Abstract Background The dysconnectivity hypothesis suggests that psychotic illnesses arise not from regionally specific focal pathophysiology, but rather from impaired neuroanatomical integration ...across networks of brain regions. Decreased white matter organization has been hypothesized to be a feature of psychotic illnesses in general, which is supported by meta-analyses of DTI studies in bipolar disorder and schizophrenia. Although many diffusion MRI studies investigate bipolar disorder and schizophrenia alone, relatively few studies directly compare structural features in these psychotic illnesses. Recently, the application of graph theory analyses to DTI data has supported the dysconnectivity hypothesis in bipolar disorder and schizophrenia, employing topological properties to assess neuroanatomical dysconnectivity. Methods This selective review evaluates white matter alterations using Diffusion Tensor Imaging (DTI) in bipolar disorder and schizophrenia, with a focus upon direct comparison DTI studies in both psychotic illnesses. We then expand in more detail on the development of network analyses and the application of these techniques in bipolar disorder and schizophrenia. Results Converging evidence indicates that frontal connectivity alterations are common to both disorders, with prominent fronto-temporal deficits identified in schizophrenia and inter-hemispheric and limbic alterations reported in bipolar disorder. Limitations In bipolar disorder, most connectome reports use cortical maps alone, which given the importance of the limbic system in emotional regulation may limit the scope of network approaches in mood disorders. Conclusions Further direct connectivity comparisons between these psychotic illnesses may assist in unravelling the neuroanatomical deviations underpinning the overlapping features of psychosis and cognitive impairment, and the more diagnostically distinctive features of affective disturbance in bipolar disorder and deficit syndrome in schizophrenia.
Brain disorders comprise several psychiatric and neurological disorders which can be characterized by impaired cognition, mood alteration, psychosis, depressive episodes, and neurodegeneration. ...Clinical diagnoses primarily rely on a combination of life history information and questionnaires, with a distinct lack of discriminative biomarkers in use for psychiatric disorders. Symptoms across brain conditions are associated with functional alterations of cognitive and emotional processes, which can correlate with anatomical variation; structural magnetic resonance imaging (MRI) data of the brain are therefore an important focus of research, particularly for predictive modelling. With the advent of large MRI data consortia (such as the Alzheimer's Disease Neuroimaging Initiative) facilitating a greater number of MRI‐based classification studies, convolutional neural networks (CNNs)—deep learning models well suited to image processing tasks—have become increasingly popular for research into brain conditions. This has resulted in a myriad of studies reporting impressive predictive performances, demonstrating the potential clinical value of deep learning systems. However, methodologies can vary widely across studies, making them difficult to compare and/or reproduce, potentially limiting their clinical application. Here, we conduct a qualitative systematic literature review of 55 studies carrying out CNN‐based predictive modelling of brain disorders using MRI data and evaluate them based on three principles—modelling practices, transparency, and interpretability. We propose several recommendations to enhance the potential for the integration of CNNs into clinical care.
Predictive modelling of brain disorders using convolutional neural networks applied to structural neuroimaging data has become popular in recent years. We systematically review 55 papers in the field and evaluate their modelling practices, transparency, and considerations of interpretability.
Schizophrenia is a chronic debilitating neuropsychiatric disorder with a complex genetic contribution. Although multiple genetic, immunological and environmental factors are known to contribute to ...schizophrenia susceptibility, the underlying neurobiological mechanism(s) is yet to be established. The immune system dysfunction theory of schizophrenia is experiencing a period of renewal due to a growth in evidence implicating components of the immune system in brain function and human behavior. Current evidence indicates that certain immune molecules such as Major Histocompatibility Complex (MHC) and cytokines, the key regulators of immunity and inflammation are directly involved in the neurobiological processes related to neurodevelopment, neuronal plasticity, learning, memory and behavior. However, the strongest support in favor of the immune hypothesis has recently emerged from on-going genome wide association studies advocating MHC region variants as major determinants of one's risk for developing schizophrenia. Further identification of the interacting partners and receptors of MHC molecules in the brain and their role in down-stream signaling pathways of neurotransmission have implicated these molecules as potential schizophrenia risk factors. More recently, combined brain imaging and genetic studies have revealed a relationship between genetic variations within the MHC region and neuromorphometric changes during schizophrenia. Furthermore, MHC molecules play a significant role in the immune-infective and neurodevelopmental pathogenetic pathways, currently hypothesized to contribute to the pathophysiology of schizophrenia. Herein, we review the immunological, genetic and expression studies assessing the role of the MHC in conferring risk for developing schizophrenia, we summarize and discuss the possible mechanisms involved, making note of the challenges to, and future directions of, immunogenetic research in schizophrenia.
