Lesions in the connected brain: A network perspective on brain tumors and lesional epilepsy

Stam, C.J. [Promotor]Heimans, J.J. [Promotor]Reijneveld, J.C. [Copromotor]Douw, L. [Copromotor

Connectivity in MEG resting-state networks increases after resective surgery for low-grade glioma and correlates with improved cognitive performance☆

Purpose Low-grade glioma (LGG) patients often have cognitive deficits. Several disease- and treatment related factors affect cognitive processing. Cognitive outcome of resective surgery is unpredictable, both for improvement and deterioration, especially for complex domains such as attention and executive functioning. MEG analysis of resting-state networks (RSNs) is a good candidate for presurgical prediction of cognitive outcome. In this study, we explore the relation between alterations in connectivity of RSNs and changes in cognitive processing after resective surgery, as a stepping stone to ultimately predict postsurgical cognitive outcome. Methods: Ten patients with LGG were included, who had no adjuvant therapy. MEG recording and neuropsychological assessment were obtained before and after resective surgery. MEG data were recorded during a no-task eyes-closed condition, and projected to the anatomical space of the AAL atlas. Alterations in functional connectivity, as characterized by the phase lag index (PLI), within the default mode network (DMN), executive control network (ECN), and left- and right-sided frontoparietal networks (FPN) were compared to cognitive changes. Results: Lower alpha band DMN connectivity was increased after surgery, and this increase was related to improved verbal memory functioning. Similarly, right FPN connectivity was increased after resection in the upper alpha band, which correlated with improved attention, working memory and executive functioning. Discussion Increased alpha band RSN functional connectivity in MEG recordings correlates with improved cognitive outcome after resective surgery. The mechanisms resulting in functional connectivity alterations after resection remain to be elucidated. Importantly, our findings indicate that connectivity of MEG RSNs may be used for presurgical prediction of cognitive outcome in future studies

Asthma beliefs among mothers and children from different ethnic origins living in Amsterdam, the Netherlands

<p>Abstract</p> <p>Background</p> <p>Doctors and patients hold varying beliefs concerning illness and treatment. Patients' and families' explanatory models (EMs) vary according to personality and sociocultural factors. In a multi-ethnic society, it is becoming increasingly significant that doctors understand the different beliefs of their patients in order to improve patient/doctor communication as well as patient adherence to treatment.</p> <p>Methods</p> <p>Twelve focus groups were formed, consisting of 40 children diagnosed with asthma, as well as 28 mothers of these children. These groups included mothers and children of different ethnicities who were living in Amsterdam, the Netherlands. In order to understand the beliefs that both mothers and children hold regarding asthma and its treatment, the explanatory models were analysed and compared.</p> <p>Results</p> <p>Study findings show that mothers and children, regardless of ethnicity and age, have their own EMs. Overall, there is a great deal of uncertainty related to the causes, consequences, problems, and symptoms of asthma and its treatment. It also seems that many concerns and feelings of discomfort are the result of lack of knowledge. For instance, the fact that asthma is not seen as a chronic disease requiring daily intake of an inhaled corticosteroid, but rather as an acute phenomenon triggered by various factors, may be very relevant for clinical practice. This particular belief might suggest an explanation for non-adherent behaviour.</p> <p>Conclusion</p> <p>A thorough understanding of the mothers' and children's beliefs regarding the illness and its treatment is an important aspect in the management of asthma. Gaining an understanding of these beliefs will provide a foundation for a solid clinician-patient/family partnership in asthma care. Although ethnic differences were observed, the similarities between the mothers' and children's beliefs in this multi-ethnic population were striking. In particular, a common belief is that asthma is considered an acute rather than a chronic condition. In addition, there is a lack of knowledge about the course and the self-management of asthma. Health care providers should be aware of these commonly held beliefs, and this information could be shared in educational programs.</p

Changes in perfusion, and structure of hippocampal subfields related to cognitive impairment after ECT:A pilot study using ultra high field MRI

