Multiancestry analysis of the HLA locus in Alzheimer's and Parkinson's diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aß42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Understanding the relationship between type-2 diabetes, MRI markers of neurodegeneration and small vessel disease, and dementia risk: a mediation analysis.

To explore to which extent neurodegeneration and cerebral small vessel disease (SVD) could mediate the association between type-2 diabetes and higher dementia risk. The analytical sample consisted in 2228 participants, out of the Three-City study, aged 65 and older, free of dementia at baseline who underwent brain MRI. Diabetes was defined by medication intake or fasting or non-fasting elevated glucose levels. Dementia status was assessed every 2 to 3 years, during up to 12 years of follow-up. Brain parenchymal fraction (BPF) and white matter hyperintensities volume (WMHV) were selected as markers of neurodegeneration and cerebral SVD respectively. We performed a mediation analysis of the effect of baseline BPF and WMHV (mediators) on the association between diabetes and dementia risk using linear and Cox models adjusted for age, sex, education level, hypertension, hypercholesterolemia, BMI, smoking and alcohol drinking status, APOE-ε4 status, and study site. At baseline, 8.8% of the participants had diabetes. Diabetes (yes vs. no) was associated with higher WMHV (ßdiab = 0.193, 95% CI 0.040; 0.346) and lower BPF (ßdiab = -0.342, 95% CI -0.474; -0.210), as well as with an increased risk of dementia over 12 years of follow-up (HRdiab = 1.65, 95% CI 1.04; 2.60). The association between diabetes status and dementia risk was statistically mediated by higher WMHV (HRdiab=1.05, 95% CI 1.01; 1.11, mediated part = 10.8%) and lower BPF (HRdiab = 1.12, 95% CI 1.05; 1.20, mediated part = 22.9%). This study showed that both neurodegeneration and cerebral SVD statistically explained almost 30% of the association between diabetes and dementia.

Predicting sojourn times across dementia disease stages, institutionalization, and mortality.

INTRODUCTION: Inferring the timeline from mild cognitive impairment (MCI) to severe dementia is pivotal for patients, clinicians, and researchers. Literature is sparse and often contains few patients. We aim to determine the time spent in MCI, mild-, moderate-, severe dementia, and institutionalization until death. METHODS: Multistate modeling with Cox regression was used to obtain the sojourn time. Covariates were age at baseline, sex, amyloid status, and Alzheimer's disease (AD) or other dementia diagnosis. The sample included a register (SveDem) and memory clinics (Amsterdam Dementia Cohort and Memento). RESULTS: Using 80,543 patients, the sojourn time from clinically identified MCI to death across all patient groups ranged from 6.20 (95% confidence interval [CI]: 5.57-6.98) to 10.08 (8.94-12.18) years. DISCUSSION: Generally, sojourn time was inversely associated with older age at baseline, males, and AD diagnosis. The results provide key estimates for researchers and clinicians to estimate prognosis.

Disease progression model anchored around clinical diagnosis in longitudinal cohorts: example of Alzheimer's disease and related dementia.

BACKGROUND: Alzheimer's disease and related dementia (ADRD) are characterized by multiple and progressive anatomo-clinical changes including accumulation of abnormal proteins in the brain, brain atrophy and severe cognitive impairment. Understanding the sequence and timing of these changes is of primary importance to gain insight into the disease natural history and ultimately allow earlier diagnosis. Yet, modeling changes over disease course from cohort data is challenging as the usual timescales (time since inclusion, chronological age) are inappropriate and time-to-clinical diagnosis is available on small subsamples of participants with short follow-up durations prior to diagnosis. One solution to circumvent this challenge is to define the disease time as a latent variable. METHODS: We developed a multivariate mixed model approach that realigns individual trajectories into the latent disease time to describe disease progression. In contrast with the existing literature, our methodology exploits the clinical diagnosis information as a partially observed and approximate reference to guide the estimation of the latent disease time. The model estimation was carried out in the Bayesian Framework using Stan. We applied the methodology to the MEMENTO study, a French multicentric clinic-based cohort of 2186 participants with 5-year intensive follow-up. Repeated measures of 12 ADRD markers stemmed from cerebrospinal fluid (CSF), brain imaging and cognitive tests were analyzed. RESULTS: The estimated latent disease time spanned over twenty years before the clinical diagnosis. Considering the profile of a woman aged 70 with a high level of education and APOE4 carrier (the main genetic risk factor for ADRD), CSF markers of tau proteins accumulation preceded markers of brain atrophy by 5 years and cognitive decline by 10 years. However we observed that individual characteristics could substantially modify the sequence and timing of these changes, in particular for CSF level of A[Formula: see text]. CONCLUSION: By leveraging the available clinical diagnosis timing information, our disease progression model does not only realign trajectories into the most homogeneous way. It accounts for the inherent residual inter-individual variability in dementia progression to describe the long-term anatomo-clinical degradations according to the years preceding clinical diagnosis, and to provide clinically meaningful information on the sequence of events. TRIAL REGISTRATION: clinicaltrials.gov, NCT01926249. Registered on 16 August 2013.

