Amyloid-PET imaging predicts functional decline in clinically normal individuals.

BACKGROUND: There is good evidence that elevated amyloid-ß (Aß) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aß burden and decline in daily living activities in this population. Moreover, Aß-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. METHODS: Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aß groups (CL < 12 = Aß-, 12 ≤ CL ≤ 50 = Aß-intermediate/Aß± , CL > 50 = Aß+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. RESULTS: Participants included 765 Aß- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aß± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aß+ individuals (15%, Mdnage = 73.0, IQRage = 68.0-78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p = .002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aß+ CN individuals (HRAß+ vs Aß- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAß+ vs Aß- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAß+ vs Aß- = -0.693/year, 95% CI [-1.179,-0.208], p = .005). CONCLUSIONS: Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. TRIAL REGISTRATION: The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.

Continuous ß-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity.

BACKGROUND AND OBJECTIVES: Discordance between CSF and PET biomarkers of ß-amyloid (Aß) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aß-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aß, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories. METHODS: Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aß42 and global Aß-PET to a hyperbolic regression model, deriving a participant-specific Aß-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aß and positive values more aggregated relative to soluble Aß. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aß-aggregation scores. With linear mixed models, we assessed whether Aß-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years). RESULTS: The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aß-aggregation scores were associated with larger ventricular volume (ß = 0.13, p < 0.001), male sex (ß = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (ß = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (ß = 0.17, p < 0.001) and t-tau (ß = 0.16, p < 0.001), better baseline executive functioning (ß = 0.12, p < 0.001), and slower global cognitive decline (ß = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition. DISCUSSION: We propose a novel continuous model of Aß CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aß pools in 2 independent cohorts across the full Aß continuum. Aß-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

The clinical importance of suspected non-Alzheimer disease pathophysiology.

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

Feasibility and usability of remote monitoring in Alzheimer's disease.

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.

Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study.

INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-ß (Aß) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aß-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.

Facilitating clinical use of the Amsterdam Instrumental Activities of Daily Living Questionnaire: Normative data and a diagnostic cutoff value.

OBJECTIVE: The Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q) is well validated and commonly used to assess difficulties in everyday functioning regarding dementia. To facilitate interpretation and clinical implementation across different European countries, we aim to provide normative data and a diagnostic cutoff for dementia. METHODS: Cross-sectional data from Dutch Brain Research Registry (N = 1,064; mean (M) age = 62 ± 11 year; 69.5% female), European Medial Information Framework-Alzheimer's Disease 90 + (N = 63; Mage = 92 ± 2 year; 52.4% female), and European Prevention of Alzheimer's Dementia Longitudinal Cohort Study (N = 247; Mage = 63 ± 7 year; 72.1% female) were used. The generalized additive models for location, scale, and shape framework were used to obtain normative values (Z-scores). The beta distribution was applied, and combinations of age, sex, and educational attainment were modeled. The optimal cutoff for dementia was calculated using area under receiver operating curves (AUC-ROC) and Youden Index, using data from Amsterdam Dementia Cohort (N = 2,511, Mage = 64 ± 8 year, 44.4% female). RESULTS: The best normative model accounted for a cubic-like decrease of IADL performance with age that was more pronounced in low compared to medium/high educational attainment. The cutoff for dementia was 1.85 standard deviation below the population mean (AUC = 0.97; 95% CI [0.97-0.98]). CONCLUSION: We provide regression-based norms for A-IADL-Q and a diagnostic cutoff for dementia, which help improve clinical assessment of IADL performance across European countries.

Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia.

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins (proximity extension-based (PEA) immunoassays) in a deeply-phenotyped mixed-memory clinic cohort (n=502, mean age (sd) = 64.1 [8.7] years, 181 female [35.4%]), including patients with Alzheimer's disease (AD, n=213), dementia with Lewy bodies (DLB, n=50) and frontotemporal dementia (FTD, n=93), and controls (n=146). Validation was assessed in independent cohorts (n=99 PEA platform, n=198, MRM-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1-CR2 (rs3818361, P=1.65e-08), ZCWPW1-PILRB (rs1476679, P=2.73e-32), CTSH-CTSH (rs3784539, P=2.88e-24) and HESX1-RETN (rs186108507, P=8.39e-08), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90e-7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for frontotemporal dementia, either for the total sample as for analyses performed within FTD only. pQTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia.

Depressive Symptoms and Plasma Markers of Alzheimer's Disease and Neurodegeneration: A Coordinated Meta-Analysis of 8 Cohort Studies.

