(Dis-)Connected Dots in Dementia with Lewy Bodies—A Systematic Review of Connectivity Studies

Studies on dementia with Lewy bodies (DLB) have mainly focused on the degeneration of distinct cortical and subcortical regions related to the deposition of Lewy bodies. In view of the proposed trans-synaptic spread of the α-synuclein pathology, investigating the disease only in this segregated fashion would be detrimental to our understanding of its progression. In this systematic review, we summarize findings on structural and functional brain connectivity in DLB, as connectivity measures may offer better insights on how the brain is affected by the spread of the pathology. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Web of Science, PubMed, and SCOPUS for relevant articles published up to November 1, 2021. Of 1215 identified records, we selected and systematically reviewed 53 articles that compared connectivity features between patients with DLB and healthy controls. Structural and functional magnetic resonance imaging, positron emission tomography, single-positron emission computer tomography, and electroencephalography assessments of patients revealed widespread abnormalities within and across brain networks in DLB. Frontoparietal, default mode, and visual networks and their connections to other brain regions featured the most consistent disruptions, which were also associated with core clinical features and cognitive impairments. Furthermore, graph theoretical measures revealed disease-related decreases in local and global network efficiency. This systematic review shows that structural and functional connectivity characteristics in DLB may be particularly valuable at early stages, before overt brain atrophy can be observed. This knowledge may help improve the diagnosis and prognosis in DLB as well as pinpoint targets for future disease-modifying treatments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Subtypes of Alzheimer's Disease Display Distinct Network Abnormalities Extending Beyond Their Pattern of Brain Atrophy

Different subtypes of Alzheimer's disease (AD) with characteristic distributions of neurofibrillary tangles and corresponding brain atrophy patterns have been identified using structural magnetic resonance imaging (MRI). However, the underlying biological mechanisms that determine this differential expression of neurofibrillary tangles are still unknown. Here, we applied graph theoretical analysis to structural MRI data to test the hypothesis that differential network disruption is at the basis of the emergence of these AD subtypes. We studied a total of 175 AD patients and 81 controls. Subtyping was done using the Scheltens' scale for medial temporal lobe atrophy, the Koedam's scale for posterior atrophy, and the Pasquier's global cortical atrophy scale for frontal atrophy. A total of 89 AD patients showed a brain atrophy pattern consistent with typical AD; 30 patients showed a limbic-predominant pattern; 29 patients showed a hippocampal-sparing pattern; and 27 showed minimal atrophy. We built brain structural networks from 68 cortical regions and 14 subcortical gray matter structures for each AD subtype and for the controls, and we compared between-group measures of integration, segregation, and modular organization. At the global level, modularity was increased and differential modular reorganization was detected in the four subtypes. We also found a decrease of transitivity in the typical and hippocampal-sparing subtypes, as well as an increase of average local efficiency in the minimal atrophy and hippocampal-sparing subtypes. We conclude that the AD subtypes have a distinct signature of network disruption associated with their atrophy patterns and further extending to other brain regions, presumably reflecting the differential spread of neurofibrillary tangles. We discuss the hypothetical emergence of these subtypes and possible clinical implications

Meta-Review of CSF Core Biomarkers in Alzheimer’s Disease: The State-of-the-Art after the New Revised Diagnostic Criteria