Gene-mapping study of extremes of cerebral small vessel disease reveals TRIM47 as a strong candidate.

Cerebral small vessel disease is a leading cause of stroke and a major contributor to cognitive decline and dementia, but our understanding of specific genes underlying the cause of sporadic cerebral small vessel disease is limited. We report a genome-wide association study and a whole-exome association study on a composite extreme phenotype of cerebral small vessel disease derived from its most common MRI features: white matter hyperintensities and lacunes. Seventeen population-based cohorts of older persons with MRI measurements and genome-wide genotyping (n = 41 326), whole-exome sequencing (n = 15 965), or exome chip (n = 5249) data contributed 13 776 and 7079 extreme small vessel disease samples for the genome-wide association study and whole-exome association study, respectively. The genome-wide association study identified significant association of common variants in 11 loci with extreme small vessel disease, of which the chr12q24.11 locus was not previously reported to be associated with any MRI marker of cerebral small vessel disease. The whole-exome association study identified significant associations of extreme small vessel disease with common variants in the 5' UTR region of EFEMP1 (chr2p16.1) and one probably damaging common missense variant in TRIM47 (chr17q25.1). Mendelian randomization supports the causal association of extensive small vessel disease severity with increased risk of stroke and Alzheimer's disease. Combined evidence from summary-based Mendelian randomization studies and profiling of human loss-of-function allele carriers showed an inverse relation between TRIM47 expression in the brain and blood vessels and extensive small vessel disease severity. We observed significant enrichment of Trim47 in isolated brain vessel preparations compared to total brain fraction in mice, in line with the literature showing Trim47 enrichment in brain endothelial cells at single cell level. Functional evaluation of TRIM47 by small interfering RNAs-mediated knockdown in human brain endothelial cells showed increased endothelial permeability, an important hallmark of cerebral small vessel disease pathology. Overall, our comprehensive gene-mapping study and preliminary functional evaluation suggests a putative role of TRIM47 in the pathophysiology of cerebral small vessel disease, making it an important candidate for extensive in vivo explorations and future translational work.

Evaluating the harmonisation potential of diverse cohort datasets.

Data discovery, the ability to find datasets relevant to an analysis, increases scientific opportunity, improves rigour and accelerates activity. Rapid growth in the depth, breadth, quantity and availability of data provides unprecedented opportunities and challenges for data discovery. A potential tool for increasing the efficiency of data discovery, particularly across multiple datasets is data harmonisation.A set of 124 variables, identified as being of broad interest to neurodegeneration, were harmonised using the C-Surv data model. Harmonisation strategies used were simple calibration, algorithmic transformation and standardisation to the Z-distribution. Widely used data conventions, optimised for inclusiveness rather than aetiological precision, were used as harmonisation rules. The harmonisation scheme was applied to data from four diverse population cohorts.Of the 120 variables that were found in the datasets, correspondence between the harmonised data schema and cohort-specific data models was complete or close for 111 (93%). For the remainder, harmonisation was possible with a marginal a loss of granularity.Although harmonisation is not an exact science, sufficient comparability across datasets was achieved to enable data discovery with relatively little loss of informativeness. This provides a basis for further work extending harmonisation to a larger variable list, applying the harmonisation to further datasets, and incentivising the development of data discovery tools.

Physical activity, biomarkers of brain pathologies and dementia risk: Results from the Memento clinical cohort.

