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The Remote Assessment of Disease and Relapse – Alzheimer’s Disease (RADAR-AD) consortium evaluated remote measurement technologies (RMTs) for assessing functional status in AD. The consortium engaged with the European Medicines Agency (EMA) to obtain feedback on identification of meaningful functional domains, selection of RMTs and clinical study design to assess the feasibility of using RMTs in AD clinical studies. We summarized the feedback and the lessons learned to guide future projects.

Abstract Visual hallucinations in Lewy body disease (LBD) can be differentiated based on phenomenology into minor phenomena (MVH) and complex hallucinations (CVH). MVH include a variety of phenomena, such as illusions, presence and passage hallucinations occurring at early stages of LBD. The neural mechanisms of visual hallucinations are largely unknown. The hodotopic model posits that the hallucination state is due to abnormal activity in specialized visual areas, that occurs in the context of wider network connectivity alterations and that phenomenology of VH, including content and temporal characteristics, may help identify brain regions underpinning these phenomena. Here we investigated both the topological and hodological neural basis of visual hallucinations integrating grey and white matter imaging analyses. We studied LBD patients with VH and age matched healthy controls (HC). VH were assessed using a North-East-Visual-Hallucinations-Interview that captures phenomenological detail. Then we applied voxel-based morphometry and tract based spatial statistics approaches to identify grey and white matter changes. First, we compared LBD patients and HC. We found a reduced grey matter volume and a widespread damage of white tracts in LBD compared to HC. Then we tested the association between CVH and MVH and grey and white matter indices. We found that CVH duration was associated with decreased grey matter volume in the fusiform gyrus suggesting that LBD neurodegeneration-related abnormal activity in this area is responsible for CVH. An unexpected finding was that MVH severity was associated with a greater integrity of white matter tracts, specifically those connecting dorsal, ventral attention networks and visual areas. Our results suggest that networks underlying MVH need to be partly intact and functional for MVH experiences to occur, while CVH occur when cortical areas are damaged. The findings support the hodotopic view and the hypothesis that MVH and CVH relate to different neural mechanisms, with wider implications for the treatment of these symptoms in a clinical context.

BackgroundTelomere length (TL) has been linked to cognitive function, decline and dementia. This study aimed to explore whether both measured TL and genetic disposition for TL predict dimensions of cognitive performance in a longitudinal sample of older UK adults.MethodsWe analysed data from PROTECT study participants aged ≥50 years without a dementia diagnosis, who had completed longitudinal cognitive testing. We calculated polygenic scores for telomere length (PGS-TL) for 7,877 participants and measured relative telomere length (RTL) in a subgroup of 846 participants using DNA extracted from saliva samples collected within 6 months either side of their baseline cognitive testing. Latent growth models were used to examine whether RTL and PGS-TL predict both baseline and longitudinal changes in cognitive performance (4 time-points, annually).ResultsIn the whole sample, we did not observe significant associations between either measure of telomere length and initial or longitudinal changes in cognitive performance. Stratifying by median age, in older adults (≥ ∼62 years), longer baseline RTL showed a nominal association with poorer baseline verbal reasoning performance (n = 423, Mintercept = 47.58, B = −1.05, p = .011) and PGS-TL was associated with performance over time (n = 3,939; slope factor, Mslope = 3.23, B = −0.45, p = .001; slope2 factor, Mslope2 = 0.21, B = 0.13, p = .002).ConclusionOur findings suggest either the absence of a significant relationship between telomere length (RTL and PGS-TL) and cognitive performance (baseline and change over time), or possibly a weak age-dependent and domain-specific relationship, in older adults of European ancestry. More research is needed in representative and ancestrally diverse samples over a longer assessment period. Alternative biological ageing indicators may still provide utility in the early detection of individuals at risk for cognitive decline (e.g., pace-of ageing epigenetic clocks).

Background: Dementia poses a significant global health challenge. Anthocyanins neutralize free radicals, modulate signaling pathways, inhibit pro-inflammatory genes, and suppress cytokine production and may thus have positive cognitive effects in people at increased risk of dementia. We aim to investigate the effects of purified anthocyanins on cognitive function in people at increased risk of dementia according to their inflammation status based on blood-based inflammatory biomarkers. Methods: This is a secondary analysis of a 24-week randomized, double-blind, placebo-controlled trial. Cluster analysis was performed to categorize two groups based on their individual inflammatory biomarker profile using multiplex sandwich ELISA for the quantitative measurement of cytokines. Descriptive statistics and longitudinal models assessed cognitive outcomes. The primary comparison was the group difference at week 24 based on a modified intention-to-treat analysis. Results: Cluster analysis revealed two distinct inflammatory biomarker profiles. In Cluster 1 (high levels of inflammation biomarkers), anthocyanin treatment showed a statistically significant improvement on cognitive function compared to placebo at 24 weeks. No significant differences were observed in Cluster 2 (low levels of inflammation biomarkers). The demographic characteristics, cognitive scores, and biomarker distributions were similar between treatment groups at baseline. However, cluster 1 exhibited higher BMI, diabetes prevalence, medication usage, and lower HDL cholesterol levels. Conclusion: Individuals with elevated levels of inflammation markers benefited from anthocyanin treatment to enhance cognitive performance, whereas those with lower levels did not. The anti-inflammatory and antioxidant properties of anthocyanins make them a promising intervention, and future prospective trials in people with increased inflammation are warranted.

