Search

BackgroundWe aimed to disentangle within-person and between-person effects in the temporal relationship between depressive symptoms and cognitive function.MethodsWe performed a prospective population-based cohort study on participants of the Survey of Health, Ageing and Retirement in Europe. Cognitive function was assessed by tests on verbal fluency, immediate recall and delayed recall. Depressive symptoms were measured with EURO-D scale. To determine the temporal order of the association between cognitive function and depressive symptoms, we employed the fully saturated cross-lagged panel model (between-person effects), and random intercept cross-lagged panel model (within-person effects).ResultsIn 59,311 participants (mean age 65, ranging 46–100), between-person effects showed a bi-directional relationship that could be seen in three stages: First, the effect of cognitive function on depressive symptoms was initially slightly stronger than vice versa. Second, the effect of depressive symptoms on cognitive function became stronger during the follow-up. Third, all effects were small and no direction dominated. Within-person effects, however, revealed a dominant effect from depressive symptoms on cognitive function. Some effects from cognitive function on depressive symptoms were apparent only in older adults, in particular men. All effects were small and strongest for individuals aged 65 years and above.LimitationsThe sample is healthier than general population and thus not fully representative. A comprehensive cognitive battery was not available.ConclusionsLong-term relationship between depressive symptoms and cognitive function is bi-directional. However, to achieve improvement in an individual in the short-term, the focus should be on decreasing depressive symptoms to improve cognitive function.

Alzheimer’s disease (AD) and other neurodegenerative diseases such as Parkinson’s disease (PD) and Huntington’s disease (HD) are associated with progressive cognitive, motor, affective and consequently functional decline considerably affecting Activities of Daily Living (ADL) and quality of life. Standard assessments, such as questionnaires and interviews, cognitive testing, and mobility assessments, lack sensitivity, especially in early stages of neurodegenerative diseases and in the disease progression, and have therefore a limited utility as outcome measurements in clinical trials. Major advances in the last decade in digital technologies have opened a window of opportunity to introduce digital endpoints into clinical trials that can reform the assessment and tracking of neurodegenerative symptoms. The Innovative Health Initiative (IMI)-funded projects RADAR-AD (Remote assessment of disease and relapse—Alzheimer’s disease), IDEA-FAST (Identifying digital endpoints to assess fatigue, sleep and ADL in neurodegenerative disorders and immune-mediated inflammatory diseases) and Mobilise-D (Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement) aim to identify digital endpoints relevant for neurodegenerative diseases that provide reliable, objective, and sensitive evaluation of disability and health-related quality of life. In this article, we will draw from the findings and experiences of the different IMI projects in discussing (1) the value of remote technologies to assess neurodegenerative diseases; (2) feasibility, acceptability and usability of digital assessments; (3) challenges related to the use of digital tools; (4) public involvement and the implementation of patient advisory boards; (5) regulatory learnings; and (6) the significance of inter-project exchange and data- and algorithm-sharing.

The original version of this Article omitted from the author list the 212th author Patrizia Mecocci, who is from the Institute of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy. Consequently, the “Sample Contribution” section of Author Contributions was updated to add “P.M” between “P.D.” and “R.C.”. Additionally, the original version of this Article contained the incorrect affiliation for author Patrick Gavin Kehoe, which incorrectly read “German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany”. The correct version replaces this affiliation with “Bristol Medical School (THS), University of Bristol, Southmead Hospital, Bristol, UK”. This has been corrected in both the PDF and HTML versions of the Article. CA extern

INTRODUCTION Operationalized research criteria for mild cognitive impairment with Lewy bodies (MCI-LB) were published in 2020. The aim of this systematic review and meta-analysis was to review the evidence for the diagnostic clinical features and biomarkers in MCI-LB set out in the criteria. METHODS MEDLINE, PubMed, and Embase were searched on 9/28/22 for relevant articles. Articles were included if they presented original data reporting the rates of diagnostic features in MCI-LB. RESULTS Fifty-seven articles were included. The meta-analysis supported the inclusion of the current clinical features in the diagnostic criteria. Evidence for striatal dopaminergic imaging and meta-iodobenzylguanidine cardiac scintigraphy, though limited, supports their inclusion. Quantitative electroencephalogram (EEG) and fluorodeoxyglucose positron emission tomography (PET) show promise as diagnostic biomarkers. DISCUSSION The available evidence largely supports the current diagnostic criteria for MCI-LB. Further evidence will help refine the diagnostic criteria and understand how best to apply them in clinical practice and research. HIGHLIGHTS A meta-analysis of the diagnostic features of MCI-LB was carried out. The four core clinical features were more common in MCI-LB than MCI-AD/stable MCI. Neuropsychiatric and autonomic features were also more common in MCI-LB. More evidence is needed for the proposed biomarkers. FDG-PET and quantitative EEG show promise as diagnostic biomarkers in MCI-LB.