► MHC molecules regulate immunity and core functions of the brain. ► Infection and MHC might affect schizophrenia by inducing autoimmunity or inflammation. ► MHC variants are associated with various schizophrenia endophenotypes. ► MHC might increase the risk of schizophrenia by affecting neurodevelopment. ► MHC possibly enhances the risk of schizophrenia by disrupting synaptic transmission.
Background White matter microstructural changes detected using diffusion tensor imaging have been reported in bipolar disorder. However, findings are heterogeneous, which may be related to the use of ...analysis techniques that cannot adequately model crossing fibers in the brain. We therefore sought to identify altered diffusion anisotropy and diffusivity changes using an improved high angular resolution fiber-tracking technique. Methods Diffusion magnetic resonance imaging data was obtained from 35 prospectively confirmed euthymic bipolar disorder type 1 patients (age 22–59) and 43 control subjects (age 22–59) drawn from a sample of 120 age- and gender-matched demographically similar case-control pairs. Tractography using a constrained spherical deconvolution approach to account for crossing fibers was implemented. Changes in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity between patient and control groups in subdivisions of the corpus callosum, cingulum, and fornix were measured as indicators of trait differences in white matter microstructural organization in bipolar disorder. Results Patients had significantly reduced fractional anisotropy and increased mean diffusivity and radial diffusivity in all divisions of the corpus callosum, left fornix, and subgenual cingulum compared with control subjects. Axial diffusivity was increased in the fornix bilaterally and right dorsal-anterior cingulum. Conclusions By using an improved fiber-tracking method in a clinically homogeneous population, we were able to localize trait diffusivity changes to specific subdivisions of limbic fiber pathways, including the fornix. Our findings extend previous reports of altered limbic system microstructural disorganization as a trait feature of bipolar disorder.
Introduction
Alcohol use in bipolar disorder (BD) is associated with mood lability and negative illness trajectory, while also impacting functional networks related to emotion, cognition, and ...introspection. The adverse impact of alcohol use in BD may be explained by its additive effects on these networks, thereby contributing to a poorer clinical outcome.
Methods
Forty BD‐I (DSM‐IV‐TR) and 46 psychiatrically healthy controls underwent T1 and resting state functional MRI scanning and the Alcohol Use Disorders Identification Test‐Consumption (AUDIT‐C) to assess alcohol use. Functional images were decomposed using spatial independent component analysis into 14 resting state networks (RSN), which were examined for effect of alcohol use and diagnosis‐by‐alcohol use accounting for age, sex, and diagnosis.
Results
Despite the groups consuming similar amounts of alcohol (BD: mean score ± SD 3.63 ± 3; HC 4.72 ± 3, U = 713, p = .07), for BD participants, greater alcohol use was associated with increased connectivity of the paracingulate gyrus within a default mode network (DMN) and reduced connectivity within an executive control network (ECN) relative to controls. Independently, greater alcohol use was associated with increased connectivity within an ECN and reduced connectivity within a DMN. A diagnosis of BD was associated with increased connectivity of a DMN and reduced connectivity of an ECN.
Conclusion
Affective symptomatology in BD is suggested to arise from the aberrant functionality of networks subserving emotive, cognitive, and introspective processes. Taken together, our results suggest that during euthymic periods, alcohol can contribute to the weakening of emotional regulation and response, potentially explaining the increased lability of mood and vulnerability to relapse within the disorder.
We find that having a diagnosis of BD, but moreover having a diagnosis of BD and consuming alcohol is significantly associated with increased connectivity within default mode networks and reduced spectral power at 0.05–0.1 Hz in an executive control network. These results suggest that introspective and cognitive networks are impacted by alcohol, over and above BD alone.
Despite evidence that clozapine may be neuroprotective, there are few longitudinal magnetic resonance imaging (MRI) studies that have specifically explored an association between commencement of ...clozapine treatment for schizophrenia and changes in regional brain volume or cortical thickness. A total of 33 patients with treatment-resistant schizophrenia and 31 healthy controls matched for age and gender underwent structural MRI brain scans at baseline and 6-9 months after commencing clozapine. MRI images were analyzed using SIENA (Structural Image Evaluation, using Normalization, of Atrophy) and FreeSurfer to investigate changes over time in brain volume and cortical thickness respectively. Significantly greater reductions in volume were detected in the right and left medial prefrontal cortex and in the periventricular area in the patient group regardless of treatment response. Widespread further cortical thinning was observed in patients compared with healthy controls. The majority of patients improved symptomatically and functionally over the study period, and patients who improved were more likely to have less cortical thinning of the left medial frontal cortex and the right middle temporal cortex. These findings demonstrate on-going reductions in brain volume and progressive cortical thinning in patients with schizophrenia who are switched to clozapine treatment. It is possible that this gray matter loss reflects a progressive disease process irrespective of medication use or that it is contributed to by switching to clozapine treatment. The clinical improvement of most patients indicates that antipsychotic-related gray matter volume loss may not necessarily be harmful or reflect neurotoxicity.
