Multimodal Brain Changes in First-Episode Mania: A Voxel-Based Morphometry, Functional Magnetic Resonance Imaging, and Connectivity Study

Background: Brain structural and functional changes in bipolar disorder (BD) are well-established findings, but it is uncertain whether these changes are already present in first episode mania (FEM). Methods: We compared 31 FEM subjects, with 31 healthy individuals matched for age, sex, and premorbid IQ. Whole-brain voxel-wise morphometry, functional magnetic resonance imaging during the n-back task, and a functional connectivity analysis were performed. Results: There were no volumetric differences between the 2 groups. During the 2-back task, FEM patients did not perform differently from controls and activated similar regions, but they showed less deactivation in the ventromedial prefrontal cortex (vmPFC), the anterior hub of the default mode network (DMN). They showed preserved functional connectivity between the vmPFC and other regions of the DMN, but increased connectivity with the superior frontal gyrus. Conclusions: The absence of volumetric changes in FEM patients suggests that these changes could be related to progression of the illness. On the other hand, the failure of deactivation of the anterior hub of the DMN is present from the onset of the illness and may represent a core pathophysiological feature of BD

Magnetic and structural characterization of thiol capped ferromagnetic Ag nanoparticles

Dodecanethiol capped Ag nanoparticles (NPs) have been independently synthesized by the well-known Brust method under the same physical-chemical conditions. The obtained NP present similar sizes ( ∼ 2 nm) but different magnetic behaviors. The extended x-ray absorption fine structure analyses at the K-edge of Ag did not reveal any noticeable structural nor topological differences among the samples. In clear contrast with the structure provided for thiol capped ferromagnetic Au NPs, the analysis also brings out the existence of Ag–S bonds in a diffuse region surrounding a reduced Ag core where the magnetism of the Ag NPs would be located. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Hypercholesterolemia and 27-Hydroxycholesterol Increase S100A8 and RAGE Expression in the Brain: a Link Between Cholesterol, Alarmins, and Neurodegeneration

Alterations in cholesterol metabolism in the brain have a major role in the physiology of Alzheimer’s disease (AD). Oxysterols are cholesterol metabolites with multiple implications in memory functions and in neurodegeneration. Previous studies have shown detrimental effects of cholesterol metabolites in neurons, but its effect in glial cells is unknown. We used a high-fat/high-cholesterol diet in mice to study the effects of hypercholesterolemia over the alarmin S100A8 cascade in the hippocampus. Using CYP27Tg, a transgenic mouse model, we show that the hypercholesterolemia influence on the brain is mediated by the excess of 27-hydroxycholesterol (27-OH), a cholesterol metabolite. We also employed an acute model of 27-OH intraventricular injection in the brain to study RAGE and S100A8 response. We used primary cultures of neurons and astrocytes to study the effect of high levels of 27-OH over the S100A8 alarmin cascade. We report that a high-fat/high-cholesterol diet leads to an increase in S100A8 production in the brain. In CYP27Tg, we report an increase of S100A8 and its receptor RAGE in the hippocampus under elevated 27-OH in the brain. Using siRNA, we found that 27-OH upregulation of RAGE in astrocytes and neurons is mediated by the nuclear receptor RXRγ. Silencing RXRγ in neurons prevented 27-OH-mediated upregulation of RAGE. These results show that S100A8 alarmin and RAGE respond to high levels of 27-OH in the brain in both neurons and astrocytes through RXRγ. Our study supports the notion that 27-OH mediates detrimental effects of hypercholesterolemia to the brain via alarmin signaling.Open access funding provided by Karolinska Institute. This research was supported by the following Swedish foundations: Swedish Brain Power, the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, Strategic Neuroscience Program, Margaretha af Ugglas Foundation, Gun och Bertil Stohnes Stiftelse, Karolinska Institutet fund for geriatric research, Stiftelsen Gamla Tjänarinnor, Demensfonden,Lindhés Advokatbyrå, Hjärnfonden, and Alzheimerfonden. R. L.-V. was fnancially supported by Mexico’s National Council for Science and Technology (CONACYT) CVU, 209252, and by Olle Enqvist Foundation grant no. 2014/778. Ramon Areces Foundation, Spain, supported E. P., EMBO Long-Term Fellowship (ALTF 696–2013), the SSMF postdoctoral fellowship, and Juan de la Cierva-Incorporación. (IJCI-2016–27,658) supported P. M.-S

Brain functional abnormality in schizo-affective disorder: an fMRI study.

Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction

Alzheimer's disease biomarker profiling in a memory clinic cohort without common comorbidities

Alzheimer's disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolaemia and diabetes are known contributors to disease progression. However, less is known about their mechanistic contribution to Alzheimer's pathology and neurodegeneration. The aim of this study was to investigate the relationship of several biomarkers related to risk mechanisms in Alzheimer's disease with the well-established Alzheimer's disease markers in a memory clinic population without common comorbidities. We investigated 13 molecular markers representing key mechanisms underlying Alzheimer's disease pathogenesis in CSF from memory clinic patients without diagnosed hypertension, hypercholesterolaemia or diabetes nor other neurodegenerative disorders. An analysis of covariance was used to compare biomarker levels between clinical groups. Associations were analysed by linear regression. Two-step cluster analysis was used to determine patient clusters. Two key markers were analysed by immunofluorescence staining in the hippocampus of non-demented control and Alzheimer's disease individuals. CSF samples from a total of 90 participants were included in this study: 30 from patients with subjective cognitive decline (age 62.4 ± 4.38, female 60%), 30 with mild cognitive impairment (age 65.6 ± 7.48, female 50%) and 30 with Alzheimer's disease (age 68.2 ± 7.86, female 50%). Angiotensinogen, thioredoxin-1 and interleukin-15 had the most prominent associations with Alzheimer's disease pathology, synaptic and axonal damage markers. Synaptosomal-associated protein 25 kDa and neurofilament light chain were increased in mild cognitive impairment and Alzheimer's disease patients. Grouping biomarkers by biological function showed that inflammatory and survival components were associated with Alzheimer's disease pathology, synaptic dysfunction and axonal damage. Moreover, a vascular/metabolic component was associated with synaptic dysfunction. In the data-driven analysis, two patient clusters were identified: Cluster 1 had increased CSF markers of oxidative stress, vascular pathology and neuroinflammation and was characterized by elevated synaptic and axonal damage, compared with Cluster 2. Clinical groups were evenly distributed between the clusters. An analysis of post-mortem hippocampal tissue showed that compared with non-demented controls, angiotensinogen staining was higher in Alzheimer's disease and co-localized with phosphorylated-tau. The identification of biomarker-driven endophenotypes in cognitive disorder patients further highlights the biological heterogeneity of Alzheimer's disease and the importance of tailored prevention and treatment strategies

Serum Thioredoxin-80 is associated with age, ApoE4, and neuropathological biomarkers in Alzheimer's disease: a potential early sign of AD

Background: Thioredoxin-80 (Trx80) is a cleavage product from the redox-active protein Thioredoxin-1 and has been previously described as a pro-inflammatory cytokine secreted by immune cells. Previous studies in our group reported that Trx80 levels are depleted in Alzheimer's disease (AD) brains. However, no studies so far have investigated peripheral Trx80 levels in the context of AD pathology and whether could be associated with the main known AD risk factors and biomarkers.Methods: Trx80 was measured in serum samples from participants from two different cohorts: the observational memory clinic biobank (GEDOC) (N = 99) with AD CSF biomarker data was available and the population-based lifestyle multidomain intervention trial Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (N = 47), with neuroimaging data and blood markers of inflammation available. The GEDOC cohort consists of participants diagnosed with subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD, whereas the FINGER participants are older adults at-risk of dementia, but without substantial cognitive impairment. One-way ANOVA and multiple comparison tests were used to assess the levels of Trx80 between groups. Linear regression models were used to explore associations of Trx80 with cognition, AD CSF biomarkers (Aβ42, t-tau, p-tau and p-tau/t-tau ratio), inflammatory cytokines, and neuroimaging markers.Results: In the GEDOC cohort, Trx80 was associated to p-tau/t-tau ratio in the MCI group. In the FINGER cohort, serum Trx80 levels correlated with lower hippocampal volume and higher pro-inflammatory cytokine levels. In both GEDOC and FINGER cohorts, ApoE4 carriers had significantly higher serum Trx80 levels compared to non-ApoE4 carriers. However, Trx80 levels in the brain were further decreased in AD patients with ApoE4 genotype.Conclusion: We report that serum Trx80 levels are associated to AD disease stage as well as to several risk factors for AD such as age and ApoE4 genotype, which suggests that Trx80 could have potential as serum AD biomarker. Increased serum Trx80 and decreased brain Trx80 levels was particularly seen in ApoE4 carriers. Whether this could contribute to the mechanism by which ApoE4 show increased vulnerability to develop AD would need to be further investigated.</p