BACKGROUND: Depressive symptoms are associated with an increased risk of Alzheimer's disease (AD). There has been a recent emergence in plasma biomarkers for AD pathophysiology, such as amyloid-beta (Aß) and phosphorylated tau (p-tau), as well as for axonal damage (neurofilament light, NfL) and astrocytic activation (glial fibrillary acidic protein, GFAP). Hypothesizing that depressive symptoms may occur along the AD process, we investigated associations between plasma biomarkers of AD with depressive symptoms in individuals without dementia. METHODS: A two-stage meta-analysis was performed on 2 clinic-based and 6 population-based cohorts (N = 7210) as part of the Netherlands Consortium of Dementia Cohorts. Plasma markers (Aß42/40, p-tau181, NfL, and GFAP) were measured using Single Molecular Array (Simoa; Quanterix) assays. Depressive symptoms were measured with validated questionnaires. We estimated the cross-sectional association of each standardized plasma marker (determinants) with standardized depressive symptoms (outcome) using linear regressions, correcting for age, sex, education, and APOE ε4 allele presence, as well as subgrouping by sex and APOE ε4 allele. Effect estimates were entered into a random-effects meta-analysis. RESULTS: Mean age of participants was 71 years. The prevalence of clinically relevant depressive symptoms ranged from 1% to 22%. None of the plasma markers were associated with depressive symptoms in the meta-analyses. However, NfL was associated with depressive symptoms only in APOE ε4 carriers (ß 0.11; 95% CI: 0.05-0.17). CONCLUSIONS: Late-life depressive symptoms did not show an association to plasma biomarkers of AD pathology. However, in APOE ε4 allele carriers, a more profound role of neurodegeneration was suggested with depressive symptoms.

Plasma Markers of Alzheimer's Disease Pathology, Neuronal Injury, and Astrocytic Activation and MRI Load of Vascular Pathology and Neurodegeneration: The SMART-MR Study.

BACKGROUND: Two of the main causes for dementia are Alzheimer's disease (AD) and vascular pathology, with most patients showing mixed pathology. Plasma biomarkers for Alzheimer's disease-related pathology have recently emerged, including Aß (amyloid-beta), p-tau (phosphorylated tau), NfL (neurofilament light), and GFAP (glial fibrillary acidic protein). There is a current gap in the literature regarding whether there is an association between these plasma biomarkers with vascular pathology and neurodegeneration. METHODS AND RESULTS: Cross-sectional data from 594 individuals (mean [SD] age: 64 [8] years; 17% female) were included from the SMART-MR (Second Manifestations of Arterial Disease-Magnetic Resonance) study, a prospective cohort study of individuals with a history of arterial disease. Plasma markers were assessed using single molecular array assays (Quanterix). Magnetic resonance imaging markers included white matter hyperintensity volume, presence of infarcts (yes/no), total brain volume, and hippocampal volume assessed on 1.5T magnetic resonance imaging. Linear regressions were performed for each standardized plasma marker with white matter hyperintensity volume, total brain volume, and hippocampal volume as separate outcomes, correcting for age, sex, education, and intracranial volume. Logistic regressions were performed for the presence of lacunar and cortical infarcts. Higher p-tau181 was associated with larger white matter hyperintensity volume (b per SD increase=0.16 [95% CI, 0.06-0.26], P=0.015). Higher NfL (b=-5.63, [95% CI, -8.95 to -2.31], P=0.015) was associated with lower total brain volume and the presence of infarcts (odds ratio [OR], 1.42 [95% CI, 1.13-1.78], P=0.039). Higher GFAP levels were associated with cortical infarcts (OR, 1.45 [95% CI, 1.09-1.92], P=0.010). CONCLUSIONS: Plasma biomarkers that have been associated with tau pathology, axonal injury, and astrocytic activation are related to magnetic resonance imagingmarkers of vascular pathology and neurodegeneration in patients with manifest arterial disease.

The association of glucose metabolism measures and diabetes status with Alzheimer's disease biomarkers of amyloid and tau: A systematic review and meta-analysis.

Conflicting evidence exists on the relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) biomarkers. Therefore, we conducted a random-effects meta-analysis to evaluate the correlation of glucose metabolism measures (glycated hemoglobin, fasting blood glucose, insulin resistance indices) and DM status with AD biomarkers of amyloid-ß and tau measured by positron emission tomography or cerebrospinal fluid. We selected 37 studies from PubMed and Embase, including 11,694 individuals. More impaired glucose metabolism and DM status were associated with higher tau biomarkers (r=0.11[0.03-0.18], p=0.008; I2=68%), but were not associated with amyloid-ß biomarkers (r=-0.06[-0.13-0.01], p=0.08; I2=81%). Meta-regression revealed that glucose metabolism and DM were specifically associated with tau biomarkers in population settings (p=0.001). Furthermore, more impaired glucose metabolism and DM status were associated with lower amyloid-ß biomarkers in memory clinic settings (p=0.004), and in studies with a higher prevalence of dementia (p<0.001) or lower cognitive scores (p=0.04). These findings indicate that DM is associated with biomarkers of tau but not with amyloid-ß. This knowledge is valuable for improving dementia and DM diagnostics and treatment.