Additional file 1: Table S1. Multiple comparisons of each inflammatory marker among diagnostic groups, using non-parametric Kruskal–Wallis ANOVA tests. Table S2. Associations between each inflammatory marker in temporal cortex with diagnostic groups. Table S3. Multiple comparisons of each inflammatory marker in the presence versus absence of neuropathological features, using non-parametric Mann–Whitney U tests. Table S4. Associations between each inflammatory marker in temporal cortex with the presence of Moderate/Severe NFT. Figure S1. Pro-inflammatory markers in frontal and parietal lobes of AD and LBD. Figure S2. Anti-inflammatory markers in frontal and parietal lobes of AD and LBD.

The FAS phonemic fluency test is a commonly used neuropsychological test of executive function and processing speed. Although Norwegian discrete norms have been developed for the FAS test, American regression-based norms are frequently used by clinicians in Norway. However, language and cultural differences impact performance on the FAS test, and using foreign norms may not be appropriate. Moreover, while discrete norming relies on stratified subgroups of demographics, regression-based norming uses the entire sample to estimate the influence of demographics on performance and may thus improve normative estimates. Here we develop regression-based norms for the FAS phonemic fluency test based on n = 204 healthy Norwegian controls between the ages 40−84 from the Norwegian Dementia Disease Initiation cohort (DDI). We compare the proposed regression norms to published Norwegian discrete norms and American regression-based norms in an independent sample of n = 182 cognitively healthy adults reporting subjective cognitive decline (SCD). We found that years of education was the only significant predictor of FAS performance in our normative sample, accounting for 14.9% of the variance. Both the proposed regression-based norms and previously published discrete norms adequately adjusted for demographics in the independent sample. In contrast, the American norms underestimated the effect of education and overestimated the effect of age. While both the proposed Norwegian regression norms and the previously published discrete norms are suitable for use in Norway, the proposed regression norms may be less vulnerable to sub-stratification sample characteristics posed by discrete norming procedures, and thereby improve normative estimation.

BackgroundUnlike traditional pen-and-paper clinical assessments, remote monitoring technologies (RMTs) can assess participants’ function continuously and objectively during activities of daily living. Despite the potential of RMTs to assess function or assist early disease detection, there is skepticism that age or impairment may render participants unable or unwilling to comply with complex RMT protocols. The 8-week RADAR-AD study protocol asks Alzheimer’s disease (AD) patients in all disease stages to wear, amongst others, two activity trackers (Axivity, Fitbit), a wearable camera (Autographer), and use an active smartphone app (Mezurio), with a daily schedule totaling over 400 separate tasks and a parallel schedule for caregivers. This abstract presents preliminary compliance data and participant feedback.MethodWe included amyloid negative control participants (n=47) and amyloid positive preclinical (n=16), prodromal (n=19) and mild-to-moderate (n=16) AD participants (Table 1), based on MMSE and CDR scores, in 8 European countries. Metrics based on device data were calculated for participant commitment (study duration completion percentage or wear time) and compliance (task completion percentage). Patient experiences were monitored using bi-weekly semi-structured phone interviews.ResultMezurio average commitment and compliance were 90% and 85% respectively (Table 2) and were comparable across diagnostic groups. Wear time of Axivity, Fitbit and wearable camera was high (>86%), with 48% of those offered adopting the optional wearable camera (Table 2). Participant feedback was positive, with relatively few problems reported (Figure 1).ConclusionRADAR-AD shows that age and impairment are not necessarily barriers to successful deployment of complex RMT study protocols. We acknowledge that our high commitment and compliance rates benefitted from an active rapport between researchers, participants and care givers, which may not be reproducible in every scenario. Nevertheless, this study shows that AD patients are able and willing to comply and engage with technology.This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking (grant No 806999). www.imi.europa.eu. This communication reflects the views of the RADAR-AD consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein.

Drug repositioning and repurposing has proved useful in identifying new treatments for many diseases, which can then rapidly be brought into clinical practice. Currently, there are few effective pharmacological treatments for Lewy body dementia (which includes both dementia with Lewy bodies and Parkinson’s disease dementia) apart from cholinesterase inhibitors. We reviewed several promising compounds that might potentially be disease-modifying agents for Lewy body dementia and then undertook an International Delphi consensus study to prioritise compounds. We identified ambroxol as the top ranked agent for repurposing and identified a further six agents from the classes of tyrosine kinase inhibitors, GLP-1 receptor agonists, and angiotensin receptor blockers that were rated by the majority of our expert panel as justifying a clinical trial. It would now be timely to take forward all these compounds to Phase II or III clinical trials in Lewy body dementia.

Background: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. Results: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. Conclusions: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones. Funding Agencies|Center for Applied Intelligent System Research (CAISR) at Halmstad University, Sweden; Department of Clinical Physiology, Department of Radiology; Center for Medical Imaging Visualization (CMIV) at Linkoeping University Hospital, Sweden; European DLB consortium; Analytic Imaging Diagnostics Arena (AIDA) initiative; VINNOVA; Formas [2017-02447]; Swedish Energy Agency; Swiss National Science Foundation; Velux Foundation [320030_169876, 320030_185028]; Flanders Research Foundation [1123]; [FWO 12I2121N]

