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Abstract Background There is good evidence that elevated amyloid-β (Aβ) 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 Aβ burden and decline in daily living activities in this population. Moreover, Aβ-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 Aβ groups (CL 50 = Aβ+). 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 Aβ- (61%, Mdn age = 66.0, IQR age = 61.0–71.0; 59% women), 301 Aβ± (24%; Mdn age = 69.0, IQR age = 64.0–75.0; 53% women) and 194 Aβ+ individuals (15%, Mdn age = 73.0, IQR age = 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 (b CL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (b CL*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 Aβ+ CN individuals (HR Aβ+ vs Aβ- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (b Aβ+ vs Aβ- = 0.137/year, 95% CI [0.069,0.206], p

Abstract Objective Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non‐invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE‐ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non‐demented older adults. Methods Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β1‐42 and p‐Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow‐up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed‐effects model for each tract. Results AD pathology, APOE‐ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE‐ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. Interpretation Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

Abstract Background The Eatwell guide reflects the UK government's recommendations for a healthy and balanced diet. Previous research has identified associations between healthy eating patterns and both cardiovascular and brain health, although there is little evidence specifically focusing on the Eatwell Guide. To date no research has investigated associations between the Eatwell Guide and risk for future dementia. Methods Data from the PREVENT dementia cohort study baseline visit was used in this analysis. Binary and graded Eatwell Guide scores (BEWG, GEWG) were created from a self-reported Food Frequency Questionnaire. The CAIDE score was included as the primary outcome measure to represent risk for future Alzheimer’s disease. Secondary outcome measures included cardiometabolic health measures and brain health measures. Generalised additive models were run in R. Results A total of 517 participants were included in the analysis, with a mean BEWG score of 4.39 (± 1.66) (out of a possible 12 points) and GEWG score of 39.88 (± 6.19) (out of a possible 60 points). There was no significant association between either Eatwell Guide score and the CAIDE score (BEWG β: 0.07, 95% confidence interval (CI): -0.07, 0.22; GEWG β: 0.02, 95% CI: -0.02, 0.06) or any measures of brain health. There was a significant association between higher GEWG score and lower systolic and diastolic blood pressure and body mass index (BMI) (systolic β: -0.24, 95% CI: -0.45, -0.03; diastolic β: -0.16, 95% CI: -0.29, -0.03; BMI β: -0.09, 95% CI: -0.16, -0.01). Conclusions Although not directly associated with the CAIDE score, the Eatwell Guide dietary pattern may be beneficial for dementia prevention efforts through the modification of hypertension and obesity, which are both known risk factors for dementia. Future work could replicate these findings in other UK-based cohorts as well as further development of Eatwell Guide scoring methodologies.

Abstract INTRODUCTION We tested associations between two retinal measures (optic disc pallor, peripapillary retinal nerve fiber layer [pRNFL] thickness) and four magnetic resonance imaging markers of cerebral small vessel disease (SVD; lacunes, microbleeds, white matter hyperintensities, and enlarged perivascular spaces [ePVSs]). METHODS We used PallorMetrics to quantify optic disc pallor from fundus photographs, and pRNFL thickness from optical coherence tomography scans. Linear and logistic regression assessed relationships between retinal measures and SVD markers. Participants (N = 108, mean age 51.6) were from the PREVENT Dementia study. RESULTS Global optic disc pallor was linked to ePVSs in the basal ganglia in both left (β = 0.12, standard error [SE] = 0.05, P

Abstract To date, there is a considerable heterogeneity of methods to score Allostatic Load (AL). Here we propose a comprehensive algorithm (ALCS) that integrates commonly used approaches to generate AL risk categories and assess associations to brain structure deterioration. In a cohort of cognitively normal mid-life adults (n = 620, age 51.3 ± 5.48 years), we developed a comprehensive composite for AL scoring incorporating gender and age differences, high quartile approach, clinical reference values, and current medications, to then generate AL risk categories. Compared to the empirical approach (ALES), ALCS showed better model fit criteria and a strong association with age and sex. ALSC categories were regressed against brain and white matter hyperintensity (WMH) volumes. Higher AL risk categories were associated with increased total, periventricular, frontal, and left parietal WMH volumes, also showing better fit compared to ALES. When cardiovascular biomarkers were removed from the ALSC algorithm, only left-frontal WMHV remained associated with AL, revealing a strong vascular burden influencing the index. Our results agree with previous evidence and suggest that sustained stress exposure enhances brain deterioration in mid-life adults. Showing better fit than ALES, our comprehensive algorithm can provide a more accurate AL estimation to explore how stress exposure enhances age-related health decline.