Abstract Sex differences permeate many aspects of dementia with Lewy bodies (DLB), yet sex differences in patterns of neurodegeneration in DLB remain largely unexplored. Here, we test whether grey matter networks differ between sexes in DLB and compare these findings to sex differences in healthy controls. In this cross-sectional study, we analysed clinical and neuroimaging data of patients with DLB and cognitively healthy controls matched for age and sex. Grey matter networks were constructed by pairwise correlations between 58 regional volumes after correction for age, intracranial volume, and centre. Network properties were compared between sexes and diagnostic groups. Additional analyses were conducted on w-scored data to identify DLB-specific sex differences. Data from 119 (68.7 ± 8.4 years) men and 45 women (69.9 ± 9.1 years) with DLB, and 164 healthy controls were included in this study. Networks of men had a lower nodal strength compared to women. In comparison to healthy women, the grey matter networks of healthy men showed a higher global efficiency, modularity, and fewer modules. None of the network measures showed significant sex differences in DLB. Comparing DLB patients with healthy controls revealed global differences in women and more local differences in men. Modular analyses showed a more distinct demarcation between cortical and subcortical regions in men compared with women. While topologies of grey matter networks differed between sexes in healthy controls, those sex differences were diluted in DLB patients. These findings suggest a disease-driven convergence of neurodegenerative patterns in women and men with DLB, which may inform precision medicine in DLB.

Abstract Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer’s disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ (“A”) and neurodegeneration (“N”) abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.

Abstract Background Sarcopenia is associated with multiple adverse outcomes. Traditional methods to determine low muscle mass for the diagnosis of sarcopenia are mainly based on dual‐energy X‐ray absorptiometry (DXA), whole‐body magnetic resonance imaging (MRI) and bioelectrical impedance analysis. These tests are not always available and are rather time consuming and expensive. However, many brain and head diseases require a head MRI. In this study, we aim to provide a more accessible way to detect sarcopenia by comparing the traditional method of DXA lean mass estimation versus the tongue and masseter muscle mass assessed in a standard brain MRI. Methods The H70 study is a longitudinal study of older people living in Gothenburg, Sweden. In this cross‐sectional analysis, from 1203 participants aged 70 years at baseline, we included 495 with clinical data and MRI images available. We used the appendicular lean soft tissue index (ALSTI) in DXA images as our reference measure of lean mass. Images from the masseter and tongue were analysed and segmented using 3D Slicer. For the statistical analysis, the Spearman correlation coefficient was used, and concordance was estimated with the Kappa coefficient. Results The final sample consisted of 495 participants, of which 52.3% were females. We found a significant correlation coefficient between both tongue (0.26) and masseter (0.33) with ALSTI (P

Abstract Dementia with Lewy bodies (DLB) is a common form of dementia in the elderly population. We performed genome-wide DNA methylation mapping of cerebellar tissue from pathologically confirmed DLB cases and controls to study the epigenetic profile of this understudied disease. After quality control filtering, 728,197 CpG-sites in 278 cases and 172 controls were available for the analysis. We undertook an epigenome-wide association study, which found a differential methylation signature in DLB cases. Our analysis identified seven differentially methylated probes and three regions associated with DLB. The most significant CpGs were located in ARSB (cg16086807), LINC00173 (cg18800161), and MGRN1 (cg16250093). Functional enrichment evaluations found widespread epigenetic dysregulation in genes associated with neuron-to-neuron synapse, postsynaptic specialization, postsynaptic density, and CTCF-mediated synaptic plasticity. In conclusion, our study highlights the potential importance of epigenetic alterations in the pathogenesis of DLB and provides insights into the modified genes, regions and pathways that may guide therapeutic developments.

Abstract Augmented reality (AR) apps, in which the virtual and real world are combined, can recreate instrumental activities of daily living (IADL) and are therefore promising to measure cognition needed for IADL in early Alzheimer’s disease (AD) both in the clinic and in the home settings. The primary aim of this study was to distinguish and classify healthy controls (HC) from participants with AD pathology in an early AD stage using an AR app. The secondary aims were to test the association of the app with clinical cognitive and functional tests and investigate the feasibility of at-home testing using AR. We furthermore investigated the test-retest reliability and potential learning effects of the task. The digital score from the AR app could significantly distinguish HC from preclinical AD (preAD) and prodromal AD (proAD), and preAD from proAD, both with in-clinic and at-home tests. For the classification of the proAD group, the digital score (AUCclinic_visit = 0.84 [0.75–0.93], AUCat_home = 0.77 [0.61–0.93]) was as good as the cognitive score (AUC = 0.85 [0.78–0.93]), while for classifying the preAD group, the digital score (AUCclinic_visit = 0.66 [0.53–0.78], AUCat_home = 0.76 [0.61–0.91]) was superior to the cognitive score (AUC = 0.55 [0.42–0.68]). In-clinic and at-home tests moderately correlated (rho = 0.57, p

ABSTRACT INTRODUCTION: Depressive symptoms are associated with Alzheimer’s disease (AD), but their neurobiological and neuropsychological correlates remain poorly understood. We investigate if depressive symptoms are associated with amyloid (Aβ) pathology and cognition in predementia AD. METHODS: We included Subjective Cognitive Decline (SCD, n= 160) and Mild Cognitive Impairment (MCI, n=192) from the Dementia Disease Initiation cohort. Depressive symptoms were assessed using the Geriatric Depression Scale (GDS-15). Aβ pathology was determined using cerebrospinal fluid (CSF) Aβ42/40 ratio. Associations between depressive symptoms and cognition were assessed with logistic regression. RESULTS: Only the Aβ negative MCI group (MCI-Aβ-) was associated with depressive symptoms (OR=2.65, p=.005). Depressive symptoms were associated with worse memory in MCI-Aβ- (OR=0.94, p=.039), but with better performance in MCI-Aβ+ (OR=1.103, p=.001). DISCUSSION: Our results suggest that depressive symptoms in MCI are neither associated with Aβ pathology, nor AD-associated memory impairment. However, memory impairment in non-AD MCI may relate to depressive symptoms.