Dementia with Lewy bodies (DLB) is an important cause of dementia with a range of clinical manifestations, including motor, neuropsychiatric, and autonomic symptoms. Compared with more common forms of dementia such as Alzheimer's disease, DLB has been the focus of significantly fewer treatment studies, often with diverse outcome measures, making comparison and clinical implementation difficult. A core outcome set (COS) can address this by ensuring that data are comparable, relevant, useful, and usable for making the best healthcare decisions. Using a multi-stage approach, development of the DLB-COS will include the following stages: (1) A systematic review, following PRISMA guidelines to create an initial long list of outcomes; (2) A two-round online Delphi including clinicians, scientists, policymakers, and individuals with lived experience of DLB and their representatives; (3) An online consensus meeting to agree on the final core list of outcomes (the final DLB-COS) for use in research and clinical practice; (4) A literature search to identify appropriate measurement instruments for the DLB-COS outcomes; (5) A final consensus meeting of the professional stakeholders who attended the online consensus meeting to agree on the instruments that should be used to measure the outcomes in the DLB-COS; and (6) Global dissemination. This is a multi-stage project to develop a COS to be used in treatment trials for DLB. A DLB-COS will ensure the selection of relevant outcomes and will identify the instruments to be used to measure DLB globally. [Abstract copyright: Copyright: © 2022 Grycuk E et al.]

The selection of appropriate outcome measures is fundamental to the design of any successful clinical trial. Although dementia with Lewy bodies (DLB) is one of the most common neurodegenerative conditions, assessment of therapeutic benefit in clinical trials often relies on tools developed for other conditions, such as Alzheimer’s or Parkinson’s disease. These may not be sufficiently valid or sensitive to treatment changes in DLB, decreasing their utility. In this review, we discuss the limitations and strengths of selected available tools used to measure DLB-associated outcomes in clinical trials and highlight the potential roles for more specific objective measures. We emphasize that the existing outcome measures require validation in the DLB population and that DLB-specific outcomes need to be developed. Finally, we highlight how the selection of outcome measures may vary between symptomatic and disease-modifying therapy trials. publishedVersion

Every year around 10 million people are diagnosed with dementia worldwide. Higher life expectancy and population growth could inflate this number even further in the near future. Alzheimer's disease (AD) is one of the primary and most frequently diagnosed dementia disease in elderly subjects. On the other hand, dementia with Lewy Bodies (DLB) is the third most common cause of dementia. A timely and accurate diagnosis of dementia is critical for patients' management and treatment. However, its diagnostic is often challenging due to overlapping symptoms between the different forms of thee disease. Deep learning (DL) combined with magnetic resonance imaging (MRI) has shown potential improving the diagnostic accuracy of several neurodegenerative diseases. In spite of it, DL methods heavily rely on the availability of annotated data. Classic augmentation techniques such as translation are commonly used to increase data availability. In addition, synthetic samples obtained through generative adversarial networks (GAN) are becoming an alternative to classic augmentation. Such techniques are well-known and explored for 2D images, but little is known about their effects in a 3D setting. In this work, we explore the effects of 3D classic augmentation and 3D GAN-based augmentation to classify between AD, DLB and control subjects.

Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Exposures: Alzheimer disease biomarkers detected on PET or in CSF.Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Results: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).Conclusions and Relevance: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Objectives\ud Research with younger adults has begun to explore associations between autism/autistic traits and vulnerability to Post Traumatic Stress Disorder (PTSD). Large scale studies and/or examination of age-effects have not been conducted.\ud \ud Methods\ud Adults aged 50 years+ from the PROTECT study (n = 20,220) completed items about current and childhood socio-communicative difficulties characteristic of autism. Approximately 1% (n = 251) endorsed high autistic traits, henceforth the Autism Spectrum Traits (AST) group. Differences between the AST and an age—and sex-matched “Comparison Older Adults” (COA; n = 9179) group were explored for lifetime traumatic experiences and current symptoms of PTSD, depression, and anxiety.\ud \ud Results\ud Almost 30% of the AST group, compared to less than 8% of the COA, reported severe trauma in childhood/adulthood, including emotional, physical or sexual abuse. Elevated current PTSD symptoms were reported by AST compared to COA. An interaction was observed between autistic traits and trauma severity; the effect of level of trauma on PTSD symptoms was significantly greater for AST versus COA participants. This interaction remained significant when controlling for current depression and anxiety symptoms.\ud \ud Conclusions\ud The findings suggest that high autistic traits may increase the likelihood of experiencing trauma across the lifespan, and the impact of severe trauma on PTSD symptoms. Older adults with high (vs. low) autistic traits may be at greater risk of experiencing PTSD symptoms in latter life. Future research should test whether the pattern of results is similar for diagnosed autistic adults.

Additional file 3 Supplementary Fig. 1. Random forest classification models for the discrimination between a given cluster and all other clusters. This figure depicts the lollipops of importance to report the results of the random forest models for the discrimination between a given cluster and all other clusters.

Additional file 1. Table S1: Cognitive and neuropsychological measures utilized in DLB clinical trials.

Additional file 2. Table S2: Selected cognitive fluctuations outcomes.

Additional file 1 Supplementary table 1: Overview of MRI parameters per center. Supplementary table 2: Overview of CSF procedures per center. These tables present detailed information about MRI parameters and CSF procedures per collaborating center.

Additional file 2 Supplementary methods. This file contains detail information of the supervised random forest classification model for the discrimination of each cluster from all other clusters.