Abstract 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 (β = − 0.22, OR = 0.80, p

IntroductionAs the global population ages, the economic, societal, and personal burdens associated with worsening cognition and dementia onset are growing. It is therefore becoming ever more critical to understand the factors associated with cognitive decline. One such factor is sleep. Adequate sleep has been shown to maintain cognitive function and protect against the onset of chronic disease, whereas sleep deprivation has been linked to cognitive impairment and the onset of depression and dementia.ObjectivesHere, we aim to identify and explore mechanistic links between several sleep parameters, depressive symptoms and cognition in a cohort of middle-aged adults.MethodsWe investigated data from the PREVENT dementia programme via structural equation modeling to illustrate links between predictor variables, moderator variables, and two cognitive constructs (i.e., Executive Function and Memory).ResultsOur model demonstrated that sleep quality, and total hours of sleep were related to participants' depressive symptoms, and that, participant apathy was related to higher scores on the Epworth Sleepiness and Lausanne NoSAS Scales. Subsequently, depressive symptoms, but not sleep or apathy ratings, were associated with Executive Function.ConclusionsWe provide evidence for an indirect relationship between sleep and cognition mediated by depressive symptoms in a middle-aged population. Our results provide a base from which cognition, dementia onset, and potential points of intervention, may be better understood.

Abstract Background The risk of dementia is higher in women than men. The metabolic consequences of estrogen decline during menopause accelerate neuropathology in women. The use of hormone replacement therapy (HRT) in the prevention of cognitive decline has shown conflicting results. Here we investigate the modulating role of APOE genotype and age at HRT initiation on the heterogeneity in cognitive response to HRT. Methods The analysis used baseline data from participants in the European Prevention of Alzheimer’s Dementia (EPAD) cohort (total n= 1906, women= 1178, 61.8%). Analysis of covariate (ANCOVA) models were employed to test the independent and interactive impact of APOE genotype and HRT on select cognitive tests, such as MMSE, RBANS, dot counting, Four Mountain Test (FMT), and the supermarket trolley test (SMT), together with volumes of the medial temporal lobe (MTL) regions by MRI. Multiple linear regression models were used to examine the impact of age of HRT initiation according to APOE4 carrier status on these cognitive and MRI outcomes. Results APOE4 HRT users had the highest RBANS delayed memory index score (P-APOE*HRT interaction = 0.009) compared to APOE4 non-users and to non-APOE4 carriers, with 6–10% larger entorhinal (left) and amygdala (right and left) volumes (P-interaction= 0.002, 0.003, and 0.005 respectively). Earlier introduction of HRT was associated with larger right (standardized β= −0.555, p=0.035) and left hippocampal volumes (standardized β= −0.577, p=0.028) only in APOE4 carriers. Conclusion HRT introduction is associated with improved delayed memory and larger entorhinal and amygdala volumes in APOE4 carriers only. This may represent an effective targeted strategy to mitigate the higher life-time risk of AD in this large at-risk population subgroup. Confirmation of findings in a fit for purpose RCT with prospective recruitment based on APOE genotype is needed to establish causality.