Abstract INTRODUCTION Individuals with Alzheimer's disease (AD) commonly experience neuropsychiatric symptoms of psychosis (AD+P) and/or affective disturbance (depression, anxiety, and/or irritability, AD+A). This study's goal was to identify the genetic architecture of AD+P and AD+A, as well as their genetically correlated phenotypes. METHODS Genome‐wide association meta‐analysis of 9988 AD participants from six source studies with participants characterized for AD+P AD+A, and a joint phenotype (AD+A+P). RESULTS AD+P and AD+A were genetically correlated. However, AD+P and AD+A diverged in their genetic correlations with psychiatric phenotypes in individuals without AD. AD+P was negatively genetically correlated with bipolar disorder and positively with depressive symptoms. AD+A was positively correlated with anxiety disorder and more strongly correlated than AD+P with depressive symptoms. AD+P and AD+A+P had significant estimated heritability, whereas AD+A did not. Examination of the loci most strongly associated with the three phenotypes revealed overlapping and unique associations. DISCUSSION AD+P, AD+A, and AD+A+P have both shared and divergent genetic associations pointing to the importance of incorporating genetic insights into future treatment development. Highlights It has long been known that psychotic and affective symptoms are often comorbid in individuals diagnosed with Alzheimer's disease. Here we examined for the first time the genetic architecture underlying this clinical observation, determining that psychotic and affective phenotypes in Alzheimer's disease are genetically correlated. Nevertheless, psychotic and affective phenotypes in Alzheimer's disease diverged in their genetic correlations with psychiatric phenotypes assessed in individuals without Alzheimer's disease. Psychosis in Alzheimer's disease was negatively genetically correlated with bipolar disorder and positively with depressive symptoms, whereas the affective phenotypes in Alzheimer's disease were positively correlated with anxiety disorder and more strongly correlated than psychosis with depressive symptoms. Psychosis in Alzheimer's disease, and the joint psychotic and affective phenotype, had significant estimated heritability, whereas the affective in AD did not. Examination of the loci most strongly associated with the psychotic, affective, or joint phenotypes revealed overlapping and unique associations.

Introduction Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants. Methods For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews. Results Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible. Conclusions This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.

DailyColors™ is a supplement made up of several phytonutrients that aims to replicate elements from the Mediterranean diet. These include fruit, berry and vegetable extracts that are rich in key phytochemicals such as Quercetin, Catechins, Phloretin, Ellagic Acid, and Anthocyanins. Here, we determined the effects of DailyColors™ on the blood biomarkers associated with the diverse mechanisms implicated in ageing and age-related diseases, including mitochondrial function, inflammation, and oxidative stress, as well as on saliva’s DNA methylation pattern. Thirty adult participants (mean (SD) age = 67.0 (7.5) years) with a body mass index over 25 were recruited into this randomised, double-blind, placebo-controlled, cross-over trial (two one-week treatment periods, separated by a one-week washout period). During the placebo period, we observed a significant increase in blood CD38 concentrations from the baseline to 24 h (p-value = 0.019). This was not observed in the active period. Increased CD38 is reportedly associated with subsequent mitochondrial dysfunction and inflammation. Next, there was a decreasing trend of plasma 4-HNE levels, an oxidative stress biomarker, after a one-week intake of DailyColors™. Furthermore, following a one-month open-label follow-up in 26 participants, we observed hypermethylation of the candidate CpG site cg13108341 (q-value = 0.021), which was against the observed trend for this site during ageing. Taken together, while minimal effects were observed in this study, DailyColors™ supplementation may be beneficial by altering and alleviating age-related changes. Longer and larger scale trials of DailyColors™ supplementation are warranted.

Abstract Background Currently, the main pharmaceutical intervention for COVID-19 is vaccination. While antidepressant (AD) drugs have shown some efficacy in treatment of symptomatic COVID-19, their preventative potential remains largely unexplored. Analysis of association between prescription of ADs and COVID-19 incidence in the population would be beneficial for assessing the utility of ADs in COVID-19 prevention. Methods Retrospective study of association between AD prescription and COVID-19 diagnosis was performed in a cohort of community-dwelling adult mental health outpatients during the 1st wave of COVID-19 pandemic in the UK. Clinical record interactive search (CRIS) was performed for mentions of ADs within 3 months preceding admission to inpatient care of the South London and Maudsley (SLaM) NHS Foundation Trust. Incidence of positive COVID-19 tests upon admission and during inpatient treatment was the primary outcome measure. Results AD mention was associated with approximately 40% lower incidence of positive COVID-19 test results when adjusted for socioeconomic parameters and physical health. This association was also observed for prescription of ADs of the selective serotonin reuptake inhibitor (SSRI) class. Conclusions This preliminary study suggests that ADs, and SSRIs in particular, may be of benefit for preventing COVID-19 infection spread in the community. The key limitations of the study are its retrospective nature and the focus on a mental health patient cohort. A more definitive assessment of AD and SSRI preventative potential warrants prospective studies in the wider demographic.

