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Background/aims: As a protrusion from the brain, the retina might reflect the status of the brain. Previous studies showed a decrease in vessel density and foveal avascular zone (FAZ) enlargement on optical coherence tomography angiography (OCTA) in individuals suffering from Alzheimer's disease (AD). This study aims to assess whether such changes are already present in preclinical stages of AD, in a population of monozygotic (MZ) twins., Methods: 124 cognitively healthy individuals (MZ twins, ages 60-93 years) underwent [ 18 F]flutemetamol amyloid positron emission tomography (PET) scanning and OCTA. PET scans were visually rated for cortical amyloid-beta (Aβ) positivity. Parametric global cortical non-displaceable binding potential ( BP ND ) was used as a continuous measure for Aβ aggregation. FAZ size and vessel densities for the inner and outer ring of the macular ETDRS grid and in a 3-6 mm ring around the optic nerve head (ONH) were measured.OCTA measures were associated with visual Aβ score, BP ND and amyloid load estimated by twin concordance on visual Aβ score. Twin correlations were estimated as a measure of maximum heritability of OCTA measures., Results: 13 of 124 participants were Aβ+. Aβ+ individuals had significantly higher vessel density than Aβ- individuals in all regions but did not differ in FAZ size. Twin analyses showed a positive association between and vessel densities in all regions. BP ND tended to be associated with higher vessel density in the inner ring. Twin correlations were moderate/high for all OCTA parameters except vessel density around the ONH, which correlated weakly., Conclusion: Retinal vessel density was higher in individuals with preclinical AD., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h 2 total ), and the proportion of heritability captured by known metabolite loci (h 2 Metabolite-hits ) for 309 lipids and 52 organic acids. Our study reveals significant differences in h 2 Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h 2 Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.

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.

We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

Background: Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown., Objective: We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes., Methods: We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677)., Results: We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts., Conclusions: Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.

Background: Gait analysis with accelerometers is a relatively inexpensive and easy to use method to potentially support clinical diagnoses of Alzheimer's disease and other dementias. It is not clear, however, which gait features are most informative and how these measures relate to Alzheimer's disease pathology., Objective: In this study, we tested if calculated features of gait 1) differ between cognitively normal subjects (CN), mild cognitive impairment (MCI) patients, and dementia patients, 2) are correlated with cerebrospinal fluid (CSF) biomarkers related to Alzheimer's disease, and 3) predict cognitive decline., Methods: Gait was measured using tri-axial accelerometers attached to the fifth lumbar vertebra (L5) in 58 CN, 58 MCI, and 26 dementia participants, while performing a walk and dual task. Ten gait features were calculated from the vertical L5 accelerations, following principal component analysis clustered in four domains, namely pace, rhythm, time variability, and length variability. Cognitive decline over time was measured using MMSE, and CSF biomarkers were available in a sub-group., Results: Linear mixed models showed that dementia patients had lower pace scores than MCI patients and CN subjects (p < 0.05). In addition, we found associations between the rhythm domain and CSF-tau, especially in the dual task. Gait was not associated with CSF Aβ42 levels and cognitive decline over time as measured with the MMSE., Conclusion: These findings suggest that gait - particularly measures related to pace and rhythm - are altered in dementia and have a direct link with measures of neurodegeneration.

Introduction: Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers., Methods: This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV)., Results: On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively., Discussion: This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders., (© 2019 The Authors.)

