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Background: While the association between tau deposition on PET and brain atrophy on MRI is well documented in the literature, the relation between amyloid deposition and neurodegeneration in the earliest stages of Alzheimer's disease (AD) is less studied. We investigated this relationship in a large cohort of non‐demented individuals. Method: We included 1355 participants from the AMYPAD Prognostic & Natural History study (PNHS) with available MRI and amyloid‐PET. Among those, 753 had longitudinal MRI, with a mean follow‐up time of 3.47 years (SD = 1.55). The FreeSurfer 7.0.1 longitudinal pipeline was used to measure gray matter (GM) thickness and volumes in 40 regions (Reuter et al., 2012; Desikan et al., 2006). From PET scans, cortical amyloid burden was assessed globally using the Centiloid (CL) method. MRI‐derived regional volumes and thickness were harmonized across sites with neuroCombat (Fortin et al., 2018); all variables were Z‐scored. Linear mixed‐effect models were used to investigate the effect of amyloid burden at baseline and its interaction with time on regional volume and thickness measurements. Models were corrected for age, sex, and CDR. P‐values were FDR‐adjusted. Result: Cohort characteristics are shown in Table 1. Decreasing cortical thickness and volumes were observed over time in most regions. At baseline, higher amyloid burden was related to smaller volumes of the hippocampus, amygdala, putamen, and lateral ventricles; and thinner entorhinal cortex, precuneus and posterior cingulate cortex. At follow‐up, subjects with higher baseline amyloid burden showed greater loss of volume and thickness in mainly temporal and parietal regions, as well as amygdala and hippocampal volume (Figure 1). Conclusion: In the largely asymptomatic AMYPAD PNHS cohort, we show that amyloid burden at baseline is predictive of future neurodegeneration, especially affecting temporal volume and parietal thickness. Cortical thickness was slightly more sensitive towards amyloid burden at baseline, while loss of cortical volume was greater than loss of thickness. [ABSTRACT FROM AUTHOR]

Background: Remote monitoring technologies (RMTs), such as smartphone apps and smartwatches, are changing the way functional and cognitive performance are measured in Alzheimer's disease (AD). Due to their sensitivity, objectivity, and the option of long‐term and continuous measurement, RMTs have the potential to detect a subtle decline in the earliest stages of AD. Here, we present the results of the European RADAR‐AD project (Remote Assessment of Disease and Relapse – Alzheimer's disease), which aims to test feasibility, acceptability and validity of RMT measures across all stages of AD, from cognitively normal to mild dementia. Method: Four study groups (amyloid negative healthy controls, and amyloid positive preclinical AD, prodromal AD, mild‐to‐moderate AD) were included in this cross‐sectional study (N = 175). During 8 weeks, participants wore two activity trackers (Fitbit and Axivity) measuring physical activity, heart rate and sleep continuously, and used two interactive smartphone apps (Mezurio and Altoida's research algorithm: DNS‐MCI) measuring cognition daily/weekly. At baseline, participants underwent extensive neuropsychological, physical examinations, and did two sensor‐based tests (banking app and walk test). Features were extracted for all RMTs (Figure 1) and compared across groups using ANCOVA, with adjustment for relevant confounders. This study is part of an ongoing investigation into high‐end multimodal analyses for real‐world functional performance of continuous RMT data streams. Result: Compliance was high, but decreased with cognitive impairment (feasibility). User experience did not differ between groups but was lower for smartwatches compared to interactive smartphone apps (Table 1) (acceptability). Various individual sensors discriminated symptomatic AD participants from asymptomatic participants (p<0.05), for example the two active apps, but did not discriminate preclinical AD from healthy controls (Table 1) (validity). Conclusion: The RADAR‐AD study provides unique insights in the feasibility, acceptability, and validity of remote monitoring of functional abilities in AD and their potential to differentiate between syndromic stages. This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking (grant No 806999) and their associated partners. 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. [ABSTRACT FROM AUTHOR]