BackgroundThe Rho-kinase (ROCK) inhibitor Fasudil has shown symptomatic and disease-modifying effects in Parkinson’s disease (PD) models in vitro and in vivo. In Japan, Fasudil has been approved for the treatment of subarachnoid haemorrhage since 1995 and shows a favourable safety profile.Objectives/designTo investigate the safety, tolerability, and symptomatic efficacy of ROCK-inhibitor Fasudil in comparison to placebo in a randomized, national, multicenter, double-blind phase IIa study in patients with PD.Methods/analysisWe plan to include 75 patients with at least ‘probable’ PD (MDS criteria), Hoehn and Yahr stages 1–3, and age 30–80 years in 13 German study sites. Patients must be non-fluctuating and their response to PD medication must have been stable for 6 weeks. Patients will be randomly allocated to treatment with the oral investigational medicinal product (IMP) containing either Fasudil in two dosages, or placebo, for a total of 22 days. As primary analysis, non-inferiority of low/high dose of Fasudil on the combined endpoint consisting of occurrence of intolerance and/or treatment-related serious adverse events (SAEs) over 22 days will be assessed in a sequential order, starting with the lower dose. Secondary endpoints will include tolerability alone over 22 days and occurrence of treatment-related SAEs (SARs) over 22 and 50 days and will be compared on group level. Additional secondary endpoints include efficacy on motor and non-motor symptoms, measured on established scales, and will be assessed at several timepoints. Biomaterial will be collected to determine pharmacokinetics of Fasudil and its active metabolite, and to evaluate biomarkers of neurodegeneration.Ethics/registration/discussionAfter positive evaluation by the competent authority and the ethics committee, patient recruitment started in the 3rd quarter of 2023. ROCK-PD is registered with Eudra-CT (2021-003879-34) and clinicaltrials.gov (NCT05931575). Results of this trial can pave way for conducting extended-duration studies assessing both symptomatic efficacy and disease-modifying properties of Fasudil.

Background Cognitive deficits are associated with poor quality of life and increased risk of development of dementia in patients with Parkinson’s disease (PD) psychosis. The trajectory of cognitive decline in PD psychosis remains however unclear.Objective We examined this using data from the Parkinson’s Progression Markers Initiative study.Methods We analysed data from patients with drug-naïve PD (n=676) and healthy controls (HC, n=187) over 5 years, and examined all cognitive measures assessed at each time point. We classified patients with PD into those who developed psychosis over the course of the study (PDP) and those without psychosis throughout (PDnP) using the Movement Disorders Society Unified Parkinson’s Disease Rating Scale part I hallucinations/psychosis item. We used linear mixed-effect models with restricted maximum likelihood. Age, sex, ethnicity, education and neuropsychiatric and PD-specific symptoms were entered as covariates of interest.Findings There were no baseline cognitive differences between PD patient groups. There were differences in cognitive performance between PD and HC across the majority of the assessments.Patients with PDP exhibited greater cognitive decline over 5 years compared with PDnP across most domains even after controlling for sociodemographics, depression, sleepiness, rapid eye movement sleep behaviour disorder and motor symptom severity (immediate recall, b=−0.288, p=0.003; delayed recall, b=−0.146, p=0.003; global cognition, Montreal Cognitive Assessment, b=−0.206, p

ABSTRACTBackground: Traumatic brain injury (TBI) is prevalent in veterans and may occur at any stages of their life (before, during, or after military service). This is of particular concern, as previous evidence in the general population has identified TBI as a strong risk factor for mild cognitive impairment (MCI), a known precursor of dementia.Objectives: This study aimed to investigate whether exposure to at least one TBI across the lifetime was a risk factor for MCI in ageing UK veterans compared to non-veterans.Method: This cross-sectional study comprised of data from PROTECT, a cohort study comprising UK veterans and non-veterans aged ≥ 50 years at baseline. Veteran and TBI status were self-reported using the Military Service History Questionnaire (MSHQ) and the Brain Injury Screening Questionnaire (BISQ), respectively. MCI was the outcome of interest, and was defined as subjective cognitive impairment and objective cognitive impairment.Results: The sample population comprised of veterans (n = 701) and non-veterans (n = 12,389). TBI was a significant risk factor for MCI in the overall sample (OR = 1.21, 95% CI 1.11–1.31) compared to individuals without TBI. The prevalence of TBI was significantly higher in veterans compared to non-veterans (69.9% vs 59.5%, p

Abstract Background Chronically dysregulated neuroinflammation has been implicated in neurodegenerative dementias, with separate studies reporting increased brain levels of inflammatory mediators and gliosis in Alzheimer’s disease (AD) as well as in Lewy body dementias (LBD). However, it is unclear whether the nature and extent of neuroinflammatory responses in LBD are comparable to those in AD. In this study, we performed head-to-head measurements of a panel of cytokines in the post-mortem neocortex of AD versus the two major clinical subtypes of LBD, namely, dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD). Methods Post-mortem tissues from the mid-temporal cortex (Brodmann area 21) of a cohort of neuropathologically well-defined AD, PDD and DLB patients were processed and measured for a comprehensive range of cytokines (IL-1α, IL-1Ra, IL-8, IL-10, IL-12p70, IL-13, IFN-γ, GM-CSF and FGF-2) using a multiplex immunoassay platform. Associations between inflammation markers and neuropathological measures of neuritic plaques, neurofibrillary tangles as well as Lewy bodies were also performed. Results We found IL-1α, IFN-γ, GM-CSF and IL-13 to be elevated in the mid-temporal cortex of AD patients. In contrast, none of the measured cytokines were significantly altered in either DLB or PDD. Similar cytokine changes were observed in two other neocortical areas of AD patients. Furthermore, increases of IL-1α, IFN-γ, GM-CSF, IL-10 and IL-13 associated with moderate-to-severe neurofibrillary tangle burden, but not with neuritic plaques or Lewy bodies. Our findings of elevated neocortical pro- and anti-inflammatory cytokines in AD, but not in DLB or PDD, suggest that neuroinflammatory responses are strongly linked to neurofibrillary tangle burden, which is higher in AD compared to LBD. In conclusion, neuroinflammation may not play a prominent role in the pathophysiology of late-stage LBD.