INTRODUCTION: This study aims to examine whether physical activity moderates the association between biomarkers of brain pathologies and dementia risk. METHODS: From the Memento cohort, we analyzed 1044 patients with mild cognitive impairment, aged 60 and older. Self-reported physical activity was assessed using the International Physical Activity Questionnaire. Biomarkers of brain pathologies comprised medial temporal lobe atrophy (MTA), white matter lesions, and plasma amyloid beta (Aß)42/40 and phosphorylated tau181. Association between physical activity and risk of developing dementia over 5 years of follow-up, and interactions with biomarkers of brain pathologies were tested. RESULTS: Physical activity moderated the association between MTA and plasma Aß42/40 level and increased dementia risk. Compared to participants with low physical activity, associations of both MTA and plasma Aß42/40 on dementia risk were attenuated in participants with high physical activity. DISCUSSION: Although reverse causality cannot be excluded, this work suggests that physical activity may contribute to cognitive reserve. HIGHLIGHTS: Physical activity is an interesting modifiable target for dementia prevention. Physical activity may moderate the impact of brain pathology on dementia risk. Medial temporal lobe atrophy and plasma amyloid beta 42/40 ratio were associated with increased dementia risk especially in those with low level of physical activity.

Associations among hypertension, dementia biomarkers, and cognition: The MEMENTO cohort.

INTRODUCTION: Approximately 40% of dementia cases could be delayed or prevented acting on modifiable risk factors including hypertension. However, the mechanisms underlying the hypertension-dementia association are still poorly understood. METHODS: We conducted a cross-sectional analysis in 2048 patients from the MEMENTO cohort, a French multicenter clinic-based study of outpatients with either isolated cognitive complaints or mild cognitive impairment. Exposure to hypertension was defined as a combination of high blood pressure (BP) status and antihypertensive treatment intake. Pathway associations were examined through structural equation modeling integrating extensive collection of neuroimaging biomarkers and clinical data. RESULTS: Participants treated with high BP had significantly lower cognition compared to the others. This association was mediated by higher neurodegeneration and higher white matter hyperintensities load but not by Alzheimer's disease (AD) biomarkers. DISCUSSION: These results highlight the importance of controlling hypertension for prevention of cognitive decline and offer new insights on mechanisms underlying the hypertension-dementia association. HIGHLIGHTS: Paths of hypertension-cognition association were assessed by structural equation models. The hypertension-cognition association is not mediated by Alzheimer's disease biomarkers. The hypertension-cognition association is mediated by neurodegeneration and leukoaraiosis. Lower cognition was limited to participants treated with uncontrolled blood pressure. Blood pressure control could contribute to promote healthier brain aging.

Association of APOE ε4 with cerebral gray matter volumes in non-demented older adults: The MEMENTO cohort study.

Data on 2,045 non-demented individuals with memory complaints were drawn from the Memento cohort study to examine the association between Apolipoprotein E ε4 allele (APOE4) and regional brain gray matter volumes. Linear regression was used to examine the association of APOE4 and measures of regional gray matter volumes in cross-sectional analysis and change therein using longitudinal analyses based on two brain MRI performed at baseline and at two-year follow-up. Overall, in analyses adjusted for age, sex, and intracranial volume, the presence of APOE4 was associated with lower total gray matter volume at baseline and with a higher atrophy rate over the follow-up. The hippocampus and entorhinal cortex were the two gray matter regions most associated with APOE4. Further adjustment for cardiovascular risk factors had little impact on these associations. There was an interaction between age, APOE4 status and total brain volume atrophy rate, with evidence of an earlier age at onset of atrophy in hippocampal volume in APOE4 carriers compared to non-carriers. Those results are in accordance with the role of medial temporal structures in the greater risk of dementia observed in people carrying the APOE4 allele.

Aduhelm, the Newly Approved Medication for Alzheimer Disease: What Epidemiologists Can Learn and What Epidemiology Can Offer.

Alzheimer disease (AD) is a progressive disorder common among older adults and culminating in profound cognitive impairments and high mortality risk. The US Food and Drug Administration (FDA) recently provided accelerated approval for Aduhelm, a medication for AD treatment. Aduhelm (Biogen Inc., Cambridge, Massachusetts) has been described as the first disease-modifying treatment for AD but has not been demonstrated to improve patients' cognitive or functional outcomes. In this commentary, we describe why Aduhelm approval was controversial and aspects of the current evidence of special pertinence to epidemiologists. The FDA decision was based primarily on 2 randomized controlled trials (RCTs), both terminated early, with conflicting findings about the cognitive benefits of Aduhelm. Both RCTs showed important adverse effects of the medication. The FDA cited the documented reduction in brain amyloid, an AD biomarker hypothesized as a surrogate outcome, to justify accelerated approval. Despite lack of racial/ethnic diversity in the RCT participants, concerns about health disparities have been invoked to argue for public funding of this expensive medication. The Centers for Medicare and Medicaid Services recently made a "Coverage with Evidence Development" determination for Aduhelm and similar medications. We end by describing how innovative study designs could accelerate postapproval research and evaluate the proposed surrogate outcomes.