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis

A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipolar disorder, allowing the clinically relevant discrimination between both psychotic diagnostics. To assess the efficacy of sMRI data for diagnostic prediction in psychosis we objectively evaluated the discriminative power of a wide range of commonly used machine learning algorithms (ridge, lasso, elastic net and L0 norm regularized logistic regressions, a support vector classifier, regularized discriminant analysis, random forests and a Gaussian process classifier) on main sMRI features including grey and white matter voxel-based morphometry (VBM), vertex-based cortical thickness and volume, region of interest volumetric measures and wavelet-based morphometry (WBM) maps. All possible combinations of algorithms and data features were considered in pairwise classifications of matched samples of healthy controls (N = 127), patients with schizophrenia (N = 128) and patients with bipolar disorder (N = 128). Results show that the selection of feature type is important, with grey matter VBM (without data reduction) delivering the best diagnostic prediction rates (averaging over classifiers: schizophrenia vs. healthy 75%, bipolar disorder vs. healthy 63% and schizophrenia vs. bipolar disorder 62%) whereas algorithms usually yielded very similar results. Indeed, those grey matter VBM accuracy rates were not even improved by combining all feature types in a single prediction model. Further multi-class classifications considering the three groups simultaneously made evident a lack of predictive power for the bipolar group, probably due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients with schizophrenia. Finally, we provide MRIPredict (https://www.nitrc.org/projects/mripredict/), a free tool for SPM, FSL and R, to easily carry out voxelwise predictions based on VBM images

Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder

Brain structural changes in schizoaffective disorder, and how far they resemble those seen in schizophrenia and bipolar disorder, have only been studied to a limited extent. Forty-five patients meeting - and criteria for schizoaffective disorder, groups of patients with 45 matched schizophrenia and bipolar disorder, and 45 matched healthy controls were examined using voxel-based morphometry (). Analyses comparing each patient group with the healthy control subjects found that the patients with schizoaffective disorder and the patients with schizophrenia showed widespread and overlapping areas of significant volume reduction, but the patients with bipolar disorder did not. A subsequent analysis compared the combined group of patients with the controls followed by extraction of clusters. In regions where the patients differed significantly from the controls, no significant differences in mean volume between patients with schizoaffective disorder and patients with schizophrenia in any of five regions of volume reduction were found, but mean volumes in the patients with bipolar disorder were significantly smaller in three of five. The findings provide evidence that, in terms of structural gray matter brain abnormality, schizoaffective disorder resembles schizophrenia more than bipolar disorder

Structural and Functional Brain Correlates of Cognitive Impairment in Euthymic Patients with Bipolar Disorder

Introduction Cognitive impairment in the euthymic phase is a well-established finding in bipolar disorder. However, its brain structural and/or functional correlates are uncertain. Methods Thirty-three euthymic bipolar patients with preserved memory and executive function and 28 euthymic bipolar patients with significant memory and/or executive impairment, as defined using two test batteries, the Rivermead Behavioural Memory Test (RBMT) and the Behavioural Assessment of the Dysexecutive Syndrome (BADS), plus 28 healthy controls underwent structural MRI using voxel-based morphometry (VBM). Twenty-seven of the cognitively preserved patients, 23 of the cognitively impaired patients and 28 controls also underwent fMRI during performance of the n-back working memory task. Results No clusters of grey or white matter volume difference were found between the two patient groups. During n-back performance, the cognitively impaired patients showed hypoactiva- tion compared to the cognitively preserved patients in a circumscribed region in the right dorsolateral prefrontal cortex. Both patient groups showed failure of de-activation in the medial frontal cortex compared to the healthy controls. Conclusions Cognitive impairment in euthymic bipolar patients appears from this study to be unrelated to structural brain abnormality, but there was some evidence for an association with altered prefrontal function