Background: Augmented reality apps merge real world with virtual experiences and can be used to remotely assess complex instrumental activities of daily living (iADL) that are affected early in Alzheimer's disease (AD). Our aim was to compare standard clinical measures with an augmented reality app to assess iADL that are related to memory and spatial navigation in early AD and its feasibility in the home‐setting. Method: We administered an augmented reality app (Altoida Inc., Washington DC, USA) in an on‐going cross‐sectional study (RADAR‐AD: Remote Assessment of Disease and Relapse – Alzheimer's Disease) in three groups: 1) amyloid negative healthy controls (HC, N = 49); and amyloid positive 2) preclinical AD (PreAD, N = 17); and 3) prodromal AD (ProAD, N = 29) (Table 1). Altoida's research algorithm DNS‐MCI (Digital Neuro Signature) produces the outcome of a machine learning model trained to identify cognitively normal individuals from those with cognitive impairment). DNS‐MCI reflects performance in app‐based tasks assessing memory and visuo‐spatial function (placing and finding virtual objects, fire drill simulation) further including attention and motor performance (reaction time, finger tapping, navigational trajectory). At baseline, app‐based tasks were performed in the clinic together with a standard neuropsychological assessment and iADL questionnaires (Figure 1). Participants were furthermore given the option of using Altoida in the home environment. Result: The DNS‐MCI score could significantly distinguish HC and PreAD participants from the ProAD group and was correlated with all neuropsychological tests and iADL questionnaires (Figures 1 and 2). Participants used the app on average 3‐4 times at home (Table 1). Baseline in‐clinic assessments were strongly correlated with at‐home assessments (r = 0.53, p<.001). Conclusion: App‐based augmented reality tasks are applicable in the home setting and successful in capturing cognitive impairment in early AD. Future research should focus on fine graining algorithms to also detect possible subtle impairment in preAD. 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. [ABSTRACT FROM AUTHOR]

Background: The choroid plexus (CP) is responsible for the production of cerebrospinal fluid (CSF), transport of proteins to the CSF and clearance of proteins from the CSF. The CP becomes compromised during aging, which is exacerbated in AD. Nonetheless, the relation between CP and AD pathophysiology remains unclear. We aim to investigate the pathophysiology underlying the CP involvement in AD, utilizing human CSF proteomics and mouse CP transcriptomics. Method: We included 526 individuals from EMIF‐AD MBD, St Louis Knight ADRC and Maastricht BB‐ACL studies. Based on CSF Aβ1‐42 (A, data‐driven cut‐offs), individuals were classified as controls (cognitively normal (CN) A‐, n = 171) or as amyloid‐positive (CN A+, n = 120; mild cognitive impairment (MCI) A+, n = 154; AD A+, n = 81). CSF proteomic data were generated using TMT spectrometry and protein concentrations were compared using ANOVA adjusted for age and sex. Transcriptomic was performed in CP tissue of APPNL‐G‐F (n = 17) and wild‐type C57BL/6J (n = 17) mice using Illumina RNA‐Seq and differential expression analysis was conducted. Next, Gene Ontology and Ingenuity Pathway analyses were performed. For proteomics, high expression of proteins in the CP was identified based on Allen Brain Atlas and the R package ABAEnrichment. Result: In CN A+, 51 proteins were increased and 21 decreased relative to controls. Out of those increased proteins, 57% were enriched for expression in the CP (ABAEnrichment P<0.001, Figure 1) and were associated with lysosomes and the CLEAR pathway, extracellular matrix and coagulation. A similar pattern was observed for both MCI A+ and AD A+ compared to controls, with a significant percentage of increased proteins enriched for expression in the CP (22 to 30%), which are related to lysosomes and the CLEAR pathway, extracellular matrix and coagulation. In APPNL‐G‐F compared to wild‐type mice, CP transcriptomics revealed 313 upregulated and 198 downregulated genes (Figure 2). The upregulated genes were also associated with the lysosomes and the CLEAR pathway, as well as energy metabolism and lipids. Conclusion: Human proteomics and mice transcriptomics studies suggest an association between amyloid pathology, CP functioning and lysosomes. Dysfunction of lysosomes in AD could relate to compromised clearing events. This is important for future research and AD treatment development. [ABSTRACT FROM AUTHOR]