How Selection Over Time Contributes to the Inconsistency of the Association Between Sex/Gender and Cognitive Decline Across Cognitive Aging Cohorts.

The association between sex/gender and aging-related cognitive decline remains poorly understood because of inconsistencies in findings. Such heterogeneity could be attributable to the cognitive functions studied and study population characteristics, but also to differential selection by dropout and death between men and women. We aimed to evaluate the impact of selection by dropout and death on the association between sex/gender and cognitive decline. We first compared the statistical methods most frequently used for longitudinal data, targeting either population estimands (marginal models fitted by generalized estimating equations) or subject-specific estimands (mixed/joint models fitted by likelihood maximization) in 8 studies of aging: 6 population-based studies (the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) Study (1996-2009), Personnes Âgées QUID (PAQUID; 1988-2014), the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study (2003-2016), the Three-City Study (Bordeaux only; 1999-2016), the Washington Heights-Inwood Community Aging Project (WHICAP; 1992-2017), and the Whitehall II Study (2007-2016)) and 2 clinic-based studies (the Alzheimer's Disease Neuroimaging Initiative (ADNI; 2004-2017) and a nationwide French cohort study, MEMENTO (2011-2016)). We illustrate differences in the estimands of the association between sex/gender and cognitive decline in selected examples and highlight the critical role of differential selection by dropout and death. Using the same estimand, we then contrast the sex/gender-cognitive decline associations across cohorts and cognitive measures suggesting a residual differential sex/gender association depending on the targeted cognitive measure (memory or animal fluency) and the initial cohort selection. We recommend focusing on subject-specific estimands in the living population for assessing sex/gender differences while handling differential selection over time.

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers.

Amyloid-beta 42 (Aß42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aß42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aß42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.

Personalized prediction of progression in pre-dementia patients based on individual biomarker profile: A development and validation study.

INTRODUCTION: The prognosis of patients at the pre-dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker-based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population. METHODS: Disease-progression modeling of longitudinal cognitive scores of pre-dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative. RESULTS: Of nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model-based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut-offs, inclusion criteria based on biomarker-profile cut-offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns. DISCUSSION: The biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web-based application for prediction of patients' future cognitive progression is available online.

Investigating the association between cancer and the risk of dementia: Results from the Memento cohort.

INTRODUCTION: Studies on the association of cancer and risk of dementia are inconclusive due to result heterogeneity and concerns of survivor bias and unmeasured confounding. METHODS: This study uses data from the Memento cohort, a French multicenter cohort following persons with either mild or isolated cognitive complaints for a median of 5 years. Illness-death models (IDMs) were used to estimate transition-specific hazard ratios (HRs) and 95% confidence intervals (CIs) for incident cancer in relation to dementia from time since study entry. RESULTS: The analytical sample (N = 2258) excluded 65 individuals without follow-up information. At the end of follow-up, 286 individuals were diagnosed with dementia, 166 with incident cancer, and 95 died. Incident cancer was associated with a reduced risk of dementia (HR = 0.58, 95% CI = 0.35-0.97), with a corresponding E-value of 2.84 (lower CI = 1.21). DISCUSSION: This study supports a protective relationship between incident cancer and dementia, encouraging further investigations to understand potential underlying mechanisms.

Clinical relevance of brain atrophy subtypes categorization in memory clinics.

INTRODUCTION: The clinical relevance of brain atrophy subtypes categorization in non-demented persons without a priori knowledge regarding their amyloid status or clinical presentation is unknown. METHODS: A total of 2083 outpatients with either subjective cognitive complaint or mild cognitive impairment at study entry were followed during 4 years (MEMENTO cohort). Atrophy subtypes were defined using baseline magnetic resonance imaging (MRI) and previously described algorithms. RESULTS: Typical/diffuse atrophy was associated with faster cognitive decline and the highest risk of developing dementia and Alzheimer's disease (AD) over time, both in the whole analytic sample and in amyloid-positive participants. Hippocampal-sparing and limbic-predominant atrophy were also associated with incident dementia, with faster cognitive decline in the limbic predominant atrophy group. Lewy body dementia was more frequent in the hippocampal-sparing and minimal/no atrophy groups. DISCUSSION: Atrophy subtypes categorization predicted different subsequent patterns of cognitive decline and rates of conversion to distinct etiologies of dementia in persons attending memory clinics.

State School Policies as Predictors of Physical and Mental Health: A Natural Experiment in the REGARDS Cohort.