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.
The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. This study investigated subcortical morphometric changes 6 months after switching ...treatment to clozapine in patients with treatment-resistant schizophrenia compared with healthy volunteers, and the relationships between longitudinal volume changes and clinical variables. In total, 1.5T MRI images were acquired at baseline before commencing clozapine and again after 6 months of treatment for 33 patients with treatment-resistant schizophrenia and 31 controls, and processed using the longitudinal pipeline of Freesurfer v.5.3.0. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Whereas no significant subcortical volume differences were found between patients and controls at baseline (F(8,52) = 1.79; p = 0.101), there was a significant interaction between time, group and structure (F(7,143) = 52.54; p < 0.001). Corrected post-hoc analyses demonstrated that patients had significant enlargement of lateral ventricles (F(1,59) = 48.89; p < 0.001) and reduction of thalamus (F(1,59) = 34.85; p < 0.001), caudate (F(1,59) = 59.35; p < 0.001), putamen (F(1,59) = 87.20; p < 0.001) and hippocampus (F(1,59) = 14.49; p < 0.001) volumes. Thalamus and putamen volume reduction was associated with improvement in PANSS (r = 0.42; p = 0.021, r = 0.39; p = 0.033), SANS (r = 0.36; p = 0.049, r = 0.40; p = 0.027) and GAF (r = -0.39; p = 0.038, r = -0.42; p = 0.024) scores. Reduced thalamic volume over time was associated with increased serum clozapine level at follow-up (r = -0.44; p = 0.010). Patients with treatment-resistant schizophrenia display progressive subcortical volume deficits after switching to clozapine despite experiencing symptomatic improvement. Thalamo-striatal progressive volumetric deficit associated with symptomatic improvement after clozapine exposure may reflect an adaptive response related to improved outcome rather than a harmful process.
Background Studies have demonstrated neuropsychological deficits across a variety of cognitive domains in depression. Few studies have directly compared depressed subjects with major depressive ...disorder (MDD) and bipolar disorder (BD), and many are confounded by medication status across subjects. In this study, we compared the performance of unmedicated currently depressed MDD and BD groups on a battery of neuropsychological tests that included measures of risk taking and reflection impulsivity. Methods Twenty-two MDD, seventeen BDII, and 25 healthy control subjects (HC), matched for age and IQ, were assessed on a battery of neuropsychological tests. Results The depressed groups showed comparable ratings of depression severity and age of illness onset. The MDD group was impaired on tests of spatial working memory and attentional shifting, sampled less information on a test of reflection impulsivity, and was oversensitive to loss trials on a decision-making test. The BDII subjects were generally intact and did not differ significantly from control subjects on any test. Conclusions These data indicate differing profiles of cognitive impairment in unmedicated depressed MDD versus BDII subjects. Moderately depressed BDII subjects displayed relatively intact cognitive function, whereas MDD subjects demonstrated a broader range of executive impairments. These cognitive deficits in depression were not attributable to current medication status.
Current treatment options for the management of depressive episodes in bipolar disorder are often sub-optimal, with some treatments either noted to be only partially effective or to require long ...durations of treatment prior to a therapeutic response. Therefore, pharmaco-therapeutic options that reduce depressive symptoms in a more rapid manner might provide a viable therapeutic option for some people. Intravenous (IV) scopolamine, a pan muscarinic antagonist, has been demonstrated in a number of studies to confer a rapid antidepressant effect, albeit no study to date has exclusively evaluated its potential therapeutic effect in a cohort consisting solely of individuals with bipolar disorder.
Individuals with bipolar disorder who are currently experiencing a depressive episode of at least moderate severity will be included in this study. Eligible participants will undergo a screening and placebo-run in visit and will be randomised at visit 3 to the treatment or placebo group. Participants will receive the three blinded infusions over the course of 2 weeks, with two subsequent follow-up visits, 1 and 3 weeks after the last infusion visit. The total duration of the study will be approximately 6 weeks. Patients will continue their regular treatment regime in addition to study medication. Objective and subjective mood questionnaires, cognitive assessments and other psychometric instruments will be administered and recorded.
To our knowledge, this is the first study to investigate the antidepressant effects of IV scopolamine in an exclusively bipolar disorder cohort. Trial findings will contribute to the evidence base regarding the cholinergic hypothesis of mood disorders and specifically might result in an additional safe therapeutic option for the management of depressive episodes in bipolar disorder.
ClinicalTrials.gov NCT04211961 . December 26, 2019. EudraCT Number 2017-003112-39.
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