Additional file 3. Table S3: Selected visual hallucinations outcomes.

Importance: Plasma phosphorylated tau (p-tau) has proven to be an accurate biomarker for Alzheimer disease (AD) pathologic characteristics, offering a less expensive and less invasive alternative to cerebrospinal fluid (CSF) and positron emission tomography biomarkers for amyloid-β and tau. Alzheimer disease comorbid pathologic characteristics are common and are associated with more rapid cognitive decline in patients with dementia with Lewy bodies (DLB); therefore, it is anticipated that plasma p-tau concentrations may have utility in assessing cognitive impairment in individuals with this disorder. Objective: To measure the concentrations of plasma p-tau (p-tau181 and p-tau231) and evaluate their associations with cognitive decline in individuals with probable DLB. Design, Setting, and Participants: This multicenter longitudinal cohort study included participants from the European-DLB (E-DLB) Consortium cohort enrolled at 10 centers with harmonized diagnostic procedures from January 1, 2002, to December 31, 2020, with up to 5 years of follow-up. A total of 1122 participants with plasma samples were available. Participants with acute delirium or terminal illness and patients with other previous major psychiatric or neurologic disorders were excluded, leaving a cohort of 987 clinically diagnosed participants with probable DLB (n = 371), Parkinson disease (n = 204), AD (n = 207), as well as healthy controls (HCs) (n = 205). Main Outcomes and Measures: The main outcome was plasma p-tau181 and p-tau231 levels measured with in-house single molecule array assays. The Mini-Mental State Examination (MMSE) was used to measure cognition. Results: Among this cohort of 987 patients (512 men [51.9%]; mean [SD] age, 70.0 [8.8] years), patients with DLB did not differ significantly regarding age, sex, or years of education from those in the AD group, but the DLB group was older than the HC group and included more men than the AD and HC groups. Baseline concentrations of plasma p-tau181 and p-tau231 in patients with DLB were significantly higher than those in the HC group but lower than in the AD group and similar to the Parkinson disease group. Higher plasma concentrations of both p-tau markers were found in a subgroup of patients with DLB with abnormal CSF amyloid-β42 levels compared with those with normal levels (difference in the groups in p-tau181, -3.61 pg/mL; 95% CI, -5.43 to -1.79 pg/mL; P =.049; difference in the groups in p-tau231, -2.51 pg/mL; 95% CI, -3.63 to -1.39 pg/mL; P =.02). There was no difference between p-tau181 level and p-tau231 level across confirmed AD pathologic characteristcs based on reduced Aβ42 level in CSF in individuals with DLB. In DLB, a significant association was found between higher plasma p-tau181 and p-tau231 levels and lower MMSE scores at baseline (for p-tau181, -0.092 MMSE points; 95% CI, -0.12 to -0.06 MMSE points; P =.001; for p-tau231, -0.16 MMSE points; 95% CI, -0.21 to -0.12 MMSE points; P

Additional file 4. Table S4: Selected motor outcomes.

Additional file 5. Table S5: Selected REM-sleep behavior disorder outcomes.

In the original version of this Primer the hyperlink for the MoCA test was incorrectly written as www.mocatest.com, whereas it should have been www.mocatest.org. This has been corrected in the HTML and PDF versions of the manuscript.

Introduction We investigated the efficacy and acceptability of pharmacotherapy for dementia with Lewy bodies (DLB) while simultaneously considering the neuropsychiatric symptoms (NPS), cognitive function, motor symptoms, and acceptability. Methods Electronic databases were searched from inception through June 5, 2019, for randomized controlled trials (RCTs) and open-label trials (OLTs) in patients with DLB. We performed a pairwise conventional meta-analysis (PWMA) and network meta-analysis (NMA) within a frequentist framework. The main outcomes were mean change scores in NPS, general cognition, motor symptoms and acceptability. The effect sizes and odds ratios with 95% confidence intervals (CIs) were calculated. This study was registered with PROSPERO (CRD42018096996). Results In total, we included 29 studies (9 RCTs and 20 OLTs). In the NMA with 9 RCTs, both high- (mean difference [MD] 2.00, 95% CIs, 0.69 to 3.31) and low-dose (1.86, 0.58 to 3.15) donepezil were associated with a greater cognitive improvement than placebo. High-dose zonisamide was associated with greater motor symptom improvement ( -4.10, -7.03 to -1.17]). No medications reached statistical significance regarding improving neuropsychiatric symptoms or developing intolerable adverse effects as compared to placebo. In the second NMA, with 29 studies as an exploratory analysis, aripiprazole and yokukansan may be effective for neuropsychiatric symptoms, while levodopa may be associated with cognitive impairment. Conclusions We report the most comprehensive evidence for the selection of pharmacotherapy for treating different clusters of DLB-related symptoms. Due to the limited availability of RCTs on DLB, more well-conducted RCTs are needed for MMA to warrant clinical efficacy in the future.