Abstract Background Considerable overlap exists between the risk factors of dementia and cerebral small vessel disease (SVD). However, studies remain limited to older cohorts wherein pathologies of both dementia (e.g. amyloid) and SVD (e.g. white matter hyperintensities) already co-exist. In younger asymptomatic adults, we investigated differential associations and interactions of modifiable and non-modifiable inherited risk factors of (future) late-life dementia to (present-day) mid-life SVD. Methods Cognitively healthy middle-aged adults (aged 40–59; mean 51.2 years) underwent 3T MRI (n = 630) as part of the PREVENT-Dementia study. To assess SVD, we quantified white matter hyperintensities, enlarged perivascular spaces, microbleeds, lacunes, and computed composite scores of SVD burden and subtypes of hypertensive arteriopathy and cerebral amyloid angiopathy (CAA). Non-modifiable (inherited) risk factors were APOE4 status and parental family history of dementia. Modifiable risk factors were derived from the 2020 Lancet Commission on dementia prevention (early/midlife: education, hypertension, obesity, alcohol, hearing impairment, head injuries). Confirmatory factor analysis (CFA) was used to evaluate the latent variables of SVD and risk factors. Structural equation modelling (SEM) of the full structural assessed associations of SVD with risk factors and APOE4*risk interaction. Results In SEM, the latent variable of global SVD related to the latent variable of modifiable midlife risk SVD (β = 0.80, p = .009) but not non-modifiable inherited risk factors of APOE4 or family history of dementia. Interaction analysis demonstrated that the effect of modifiable risk on SVD was amplified in APOE4 non-carriers (β = − 0.31, p = .009), rather than carriers. These associations and interaction effects were observed in relation to the SVD subtype of hypertensive arteriopathy, rather than CAA. Sensitivity analyses using separate general linear models validated SEM results. Conclusions Established modifiable risk factors of future (late-life) dementia related to present-day (mid-life) SVD, suggesting that early lifestyle modifications could potentially reduce rates of vascular cognitive impairment attributed to SVD, a major ‘silent’ contributor to global dementia cases. This association was amplified in APOE4 non-carriers, suggesting that lifestyle modifications could be effective even in those with genetic predisposition to dementia.

Abstract Background Mild cognitive impairment (MCI) is a condition that exists between normal healthy ageing and dementia with an uncertain aetiology and prognosis. This uncertainty creates a complex dynamic between the clinicians’ conception of MCI, what is communicated to the individual about their condition, and how the individual responds to the information conveyed to them. The aim of this study was to explore clinicians’ views around the assessment and communication of MCI in memory clinics. Method As part of a larger longitudinal study looking at patients’ adjustment to MCI disclosure, we interviewed Old Age Psychiatrists at the five participating sites across Scotland. The study obtained ethics approvals and the interviews (carried out between Nov 2020–Jan 2021) followed a semi-structured schedule focusing on [1] how likely clinicians are to use the term MCI with patients; [2] what tests clinicians rely on and how much utility they see in them; and [3] how clinicians communicate risk of progression to dementia. The interviews were voice recorded and were analysed using reflective thematic analysis. Results Initial results show that most clinicians interviewed (Total N = 19) considered MCI to have significant limitations as a diagnostic term. Nevertheless, most clinicians reported using the term MCI (n = 15/19). Clinical history was commonly described as the primary aid in the diagnostic process and also to rule out functional impairment (which was sometimes corroborated by Occupational Therapy assessment). All clinicians reported using the Addenbrooke’s Cognitive Examination-III as a primary assessment tool. Neuroimaging was frequently found to have minimal usefulness due to the neuroradiological reports being non-specific. Conclusion Our study revealed a mixture of approaches to assessing and disclosing test results for MCI. Some clinicians consider the condition as a separate entity among neurodegenerative disorders whereas others find the term unhelpful due to its uncertain prognosis. Clinicians report a lack of specific and sensitive assessment methods for identifying the aetiology of MCI in clinical practice. Our study demonstrates a broad range of views and therefore variability in MCI risk disclosure in memory assessment services which may impact the management of individuals with MCI.

Previous studies have demonstrated an association between adherence to the Mediterranean diet (MedDiet) and better cognitive performance, lower incidence of dementia and lower Alzheimer's disease biomarker burden. The aim of this systematic review was to evaluate the evidence base for MedDiet associations with hippocampal volume and white matter hyperintensity volume (WMHV). We searched systematically for studies reporting on MedDiet and hippocampal volume or WMHV in MedLine, EMBASE, CINAHL and PsycInfo. Searches were initially carried out on 21st July 2021 with final searches run on 23rd November 2022. Risk of bias was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Of an initial 112 papers identified, seven papers were eligible for inclusion in the review reporting on 21,933 participants. Four studies reported on hippocampal volume, with inconclusive or no associations seen with MedDiet adherence. Two studies found a significant association between higher MedDiet adherence and lower WMHV, while two other studies found no significant associations. Overall these results highlight a gap in our knowledge about the associations between the MedDiet and AD and cerebrovascular related structural neuroimaging findings.