Purpose: There is urgent need for non-invasive diagnostic biomarkers in the preclinical phase of Alzheimer's Disease (AD). Several studies suggest that retinal thickness is reduced in AD. Here, we aim to test the diagnostic value of retinal thickness in preclinical AD, as defined by cognitively normal individuals with amyloid pathology on PET., Methods: One hundred and sixty five cognitively healthy monozygotic twins aged ≥ 60 were included from the Netherlands Twin Register taking part in the European Medical Information Framework for Alzheimer's Disease PreclinAD study. Participants underwent [ 18 F] flutemetamol PET that was visually rated for presence or absence of cortical amyloid beta (Aβ). Binding potential (BP ND ) was calculated as continuous measure for Aβ. Spectral Domain OCT was used to asses total and individual inner retinal layer thickness in the macular region (ETDRS circles) as well as peripapillary retinal nerve fibre layer (pRNFL) thickness. Differences between Aβ+ and Aβ- individuals and associations between BP ND and retinal thickness were analyzed., Results: No differences were found in retinal layer thickness in the macula or pRNFL between Aβ+ and Aβ- individuals. A positive associations between BP ND and macular total retinal thickness was observed in the inner ring (p = 0.018), but this was not statistically significant after correction for multiple testing (p = 0.144). Brain/eye parameters had moderate to high intra-twin correlations (p < 0.001) except visual rating score of Aβ, which did not correlate (r = 0.21, p = 0.068)., Conclusion: Variation in retinal thickness likely reflects genetic differences between individuals, but cannot discriminate between healthy and preclinical AD cases, making its use as biomarker in these early stages limited., (© 2019 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Background: Results from recent clinical studies suggest that cerebrospinal fluid (CSF) biomarkers that are indicative of Alzheimer's disease (AD) can be replicated in blood, e.g. amyloid-beta peptides (Aβ 42 and Aβ 40 ) and neurofilament light chain (NFL). Such data proposes that blood is a rich source of potential biomarkers reflecting central nervous system pathophysiology and should be fully explored for biomarkers that show promise in CSF. Recently, soluble fragments of the triggering receptor expressed on myeloid cells 2 (sTREM2) protein in CSF have been reported to be increased in prodromal AD and also in individuals with TREM2 rare genetic variants that increase the likelihood of developing dementia., Methods: In this study, we measured the levels of plasma sTREM2 and plasma NFL using the MesoScale Discovery and single molecule array platforms, respectively, in 48 confirmed TREM2 rare variant carriers and 49 non-carriers., Results: Our results indicate that there are no changes in plasma sTREM2 and NFL concentrations between TREM2 rare variant carriers and non-carriers. Furthermore, plasma sTREM2 is not different between healthy controls, mild cognitive impairment (MCI) or AD., Conclusion: Concentrations of plasma sTREM2 do not mimic the recent changes found in CSF sTREM2.

Introduction: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins., Methods: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid., Results: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization., Discussion: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia., Methods: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework., Findings: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76)., Interpretation: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour., Funding: ZonMW-Memorabel., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Importance: Neurofilament light protein (NfL) is elevated in cerebrospinal fluid (CSF) of a number of neurological conditions compared with healthy controls (HC) and is a candidate biomarker for neuroaxonal damage. The influence of age and sex is largely unknown, and levels across neurological disorders have not been compared systematically to date., Objectives: To assess the associations of age, sex, and diagnosis with NfL in CSF (cNfL) and to evaluate its potential in discriminating clinically similar conditions., Data Sources: PubMed was searched for studies published between January 1, 2006, and January 1, 2016, reporting cNfL levels (using the search terms neurofilament light and cerebrospinal fluid) in neurological or psychiatric conditions and/or in HC., Study Selection: Studies reporting NfL levels measured in lumbar CSF using a commercially available immunoassay, as well as age and sex., Data Extraction and Synthesis: Individual-level data were requested from study authors. Generalized linear mixed-effects models were used to estimate the fixed effects of age, sex, and diagnosis on log-transformed NfL levels, with cohort of origin modeled as a random intercept., Main Outcome and Measure: The cNfL levels adjusted for age and sex across diagnoses., Results: Data were collected for 10 059 individuals (mean [SD] age, 59.7 [18.8] years; 54.1% female). Thirty-five diagnoses were identified, including inflammatory diseases of the central nervous system (n = 2795), dementias and predementia stages (n = 4284), parkinsonian disorders (n = 984), and HC (n = 1332). The cNfL was elevated compared with HC in a majority of neurological conditions studied. Highest levels were observed in cognitively impaired HIV-positive individuals (iHIV), amyotrophic lateral sclerosis, frontotemporal dementia (FTD), and Huntington disease. In 33.3% of diagnoses, including HC, multiple sclerosis, Alzheimer disease (AD), and Parkinson disease (PD), cNfL was higher in men than women. The cNfL increased with age in HC and a majority of neurological conditions, although the association was strongest in HC. The cNfL overlapped in most clinically similar diagnoses except for FTD and iHIV, which segregated from other dementias, and PD, which segregated from atypical parkinsonian syndromes., Conclusions and Relevance: These data support the use of cNfL as a biomarker of neuroaxonal damage and indicate that age-specific and sex-specific (and in some cases disease-specific) reference values may be needed. The cNfL has potential to assist the differentiation of FTD from AD and PD from atypical parkinsonian syndromes.