Background: Current research criteria for Alzheimer’s disease (AD) include cerebrospinal fluid (CSF) biomarkers into the diagnostic algorithm. However, spreading their use to the clinical routine is still questionable. Objective: To provide an updated, systematic and critical review on the diagnostic utility of the CSF core biomarkers for AD. Data sources: MEDLINE, PreMedline, EMBASE, PsycInfo, CINAHL, Cochrane Library, and CRD. Eligibility criteria: (1a) Systematic reviews with meta-analysis; (1b) Primary studies published after the new revised diagnostic criteria; (2) Evaluation of the diagnostic performance of at least one CSF core biomarker. Results: The diagnostic performance of CSF biomarkers is generally satisfactory. They are optimal for discriminating AD patients from healthy controls. Their combination may also be suitable for mild cognitive impairment (MCI) prognosis. However, CSF biomarkers fail to distinguish AD from other forms of dementia. Limitations: (1) Use of clinical diagnosis as standard instead of pathological postmortem confirmation; (2) variability of methodological aspects; (3) insufficiently long follow-up periods in MCI studies; and (4) lower diagnostic accuracy in primary care compared with memory clinics. Conclusion: Additional work needs to be done to validate the application of CSF core biomarkers as they are proposed in the new revised diagnostic criteria. The use of CSF core biomarkers in clinical routine is more likely if these limitations are overcome. Early diagnosis is going to be of utmost importance when effective pharmacological treatment will be available and the CSF core biomarkers can also be implemented in clinical trials for drug development

A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies

Background: Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the major sources of bias in such comparisons. Better performance in one or a few instances does not necessarily imply so on an average or on a population level and simulation studies may be a better alternative for objectively comparing the performances of machine learning algorithms. Methods: We compare the classification performance of a number of important and widely used machine learning algorithms, namely the Random Forests (RF), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and k-Nearest Neighbour (kNN). Using massively parallel processing on high-performance supercomputers, we compare the generalisation errors at various combinations of levels of several factors: number of features, training sample size, biological variation, experimental variation, effect size, replication and correlation between features. Results: For smaller number of correlated features, number of features not exceeding approximately half the sample size, LDA was found to be the method of choice in terms of average generalisation errors as well as stability (precision) of error estimates. SVM (with RBF kernel) outperforms LDA as well as RF and kNN by a clear margin as the feature set gets larger provided the sample size is not too small (at least 20). The performance of kNN also improves as the number of features grows and outplays that of LDA and RF unless the data variability is too high and/or effect sizes are too small. RF was found to outperform only kNN in some instances where the data are more variable and have smaller effect sizes, in which cases it also provide more stable error estimates than kNN and LDA. Applications to a number of real datasets supported the findings from the simulation study

European DLB consortium: diagnostic and prognostic biomarkers in dementia with Lewy bodies, a multicenter international initiative

Q3247-250As the population ages, the incidence of chronic diseases such as dementia increases. Dementia with Lewy bodies(DLB) is the second most common neurodegenerative dementia after Alzheimer’s disease (AD) and even thoughboth diseases are clinically separate entities

Nitric oxide production in the exhaled air of patients with pulmonary tuberculosis in relation to HIV co-infection

<p>Abstract</p> <p>Background</p> <p>Nitric oxide (NO) is essential for host defense in rodents, but the role of NO during tuberculosis (TB) in man remains controversial. However, earlier observations that arginine supplementation facilitates anti-TB treatment, supports the hypothesis that NO is important in the host defense against TB. Local production of NO measured in fractional exhaled air (FeNO) in TB patients with and without HIV co-infection has not been reported previously. Thus, our aim was to investigate levels of FeNO in relation to clinical symptoms and urinary NO metabolites (uNO).</p> <p>Methods</p> <p>In a cross sectional study, FeNO and uNO were measured and clinical symptoms, chest x-ray, together with serum levels of arginine, tumor necrosis factor alpha (TNF-alpha) and interleukin 12 (IL-12) were evaluated in sputum smear positive TB patients (HIV+/TB, n = 36, HIV-/TB, n = 59), their household contacts (n = 17) and blood donors (n = 46) from Gondar University Hospital, Ethiopia.</p> <p>Results</p> <p>The proportion of HIV-/TB patients with an increased FeNO level (> 25 ppb) was significantly higher as compared to HIV+/TB patients, but HIV+/TB patients had significantly higher uNO than HIV-/TB patients. HIV+ and HIV-/TB patients both had lower levels of FeNO compared to blood donors and household contacts. The highest levels of both uNO and FeNO were found in household contacts. Less advanced findings on chest x-ray, as well as higher sedimentation rate were observed in HIV+/TB patients as compared to HIV-/TB patients. However, no significant correlation was found between FeNO and uNO, chest x-ray grading, clinical symptoms, TNF-alpha, IL-12, arginine levels or sedimentation rate.</p> <p>Conclusion</p> <p>In both HIV negative and HIV co infected TB patients, low levels of exhaled NO compared to blood donors and household were observed. Future studies are needed to confirm whether low levels of exhaled NO could be a risk factor in acquiring TB and the relative importance of NO in human TB.</p