Background: Electroconvulsive therapy (ECT) in patients with major depression is associated with volume changes and markers of neuroplasticity in the hippocampus, in particular in the dentate gyrus. It is unclear if these changes are associated with cognitive side effects. Objectives: We investigated whether changes in cognitive functioning after ECT were associated with hippocampal structural changes. It was hypothesized that 1) volume increase of hippocampal subfields and 2) changes in perfusion and diffusion of the hippocampus correlated with cognitive decline. Methods: Using ultra high field (7 T) MRI, intravoxel incoherent motion and volumetric data were acquired and neurocognitive functioning was assessed before and after ECT in 23 patients with major depression. Repeated measures correlation analysis was used to examine the relation between cognitive functioning and structural characteristics of the hippocampus. Results: Left hippocampal volume, left and right dentate gyrus and right CA1 volume increase correlated with decreases in verbal memory functioning. In addition, a decrease of mean diffusivity in the left hippocampus correlated with a decrease in letter fluency. Limitations: Due to methodological restrictions direct study of neuroplasticity is not possible. MRI is used as an indirect measure. Conclusion: As both volume increase in the hippocampus and MD decrease can be interpreted as indirect markers for neuroplasticity that co-occur with a decrease in cognitive functioning, our results may indicate that neuroplastic processes are affecting cognitive processes after ECT.</p

Syntactic Network Analysis in Schizophrenia-Spectrum Disorders

BACKGROUND: Language anomalies are a hallmark feature of schizophrenia-spectrum disorders (SSD). Here, we used network analysis to examine possible differences in syntactic relations between patients with SSD and healthy controls. Moreover, we assessed their relationship with sociodemographic factors, psychotic symptoms, and cognitive functioning, and we evaluated whether the quantification of syntactic network measures has diagnostic value. STUDY DESIGN: Using a semi-structured interview, we collected speech samples from 63 patients with SSD and 63 controls. Per sentence, a syntactic representation (ie, parse tree) was obtained and used as input for network analysis. The resulting syntactic networks were analyzed for 11 local and global network measures, which were compared between groups using multivariate analysis of covariance, considering the effects of age, sex, and education. RESULTS: Patients with SSD and controls significantly differed on most syntactic network measures. Sex had a significant effect on syntactic measures, and there was a significant interaction between sex and group, as the anomalies in syntactic relations were most pronounced in women with SSD. Syntactic measures were correlated with negative symptoms (Positive and Negative Syndrome Scale) and cognition (Brief Assessment of Cognition in Schizophrenia). A random forest classifier based on the best set of network features distinguished patients from controls with 74% cross-validated accuracy. CONCLUSIONS: Examining syntactic relations from a network perspective revealed robust differences between patients with SSD and healthy controls, especially in women. Our results support the validity of linguistic network analysis in SSD and have the potential to be used in combination with other automated language measures as a marker for SSD.</p

A role for human leucocyte antigens in the susceptibility to SARS‐Cov‐2 infection observed in transplant patients

We analysed data from 80 patients who tested positive for SARS‐CoV‐2 RNA who had previously been HLA typed to support transplantation. Data were combined from two adjacent centres in Manchester and Leeds to achieve a sufficient number for early analysis. HLA frequencies observed were compared against two control populations: first, against published frequencies in a UK deceased donor population (n = 10,000) representing the target population of the virus, and second, using a cohort of individuals from the combined transplant waiting lists of both centres (n = 308), representing a comparator group of unaffected individuals of the same demographic. We report a significant HLA association with HLA‐ DQB1*06 (53% vs. 36%; p < .012; OR 1.96; 95% CI 1.94–3.22) and infection. A bias towards an increased representation of HLA‐A*26, HLA‐DRB1*15, HLA‐DRB1*10 and DRB1*11 was also noted but these were either only significant using the UK donor controls, or did not remain significant after correction for multiple tests. Likewise, HLA‐A*02, HLA‐B*44 and HLA‐C*05 may exert a protective effect, but these associations did not remain significant after correction for multiple tests. This is relevant information for the clinical management of patients in the setting of the current SARS‐CoV‐2 pandemic and potentially in risk‐assessing staff interactions with infected patients