Objectives: There is an urgent clinical need for identifying blood-based diagnostic biomarkers for Dementia with Lewy Bodies (DLB). Transcriptomic studies have reported unique RNA changes in post-mortem DLB brains. Small extracellular vesicles (SEV) that transport RNA between brain and peripheral circulation enable identifying molecular changes in living human brain. Hence, we aimed to identify differentially expressed RNA in serum SEVs from people with DLB.Methods: We investigated serum SEV total RNA profiles in people with DLB (n=10) and age and gender matched comparisons (n=10) using next-generation RNA-sequencing. SEVs were separated by ultracentrifugation with density gradient and were characterized by nanoparticle analysis and western blotting. We verified identified differentially expressed genes (DEG) using high-throughput qPCR. Functional implications of identified DEG were evaluated using Ingenuity pathway analyses. Results: We identified 846 nominally significant DEG including 30 miRNAs in DLB serum SEVs. We identified significant downregulation of pro-inflammatory genes, IL1B, CXCL8 and IKBKB. Previously reported post-mortem DLB brain DEGs were significantly enriched (?2=4.99; df=1; p=0.03) among the identified DEGs, and the differential expression of 40 post-mortem DLB brain DEGs could be detected in serum SEVs of people living with DLB. Functional pathway and network analyses highlighted the importance of immunosenescence, ubiquitin proteasome system (UPS) dysfunction, DNA repair and RNA post-transcriptional modification deficits in DLB pathology.Conclusion: Identified DEGs, especially reduced expression levels of inflammation and UPS associated RNA, may aid diagnosing DLB, and their biomarker potential warrants further investigation in larger clinical cohorts. Our findings corroborate the absence of chronic neuroinflammation in DLB.

Background Identifying predictors of incident cognitive impairment (CI), one of the most problematic long‐term outcomes, in Parkinson's disease (PD) is highly relevant for personalized medicine and prognostic counseling. The Nonmotor Symptoms Scale (NMSS) provides a global clinical assessment of a range of NMS, reflecting NMS burden (NMSB), and thus may assist in the identification of an “at‐risk” CI group based on overall NMSB cutoff scores. Methods To investigate whether specific patterns of PD NMS profiles predict incident CI, we performed a retrospective longitudinal study on a convenience sample of 541 nondemented PD patients taking part in the Nonmotor Longitudinal International Study (NILS) cohort, with Mini‐Mental State Examination (MMSE), NMSS, and Scales for Outcomes in PD Motor Scale (SCOPA Motor) scores at baseline and last follow‐up (mean 3.2 years) being available. Results PD patients with incident CI (i.e., MMSE score ≤ 25) at last follow‐up (n = 107) had severe overall NMSB level, significantly worse NMSS hallucinations/perceptual problems and higher NMSS attention/memory scores at baseline. Patients with CI also were older and with more advanced disease, but with no differences in disease duration, dopamine replacement therapy, sex, and comorbid depression, anxiety, and sleep disorders. Conclusions Our findings suggest that a comprehensive baseline measure of NMS and in particular hallucinations and perceptual problems assessed with a validated single instrument can be used to predict incident CI in PD. This approach provides a simple, holistic strategy to predict future CI in this population., A comprehensive baseline measure of NMS and in particular hallucinations and perceptual problems assessed with a validated single instrument can be used to predict incident cognitive impairment in PD. This approach provides a simple, holistic strategy to predict future cognitive impairment in this population.

Background: Identifying predictors of incident cognitive impairment (CI), one of the most problematic long-term outcomes, in Parkinson's disease (PD) is highly relevant for personalized medicine and prognostic counseling. The Nonmotor Symptoms Scale (NMSS) provides a global clinical assessment of a range of NMS, reflecting NMS burden (NMSB), and thus may assist in the identification of an "at-risk" CI group based on overall NMSB cutoff scores. Methods: To investigate whether specific patterns of PD NMS profiles predict incident CI, we performed a retrospective longitudinal study on a convenience sample of 541 nondemented PD patients taking part in the Nonmotor Longitudinal International Study (NILS) cohort, with Mini-Mental State Examination (MMSE), NMSS, and Scales for Outcomes in PD Motor Scale (SCOPA Motor) scores at baseline and last follow-up (mean 3.2 years) being available. Results: PD patients with incident CI (i.e., MMSE score ≤ 25) at last follow-up (n = 107) had severe overall NMSB level, significantly worse NMSS hallucinations/perceptual problems and higher NMSS attention/memory scores at baseline. Patients with CI also were older and with more advanced disease, but with no differences in disease duration, dopamine replacement therapy, sex, and comorbid depression, anxiety, and sleep disorders. Conclusions: Our findings suggest that a comprehensive baseline measure of NMS and in particular hallucinations and perceptual problems assessed with a validated single instrument can be used to predict incident CI in PD. This approach provides a simple, holistic strategy to predict future CI in this population. Albert‐Ludwigs‐Universität Freiburg: D637 Sí

Contains fulltext : 233579.pdf (Publisher’s version ) (Open Access)

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Purpose of reviewTo review the incidence, treatment and genetics of psychosis in people with mild cognitive impairment (MCI) and Alzheimer's disease (AD).Recent findingsPsychosis in Alzheimer's disease (AD) has an incidence of ~ 10% per year. There is limited evidence regarding psychological interventions. Pharmacological management has focused on atypical antipsychotics, balancing modest benefits with evidence of long-term harms. The 5HT2A inverse agonist pimavanserin appears to confer benefit in PD psychosis with initial evidence of benefit in AD. Cholinesterase inhibitors give modest benefits in DLB psychosis. The utility of muscarinic agonists, lithium, glutamatergic and noradrenergic modulators needs further study. Recent work has confirmed the importance of psychosis in MCI as well as AD. The lack of evidence regarding psychological therapies is an urgent knowledge gap, but there is encouraging evidence for emerging pharmacological treatments. Genetics will provide an opportunity for precision medicine and new treatment targets.