Introduction: Vascular factors increase the risk of Alzheimer's disease (AD). We investigated the associations between such factors, longitudinal AD cerebrospinal fluid biomarkers, and cognition., Methods: 433 cognitively normal participants were classified into four biomarker groups using their baseline amyloid (A+/-) and tau status (T+/-). 184 participants had undergone serial cerebrospinal fluid collection. Frequencies of risk factors and the Framingham Risk Score (FRS) were compared, and we tested the influence of risk factors on change in biomarker concentrations and cognition., Results: The absence of obesity, presence of hypertension, and a high FRS were associated with an increase in tau levels, particularly in A+T+ individuals. Risk factors were not associated with amyloid. Depression was associated with higher cognitive scores, whereas high FRS was associated with lower scores and a faster decline., Discussion: Our results demonstrate that vascular risk factors may enhance neurodegeneration but not amyloid accumulation in preclinical AD., (Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Objectives: To study the interactive effect of white matter hyperintensities (WMH) and hippocampal atrophy on cognition in the oldest old., Design: Ongoing longitudinal study., Setting: In Southern California, brain magnetic resonance imaging (MRI) scans were conducted between May 2014 and December 2017., Participants: Individuals from The 90+ Study with a valid brain MRI scan (N = 141; 94 cognitively normal and 47 with cognitive impairment)., Measurements: Cognitive testing was performed every 6 months with a mean follow-up of 2 years and included these tests: Mini-Mental State Examination (MMSE), modified MMSE (3MS), California Verbal Learning Test (CVLT) immediate recall over four trials and delayed recall, Digit Span Backward, Animal Fluency, and Trail Making Test (TMT) A, B, and C. We used one linear mixed model for each cognitive test to study the baseline and longitudinal association of WMH and hippocampal volume (HV) with cognition. Models were adjusted for age, sex, and education., Results: Mean age was 94.3 years (standard deviation [SD] = 3.2 y). At baseline, higher WMH volumes were associated with worse scores on the 3MS, CVLT immediate and delayed recall, and TMT B. Lower HVs were associated with worse baseline scores on all cognitive tests, except for the Digit Span Backward. Longitudinally, higher WMH and lower HVs were associated with faster decline in the 3MS and MMSE, and lower HV was also associated with faster decline in the CVLT immediate recall. No association was observed between WMH and HV and no interaction between WMH and HV in their association with baseline cognition or cognitive decline., Conclusion: We show that WMH and hippocampal atrophy have an independent, negative effect on cognition that make these biomarkers relevant to evaluate in the diagnostic work-up of the oldest-old individuals with cognitive complaints. However, the predictive value of WMH for cognitive decline seems to be less evident in the oldest-old compared with a younger group of older adults. J Am Geriatr Soc 67:1827-1834, 2019., (© 2019 The American Geriatrics Society.)