Outcome prediction of electroconvulsive therapy for depression

Introduction: We developed and tested a Bayesian network(BN) model to predict ECT remission for depression, with non-response as a secondary outcome. Methods: We performed a systematic literature search on clinically available predictors. We combined these predictors with variables from a dataset of clinical ECT trajectories (performed in the University Medical Center Utrecht) to create priors and train the BN. Temporal validation was performed in an independent sample. Results: The systematic literature search yielded three meta-analyses, which provided prior knowledge on outcome predictors. The clinical dataset consisted of 248 treatment trajectories in the training set and 44 trajectories in the test set at the same medical center. The AUC for the primary outcome remission estimated on an independent validation set was 0.686 (95%CI 0.513–0.859) (AUC values of 0.505 – 0.763 observed in 5-fold cross validation of the model within the train set). Accuracy 0.73 (balanced accuracy 0.67), sensitivity 0.55, specificity 0.79, after temporal validation in the independent sample. Prior literature information marginally reduced CI width. Discussion: A BN model comprised of prior knowledge and clinical data can predict remission of depression after ECT with reasonable performance. This approach can be used to make outcome predictions in psychiatry, and offers a methodological framework to weigh additional information, such as patient characteristics, symptoms and biomarkers. In time, it may be used to improve shared decision-making in clinical practice

Functional connectome differences in individuals with hallucinations across the psychosis continuum

Hallucinations may arise from an imbalance between sensory and higher cognitive brain regions, reflected by alterations in functional connectivity. It is unknown whether hallucinations across the psychosis continuum exhibit similar alterations in functional connectivity, suggesting a common neural mechanism, or whether different mechanisms link to hallucinations across phenotypes. We acquired resting-state functional MRI scans of 483 participants, including 40 non-clinical individuals with hallucinations, 99 schizophrenia patients with hallucinations, 74 bipolar-I disorder patients with hallucinations, 42 bipolar-I disorder patients without hallucinations, and 228 healthy controls. The weighted connectivity matrices were compared using network-based statistics. Non-clinical individuals with hallucinations and schizophrenia patients with hallucinations exhibited increased connectivity, mainly among fronto-temporal and fronto-insula/cingulate areas compared to controls (P < 0.001 adjusted). Differential effects were observed for bipolar-I disorder patients with hallucinations versus controls, mainly characterized by decreased connectivity between fronto-temporal and fronto-striatal areas (P = 0.012 adjusted). No connectivity alterations were found between bipolar-I disorder patients without hallucinations and controls. Our results support the notion that hallucinations in non-clinical individuals and schizophrenia patients are related to altered interactions between sensory and higher-order cognitive brain regions. However, a different dysconnectivity pattern was observed for bipolar-I disorder patients with hallucinations, which implies a different neural mechanism across the psychosis continuum.publishedVersio

fMRI network correlates of predisposing risk factors for delirium: a cross-sectional study

Delirium, the clinical expression of acute encephalopathy, is a common neuropsychiatric syndrome that is related to poor outcomes, such as long-term cognitive impairment. Disturbances of functional brain networks are hypothesized to predispose for delirium. The aim of this study in non-delirious elderly individuals was to investigate whether predisposing risk factors for delirium are associated with fMRI network characteristics that have been observed during delirium. As predisposing risk factors, we studied age, alcohol misuse, cognitive impairment, depression, functional impairment, history of transient ischemic attack or stroke, and physical status. In this multicenter study, we included 554 subjects and analyzed resting-state fMRI data from 222 elderly subjects (63% male, age range: 65-85 year) after rigorous motion correction. Functional network characteristics were analyzed and based on the minimum spanning tree (MST). Global functional connectivity strength, network efficiency (MST diameter) and network integration (MST leaf fraction) were analyzed, as these measures were altered during delirium in previous studies. Linear regression analyses were used to investigate the relation between predisposing delirium risk factors and delirium-related fMRI characteristics, adjusted for confounding and multiple testing. Predisposing risk factors for delirium were not associated with delirium-related fMRI network characteristics. Older age within our elderly cohort was related to global functional connectivity strength (beta = 0.182, p < 0.05), but in the opposite direction than hypothesized. Delirium-related functional network impairments can therefore not be considered as the common mechanism for predisposition for delirium.Neuro Imaging Researc