Background: Little is known about the genetic factors and downstream molecular pathways determining individual variability in fluid and imaging biomarkers associated with Alzheimer's disease(AD). We studied polygenic risk scores (PRS) and pathway‐specific PRS in relationship with AD fluid and imaging biomarkers, in non‐demented individuals from the European Prevention of Alzheimer's Dementia (EPAD) cohort. Method: EPAD inclusion criteria were age>50 and Clinical Dementia Rating≤0.5 (n = 1886, Table 1). AD‐PRS was based on 85 previously identified loci, including and excluding APOE (PRSAPOE, PRSnoAPOE)[1]. Using gene‐variant and variant‐pathway mapping[2], six pathway‐specific PRSnoAPOE were identified:1) immune‐activation, 2) signal‐transduction, 3) inflammatory‐response, 4) migration, 5) amyloid‐production, and 6) clearance. Linear models were used to assess the relationship of all PRS with fluid AD biomarkers, including Aβ1‐42, p‐Tau181, and t‐tau; and several imaging biomarkers, including hippocampal volume, global and lobar white matter hyperintensities (WMH) volumes, fractional anisotropy (FA) in 14 regions of interest from diffusion tensor imaging, and 10 resting‐state network connectivity from functional MRI. Models were adjusted for age, sex, site, and multiple comparisons. Result: Models' coefficients are reported in Table 2. PRSAPOE was significantly associated with decreased Aβ1‐42, and increased p‐Tau181 and t‐Tau. PRSnoAPOE showed a weaker, but still significant, negative association with Aβ1‐42 levels, and a significant positive association with p‐Tau181 and t‐Tau. Aβ1‐42 was only significantly associated with the migration, amyloid, and clearance pathways, while all pathways were significantly positively associated with p‐Tau181 and t‐Tau. Hippocampal volume was only significantly associated with PRSAPOE. Regarding WMH load, PRSAPOE showed a positive association with global, frontal periventricular, and parietal deep lobes. Furthermore, the clearance pathway was related to WMH load in all regions, most strongly in periventricular areas. Only the migration pathway was related to increases in FA in the splenium, body, and genu of the corpus callosum. Only the PRSAPOE was related to reduced functional connectivity (FC) in the default mode, control, and visual networks. Conclusion: We show that genetic risk beyond APOE facilitates the manifestation of AD related pathologies. Moreover, clearance and migration pathways were associated with neuroimaging measures of white matter integrity, while FC and hippocampal volume were associated with overall AD genetic risk. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common cause of dementia, and due to increasing life expectancy the number of patients is expected to grow. The diagnosis of AD involves the use of biomarkers determined by an amyloid PET scan or cerebrospinal fluid analyses that are either invasive or expensive, and not available in each hospital, thus limiting their usage as a front-line screener. The TearAD study aims to use tear fluid as a potential source for AD biomarkers. In previous reports, we demonstrated that AD biomarkers amyloid-beta and tau, are measurable in tear fluid and are associated with disease severity and neurodegeration. This study aims to validate previous results in a larger cohort and evaluate the diagnostic accuracy of tear biomarkers to discriminate between individuals with and without neurodegeneration as determined by hippocampal atrophy. Methods: The TearAD study is an observational longitudinal multi-center study that will enroll 50 cognitively healthy controls, 50 patients with subjective cognitive decline, 50 patients with mild cognitive impairment and 50 patients with AD dementia from the memory clinic. Participants will be examined at baseline, after one year, and after two years follow-up. Study assessments include neuropsychological tests and ophthalmic examination. All participants will receive a MRI scan, and a subset of the study population will undergo cerebral spinal fluid collection and an amyloid PET scan. Tear fluid will be collected with Schirmer strips and levels of Aβ38, Aβ40, Aβ42, t-tau and p-tau in tear fluid will be determined using multiplex immunoassays. Blood samples will be collected from all participants. Images of the retina will be obtained with a standard, hyperspectral and ultra-wide field fundus camera. Additionally, macular pigment optical density will be measured with the macular pigment reflectometer, and cross-sectional images of the retina will be obtained through optical coherence tomography imaging. Discussion: The TearAD study will provide insight into the potential diagnostic use of tear biomarkers as a minimally invasive and low cost tool for the screening and diagnosis of AD. Trial registration: Retrospectively registered at clinicaltrials.gov (NCT05655793). [ABSTRACT FROM AUTHOR]