Background: Adherence to the Mediterranean diet (MedDiet), a primarily plant-based eating pattern, has been associated with lower dementia incidence. Much of the research has focused on Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI), with less research looking at the preclinical symptomatically silent stages that pre-empt MCI and AD dementia. Although there is evidence from studies conducted globally, no studies have compared the effects of the MedDiet within and outside of the Mediterranean region in one cohort.Methods: Our study explored cross-sectional and longitudinal associations between MedDiet and cognition in the pan-European EPAD LCS, comparing those living within and outside of the Mediterranean region (as classified by European Union biogeographical definitions). After deriving MEDAS scores to quantify adherence to the MedDiet, we used linear regression and linear mixed effects models to test for associations between the MEDAS score and cognitive function measured by the Four Mountains Test (FMT) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). We additionally calculated MEDAS continuous and PYRAMID scores to provide alternative measures of MedDiet adherence.Results: We included 1826 participants, mean age 65.69 (±7.42) years, majority female (56.2%) with family history (65.8%) and minority APOEε4 carriers (38.9%). Higher MEDAS scores were associated with better performance on the FMT both cross-sectionally (n = 1,144, ß: −0.11, SE: 0.04, p = 0.007) and longitudinally (slope: 0.10, 95% CI: 0.04–0.17, p: 0.002). The effect was marginally greater in the Mediterranean region in the cross-sectional analysis, with a stronger effect emerging longitudinally. In exploratory analyses, the association between MEDAS and FMT scores was only seen in female participants. A sensitivity analysis excluding Toulouse and Perugia, as cities near, but not within, the biogeographical region, found significant associations between higher MEDAS and MEDAS continuous scores, and a number of RBANS total and index scores.Conclusion: MedDiet adherence is associated with better FMT scores, with effects seen most strongly in the Mediterranean region from longitudinal data. Our sensitivity analysis suggested a more global cognitive benefit of MedDiet adherence. This study highlights the need to further explore for whom and for what brain health outcomes the MedDiet confers benefit. This evidence would identify a window of opportunity in the life-course to maximise the benefit and better inform public health campaigns and patient-level interventions.

IntroductionTens of millions of people worldwide will develop Alzheimer's disease (AD), and only by intervening early in the preclinical disease can we make a fundamental difference to the rates of late-stage disease where clinical symptoms and societal burden manifest. However, collectively utilizing data, samples, and knowledge amassed by large-scale projects such as the Innovative Medicines Initiative (IMI)-funded European Prevention of Alzheimer's Dementia (EPAD) program will enable the research community to learn, adapt, and implement change.MethodIn the current article, we define and discuss the substantial assets of the EPAD project for the scientific community, patient population, and industry, describe the EPAD structure with a focus on how the public and private sector interacted and collaborated within the project, reflect how IMI specifically supported the achievements of the above, and conclude with a view for future.ResultsThe EPAD project was a €64-million investment to facilitate secondary prevention of AD dementia research. The project recruited over 2,000 research participants into the EPAD longitudinal cohort study (LCS) and included over 400 researchers from 39 partners. The EPAD LCS data and biobank are freely available and easily accessible via the Alzheimer's Disease Data Initiative's (ADDI) AD Workbench platform and the University of Edinburgh's Sample Access Committee. The trial delivery network established within the EPAD program is being incorporated into the truly global offering from the Global Alzheimer's Platform (GAP) for trial delivery, and the almost 100 early-career researchers who were part of the EPAD Academy will take forward their experience and learning from EPAD to the next stage of their careers.DiscussionThrough GAP, IMI-Neuronet, and follow-on funding from the Alzheimer's Association for the data and sample access systems, the EPAD assets will be maintained and, as and when sponsors seek a new platform trial to be established, the learnings from EPAD will ensure that this can be developed to be even more successful than this first pan-European attempt.

