Proton Magnetic Resonance Spectroscopy and Illness Stage in Schizophrenia-A Systematic Review and Meta-Analysis

Background It is not known whether regional brain N-acetyl aspartate (NAA) changes in the progression from prodrome to chronic schizophrenia. We used effect size meta-analysis to determine which brain regions show the most robust reductions in NAA first episode and chronic schizophrenia as measured by proton magnetic resonance spectroscopy and to determine whether these changes are present in individuals at high risk of developing schizophrenia. Methods We identified 131 articles, of which 97 met inclusion criteria. Data were separated by stage of illness (at risk, first episode schizophrenia, chronic schizophrenia) and by brain region. For each region, mean and SD of the NAA measure was extracted. Results Significant reductions in NAA levels were found in frontal lobe, temporal lobe, and thalamus in both patient groups (effect size > .3; p < .01). In individuals at high risk of schizophrenia (of whom approximately 20% would be expected to undergo transition to psychosis), significant NAA reductions were present in thalamus (effect size = .78; p < .05), with reductions at trend level only in temporal lobe (effect size = .32; p < .1), and no reductions in frontal lobe (effect size = .05; p = .5). Conclusions These data suggest that schizophrenia is associated with loss of neuronal integrity in frontal and temporal cortices and in the thalamus and suggest that these changes in the frontal and temporal lobe might occur in the transition between the at-risk phase and the first episode

Glutamate, N-acetyl aspartate and psychotic symptoms in chronic ketamine users

Rationale: Ketamine, a non-competitive NMDA receptor antagonist, induces acute effects resembling the positive, negative and cognitive symptoms of schizophrenia. Chronic use has been suggested to lead to persistent schizophrenia-like neurobiological changes. Objectives: This study aims to test the hypothesis that chronic ketamine users have changes in brain neurochemistry and increased subthreshold psychotic symptoms compared to matched poly-drug users. Methods: Fifteen ketamine users and 13 poly-drug users were included in the study. Psychopathology was assessed using the Comprehensive Assessment of At-Risk Mental State. Creatine-scaled glutamate (Glu/Cr), glutamate + glutamine (Glu + Gln/Cr) and N-acetyl aspartate (NAA/Cr) were measured in three brain regions—anterior cingulate, left thalamus and left medial temporal cortex using proton magnetic resonance spectroscopy. Results: Chronic ketamine users had higher levels of subthreshold psychotic symptoms (p < 0.005, Cohen’s d = 1.48) and lower thalamic NAA/Cr (p < 0.01, d = 1.17) compared to non-users. There were no differences in medial temporal cortex or anterior cingulate NAA/Cr or in Glu/Cr or Glu + Gln/Cr in any brain region between the two groups. In chronic ketamine users, CAARMS severity of abnormal perceptions was directly correlated with anterior cingulate Glu/Cr (p < 0.05, r = 0.61—uncorrected), but NAA/Cr was not related to any measures of psychopathology. Conclusions: The finding of lower thalamic NAA/Cr in chronic ketamine users may be secondary to the effects of ketamine use compared to other drugs of abuse and resembles previous reports in individuals at genetic or clinical risk of schizophrenia

Neurodegeneration in Schizophrenia: Evidence from In Vivo

Although schizophrenia is primarily considered to be a neurodevelopmental disorder, there is a growing consensus that the disorder may also involve neurodegeneration. Recent research using non-invasive neuroimaging techniques, such as magnetic resonance imaging, suggests that some patients with schizophrenia show progressive losses of gray matter in the frontal and temporal lobes of the brain. The cellular mechanisms responsible for such gray matter losses are unknown, but have been hypothesized to involve abnormal increases in apoptosis

Neural correlates of visuospatial working memory in the ‘at-risk mental state’