Background: Hippocampal atrophy is presented in Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB). Cognition, dual-tasks, muscular function, goal-related behaviors and neuropsychiatric symptoms are linked to hippocampal volumes and may lead to functional decline in activities of daily living. We examined the association between baseline hippocampal subfield volumes (HSv) in mild AD and DLB, and functional decline. Materials & methods: 12 HSv were computed from structural magnetic resonance images using Freesurfer 6.0 segmentation. Functional decline was assessed using the rapid disability rating scale score. Linear regressions were conducted. Results: In AD, HSv were smaller bilaterally. However, HSv were not associated with functional decline. Conclusion: Functional decline does not depend on HSv in mild AD and DLB

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.Competing Interest StatementThomas G. Beach is a consultant for Prothena, Vivid Genomics and Avid Radiopharmaceuticals. He is a scientific advisory board member for Vivid Genomics. John A. Hardy, Huw R. Morris, Stuart Pickering-Brown, Andrew B. Singleton, and Bryan J. Traynor hold US, EU and Canadian patents on the clinical testing and therapeutic intervention for the hexanucleotide repeat expansion of C9orf72. Michael A. Nalls is supported by a consulting contract between Data Tecnica International and the National Institute on Aging, NIH, Bethesda, MD, USA; as a possible conflict of interest Dr. Nalls also consults for Neuron23 Inc., Lysosomal Therapeutics Inc., Illumina Inc., the Michael J. Fox Foundation and Vivid Genomics among others. Jose A. Palma is an editorial board member of Movement Disorders, Parkinsonism & Related Disorders, BMC Neurology, and Clinical Autonomic Research. Bradley F. Boeve, James Leverenz, and Sonja W. Scholz serve on the Scientific Advisory Council of the Lewy Body Dementia Association. Sonja W. Scholz is an editorial board member for the Journal of Parkinson's Disease. Bryan J. Traynor is an editorial board member for JAMA Neurology; Journal of Neurology, Neurosurgery, and Psychiatry; Brain; and Neurobiology of Aging. Zbigniew K. Wszolek serves as a principal investigator or co-principal investigator on Abbvie, Inc. (M15-562 and M15-563), Biogen, Inc. (228PD201) grant, and Biohaven Pharmaceuticals, Inc. (BHV4157-206 and BHV3241-301). Zbigniew K. Wszolek serves as the principal investigator of the Mayo Clinic American Parkinson Disease Association (APDA) Information and Referral Center, and as co-principal investigator of the Mayo Clinic APDA Center for Advanced Research. All other authors report no competing interests.

The prodromal phase of dementia with Lewy bodies (DLB) includes (1) mild cognitive impairment (MCI), (2) delirium-onset, and (3) psychiatric-onset presentations. The purpose of our review is to determine whether there is sufficient information yet available to justify development of diagnostic criteria for each of these. Our goal is to achieve evidence-based recommendations for the recognition of DLB at a predementia, symptomatic stage. We propose operationalized diagnostic criteria for probable and possible mild cognitive impairment with Lewy bodies, which are intended for use in research settings pending validation for use in clinical practice. They are compatible with current criteria for other prodromal neurodegenerative disorders including Alzheimer and Parkinson disease. Although there is still insufficient evidence to propose formal criteria for delirium-onset and psychiatric-onset presentations of DLB, we feel that it is important to characterize them, raising the index of diagnostic suspicion and prioritizing them for further investigation.

In the version of this article initially published, in the phase 3 meta-analysis, the UK Biobank results were overweighed with a slightly larger (5%) N, thus resulting in a minimal underestimation of effect sizes and in P values marginally less significant than their actual values. Because the differences were on the order of the ninth decimal, there is no notable effect on the results or the conclusions drawn. The summary statistics have been updated accordingly at https://ctg.cncr.nl/software/summary_statistics. The Data availability statement has been updated to include the new URL in the HTML and PDF versions of the article.