Abstract Introduction Reviews of randomized clinical trials (RCTs) in dementia with Lewy bodies (DLB) are essential for informing ongoing research efforts of symptomatic therapies and potentially disease-modifying therapies (DMTs). Methods We performed a systematic review of all clinical trials conducted until September 27, 2022, by examining 3 international registries: ClinicalTrials.gov, the European Union Drug Regulating Authorities Clinical Trials Database, and the International Clinical Trials Registry Platform, to identify drugs in trials in DLB. Results We found 25 agents in 40 trials assessing symptomatic treatments and DMTs for DLB: 7 phase 3, 31 phase 2, and 2 phase 1 trials. We found an active pipeline for drug development in DLB, with most ongoing clinical trials in phase 2. We identified a recent trend towards including participants at the prodromal stages, although more than half of active clinical trials will enroll mild to moderate dementia patients. Additionally, repurposed agents are frequently tested, representing 65% of clinical trials. Conclusion Current challenges in DLB clinical trials include the need for disease-specific outcome measures and biomarkers, and improving representation of global and diverse populations.

This study presents the dementia researchers views of research networks, and how the networks fit into their pursuit of research objectives and dementia research funding. We conducted 10 semi-structured interviews with 10 leading dementia researchers in Norway, for a qualitative study inspired by grounded theory. The dementia researchers consider the six categories to determine the legitimacy of the proposed network and its proposing person. The six categories are: personal motivation, relationship and friendship, communication, research funding, research management, and network characteristics. The dementia researcher offers insights into best practice of research networks. The study suggests that leading dementia researchers collaborate effectively on research activities toward personal research interests and objectives, but these are not actively aligned coordinated with the interests of the public research funding institutions. Lack of coordination between the funded dementia researchers and the funding institutions limits the potential performance from the dementia research.

BackgroundNeuropsychiatric symptoms (NPS) are often overlooked and under-identified symptoms associated with dementia, despite their significant impact on the prognosis of individuals living with the disease. The specific role of certain NPS in functional prognosis remains unclear.AimsTo determine the association of different NPS with functional decline in people living with Alzheimer’s disease (AD) or Lewy body dementia (LBD).MethodsThis is an analysis of data from the Dementia Study of Western Norway (DemVest) with 196 patients included of which 111 had AD and 85 LBD. The Neuropsychiatric Inventory (NPI) and the Rapid Disability Rating Scale (RDRS-2) for activities of daily living were administered annually for 5 years. NPI total score and individual items with RDRS-2 trajectories were analyzed with linear mixed models.ResultsThe LBD group exhibited higher levels of functional impairment and a greater burden of NPS at baseline. Over the 5-year follow-up, hallucinations, aggression, depression, anxiety, apathy, disinhibition, aberrant motor behavior, nighttime behavior disturbances, and abnormal eating patterns were significantly associated with the decline in functional abilities in individuals with AD, as well as irritability and aberrant motor behavior in those with LBD.DiscussionThese results highlight the relevance of early detection and intervention of these particularly relevant NPS, due to its potential of also impacting physical function. Better detection and management of these NPS could improve functional prognosis in people living with dementia.ConclusionSpecific NPS demonstrate relevant distinct associations with Longitudinal trajectories of functional decline in AD and LBD.

Background: 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. Methods: 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. Discussion: 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 Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) data to investigate DLB subtypes. We included 165 DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid, tau, and cerebrovascular biomarkers at baseline, and cognitive decline over three years. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n = 49, 30%); a subtype with low GM volumes in fronto-occipital regions (n = 76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n = 40, 24%). This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.

Abstract 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.

Abstract Early identification of cognitive impairment in Parkinson’s disease (PD) has important clinical and research implications. The aim of our study was to investigate the role of plasma tau phosphorylated at amino acid 181 (p-tau181) and plasma neurofilament light chain (NfL) as biomarkers of cognition in PD. Baseline concentrations of plasma p-tau181 and NfL were measured in a cohort of 136 patients with PD and 63 healthy controls (HC). Forty-seven PD patients were followed up for up to 2 years. Cross-sectional and longitudinal associations between baseline plasma biomarkers and cognitive progression were investigated using linear regression and linear mixed effects models. At baseline, plasma p-tau181 concentration was significantly higher in PD subjects compared with HC (p = 0.026). In PD patients, higher plasma NfL was associated with lower MMSE score at baseline, after adjusting for age, sex and education (p = 0.027). Baseline plasma NfL also predicted MMSE decline over time in the PD group (p = 0.020). No significant association between plasma p-tau181 concentration and baseline or longitudinal cognitive performance was found. While the role of p-tau181 as a diagnostic biomarker for PD and its relationship with cognition need further elucidation, plasma NfL may serve as a feasible, non-invasive biomarker of cognitive progression in PD.