Background. Impaired spatial working memory (SWM) is a robust feature of schizophrenia and has been linked to the risk of developing psychosis in people with an at-risk mental state (ARMS). We used functional magnetic resonance imaging (fMRI) to examine the neural substrate of SWM in the ARMS and in patients who had just developed schizophrenia. Method. fMRI was used to study 17 patients with an ARMS, 10 patients with a first episode of psychosis and 15 agematched healthy comparison subjects. The blood oxygen level-dependent (BOLD) response was measured while subjects performed an object–location paired-associate memory task, with experimental manipulation of mnemonic load. Results. In all groups, increasing mnemonic load was associated with activation in the medial frontal and medial posterior parietal cortex. Significant between-group differences in activation were evident in a cluster spanning the medial frontal cortex and right precuneus, with the ARMS groups showing less activation than controls but greater activation than first-episode psychosis (FEP) patients. These group differences were more evident at the most demanding levels of the task than at the easy level. In all groups, task performance improved with repetition of the conditions. However, there was a significant group difference in the response of the right precuneus across repeated trials, with an attenuation of activation in controls but increased activation in FEP and little change in the ARMS. Conclusions. Abnormal neural activity in the medial frontal cortex and posterior parietal cortex during an SWM task may be a neural correlate of increased vulnerability to psychosis

Altered resting-state connectivity in subjects at ultra-high risk for psychosis: an fMRI study

<p>Abstract</p> <p>Background</p> <p>Individuals at ultra-high risk (UHR) for psychosis have self-disturbances and deficits in social cognition and functioning. Midline default network areas, including the medial prefrontal cortex and posterior cingulate cortex, are implicated in self-referential and social cognitive tasks. Thus, the neural substrates within the default mode network (DMN) have the potential to mediate self-referential and social cognitive information processing in UHR subjects.</p> <p>Methods</p> <p>This study utilized functional magnetic resonance imaging (fMRI) to investigate resting-state DMN and task-related network (TRN) functional connectivity in 19 UHR subjects and 20 matched healthy controls. The bilateral posterior cingulate cortex was selected as a seed region, and the intrinsic organization for all subjects was reconstructed on the basis of fMRI time series correlation.</p> <p>Results</p> <p>Default mode areas included the posterior/anterior cingulate cortices, the medial prefrontal cortex, the lateral parietal cortex, and the inferior temporal region. Task-related network areas included the dorsolateral prefrontal cortex, supplementary motor area, the inferior parietal lobule, and middle temporal cortex. Compared to healthy controls, UHR subjects exhibit hyperconnectivity within the default network regions and reduced anti-correlations (or negative correlations nearer to zero) between the posterior cingulate cortex and task-related areas.</p> <p>Conclusions</p> <p>These findings suggest that abnormal resting-state network activity may be related with the clinical features of UHR subjects. Neurodevelopmental and anatomical alterations of cortical midline structure might underlie altered intrinsic networks in UHR subjects.</p

Structural Brain Alterations in Individuals at Ultra-high Risk for Psychosis: A Review of Magnetic Resonance Imaging Studies and Future Directions

Individuals at ultra-high-risk (UHR) for psychosis have become a major focus for research designed to explore markers for early detection of and clinical intervention in schizophrenia. In particular, structural magnetic resonance imaging studies in UHR individuals have provided important insight into the neurobiological basis of psychosis and have shown the brain changes associated with clinical risk factors. In this review, we describe the structural brain abnormalities in magnetic resonance images in UHR individuals. The current accumulated data demonstrate that abnormalities in the prefrontal and temporal cortex and anterior cingulate cortex occur before illness onset. These regions are compatible with the regions of structural deficits found in schizophrenia and first-episode patients. In addition, the burgeoning evidence suggests that such structural abnormalities are potential markers for the transition to psychosis. However, most findings to date are limited because they are from cross-sectional rather than longitudinal studies. Recently, researchers have emphasized neurodevelopmental considerations with respect to brain structural alterations in UHR individuals. Future studies should be conducted to characterize the differences in the brain developmental trajectory between UHR individuals and healthy controls using a longitudinal design. These new studies should contribute to early detection and management as well as provide more predictive markers of later psychosis