We used differences in state school policies as natural experiments to evaluate the joint influence of educational quantity and quality on late-life physical and mental health. Using US Census microsample data, historical measures of state compulsory schooling and school quality (term length, student-teacher ratio, and attendance rates) were combined via regression modeling on a scale corresponding to years of education (policy-predicted years of education (PPYEd)). PPYEd values were linked to individual-level records for 8,920 black and 14,605 white participants aged ≥45 years in the Reasons for Geographic and Racial Differences in Stroke study (2003-2007). Linear and quantile regression models estimated the association between PPYEd and Physical Component Summary (PCS) and Mental Component Summary (MCS) from the Short Form Health Survey. We examined interactions by race and adjusted for sex, birth year, state of residence at age 6 years, and year of study enrollment. Higher PPYEd was associated with better median PCS (ß = 1.28, 95% confidence interval (CI): 0.40, 1.49) and possibly better median MCS (ß = 0.46, 95% CI: -0.01, 0.94). Effect estimates were higher among black (vs. white) persons (PCS × race interaction, ß = 0.22, 95% CI: -0.62, 1.05, and MCS × race interaction, ß = 0.18; 95% CI: -0.08, 0.44). When incorporating both school quality and duration, this quasiexperimental analysis found mixed evidence for a causal effect of education on health decades later.

Dementia Research Fit for the Planet: Reflections on Population Studies of Dementia for Researchers and Policy Makers Alike.

In recent years, a rapidly increasing collection of investigative methods in addition to changes in diagnostic criteria for dementia have followed "high-tech" trends in medicine, with the aim to better define the dementia syndrome and its biological substrates, mainly in order to predict risk prior to clinical expression. These approaches are not without challenge. A set of guidelines have been developed by a group of European experts in population-based cohort research through a series of workshops, funded by the Joint Program for Neurodegenerative Disorders (JPND). The aims of the guidelines are to assist policy makers and researchers to understand (1) What population studies for ageing populations should encompass and (2) How to interpret the findings from population studies. Such studies are essential to provide evidence relevant to the understanding of healthy and frail brain ageing, including the dementia syndrome for contemporary and future societies by drawing on the past.

The Dementias Platform UK (DPUK) Data Portal.

The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

Genome-wide association study of rate of cognitive decline in Alzheimer's disease patients identifies novel genes and pathways.

INTRODUCTION: Variability exists in the disease trajectories of Alzheimer's disease (AD) patients. We performed a genome-wide association study to examine rate of cognitive decline (ROD) in patients with AD. METHODS: We tested for interactions between genetic variants and time since diagnosis to predict the ROD of a composite cognitive score in 3946 AD cases and performed pathway analysis on the top genes. RESULTS: Suggestive associations (P < 1.0 × 10-6 ) were observed on chromosome 15 in DNA polymerase-γ (rs3176205, P = 1.11 × 10-7 ), chromosome 7 (rs60465337,P = 4.06 × 10-7 ) in contactin-associated protein-2, in RP11-384F7.1 on chromosome 3 (rs28853947, P = 5.93 × 10-7 ), family with sequence similarity 214 member-A on chromosome 15 (rs2899492, P = 5.94 × 10-7 ), and intergenic regions on chromosomes 16 (rs4949142, P = 4.02 × 10-7 ) and 4 (rs1304013, P = 7.73 × 10-7 ). Significant pathways involving neuronal development and function, apoptosis, memory, and inflammation were identified. DISCUSSION: Pathways related to AD, intelligence, and neurological function determine AD progression, while previously identified AD risk variants, including the apolipoprotein (APOE) ε4 and ε2 variants, do not have a major impact.

Real-world evidence in Alzheimer's disease: The ROADMAP Data Cube.

INTRODUCTION: The ROADMAP project aimed to provide an integrated overview of European real-world data on Alzheimer's disease (AD) across the disease spectrum. METHODS: Metadata were identified from data sources in catalogs of European AD projects. Priority outcomes for different stakeholders were identified through systematic literature review, patient and public consultations, and stakeholder surveys. RESULTS: Information about 66 data sources and 13 outcome domains were integrated into a Data Cube. Gap analysis identified cognitive ability, functional ability/independence, behavioral/neuropsychiatric symptoms, treatment, comorbidities, and mortality as the outcomes collected most. Data were most lacking in caregiver-related outcomes. In general, electronic health records covered a broader, less detailed data spectrum than research cohorts. DISCUSSION: This integrated real-world AD data overview provides an intuitive visual model that facilitates initial assessment and identification of gaps in relevant outcomes data to inform future prospective data collection and matching of data sources and outcomes against research protocols.