Outcome of a psychosocial health promotion intervention aimed at improving physical health and reducing alcohol use in patients with schizophrenia and psychotic disorders (MINT)

Background: Life expectancy is reduced by 19 years in men and 17 in women with psychosis in Sweden, largely due to cardiovascular disease. Aim: Assess whether a psychosocial health promotion intervention improves cardiometabolic risk factors, quality of life, and severity of illness in patients with psychotic disorders more than treatment as usual. Methods: A pragmatic intervention trial testing a manual-based multi-component health promotion intervention targeting patients with psychosis. The Swedish intervention was adapted from IMPaCT therapy, a health-promotion program based on motivational interviewing and cognitive behavioral therapy, designed to be incorporated into routine care. The intervention group consisted of 119 patients and a control group of 570 patients from specialized psychosis departments. Outcome variables were assessed 6 months before intervention during the run-in period, again at the start of intervention, and 12 months after the intervention began. The control group received treatment as usual. Results: The intervention had no significant effect on any of the outcome variables. However, BMI, waist circumference, systolic BP, heart rate, HbA1c, general health, and Clinical Global Impressions Scale score improved significantly during the run-in period before the start of the active intervention (observer effect). The multi-component design meant that treatment effects could only be calculated for the intervention as a whole. Conclusion: The results of the intervention are similar to those of the U.K. IMPaCT study, in which the modular health-promotion intervention had little effect on cardiovascular risk indicators. However, in the current study, the run-in period had a positive effect on cardiometabolic risk factors

Biomarkers of Alzheimer’s disease and cerebrovascular disease in relation to depressive symptomatology in individuals with subjective cognitive decline

Background: Subjective cognitive decline (SCD) has gained recent interest as a potential harbinger of neurodegenerative diseases such as Alzheimer’s disease (AD) and cerebrovascular disease (CVD). In addition, SCD can be related to depressive symptomatology. However, the association between AD and CVD biomarkers, depressive symptomatology, and SCD is still unclear. We investigated the association of AD and CVD biomarkers and depressive symptomatology with SCD in individuals with subjective memory complaints (SCD-memory group) and individuals with subjective concentration complaints (SCD-concentration group).// Methods: We recruited a population-based cohort of 217 individuals (all aged 70 years, 53% female, 119 SCD-memory individuals, 23 SCD-concentration individuals, 89 controls). AD and CVD were assessed through cerebrospinal fluid levels of the Aβ42/40 ratio and phosphorylated tau, and white matter signal abnormalities on magnetic resonance imaging, respectively. Associations between biomarkers, depressive symptomatology, and SCD were tested via logistic regression and correlation analyses.// Results: We found a significant association of depressive symptomatology with SCD-memory and SCD-concentration. Depressive symptomatology was not associated with AD and CVD biomarkers. Both the phosphorylated tau biomarker and depressive symptomatology predicted SCD-memory, and the Aβ42/40 ratio and depressive symptomatology predicted SCD-concentration.// Conclusions: The role of depressive symptomatology in SCD may differ depending on the stage within the spectrum of preclinical AD (as determined by amyloid-beta and tau positivity), and does not seem to reflect AD pathology. Our findings contribute to the emerging field of subclinical depressive symptomatology in SCD, and clarify the association of different types of subjective complaints with distinct syndromic and biomarker profiles