Cerebrospinal fluid proteomics in patients with Alzheimer's disease reveals five molecular subtypes with distinct genetic risk profiles.

Alzheimer's disease (AD) is heterogenous at the molecular level. Understanding this heterogeneity is critical for AD drug development. Here we define AD molecular subtypes using mass spectrometry proteomics in cerebrospinal fluid, based on 1,058 proteins, with different levels in individuals with AD (n = 419) compared to controls (n = 187). These AD subtypes had alterations in protein levels that were associated with distinct molecular processes: subtype 1 was characterized by proteins related to neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood-brain barrier impairment. Each subtype was related to specific AD genetic risk variants, for example, subtype 1 was enriched with TREM2 R47H. Subtypes also differed in clinical outcomes, survival times and anatomical patterns of brain atrophy. These results indicate molecular heterogeneity in AD and highlight the need for personalized medicine.

People get ready! A new generation of Alzheimer's therapies may require new ways to deliver and pay for healthcare.

The development of disease-modifying therapies (DMTs) for Alzheimer's disease (AD) has progressed over the last decade, and the first-ever therapies with potential to slow the progression of disease are approved in the United States. AD DMTs could provide life-changing opportunities for people living with this disease, as well as for their caregivers. They could also ease some of the immense societal and economic burden of dementia. However, AD DMTs also come with major challenges due to the large unmet medical need, high prevalence of AD, new costs related to diagnosis, treatment and monitoring, and uncertainty in the therapies' actual clinical value. This perspective article discusses, from the broad perspective of various health systems and stakeholders, how we can overcome these challenges and improve society's readiness for AD DMTs. We propose that innovative payment models such as performance-based payments, in combination with learning healthcare systems, could be the way forward to enable timely patient access to treatments, improve accuracy of cost-effectiveness evaluations and overcome budgetary barriers. Other important considerations include the need for identification of key drivers of patient value, the relevance of different economic perspectives (i.e. healthcare vs. societal) and ethical questions in terms of treatment eligibility criteria.

Contributions of amyloid beta and cerebral small vessel disease in clinical decline.

INTRODUCTION: We assessed whether co-morbid small vessel disease (SVD) has clinical predictive value in preclinical or prodromal Alzheimer's disease. METHODS: In 1090 non-demented participants (65.4 ± 10.7 years) SVD was assessed with magnetic resonance imaging and amyloid beta (Aß) with lumbar puncture and/or positron emission tomography scan (mean follow-up for cognitive function 3.1 ± 2.4 years). RESULTS: Thirty-nine percent had neither Aß nor SVD (A-V-), 21% had SVD only (A-V+), 23% Aß only (A+V-), and 17% had both (A+V+). Pooled cohort linear mixed model analyses demonstrated that compared to A-V- (reference), A+V- had a faster rate of cognitive decline. Co-morbid SVD (A+V+) did not further increase rate of decline. Cox regression showed that dementia risk was modestly increased in A-V+ (hazard ratio [95% confidence interval: 1.8 [1.0-3.2]) and most strongly in A+ groups. Also, mortality risk was increased in A+ groups. DISCUSSION: In non-demented persons Aß was predictive of cognitive decline, dementia, and mortality. SVD modestly predicts dementia in A-, but did not increase deleterious effects in A+. HIGHLIGHTS: Amyloid beta (Aß; A) was predictive for cognitive decline, dementia, and mortality. Small vessel disease (SVD) had no additional deleterious effects in A+. SVD modestly predicted dementia in A-. Aß should be assessed even when magnetic resonance imaging indicates vascular cognitive impairment.

Augmented reality versus standard tests to assess cognition and function in early Alzheimer's disease.

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 < 0.001). The digital score was associated with the clinical cognitive score (rho = 0.56, p < 0.001). No learning effects were found. Here we report the AR app distinguishes HC from otherwise healthy Aß-positive individuals, both in the outpatient setting and at home, which is currently not possible with standard cognitive tests.

Contributions of Vascular Burden and Amyloid Abnormality to Cognitive Decline in Memory Clinic Patients.