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.

Abstract Introduction Plasma tests have demonstrated high diagnostic accuracy for identifying Alzheimer's disease pathology. To facilitate the transition to clinical utility, we assessed whether plasma storage duration and temperature affect the biomarker concentrations. Methods Plasma samples from 13 participants were stored at +4°C and +18°C. Concentrations of six biomarkers were measured after 2, 4, 6, 8, 10, and 24 h by single molecule array assays. Results Phosphorylated tau 181 (p‐tau181), phosphorylated tau 231 (p‐tau231), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) concentrations were unchanged both when stored at +4°C and +18°C. Amyloid‐β 40 (Aβ40) and amyloid‐β 42 (Aβ42) concentrations were stable for 24 h at +4°C but declined when stored at +18°C for longer than 6 h. This decline did not affect the Aβ42/Aβ40 ratio. Discussion Plasma samples can be stored for 24 h at +4°C or +18°C and result in valid assay results for p‐tau181, p‐tau231, Aβ42/Aβ40 ratio, GFAP, and NfL. HIGHLIGHTS Plasma samples were stored for 24 h at +4°C and +18°C, mimicking clinical practice. Concentrations for Alzheimer's disease biomarkers were measured at six time‐points. p‐tau181, p‐tau231, NfL, and GFAP concentrations were unchanged during the experiment. Storage at +18°C affected Aβ40 and Aβ42 concentrations while storage at +4°C did not. The Aβ42/Aβ40 ratio was unaffected. These plasma tests seem suitable for use in general practice.

Abstract Introduction Late‐life onset psychosis is associated with faster progression to dementia in cognitively normal people, but little is known about its relationship with cognitive impairment in advance of dementia. Methods Clinical and genetic data from 2750 people ≥50 years of age without dementia were analyzed. Incident cognitive impairment was operationalized using the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) and psychosis was rated using the Mild Behavioral Impairment Checklist (henceforth MBI‐psychosis). The whole sample was analyzed before stratification on apolipoprotein E (APOE) ε4 status. Results In Cox proportional hazards models, MBI‐psychosis had a higher hazard for cognitive impairment relative to the No Psychosis group (hazard ratio [HR]: 3.6, 95% confidence interval [CI]: 2.2–6, p < 0.0001). The hazard for MBI‐psychosis was higher in APOE ε4 carriers and there was an interaction between the two (HR for interaction: 3.4, 95% CI: 1.2–9.8, p = 0.02). Discussion Psychosis assessment in the MBI framework is associated with incident cognitive impairment in advance of dementia. These symptoms may be particularly important in the context of APOE genotype.

Abstract 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.

Background: Education and cognition demonstrate consistent inverse associations with Alzheimer’s disease (AD). The biological underpinnings, however, remain unclear. Blood metabolites reflect the end point of biological processes and are accessible and malleable. Identifying metabolites with etiological relevance to AD and disentangling how these relate to cognitive factors along the AD causal pathway could, therefore, offer unique insights into underlying causal mechanisms. Methods: Using data from the largest metabolomics genome-wide association study (N ≈ 24,925) and three independent AD cohorts (N = 4725), cross-trait polygenic scores were generated and meta-analyzed. Metabolites genetically associated with AD were taken forward for causal analyses. Bidirectional two-sample Mendelian randomization interrogated univariable causal relationships between 1) metabolites and AD; 2) education and cognition; 3) metabolites, education, and cognition; and 4) education, cognition, and AD. Mediating relationships were computed using multivariable Mendelian randomization. Results: Thirty-four metabolites were genetically associated with AD at p < .05. Of these, glutamine and free cholesterol in extra-large high-density lipoproteins demonstrated a protective causal effect (glutamine: 95% confidence interval [CI], 0.70 to 0.92; free cholesterol in extra-large high-density lipoproteins: 95% CI, 0.75 to 0.92). An AD-protective effect was also observed for education (95% CI, 0.61 to 0.85) and cognition (95% CI, 0.60 to 0.89), with bidirectional mediation evident. Cognition as a mediator of the education-AD relationship was stronger than vice versa, however. No evidence of mediation via any metabolite was found. Conclusions: Glutamine and free cholesterol in extra-large high-density lipoproteins show protective causal effects on AD. Education and cognition also demonstrate protection, though education’s effect is almost entirely mediated by cognition. These insights provide key pieces of the AD causal puzzle, important for informing future multimodal work and progressing toward effective intervention strategies.

Abstract Background Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer’s disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We addressed this heterogeneity by investigating subgroups of patients with similar biological, clinical, and demographic features. Methods We studied 107 extensively phenotyped DLB patients from the European DLB consortium. Factorial analysis of mixed data (FAMD) was used to identify dimensions in the data, based on sex, age, years of education, disease duration, Mini-Mental State Examination (MMSE), cerebrospinal fluid (CSF) levels of AD biomarkers, core features of DLB, and regional brain atrophy. Subsequently, hierarchical clustering analysis was used to subgroup individuals based on the FAMD dimensions. Results We identified 3 dimensions using FAMD that explained 38% of the variance. Subsequent hierarchical clustering identified 4 clusters. Cluster 1 was characterized by amyloid-β and cerebrovascular pathologies, medial temporal atrophy, and cognitive fluctuations. Cluster 2 had posterior atrophy and showed the lowest frequency of visual hallucinations and cognitive fluctuations and the worst cognitive performance. Cluster 3 had the highest frequency of tau pathology, showed posterior atrophy, and had a low frequency of parkinsonism. Cluster 4 had virtually normal AD biomarkers, the least regional brain atrophy and cerebrovascular pathology, and the highest MMSE scores. Conclusions This study demonstrates that there are subgroups of DLB patients with different biological, clinical, and demographic characteristics. These findings may have implications in the diagnosis and prognosis of DLB, as well as in the treatment response in clinical trials.