Background: As cerebrovascular and Alzheimer's proteinopathy have previously shown to affect cerebral blood flow (CBF) as well as cognition, CBF could be a potential early hemodynamic biomarker of cognitive decline. Here, we investigated to what extent cardiovascular risk factors and amyloid burden affect CBF in an elderly cognitively unimpaired (CU) population. Method: We included 153 CU participants (minimal MMSE = 28) from the EMIF‐AD PreclinAD Twin60++ cohort (Table 1), who underwent [18F]flutemetamol PET and arterial spin labeling (ASL) MRI. Amyloid‐PET scans were visually assessed as negative or positive, upon which participants were grouped based on their longitudinal changes in amyloid positivity (visual read groups). Cortical amyloid burden was quantified with the Centiloid method globally and for 4 early amyloid accumulation regions of interest (ROIs). ASL scans were processed and quantified with ExploreASL for total gray matter (GM), and for vascular territories overlapping with the amyloid ROIs (Figure 1). Longitudinal analysis including baseline Centiloid values and yearly CBF change rates (Delta CBF) was performed for 98 participants with longitudinal imaging data available (4.23 years ± 0.43 follow‐up time). Associations between CBF and amyloid — with and without the interaction of vascular risk factors (i.e., Framingham score) — were assessed using generalized estimating equations (GEEs), both for baseline and rates of change measurements. Models were adjusted for age, sex, and twin dependency. Result: While no association between amyloid burden and CBF was observed across the cohort, in participants with a high Framingham vascular risk score, higher amyloid was associated with increased CBF, for most ROIs (Table 2, Figure 2). Additionally, precuneus amyloid burden was predictive of CBF change in the corresponding vascular territory (Figure 3). Visual reading shows that subjects with high amyloid burden at baseline had a higher increase of CBF at follow‐up (Stable AB+, Figure 4). Conclusion: We found that the combination of cardiovascular risk and amyloid burden in AD signature regions was associated with increased CBF in CU individuals, which may reflect a vascular or inflammatory compensatory response to early Alzheimer pathology. Future studies may help understanding how these mechanisms affect cognition. [ABSTRACT FROM AUTHOR]

Background: Previous consensus initiatives on outcomes in Alzheimer's disease (AD) have focused on clinical trials, may not be applicable to real‐world settings, and did not necessarily consider a comprehensive list or prioritize outcomes. The aim of this initiative was to achieve consensus among experts on priority outcomes and outcome measures for use in clinical practice when caring for patients with symptomatic AD. Method: The Consensus Group consisted of 20 international voting members and a non‐voting Chair representing diverse specialities relevant to AD. A Delphi approach was used to generate shortlists of the most important outcomes and measures, and to develop consensus statements/recommendations (Figure 1). Initial lists of outcomes/measures were obtained from the ROADMAP project (roadmap‐alzheimer.org), and panel members were given the opportunity to suggest additional ones. The threshold for consensus was predefined as ≥70% voting "agree" or "strongly agree". Shortlists of outcomes and measures were ranked by priority, their relative importance for mild and moderate disease was indicated, and assessment frequency was recommended. The modified GRADE criteria were used to rate the strength of recommendations and quality of evidence. Result: Strong consensus was readily reached on 37 statements/recommendations, grouped by 'General Considerations' (9) and nine domains (28) (Table 1), as well as on priority shortlists of outcomes and measures across the nine domains; an example of a priority shortlist for the domain 'Cognitive abilities' is shown in Table 2. The level of evidence for most items was low; therefore, most statements are based on panelists' expert opinion. Key recommendations include: patient quality of life (QoL) outcome assessments should measure what the person performs well in addition to deficits, and take into account the values of patients and/or caregivers; there is a need for a more comprehensive measure to assess language and communication; 'functional ability & dependency' should include an assessment of motor function. Conclusion: This Delphi consensus highlights outcomes of highest importance in AD from a professional perspective and includes recommendations regarding the most appropriate measures for use in clinical practice. Further studies are needed to raise the strength of the recommendations and to explore patient/caregiver views. [ABSTRACT FROM AUTHOR]

Introduction: We aim to provide guidance on outcomes and measures for use in patients with Alzheimer's clinical syndrome. Methods: A consensus group of 20 voting members nominated by 10 professional societies, and a non‐voting chair, used a Delphi approach and modified GRADE criteria. Results: Consensus was reached on priority outcomes (n = 66), measures (n = 49) and statements (n = 37) across nine domains. A number of outcomes and measurement instruments were ranked for: Cognitive abilities; Functional abilities/dependency; Behavioural and neuropsychiatric symptoms; Patient quality of life (QoL); Caregiver QoL; Healthcare and treatment‐related outcomes; Medical investigations; Disease‐related life events; and Global outcomes. Discussion: This work provides indications on the domains and ideal pertinent measurement instruments that clinicians may wish to use to follow patients with cognitive impairment. More work is needed to develop instruments that are more feasible in the context of the constraints of clinical routine. [ABSTRACT FROM AUTHOR]