Abstract Background Type 2 diabetes is a risk factor for Alzheimer’s disease (AD), and AD brain shows impaired insulin signalling. The role of peripheral insulin resistance on AD aetiopathogenesis in non-diabetic patients is still debated. Here we evaluated the influence of insulin resistance on brain glucose metabolism, grey matter volume and white matter lesions (WMLs) in non-diabetic AD subjects. Methods In total, 130 non-diabetic AD subjects underwent MRI and [18F]FDG PET scans with arterial cannula insertion for radioactivity measurement. T1 Volumetric and FLAIR sequences were acquired on a 3-T MRI scanner. These subjects also had measurement of glucose and insulin levels after a 4-h fast on the same day of the scan. Insulin resistance was calculated by the updated homeostatic model assessment (HOMA2). For [18F]FDG analysis, cerebral glucose metabolic rate (rCMRGlc) parametric images were generated using spectral analysis with arterial plasma input function. Results In this non-diabetic AD population, HOMA2 was negatively associated with hippocampal rCMRGlc, along with total grey matter volumes. No significant correlation was observed between HOMA2, hippocampal volume and WMLs. Conclusions In non-diabetic AD, peripheral insulin resistance is independently associated with reduced hippocampal glucose metabolism and with lower grey matter volume, suggesting that peripheral insulin resistance might influence AD pathology by its action on cerebral glucose metabolism and on neurodegeneration.

Abstract Background The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets. Methods In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). Results We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn’s disease. Conclusions Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.

Abstract Background Recruitment is often a bottleneck in secondary prevention trials in Alzheimer disease (AD). Furthermore, screen-failure rates in these trials are typically high due to relatively low prevalence of AD pathology in individuals without dementia, especially among cognitively unimpaired. Prescreening on AD risk factors may facilitate recruitment, but the efficiency will depend on how these factors link to participation rates and AD pathology. We investigated whether common AD-related factors predict trial-ready cohort participation and amyloid status across different prescreen settings. Methods We monitored the prescreening in four cohorts linked to the European Prevention of Alzheimer Dementia (EPAD) Registry (n = 16,877; mean ± SD age = 64 ± 8 years). These included a clinical cohort, a research in-person cohort, a research online cohort, and a population-based cohort. Individuals were asked to participate in the EPAD longitudinal cohort study (EPAD-LCS), which serves as a trial-ready cohort for secondary prevention trials. Amyloid positivity was measured in cerebrospinal fluid as part of the EPAD-LCS assessment. We calculated participation rates and numbers needed to prescreen (NNPS) per participant that was amyloid-positive. We tested if age, sex, education level, APOE status, family history for dementia, memory complaints or memory scores, previously collected in these cohorts, could predict participation and amyloid status. Results A total of 2595 participants were contacted for participation in the EPAD-LCS. Participation rates varied by setting between 3 and 59%. The NNPS were 6.9 (clinical cohort), 7.5 (research in-person cohort), 8.4 (research online cohort), and 88.5 (population-based cohort). Participation in the EPAD-LCS (n = 413 (16%)) was associated with lower age (odds ratio (OR) age = 0.97 [0.95–0.99]), high education (OR = 1.64 [1.23–2.17]), male sex (OR = 1.56 [1.19–2.04]), and positive family history of dementia (OR = 1.66 [1.19–2.31]). Among participants in the EPAD-LCS, amyloid positivity (33%) was associated with higher age (OR = 1.06 [1.02–1.10]) and APOE ɛ4 allele carriership (OR = 2.99 [1.81–4.94]). These results were similar across prescreen settings. Conclusions Numbers needed to prescreen varied greatly between settings. Understanding how common AD risk factors link to study participation and amyloid positivity is informative for recruitment strategy of studies on secondary prevention of AD.

A key challenge for the secondary prevention of Alzheimer’s dementia is the need to identify individuals early on in the disease process through sensitive cognitive tests and biomarkers. The European Prevention of Alzheimer’s Dementia (EPAD) consortium recruited participants into a longitudinal cohort study with the aim of building a readiness cohort for a proof-of-concept clinical trial and also to generate a rich longitudinal data-set for disease modelling. Data have been collected on a wide range of measurements including cognitive outcomes, neuroimaging, cerebrospinal fluid biomarkers, genetics and other clinical and environmental risk factors, and are available for 1,828 eligible participants at baseline, 1,567 at 6 months, 1,188 at one-year follow-up, 383 at 2 years, and 89 participants at three-year follow-up visit. We novelly apply state-of-the-art longitudinal modelling and risk stratification approaches to these data in order to characterise disease progression and biological heterogeneity within the cohort. Specifically, we use longitudinal class-specific mixed effects models to characterise the different clinical disease trajectories and a semi-supervised Bayesian clustering approach to explore whether participants can be stratified into homogeneous subgroups that have different patterns of cognitive functioning evolution, while also having subgroup-specific profiles in terms of baseline biomarkers and longitudinal rate of change in biomarkers.

