilst 57 experienced isolated or sub-clinical psychotic symptoms, and 70 remained well. We used Freesurfer to extract volumetric measurements of the hippocampus, amygdala and nucleus accumbens with the aim of assessing whether any alterations found were present in all those at high risk, or selectively in the high risk cohort based on future clinical outcome, or only in those experiencing their first-episode of psychosis. We found no significant differences in any examined regions between controls and those at high risk, or between those at high risk who later developed schizophrenia and those who remained well. However, patients with first-episode schizophrenia demonstrated significant volumetric reductions in the bilateral hippocampus, left amygdala, and right nucleus accumbens compared to high risk individuals and healthy controls, which were not significantly associated with the intake of anti-psychotic medication or duration of illness. We found that patients had significantly smaller left amygdalae and bilateral hippocampus compared to HR[ill]. Our findings suggest that volumetric reductions of the hippocampus, amygdala and nucleus accumbens occur early in the first-episode of psychosis. The apparent absence of high risk versus control differences we found using Freesurfer is at odds with our previous studies conducted on the same sample, and possible methodological reasons for these apparent discrepancies are discussed., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Background: Schizophrenia is associated with cortical thickness reductions in the brain, but it is unclear whether these are present before illness onset, and to what extent they are driven by genetic factors., Methods: In the Edinburgh High Risk Study, structural MRI scans of 150 young individuals at high familial risk for schizophrenia, 34 patients with first-episode schizophrenia and 36 matched controls were acquired, and clinical information was collected for the following 10 years for the high-risk and control group. During this time, 17 high-risk individuals developed schizophrenia, on average 2.5 years after the scan, and 57 experienced isolated or sub-clinical psychotic symptoms. We applied surface-based analysis of the cerebral cortex to this cohort, and extracted cortical thickness in automatically parcellated regions., Results: Analysis of variance revealed widespread thinning of the cerebral cortex in first-episode patients, most pronounced in superior frontal, medial parietal, and lateral occipital regions (corrected p<10(-4)). In contrast, cortical thickness reductions were only found in high-risk individuals in the left middle temporal gyrus (corrected p<0.05). There were no significant differences between those at high risk who later developed schizophrenia and those who remained well., Conclusions: These findings confirm cortical thickness reductions in schizophrenia patients. Increased familial risk for schizophrenia is associated with thinning in the left middle temporal lobe, irrespective of subsequent disease onset. The absence of widespread cortical thinning before disease onset implies that the cortical thinning is unlikely to simply reflect genetic liability to schizophrenia but is predominantly driven by disease-associated factors., (© 2013 Elsevier B.V. All rights reserved.)

Behavioral abnormalities related to processing negative emotions such as fear have been demonstrated in schizophrenia. The amygdala is strongly associated with fear processing, and alterations in amygdala function and structure have been demonstrated in schizophrenia. Further, functional disconnectivity has been attributed as key to the etiology of schizophrenia, with a number of lines of evidence supporting this theory. In the present study, we examine the effective connectivity corresponding to fear processing, from the amygdala to the whole brain, and compare this between patients with schizophrenia and control participants. An implicit facial emotion processing task was performed by 19 patients with schizophrenia and 24 matched controls during fMRI scanning. During the task, participants made gender judgments from facial images with either neutral or fearful emotion. Neural response to fearful images versus neutral was used as contrast of interest to estimate effective connectivity between the amygdala and the whole brain using the psycho-physiological interactions approach. This connectivity was compared between patients with schizophrenia and healthy controls. We show that when looking at fearful compared to neutral faces patients with schizophrenia show significantly reduced effective connectivity from the amygdala to a large cluster of regions including parts of the precuneus and parietal lobe, compared to healthy controls. These regions have been associated with emotion processing and high level social cognition tasks involving self related processing and mental representations about other people. The reduced amygdala connectivity in schizophrenia shown here further illuminates the neural basis for the behavioral abnormalities in emotional and social function found in the disorder., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Diffusion tensor imaging (DTI) has previously shown compromised white matter integrity in frontotemporal white matter fibers in patients with schizophrenia, as indicated by reduced fractional anisotropy (FA). In the present study we investigated whether reduced white matter FA is also present in relatives of individuals with schizophrenia who are at high risk (HR) for genetic reasons. Twenty-two HR subjects, 31 patients with schizophrenia and 51 control subjects underwent DTI. We compared FA between the three groups in the cingulum cingulate gyri, the uncinate and the arcuate fasciculi and the anterior limb of the internal capsules (ALIC). A voxel-based analysis showed lower FA in patients with schizophrenia compared to controls in left and right uncinate (p<0.03), the left arcuate (p<0.03) and left and right ALIC (p<0.01). Using an automatic region-of-interest analysis, less sensitive to potential misregistration errors, produced essentially the same results, as well as reduced FA of the ALIC in the HR group compared to controls (p<0.05). This study replicates previous findings showing lower FA in frontotemporal white matter fibers of schizophrenia patients. We also found reduced FA in the ALIC of both patients and subjects at high risk of schizophrenia when compared to controls. This may be a possible indicator of the higher vulnerability of relatives to develop the disorder.