Background: Alzheimer's disease pathology and vascular burden are highly prevalent and often co-occur in elderly. It remains unclear how both relate to cognitive decline. Objective: To investigate whether amyloid abnormality and vascular burden synergistically contribute to cognitive decline in a memory clinic population. Methods: We included 227 patients from Maastricht and Aachen memory clinics. Amyloid abnormality (A+) was defined by CSF Aß42 using data-driven cut-offs. Vascular burden (V+) was defined as having moderate to severe white matter hyperintensities, or any microbleeds, macrohemorrhage or infarcts on MRI. Longitudinal change in global cognition, memory, processing speed, executive functioning, and verbal fluency was analysed across the A-V-, A-V+, A+V-, A+V+ groups by linear mixed models. Additionally, individual MRI measures, vascular risk and vascular disease were used as V definitions. Results: At baseline, the A+V+ group scored worse on global cognition and verbal fluency compared to all other groups, and showed worse memory compared to A-V+ and A-V- groups. Over time (mean 2.7+ - 1.5 years), A+V+ and A+V- groups showed faster global cognition decline than A-V+ and A-V- groups. Only the A+V- group showed decline on memory and verbal fluency. The A-V+ group did not differ from the A-V- group. Individual MRI vascular measures only indicated an independent association of microbleeds with executive functioning decline. Findings were similar using other V definitions. Conclusions: Our study demonstrates that amyloid abnormality predicts cognitive decline independent from vascular burden in a memory clinic population. Vascular burden shows a minor contribution to cognitive decline in these patients. This has important prognostic implications.

Correction: Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study.

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

Is the association between blood pressure and cognition in the oldest-old modified by physical, vascular or brain pathology markers? The EMIF-AD 90 + Study.

BACKGROUND: Prior studies suggest a changing association between blood pressure (BP) and cognition with aging, however work in the oldest-old has yielded ambiguous results. Potentially, these mixed results can be explained by modifying factors. The aim of this study was to establish whether physical, vascular or brain pathology markers that describe a state of increased vulnerability, affect the association between BP and cognition in the oldest-old. Results may influence clinicians' decisions regarding the use of antihypertensives in this age group. METHODS: We included 122 individuals (84 without cognitive impairment and 38 with cognitive impairment) from the EMIF-AD 90 + Study (mean age 92.4 years). First, we tested cross-sectional associations of systolic and diastolic BP with a cognitive composite score. Second, we tested whether these associations were modified by physical markers (waist circumference, muscle mass, gait speed and handgrip strength), vascular markers (history of cardiac disease, carotid intima media thickness as a proxy for atherosclerosis and carotid distensibility coefficient as a proxy for arterial stiffness) or brain pathology markers (white matter hyperintensities and cortical thickness). RESULTS: In the total sample, there was no association between BP and cognition, however, waist circumference modified this association (p-value for interaction with systolic BP: 0.03, with diastolic BP: 0.01). In individuals with a high waist circumference, higher systolic and diastolic BP tended to be associated with worse cognition, while in individuals with a low waist circumference, higher systolic BP was associated with better cognition. The others physical, vascular and brain pathology markers did not modify the association between BP and cognition. CONCLUSIONS: When examining various markers for physical, vascular and brain vulnerability, only waist circumference affected the association between BP and cognition. This warrants further research to evaluate whether waist circumference may be a marker in clinical practice influencing the use of antihypertensives in the oldest-old.

Recruitment of pre-dementia participants: main enrollment barriers in a longitudinal amyloid-PET study.

BACKGROUND: The mismatch between the limited availability versus the high demand of participants who are in the pre-dementia phase of Alzheimer's disease (AD) is a bottleneck for clinical studies in AD. Nevertheless, potential enrollment barriers in the pre-dementia population are relatively under-reported. In a large European longitudinal biomarker study (the AMYPAD-PNHS), we investigated main enrollment barriers in individuals with no or mild symptoms recruited from research and clinical parent cohorts (PCs) of ongoing observational studies. METHODS: Logistic regression was used to predict study refusal based on sex, age, education, global cognition (MMSE), family history of dementia, and number of prior study visits. Study refusal rates and categorized enrollment barriers were compared between PCs using chi-squared tests. RESULTS: 535/1856 (28.8%) of the participants recruited from ongoing studies declined participation in the AMYPAD-PNHS. Only for participants recruited from clinical PCs (n = 243), a higher MMSE-score (ß = - 0.22, OR = 0.80, p < .05), more prior study visits (ß = - 0.93, OR = 0.40, p < .001), and positive family history of dementia (ß = 2.08, OR = 8.02, p < .01) resulted in lower odds on study refusal. General study burden was the main enrollment barrier (36.1%), followed by amyloid-PET related burden (PCresearch = 27.4%, PCclinical = 9.0%, X2 = 10.56, p = .001), and loss of research interest (PCclinical = 46.3%, PCresearch = 16.5%, X2 = 32.34, p < .001). CONCLUSIONS: The enrollment rate for the AMYPAD-PNHS was relatively high, suggesting an advantage of recruitment via ongoing studies. In this observational cohort, study burden reduction and tailored strategies may potentially improve participant enrollment into trial readiness cohorts such as for phase-3 early anti-amyloid intervention trials. The AMYPAD-PNHS (EudraCT: 2018-002277-22) was approved by the ethical review board of the VU Medical Center (VUmc) as the Sponsor site and in every affiliated site.

Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning.

BACKGROUND: Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (ß-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. METHODS: We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. RESULTS: Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. CONCLUSIONS: These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.