Plasma levels of neurological proteins have the potential to serve as biomarkers for neurological conditions. Here, Hillary et al. perform genome- and epigenome-wide association studies for 92 neurological proteins and identify 41 genomic loci for 33 proteins and 26 CpG sites for 9 proteins.

Abstract Background The cognitive-functional composite (CFC) was designed to improve the measurement of clinically relevant changes in predementia and early dementia stages. We have previously demonstrated its good test-retest reliability and feasibility of use. The current study aimed to evaluate several quality aspects of the CFC, including construct validity, clinical relevance, and suitability for the target population. Methods Baseline data of the Capturing Changes in Cognition study was used: an international, prospective cohort study including participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD) dementia, and dementia with Lewy bodies (DLB). The CFC comprises seven existing cognitive tests focusing on memory and executive functions (EF) and the informant-based Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). Construct validity and clinical relevance were assessed by (1) confirmatory factor analyses (CFA) using all CFC subtests and (2) linear regression analyses relating the CFC score (independent) to reference measures of disease severity (dependent), correcting for age, sex, and education. To assess the suitability for the target population, we compared score distributions of the CFC to those of traditional tests (Alzheimer’s Disease Assessment Scale–Cognitive subscale, Alzheimer’s Disease Cooperative Study–Activities of Daily Living scale, and Clinical Dementia Rating scale). Results A total of 184 participants were included (age 71.8 ± 8.4; 42% female; n = 14 SCD, n = 80 MCI, n = 78 AD, and n = 12 DLB). CFA showed that the hypothesized three-factor model (memory, EF, and IADL) had adequate fit (CFI = .931, RMSEA = .091, SRMR = .06). Moreover, worse CFC performance was associated with more cognitive decline as reported by the informant (β = .61, p

Alzheimer's disease (AD) has its onset many decades before dementia develops, and work is ongoing to characterise individuals at risk of decline on the basis of early detection through biomarker and cognitive testing as well as the presence/absence of identified risk factors. Risk prediction models for AD based on various computational approaches, including machine learning, are being developed with promising results. However, these approaches have been criticised as they are unable to generalise due to over-reliance on one data source, poor internal and external validations, and lack of understanding of prediction models, thereby limiting the clinical utility of these prediction models. We propose a framework that employs a transfer-learning paradigm with ensemble learning algorithms to develop explainable personalised risk prediction models for dementia. Our prediction models, known as source models, are initially trained and tested using a publicly available dataset (n = 84,856, mean age = 69 years) with 14 years of follow-up samples to predict the individual risk of developing dementia. The decision boundaries of the best source model are further updated by using an alternative dataset from a different and much younger population (n = 473, mean age = 52 years) to obtain an additional prediction model known as the target model. We further apply the SHapely Additive exPlanation (SHAP) algorithm to visualise the risk factors responsible for the prediction at both population and individual levels. The best source model achieves a geometric accuracy of 87%, specificity of 99%, and sensitivity of 76%. In comparison to a baseline model, our target model achieves better performance across several performance metrics, within an increase in geometric accuracy of 16.9%, specificity of 2.7%, and sensitivity of 19.1%, an area under the receiver operating curve (AUROC) of 11% and a transfer learning efficacy rate of 20.6%. The strength of our approach is the large sample size used in training the source model, transferring and applying the “knowledge” to another dataset from a different and undiagnosed population for the early detection and prediction of dementia risk, and the ability to visualise the interaction of the risk factors that drive the prediction. This approach has direct clinical utility.

