Functional neuroimaging in subjects at high genetic risk of schizophrenia

Schizophrenia is an incapacitating psychiatric disorder characterized by hallucinations and delusions with a lifetime risk of around 1% worldwide. It is a highly heritable disorder which generally becomes manifest in early adult life. The established condition has been associated with structural and functional brain abnormalities, principally in prefrontal and temporal lobes, but it is unclear whether such abnormalities are related to inherited vulnerability, medication effects, or the presence of symptoms. Furthermore, the mechanisms by which the pre-morbid state switches into florid psychosis are unknown. The Edinburgh High Risk Study is designed to address these issues. The first phase (1994-1999) employed repeated clinical, neuropsychological assessments and structural imaging. In the current phase (1999-2004) functional magnetic resonance imaging (fMRI) has been added to the tests used previously.As part of the Edinburgh High Risk Study, this study used a covert verbal initiation fMRI task (the Hayling Sentence Completion Test) known to elicit frontal and temporal activation, to examine a large number of young participants at high risk of developing schizophrenia for genetic reasons, in comparison with a matched group of healthy controls. Subjects were scanned at baseline, and after approximately one year. At the time of the baseline scan none of the participants met criteria for any psychiatric disorder, however, a number of subjects reported isolated psychotic symptoms on direct questioning. Over the course of the entire study (1994-2004), 21 individuals developed schizophrenia according to standard diagnostic criteria. Four of these subjects made the transition over the course of the current study (1999-2004), i.e. subsequent to the baseline functional scanThere were three main aims of the current study (i) to use fMRI to identify the neural correlates of state and trait effects in high risk individuals, (ii) to determine ifit is possible to distinguish those who subsequently become ill from those who remain well using functional imaging, and (iii) to determine if patterns of brain activity change with the transition to illness, or vary with changes in symptomatic status of these individuals.Regarding the first aim, group differences of apparent genetic origin were found in prefrontal, thalamic, cerebellar regions, and differences in activation in those with symptoms were found in the parietal lobe. Functional connectivity analysis examining interactions between these regions also indicated similar abnormalities. These results may therefore reflect inherited deficits, and the earliest changes associated with the psychotic state, respectively. Although only a small number of subjects became ill over the course of the current study («=4), initial findings suggested abnormalities in medial prefrontal and medial temporal regions (with an indication of parietal lobe dysfunction) were able to distinguish those who later became ill versus those that remained well. Finally, there were also indications of changes in activation patterns over time in a subgroup of subjects with varying symptomatic status.To conclude, these results are consistent with previous findings in the Edinburgh High Risk Study - what is inherited by the high risk individuals is a state of heightened vulnerability manifesting, in the case of functional imaging, as abnormalities in activation and/or connectivity in preffontal-thalamiccerebellar and prefrontal-parietal regions. These finding also suggest that there are additional differences seen in those with psychotic symptoms, and to some extent in those who subsequently go on to develop the disorder. These results are not confounded by anti-psychotic medication since all subjects were anti-psychotic naive at the time of assessment. The lack of findings traditionally associated with the established illness (dorsolateral prefrontal cortex and lateral temporal lobe) indicate these may be specifically associated with the established state, or when performance differences become manifest. Overall therefore these findings reveal information regarding the pathophysiology of the state of vulnerability to the disorder and about the mechanisms involved in the development of schizophrenia or schizophrenic symptomatology

Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia

<p>Abstract</p> <p>Background:</p> <p>It has been proposed that different types of psychopathology in schizophrenia may reflect distinguishable pathological processes. In the current study we aimed to address such associations in the absence of confounders such as medication and disease chronicity by examining specific relationships between fMRI activation and individual symptom severity scores in un-medicated subjects at high genetic risk of schizophrenia.</p> <p>Methods:</p> <p>Associations were examined across two functional imaging paradigms: the Hayling sentence completion task, and an encoding/retrieval task, comprising encoding (at word classification) and retrieval (old word/new word judgement). Symptom severity was assessed using the positive and negative syndrome scale (PANSS). Items examined were hallucinations, delusions, and suspiciousness/persecution.</p> <p>Results:</p> <p>Associations were seen in the anterior middle temporal gyrus in relation to hallucination scores during the sentence completion task, and in the medial temporal lobe in association with suspiciousness/persecution scores in the encoding/retrieval task. Cerebellar activation was associated with delusions and suspiciousness/persecution scores across both tasks with differing patterns of laterality.</p> <p>Conclusion:</p> <p>These results support a role for the lateral temporal cortex in hallucinations and medial temporal lobe in positive psychotic symptoms. They also highlight the potential role of the cerebellum in the formation of delusions. That the current results are seen in un-medicated high risk subjects indicates these associations are not specific to the established illness and are not related to medication effects.</p

Cognitive biases predict symptoms of depression, anxiety and wellbeing above and beyond neuroticism in adolescence