Understanding mechanisms related to psychosis in Motor Neurone Disease

Psychosis is a challenging feature of the syndromes of motor neurone disease (MND), frontotemporal dementia (FTD) and their overlap (FTD-MND). Clinically evident psychosis is not common, except in those with C9orf72+ expansions. However, subthreshold psychosis or pre-psychosis processes are common and provide the opportunity to study the mechanisms of psychosis in MND and FTD-MND. My aim was to identify the prevalence and the cognitive and neural correlates of psychosis, and related processes, in MND. I used a tiered cohort study approach. Tier 1 introduced screening as standard in a regional MND clinic (N=111) using the Edinburgh Cognitive and Behavioural ALS Screen and Cambridge Behavioural Inventory-Revised (CBI-R). In Tier 2, 60 patients and 30 controls underwent neuropsychological assessment, including (i) evidence-based decision-making, to quantify jumping to conclusions (JTC), (ii) attentional control and associative learning, (iii) perceptual inference, and (iv) psychiatric screening with Neuropsychiatric Inventory (NPI), Brief Psychiatric Rating Scale (BRPS), and the Comprehensive Assessment of At-Risk Mental States (CAARMS). Tier 3 included magnetic resonance imaging of 30 patients and 20 controls. Carer reports in Tier 1 indicated that 10% of patients exhibited features suggestive of psychosis and 40% exhibited behavioural change. In Tier 2, many patients manifested abnormal behaviours (CBI-R 41%; NPI showed 19%; BPRS 24%), with 12-16% showing psychosis-specific symptoms (CBI-R and NPI psychosis index scores). In the jumping to conclusions task, patients made decisions based on less evidence than controls and were insensitive to negative feedback. Carer ratings of patient behaviour correlated with performance on the jumping to conclusions task when decisions were rewarded or costs fixed. Attentional shifting and perceptual inference were normal in MND. A principal component analysis (PCA) of questionnaires revealed two component scores, reflecting distinct patients’ and carers’ perspectives. The imaging analyses focused on the correlates of jumping to conclusions and insensitivity to negative feedback, as a potential risk profile for psychosis, with exploratory analyses of the correlates of the CBI-R psychosis index, and carers’ ratings of behaviour from the PCA. Using a Freesurfer regions-of-interest approach, grey matter volume correlated inversely with CBI-R psychosis index in the caudate, amygdala, cingulate and hippocampus. Using tract-based spatial statistics, increased mean diffusivity (MD) of diffusion weighted imaging correlated with the CBI-R psychosis responses in inferior longitudinal and uncinate fasciculi. Cost sensitivity in the JTC task correlated with cingulate and cerebellar grey matter volumes. White matter correlates of cost sensitivity included reduced FA with increasing cost sensitivity in white matter connecting the inferior frontal lobe in controls and patients. Although overt psychosis is uncommon in MND, many patients displayed abnormal behaviour or cognitive symptoms, including suboptimal reasoning biases and inferential impulsivity. Degeneration of cerebellar, cingulate and striatal grey matter, and adjacent major white matter tracts, may underlie these cognitive impairments and together represent a vulnerability to develop psychosis. Compromised reasoning and inference have implications for clinical management, including decisions around treatment options and management of well-being in MND.This research was funded by Alzheimer’s Research UK Studentship (PhD2017-26); Medical Research Council (SUAG 051/ G101400); and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care

Executive Dysfunction in MCI: Subtype or Early Symptom

Mild cognitive impairment (MCI) may take several forms, and amnestic MCI (aMCI) has been recognized as an early stage of Alzheimer's Disease (AD). Impairment in executive functions including attention (eMCI) may be indicative of several neurodegenerative conditions. Executive impairment is frequently found in aMCI, it is significant for prognosis, and patients with eMCI may go on to develop AD. Recent studies have found changes in white matter integrity in patients with eMCI to be more sensitive than measures of cortical atrophy. Studies of genetic high-risk groups using sensitive cognitive neuroscience paradigms indicate that changes in executive function may be a cognitive marker useful for tracking development in an AD pathophysiological process

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes that present significant differences in various brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal MRI to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer disease, schizophrenia, major depressive disorder, autism spectrum disorder, multiple sclerosis, as well as their potential in transdiagnostic settings. Subsequently, we summarize relevant machine learning methodologies and discuss an emerging paradigm which we call dimensional neuroimaging endophenotype (DNE). DNE dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into a low dimensional yet informative, quantitative brain phenotypic representation, serving as a robust intermediate phenotype (i.e., endophenotype) largely reflecting underlying genetics and etiology. Finally, we discuss the potential clinical implications of the current findings and envision future research avenues