[This corrects the article DOI: 10.1371/journal.pone.0285807.].

IntroductionClinical research with remote monitoring technologies (RMTs) has multiple advantages over standard paper-pencil tests, but also raises several ethical concerns. While several studies have addressed the issue of governance of big data in clinical research from the legal or ethical perspectives, the viewpoint of local research ethics committee (REC) members is underrepresented in the current literature. The aim of this study is therefore to find which specific ethical challenges are raised by RECs in the context of a large European study on remote monitoring in all syndromic stages of Alzheimer's disease, and what gaps remain.MethodsDocuments describing the REC review process at 10 sites in 9 European countries from the project Remote Assessment of Disease and Relapse-Alzheimer's Disease (RADAR-AD) were collected and translated. Main themes emerging in the documents were identified using a qualitative analysis approach.ResultsFour main themes emerged after analysis: data management, participant's wellbeing, methodological issues, and the issue of defining the regulatory category of RMTs. Review processes differed across sites: process duration varied from 71 to 423 days, some RECs did not raise any issues, whereas others raised up to 35 concerns, and the approval of a data protection officer was needed in half of the sites.DiscussionThe differences in the ethics review process of the same study protocol across different local settings suggest that a multi-site study would benefit from a harmonization in research ethics governance processes. More specifically, some best practices could be included in ethical reviews across institutional and national contexts, such as the opinion of an institutional data protection officer, patient advisory board reviews of the protocol and plans for how ethical reflection is embedded within the study.

The prevalence of dementia is increasing and poses a health challenge for individuals and society. Despite the desire to know their risks and the importance of initiating early therapeutic options, large parts of the population do not get access to memory clinic-based assessments. Remote memory clinics facilitate low-level access to cognitive assessments by eschewing the need for face-to-face meetings. At the same time, patients with detected impairment or increased risk can receive non-pharmacological treatment remotely. Sensor technology can evaluate the efficiency of this remote treatment and identify cognitive decline. With remote and (partly) automatized technology the process of cognitive decline can be monitored but more importantly also modified by guiding early interventions and a dementia preventative lifestyle. We highlight how sensor technology aids the expansion of assessments beyond cognition and to other domains, e.g., depression. We also illustrate applications for aiding remote treatment and describe how remote tools can facilitate health education which is the cornerstone for long-lasting lifestyle changes. Tools such as transcranial electric stimulation or sleep-based interventions have currently mostly been used in a face-to-face context but have the potential of remote deployment—a step already taken with memory training apps. Many of the presented methods are readily scalable and of low costs and there is a range of target populations, from the worried well to late-stage dementia.

Abstract To explore markers for synaptic function and Alzheimer disease (AD) pathology in late life depression (LLD), predementia AD and normal controls (NC). A cross-sectional study to compare cerebrospinal fluid (CSF) levels of neurogranin (Ng), Beta-site amyloid-precursor-protein cleaving enzyme1 (BACE1), Ng/BACE1 ratio and Amyloid-β 42/40 ratio, phosphorylated-tau and total-tau in LLD with (LLD AD) or without (LLD NoAD) AD pathology, predementia AD and normal controls (NC). We included 145 participants (NC = 41; predementia AD = 66 and LLD = 38). LLD comprised LLD AD (n = 16), LLD NoAD (n = 19), LLD with non-AD typical changes (n = 3, excluded). LLD AD (pADJ

Known genetic loci account for only a fraction of the genetic contribution to Alzheimer’s disease. Here, the authors have performed a large genome-wide meta-analysis comprising 409,435 individuals to discover 6 new loci and demonstrate the efficacy of an Alzheimer’s disease polygenic risk score.

Cerebrospinal fluid neurofilament light (NfL) is a biomarker for neurodegeneration that can also be assessed in blood. Here the authors show in a validation study the potential for plasma NfL as a biomarker for several neurodegenerative diseases.

Background: 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. Methods: 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. Discussion: 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 Background Functional decline in Alzheimer’s disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. Methods This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants’ phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. Results First results are expected to be disseminated in 2022. Conclusion Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.

Abstract Background With this study, we aim to determine the associations of the different categories of the body mass index (BMI) with activities of daily living (ADL) and cognitive performance in two different populations living in the community; Colombian and South Korean older adults. Methods We performed a cross-sectional analysis of two surveys separately; The Survey on Health, Well-Being, and Aging in Colombia (SABE) (n = 23,343) and the Korean Longitudinal Study of aging (KLoSA) (n = 4556). Participants older than 50 years were selected from rural and urban areas achieving a representative sample. Here we investigated the association between BMI categories with function using zero-inflated negative binomial regressions, and with cognition using logistic regression models. Results After adjustment, in Colombia, underweight was associated with an impaired score on the Mini-mental State Examination (MMSE) and worse performance in the instrumental activities of daily living (IADL). Also, being overweight was associated with a better score on the MMSE and the IADL. For both outcomes education level significantly influenced the predictions. In South Korea, there were no significant associations for cognition, IADL, or basic activities of daily living (BADL). Conclusions In the Colombian population, underweight, was associated with reduced cognitive performance and daily functioning. Additionally, being overweight but not obese was associated with better cognition and daily functioning. In South Korea, there were no significant associations between BMI and cognition, IADL, or BADL.