Adolescence represents a period of vulnerability to affective disorders. Neuroticism is considered a heritable risk factor for depression, but is not directly amenable to intervention. Therefore, it is important to identify the contributions of modifiable risk factors. Negative cognitive biases are implicated in the onset and maintenance of affective disorders in adults, and may represent modifiable risk factors in adolescence. This study sought to assess to what extent cognitive biases are able to predict depression, anxiety and wellbeing beyond that of neuroticism in adolescents. Adolescents (N = 99), recruited from Scottish secondary schools (54.5% female; mean age = 14.7), ensured a sample representing the breadth of the mental health spectrum. In line with prevalence estimates, 18% of this sample demonstrated clinical levels of depression symptoms. Cognitive biases of autobiographical memory, self-referential memory, ambiguous scenarios interpretation, facial expression recognition, rumination and dysfunctional attitudes were assessed. Depression, anxiety, and wellbeing were indexed using the Mood and Feelings Questionnaire, Spence Children's Anxiety Scale and the BBC Subjective Wellbeing Scale. Regression analyses demonstrated neuroticism to significantly predict depression, anxiety and wellbeing. The addition of cognitive biases resulted in a significant increase of explained variance with final models explaining just over 50% of variances of depression, anxiety and wellbeing. These findings demonstrate that cognitive biases explain mental health symptoms over and above that of neuroticism. Depressive symptomology was particularly related to self-referential memory bias, while anxiety was predicted by interpretive bias. The key clinical implication is that targeting specific biases based on diagnostic features may be of particular benefit in alleviating distress and promoting wellbeing

Pipeline comparisons of convolutional neural networks for structural connectomes: predicting sex across 3,152 participants

With several initiatives well underway towards amassing large and high-quality population-based neuroimaging datasets, deep learning is set to push the boundaries of what is possible in classification and prediction in neuroimaging studies. This includes those that derive increasingly popular structural connectomes, which map out the connections (and their relative strengths) between brain regions. Here, we test different Convolutional Neural Network (CNN) models in a benchmark sex prediction task in a large sample of N=3,152 structural connectomes acquired from the UK Biobank, and compare results across different connectome processing choices. The best results (76.5% test accuracy) were achieved using Fractional Anisotropy (FA) weighted connectomes, without sparsification, and with a simple weight normalisation through division by the maximum FA value. We also confirm that for structural connectomes, a Graph CNN approach, the recently proposed BrainNetCNN, outperforms an image-based CNN

Are working memory and glutamate concentrations involved in early-life stress and severity of psychosis?

Objective Occurrences of early‐life stress (ELS) are associated with the severity of psychotic symptoms and working memory (WM) deficits in patients with psychosis (PSY). This study investigated potential mediation roles of WM behavioral performance and glutamate concentrations in prefrontal brain regions on the association between ELS and psychotic symptom severity in PSY. Method Forty‐seven patients with PSY (established schizophrenia, n = 30; bipolar disorder, n = 17) completed measures of psychotic symptom severity. In addition, data on ELS and WM performance were collected in both patients with PSY and healthy controls (HC; n = 41). Resting‐state glutamate concentrations in the bilateral dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) were also assessed with proton magnetic resonance spectroscopy for both PSY and HC groups. t tests, analyses of variance, and regression analyses were utilized. Results Participants with PSY reported significantly more ELS occurrences and showed poorer WM performance than HC. Furthermore, individuals with PSY displayed lower glutamate concentrations in the left DLPFC than HC. Neither ELS nor WM performance were predictive of severity of psychotic symptoms in participants with PSY. However, we found a significant negative correlation between glutamate concentrations in the left DLPFC and ELS occurrence in HC only. Conclusion In individuals with PSY, the current study found no evidence that the association between ELS and psychotic symptoms is mediated by WM performance or prefrontal glutamate concentrations. In HC, the association between ELS experience and glutamate concentrations may indicate a neurometabolite effect of ELS that is independent of an illness effect in psychosis

Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia

BACKGROUND: Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms. METHODS: Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T(1)-weighted structural neuroimaging data from 84 patients (aged 16–35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16–37 years). Multidomain cognitive data from the patient sample were submitted to Heterogeneity through Discriminative Analysis (HYDRA) to identify cognitive clusters. RESULTS: HYDRA classified patients into a cognitively impaired cluster (n = 69) and a cognitively spared cluster (n = 15). Compared to healthy individuals, G-brainAGE was significantly higher in the cognitively impaired cluster (+11.08 years) who also showed widespread elevation in L-brainAGE, with the highest deviance observed in frontal and temporal regions. The cognitively spared cluster showed a moderate increase in G-brainAGE (+8.94 years), and higher L-brainAGE localized in the anterior cingulate cortex. Psychotic symptom severity in both clusters showed a positive but non-significant association with G-brainAGE. DISCUSSION: Accelerated aging in schizophrenia can be detected at the early disease stages and appears more closely associated with cognitive dysfunction rather than clinical symptoms. Future studies replicating our findings in multi-site cohorts with larger numbers of participants are warranted