Additional file 1 Supplementary Table 1 Mean and standard deviation on the four objective cognitive tasks for five levels of awareness of negative age-related cognitive changes

Alzheimer’s disease (AD) is the most common neurodegenerative dementia. Mapping the pathomechanism and providing novel therapeutic options have paramount significance. Recent studies have proposed the role of LMTK2 in AD. However, its expression pattern and association with the pathognomonic neurofibrillary tangles (NFTs) in different brain regions and neuropathological stages of AD is not clear. We performed chromogenic (CHR) LMTK2 and fluorescent phospho-tau/LMTK2 double-labelling (FDL) immunohistochemistry (IHC) on 10−10 postmortem middle frontal gyrus (MFG) and anterior hippocampus (aHPC) samples with early and late neuropathological Braak tau stages of AD. MFG in early stage was our ‘endogenous control’ region as it is not affected by NFTs. Semiquantitative CHR-IHC intensity scoring revealed significantly higher (p < 0.001) LMTK2 values in this group compared to NFT-affected regions. FDL-IHC demonstrated LMTK2 predominance in the endogenous control region, while phospho-tau overburden and decreased LMTK2 immunolabelling were detected in NFT-affected groups (aHPC in early and both regions in late stage). Spearman’s correlation coefficient showed strong negative correlation between phospho-tau/LMTK2 signals within each group. According to our results, LMTK2 expression is inversely proportionate to the extent of NFT pathology, and decreased LMTK2 level is not a general feature in AD brain, rather it is characteristic of the NFT-affected regions.

Objectives: Prevalence of Lewy body dementias (LBD) is second only to Alzheimer's disease (AD) among people with neurodegenerative dementia. LBD cause earlier mortality, more intense neuropsychiatric symptoms, more caregivers' burden, and higher costs than AD. The molecular mechanisms underlying LBD are largely unknown. As advancing molecular level mechanistic understanding is essential for identifying reliable peripheral biomarkers and novel therapeutic targets for LBD, we aimed to identify differentially expressed genes (DEG), and dysfunctional molecular networks in post-mortem LBD brains. Methods: We investigated the transcriptomics of post-mortem anterior cingulate and dorsolateral prefrontal cortices of people with pathology-verified LBD using next-generation RNA-sequencing. We verified the identified DEG using high-throughput quantitative polymerase chain reactions. Functional implications of identified DEG, and the consequent metabolic reprogramming were evaluated by Ingenuity pathway analyses, genome-scale metabolic modelling, reporter metabolite analyses, and in-silico gene silencing.Results: We identified and verified 12 novel DEGs (MPO, SELE, CTSG, ALPI, ABCA13, GALNT6, SST, RBM3, CSF3, SLC4A1, OXTR, and RAB44) in LBD brains with genome-wide statistical significance. We documented statistically significant downregulation of severalcytokine genes. Identified dysfunctional molecular networks highlighted the contributions of mitochondrial dysfunction, oxidative stress, and immunosenescence towards neurodegeneration in LBD.Conclusion: Our findings support that chronic microglial activation and neuroinflammation, well-documented in AD, are notably absent in LBD. The lack of neuroinflammation in LBD brains were corroborated by statistically significant downregulation of several inflammatory markers. Identified DEGs, especially downregulated inflammatory markers, may aid distinguishing LBD from AD, and their biomarker potential warrant further investigation.

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X20957604 for Brain amyloid and vascular risk are related to distinct white matter hyperintensity patterns by Lene Pålhaugen, Carole H Sudre, Sandra Tecelao, Arne Nakling, Ina S Almdahl, Lisa F Kalheim, M Jorge Cardoso, Stein H Johnsen, Arvid Rongve, Dag Aarsland, Atle Bjørnerud, Per Selnes and Tormod Fladby in Journal of Cerebral Blood Flow & Metabolism

Additional file 1: Table S1. Genetic variants used for associations with lipid and protein modules. Table S2. Top 10 drivers in five selected lipid modules. Table S3. Selected lipid modules and annotation. Table S4. Top 10 drivers in five selected protein modules. Table S5. Summary of gene set enrichment analyses and gene ontology enrichment analysis of protein modules. Table S6. Correlations between lipid modules/protein modules and AD genetic variants. Figure S1. Preservation summary plots for AD, MCI and control sub datasets in lipidomics dataset. Figure S2. Preservation summary plots for AD, MCI and control sub datasets in ANM proteomics dataset. Figure S3. Dendrogram and cross-tabulation based comparison of modules in ANM and ART protein cohort networks. Figure S4. A. Cluster dendrogram of weighted lipid correlation network analysis and the number of lipid features in each module; B. Cluster dendrogram of weighted protein correlation network analysis and the number of proteins in each module. Figure S5. Scatter plots of module membership versus lipids/proteins-diagnosis correlation. Figure S6. Scatter plots of eigenlipids correlation with ROD. Figure S7. Scatter plots of eigenlipids correlation with brain atrophy measures. Figure S8. Scatter plots of lipid module membership versus lipids-phenotypes correlation. Figure S9. DAGs summarize biological processes in five protein modules. Figure S10. Scatter plots of eigenproteins correlation with brain atrophy measures. Figure S11. Scatter plots of protein module membership versus proteins-phenotypes correlation. Figure S12. Scatter plots of protein module membership versus proteins-phenotypes correlation. Figure S13. Correlation networks for lipid greenyellow module and protein lightcyan module. Figure S14. Correlation networks for lipid darkturquoise module and protein lightgreen module.