Abstract Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.

Psychiatric-onset dementia with Lewy bodies (DLB) might include symptoms of depression, hallucinations, anxiety, and apathy. Here, we report a patient with DLB with recurrent panic attacks as her first symptom 5 years before a biological-based diagnosis of probable DLB. We provide an extended description of the clinical presentation and course from psychiatric-onset DLB to dementia in an 83-year-old woman. This case illustrates the common misdiagnosis of DLB and the delay of having a detailed clinical and biomarker assessment for structured diagnosis. With a detailed description of the clinical presentation of this case, the empirical treatment strategies, and the patient perspectives, we aim to make clinicians aware of panic attacks within the psychiatric-onset DLB.

Abstract Background The underlying disease mechanism of neuropsychiatric symptoms (NPS) in dementia remains unclear. Cerebrospinal fluid (CSF) biomarkers for synaptic and axonal degeneration may provide novel neuropathological information for their occurrence. The aim was to investigate the relationship between NPS and CSF biomarkers for synaptic (neurogranin [Ng], growth-associated protein 43 [GAP-43]) and axonal (neurofilament light [NFL]) injury in patients with dementia. Methods A total of 151 patients (mean age ± SD, 73.5 ± 11.0, females n = 92 [61%]) were included, of which 64 had Alzheimer’s disease (AD) (34 with high NPS, i.e., Neuropsychiatric Inventory (NPI) score > 10 and 30 with low levels of NPS) and 18 were diagnosed with vascular dementia (VaD), 27 with mixed dementia (MIX), 12 with mild cognitive impairment (MCI), and 30 with subjective cognitive impairment (SCI). NPS were primarily assessed using the NPI. CSF samples were analyzed using enzyme-linked immunosorbent assays (ELISAs) for T-tau, P-tau, Aβ1–42, Ng, NFL, and GAP-43. Results No significant differences were seen in the CSF levels of Ng, GAP-43, and NFL between AD patients with high vs low levels of NPS (but almost significantly decreased for Ng in AD patients

Abstract Background A questionnaire assessing awareness of positive and negative age-related changes (AARC gains and losses) was developed in the US and Germany. We validated the short form of the measure (AARC-10 SF) and the cognitive functioning subscale from the 50-item version of the AARC (AARC-50) questionnaire in the UK population aged 50 and over. Methods Data from 9410 participants (Mean (SD) age = 65.9 (7.1)) in the PROTECT cohort were used to explore and confirm the psychometric properties of the AARC measures including: validity of the factor structure; reliability; measurement invariance across men and women, individuals with and without a university degree, and in middle age, early old age, and advanced old age; and convergent validity with measures of self-perception of aging and mental, physical, and cognitive health. We explored the relationship between demographic variables (age, sex, marital status, employment, and university education) and AARC. Results We confirmed the two-factor structure (gains and losses) of the AARC-10 SF and the AARC-50 cognitive functioning subscale. Both scales showed good reliability and good convergent validity for AARC losses, but weak convergent validity for AARC gains. For both scales metric invariance was held for the two subgroups defined by education level and age. For the AARC-50 subscale, but not for the AARC-10 SF, strong invariance was also held for the two subgroups defined by sex. Age, sex, marital status, employment, and university education predicted AARC gains and losses. Conclusions The AARC-10 SF and AARC-50 cognitive functioning subscale identify UK individuals who perceive age-related changes in their mental, physical, and cognitive health.

Abstract Background There is an urgent need to understand the pathways and processes underlying Alzheimer’s disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer’s dementia using an unsupervised lipid, protein and gene multi-omics integrative approach. Methods A lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored. Results Five of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype). Conclusions Modules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes.

Abstract Objective To determine the evolution of numerous neuropsychiatric symptoms and cognitive abilities in Parkinson disease from disease onset. Methods Prospectively collected, longitudinal (untreated, disease onset to year 5), observational data from Parkinson's Progression Markers Initiative annual visits was used to evaluate prevalence, correlates, and treatment of 10 neuropsychiatric symptoms and cognitive impairment in Parkinson disease participants and matched healthy controls. Results Of 423 Parkinson disease participants evaluated at baseline, 315 (74.5%) were assessed at year 5. Eight neuropsychiatric symptoms studied increased in absolute prevalence by 6.2–20.9% at year 5 relative to baseline, and cognitive impairment increased by 2.7–6.2%. In comparison, the frequency of neuropsychiatric symptoms in healthy controls remained stable or declined over time. Antidepressant and anxiolytic/hypnotic use in Parkinson disease were common at baseline and increased over time (18% to 27% for the former; 13% to 24% for the latter); antipsychotic and cognitive‐enhancing medication use was uncommon throughout (2% and 5% of patients at year 5); and potentially harmful anticholinergic medication use was common and increased over time. At year 5 the cross‐sectional prevalence for having three or more neuropsychiatric disorders/cognitive impairment was 56% for Parkinson disease participants versus 13% for healthy controls, and by then seven of the examined disorders had either occurred or been treated at some time point in the majority of Parkinson disease patients. Principal component analysis suggested an affective disorder subtype only. Interpretation Neuropsychiatric features in Parkinson disease are common from the onset, increase over time, are frequently comorbid, and fluctuate in severity.