Introduction: Medication is a necessary part of treatment for severe psychiatric illnesses such as schizophrenia and nonadherence to prescribed medication is one of the most important public health issues in psychiatry today. The devastating consequences of nonadherence have motivated the development of novel therapeutic strategies, including a new long-term implantable medication delivery system., Methods: The current study assesses attitudes towards implantable medication in psychiatric patients and their family members. Patients included in the study had diagnoses of Schizophrenia, Schizoaffective Disorder, Mood or Anxiety related disorders., Results: 49.62% of patients and 74.47% of family members endorse support for implantable medication., Conclusions: This study demonstrates that implants may be an acceptable alternative to oral and injectable medication for a subset of psychiatric patients and their families.

Despite evidence for diverse neuropsychological impairment in schizophrenia, verbal declarative memory has emerged as a core deficit in the disorder. Similar but less marked impairments have been demonstrated in unaffected biological relatives of patients with schizophrenia, but the nature and extent of the memory impairment in relatives compared to controls is unclear. We have conducted a systematic review and meta-analysis of the literature investigating declarative memory in unaffected biological relatives of schizophrenics and controls, with the aim of quantifying memory deficits in relatives. The standardised mean difference between groups was calculated for nine measures of declarative memory and two measures of intellectual ability, based on 21 studies of several hundred relatives of schizophrenics and controls. Unaffected relatives showed poorer performance relative to controls on all tests of memory examined. Small to moderate effect sizes, with overlapping 95% confidence intervals, were greatest on immediate (trial 1) list recall (0.65), followed by immediate (0.53) and delayed story recall (0.52). Verbal and general IQ showed smaller standardised mean differences as the latter tests, while the smallest standardised mean difference was shown on delayed visual recall (0.32). Results suggest greater deficits on tests of increasing memory load or which place demands on effective encoding processes but more studies with these tasks are needed. Investigation of sub-groups within these cohorts (e.g. age groups within or beyond the maximum age of risk) is recommended in order to identify deficits specific to the disease process.

The grey matter (GM) segments from T1 structural magnetic resonance (MR) images of the brain in subjects at high risk of schizophrenia (n=146) were compared with normal control subjects (n=36) and first episode schizophrenic subjects (n=34) using automated voxel-based morphometry (VBM). The subjects were recruited for the Edinburgh High Risk Study (EHRS) and regional brain volumes had previously been measured using a semi-automated volumetric region of interest (ROI) method of analysis. For the current report, the images were processed using a study specific template and statistically analysed using the SPM99 program. The small volume correction tool in SPM was also used to restrict the analyses to specific voxels. Reductions in the probability of grey matter (GM) density were seen bilaterally in the anterior cingulate, and as a trend in the left parahippocampal gyrus for the high-risk vs. control subjects. In contrast, first episode schizophrenia subjects had less GM than high-risk subjects in several frontal and temporal regions. These results are compatible with the findings of our previous volumetric ROI analysis.

This study reports findings of the Edinburgh High Risk Study four years after it began. This study is designed to explore the pathogenesis of schizophrenia by examining a large sample of young adults aged 16-25 years who are at enhanced risk of developing schizophrenia by having two close relatives with the disorder, and comparing them with matched controls. This paper presents comparisons of the high risk subjects, well controls and subjects with first-episode schizophrenia in terms of demographic, childhood, psychopathological, educational and employment, forensic and social work variables. High risk subjects have more psychological difficulties, poorer educational and employment attainment, and more social work contact than controls. The enhanced social work involvement related to the presence of a schizophrenic parent (especially a mother) but the other difficulties could not be attributed to that situation. Neurotic, partially held psychotic and fully held psychotic symptoms all occurred in both subjects and controls, but all were significantly more common in high risk subjects. Clinical schizophrenia has so far developed in 10 high risk subjects and in no controls. Possible confounding effects of drug or alcohol misuse were considered but were found unlikely to be important.

Various theories have been proposed to account for poor insight in schizophrenia. This study examined the relationships between insight, mood, schizophrenic symptoms and cognitive functioning. The relationship between longitudinal changes in insight and changes in symptoms and mood was also investigated. One-hundred patients with DSM-III-R schizophrenia, recently recovered from a relapse of their illness, were rated on the Insight and Treatment Attitudes Questionnaire (ITAQ), the Positive and Negative Syndrome Scale (PANSS), the Montgomery Asberg Depression Rating Scale (MADRS), the Rivermead Behavioural Memory Test and tests of current and premorbid IQ. A random sample of 53 were then given an educational package (video and booklets) designed to improve their insight. Follow-up ratings on the ITAQ, PANSS and MADRS were subsequently obtained. At baseline, better insight was significantly correlated with lower mood and fewer positive symptoms. It was not related to cognitive functioning. Improvement in insight at follow up was related to worsening of mood, but not to change in positive symptoms. The results are consistent with the concept that poor insight, at least in part, results from the psychotic disease process itself. In addition, they suggest that poor insight may protect against depression in the early stages of recovery from schizophrenia.