Abstract Introduction In an attempt to capture clinically meaningful cognitive decline in early dementia, we developed the Cognitive‐Functional Composite (CFC). We investigated the CFC's sensitivity to decline in comparison to traditional clinical endpoints. Methods This longitudinal construct validation study included 148 participants with subjective cognitive decline, mild cognitive impairment, or mild dementia. The CFC and traditional tests were administered at baseline, 3, 6, and 12 months. Sensitivity to change was investigated using linear mixed models and r2 effect sizes. Results CFC scores declined over time (β = −.16, P

Abstract Introduction To improve the detection of changes in Alzheimer's disease (AD), we designed the cognitive‐functional composite (CFC). As a first validation step, we investigated its test–retest reliability and feasibility of use. Methods We performed a test–retest study with 2–3 weeks between assessments, including patients with mild cognitive impairment (MCI) or mild AD dementia and cognitively healthy participants. We calculated intraclass correlation coefficients (ICCs) type absolute agreement for all CFC measures and compared baseline and retest scores using paired‐samples t‐tests. We evaluated feasibility by interviewing participants. Results Forty‐three patients (40% female, mean age = 69.9) and 30 controls (50% female, mean age = 65) were included. Subtest intraclass correlation coefficients ranged from .70 to .96. We found negligible improvements after retesting on only two subtests. Overall, patients perceived the administration of the CFC as feasible. Discussion The CFC is a stable and feasible measure in MCI and mild AD dementia, and thereby meets important quality metrics for clinically meaningful outcome measures.

Abstract Context This commentary discusses the implications of disease-modifying treatments for Alzheimer’s disease which seem likely to appear in the next few years and results from a meeting of British experts in neurodegenerative diseases in Edinburgh. The availability of such treatments would help change public and professional attitudes and accelerate engagement with the prodromal and preclinical populations who might benefit from them. However, this would require an updated understanding of Alzheimer’s disease, namely the important distinction between Alzheimer’s disease and Alzheimer’s dementia. Consensus Since treatments are likely to be most effective in the early stages, identification of clinically relevant brain changes (for example, amyloid burden using imaging or cerebrospinal fluid biomarkers) will be crucial. While current biomarkers could be useful in identifying eligibility for new therapies, trial data are not available to aid decisions about stopping or continuing treatment in clinical practice. Therefore, effective monitoring of safety and effectiveness when these treatments are introduced into clinical practice will be necessary to inform wide-scale use. Equity of access is key but there is a tension between universal access for everyone with a diagnosis of Alzheimer’s disease and specifying an eligible population most likely to respond. We propose the resources necessary for an optimal care pathway as well as the necessary education and training for primary and secondary care. Conclusion The majority of current services in the UK and elsewhere would not be able to accommodate the specialist investigations required to select patients and prescribe these therapies. Therefore, a stepped approach would be necessary: from innovating sentinel clinical-academic centres that already have capacity to deliver the necessary phase IV trials, through early adoption in a hub and spoke model, to nationwide adoption for true equity of access. The optimism generated by recent and anticipated developments in the understanding and treatment of Alzheimer’s disease presents a great opportunity to innovate and adapt our services to incorporate the next exciting development in the field of dementia.

Abstract Introduction Traditional approaches to clinical research have, as yet, failed to provide effective treatments for vascular dementia (VaD). Novel approaches to collation and synthesis of data may allow for time and cost efficient hypothesis generating and testing. These approaches may have particular utility in helping us understand and treat a complex condition such as VaD. Methods We present an overview of new uses for existing data to progress VaD research. The overview is the result of consultation with various stakeholders, focused literature review and learning from the group’s experience of successful approaches to data repurposing. In particular, we benefitted from the expert discussion and input of delegates at the 9th International Congress on Vascular Dementia (Ljubljana, 16-18th October 2015). Results We agreed on key areas that could be of relevance to VaD research: systematic review of existing studies; individual patient level analyses of existing trials and cohorts and linking electronic health record data to other datasets. We illustrated each theme with a case-study of an existing project that has utilised this approach. Conclusions There are many opportunities for the VaD research community to make better use of existing data. The volume of potentially available data is increasing and the opportunities for using these resources to progress the VaD research agenda are exciting. Of course, these approaches come with inherent limitations and biases, as bigger datasets are not necessarily better datasets and maintaining rigour and critical analysis will be key to optimising data use.

Since the publication of this article [1], it has come to the attention of the authors that information for one of the authors was not included in the competing interests section. Craig Richie has declared potential competing interests with the following companies; Janssen, Eisai, Pfizer, Eli Lilly, Roche Diagnostics, Boeringher Ingleheim, Novartis, AC Immune, Ixico, Aridhia, Amgen, Berry Consultants, Lundbeck, Sanofi, Quintiles (IQVIA) and Takeda. The full competing interests section for this article can be found below.