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X20957604 for Brain amyloid and vascular risk are related to distinct white matter hyperintensity patterns by Lene Pålhaugen, Carole H Sudre, Sandra Tecelao, Arne Nakling, Ina S Almdahl, Lisa F Kalheim, M Jorge Cardoso, Stein H Johnsen, Arvid Rongve, Dag Aarsland, Atle Bjørnerud, Per Selnes and Tormod Fladby in Journal of Cerebral Blood Flow & Metabolism

“The authors would like to thank the Norwegian Dementia Genetics Network (DemGene), the European DLB Consortium (E-DLB), Dementia Genetics Spanish Consortium (DEGESCO) and Genomic Research at Fundació ACE (GR@ACE) Consortium. Fundació ACE would like to thank patients and controls who participated in this project. We are indebted to private donors for their support of Fundació ACE research programs. Fundació ACE collaborates with the Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED, Spain) and is one of the participating centers of the Dementia Genetics Spanish Consortium (DEGESCO). The study was founded by the Research Council of Norway, Norwegian Regional Health Authorities and Norwegian Health Association and 237250/EU/JPND (APGeM). The Cohort 2 results were generated with the assistance of financial support of grants PI13/02434 and PI16/01861. Acción Estratégica en Salud, integrated in the Spanish National R + D + I Plan and financed by ISCIII (Instituto de Salud Carlos III)-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER- “Una manera de Hacer Europa”). GR@ACE project has been funded by Fundación bancaria “La Caixa”, Grifols SA, Fundació ACE. The funding sources did not in any way affect the results or presentation of the results.” should read: “The authors would like to thank the Norwegian Dementia Genetics Network (DemGene), the European DLB Consortium (E-DLB), Dementia Genetics Spanish Consortium (DEGESCO) and Genomic Research at Fundació ACE (GR@ACE) Consortium. Fundació ACE would like to thank patients and controls who participated in this project. We are indebted to private donors for their support of Fundació ACE research programs. Fundació ACE collaborates with the Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED, Spain) and is one of the participating centers of the Dementia Genetics Spanish Consortium (DEGESCO). The study was founded by the Research Council of Norway, Norwegian Regional Health Authorities and Norwegian Health Association and 237250/EU/JPND (APGeM). The Cohort 2 results were generated with the assistance of financial support of grants PI13/02434 and PI16/01861. Acción Estratégica en Salud, integrated in the Spanish National R + D + I Plan and financed by ISCIII (Instituto de Salud Carlos III)-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER- “Una manera de Hacer Europa”). GR@ACE project has been funded by Fundación bancaria “La Caixa”, Grifols SA, Fundació ACE. The funding sources did not in any way affect the results or presentation of the results. This paper represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author and not necessarily those of the NIHR or the Department of Health and Social Care”.

In the version of this Article initially published, the author list and affiliations were incomplete. Karl Heilbron and Adam Auton, both with 23andMe, Inc., have been added to the author list. Further, the location for the 23andMe Research Team, now reading “Sunnyvale, CA” initially appeared as Mountain View, CA. The changes have been made to the online version of the paper. *A list of authors and their affiliations appears online.

Metal/mineral dyshomeostasis has been implicated in the development of Alzheimer’s disease (AD). The aim of the study was to investigate the difference in absolute and percentage levels of plasma phosphorus, calcium, iron, zinc, copper, selenium in cognitively normal (CN) and AD subjects. Total reflection X-ray fluorescence (TXRF) spectroscopy was used to detect plasma metals/minerals in CN and AD subjects (n = 44 per group). TXRF detected significantly increased plasma levels of phosphorus (p = 1.33 × 10−12) and calcium (p = 0.025) in AD compared to CN subjects, with higher phosphorus/calcium (p = 2.55 × 10−14) ratio in the former. Percentage concentrations calculated for phosphorus, calcium, iron, zinc, copper, selenium by dividing the concentration of each element by the total concentration of these elements and multiplying by 100%, demonstrated phosphorus was higher in AD compared to CN subjects, while calcium, iron, zinc, copper and selenium were lower in AD subjects, with area under the curves as high as 0.937 (p = 6 × 10−5) computed from receiver operating curves. With exclusion of high levels of phosphorus and calcium from percentage calculations, iron levels remained low in AD whereas zinc was higher in AD, and copper and selenium levels were similar. We demonstrate altered distribution of elements in the plasma of AD subjects with high interdependencies between elemental levels and propose the potential of TXRF measurements for disease monitoring.

OBJECTIVE: To identify brain regions whose metabolic impairment contributes to DLB clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB-hypometabolic-pattern. METHODS: Brain FDG-PET and information on core features were available in 171 patients belonging to the imaging repository of the European DLB-consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core feature-specific patterns controlling for the main confounding variables (MMSE, Age, Education, Gender, and Center). Regression analysis to the locally-normalized intensities was performed to generate a MMSE score-sensitive map. RESULTS: Parkinsonism negatively covaried with bilateral parietal, precuneus and anterior cingulate metabolism, visual-hallucinations with bilateral dorsolateral-frontal cortex, posterior cingulate and parietal metabolism and RBD with bilateral parieto-occipital cortex, precuneus and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobes metabolism. MMSE positively covaried with metabolism in left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in insula, medial frontal gyrus, hippocampus in the left hemisphere and in right cerebellum. INTERPRETATION: Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated to more prominent hypometabolism in specific regions thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. This article is protected by copyright. All rights reserved.

Figure S2. Between-group comparisons of microglial- and astroglial activation with inflammation based on clinical staging. (PDF 277 kb)