Introduction: The diagnosis of mild cognitive impairment (MCI) refers to cognitive impairment not meeting dementia criteria. A survey among members of the American Association of Neurology (AAN) showed that MCI was considered a useful diagnosis. Recently, research criteria have been proposed for the diagnosis of Alzheimer's disease (AD) in MCI based on AD biomarkers (prodromal AD/MCI due to AD). The aim of this study was to investigate the attitudes of clinicians in Europe on the clinical utility of MCI and prodromal AD/MCI due to AD criteria. We also investigated whether the prodromal AD/MCI due to AD criteria impacted management of MCI patients., Methods: An online survey was performed in 2015 among 102 members of the European Academy of Neurology (EAN) and the European Alzheimer's Disease Consortium (EADC). Questions were asked on how often criteria were used, how they were operationalized, how they changed patient management, and what were considered advantages and limitations of MCI and prodromal AD/MCI due to AD. The questionnaire consisted of 47 questions scored on a Likert scale., Results: Almost all respondents (92%) used the MCI diagnosis in clinical practice. Over 80% of the EAN/EADC respondents found a MCI diagnosis useful because it helped to label the cognitive problem, involve patients in planning for the future, and start risk reduction activities. These findings were similar to those reported in the AAN survey. Research criteria for prodromal AD/MCI due to AD were used by 68% of the EAN/EADC respondents. The most common reasons to use the criteria were increased certainty of diagnosis (86%), increased possibilities to provide counseling (51%), facilitation of follow-up planning (48%), start of medical intervention (49%), and response to patients' wish for a diagnosis (41%). Over 70% of the physicians considered that a diagnosis of prodromal AD/MCI due to AD had an added value over the MCI diagnosis., Conclusions: The diagnostic criteria of MCI and prodromal AD/MCI due to AD are commonly used among EAN/EADC members. The prodromal AD/MCI due to AD were considered clinically useful and impacted patient management and communication.

Introduction: We estimated the age-specific duration of the preclinical, prodromal, and dementia stages of Alzheimer's disease (AD) and the influence of sex, setting, apolipoprotein E (APOE) genotype, and cerebrospinal fluid tau on disease duration., Methods: We performed multistate modeling in a combined sample of 6 cohorts (n = 3268) with death as the end stage and estimated the preclinical, prodromal, and dementia stage duration., Results: The overall AD duration varied between 24 years (age 60) and 15 years (age 80). For individuals presenting with preclinical AD, age 70, the estimated preclinical AD duration was 10 years, prodromal AD 4 years, and dementia 6 years. Male sex, clinical setting, APOE ε4 allele carriership, and abnormal cerebrospinal fluid tau were associated with a shorter duration, and these effects depended on disease stage., Discussion: Estimates of AD disease duration become more accurate if age, sex, setting, APOE, and cerebrospinal fluid tau are taken into account. This will be relevant for clinical practice and trial design., (Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Introduction: Retinal thickness measured with optical coherence tomography has been proposed as a noninvasive biomarker for Alzheimer's disease (AD). We therefore measured retinal thickness in well-characterized AD and control participants, considering ophthalmological confounders., Methods: We included 57 amyloid-proven AD cases and 85 cognitively normal, amyloid-negative controls. All subjects underwent retinal thickness measurements with spectral domain optical coherence tomography and an ophthalmological assessment to exclude ocular disease., Results: Retinal thickness did not discriminate cases from controls, including stratified analyses for early- versus late-onset AD. We found significant associations between macular thickness and global cortical atrophy [β -0.358; P  = .01] and parietal cortical atrophy on magnetic resonance imaging [β -0.371; P  < .01] in AD cases., Discussion: In this study, representing the largest optical coherence tomography cohort with amyloid-proven AD cases, we show that retinal thickness does not discriminate AD from controls, despite evident changes on clinical, neuroimaging, and CSF measures, querying the use of retinal thickness measurements as an AD biomarker.

Objective: To identify potential predictors for outcome in individuals with mild cognitive impairment (MCI) who have reverted to normal cognition (NC)., Methods: We selected individuals with MCI, who reverted at follow-up to NC, with follow-up after reversion from Alzheimer's Disease Neuroimaging Initiative. Common clinical markers, Alzheimer disease (AD) biomarkers, and neurodegeneration imaging markers were used to compare MCI reverters based on subsequent clinical outcome (i.e., subsequent decline or stable reversion). For independent comparison, findings of the clinical Amsterdam Dementia Cohort are presented., Results: Seventy-seven (10%) out of 757 individuals with MCI reverted to NC and 61 of these individuals had follow-up data available. After 3.2 ± 2.2 years, 16 (24%) progressed to MCI, and 3 (5%) to dementia. Those who declined were older and had a higher amyloid PET burden and higher CSF tau levels., Conclusion: In MCI reverters, abnormal biomarkers for AD pathology are associated with subsequent decline. AD biomarkers may aid in the prognosis of reverting MCI., (Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

In most, if not all health systems, dementia is underdiagnosed, and when diagnosis occurs, it is typically at a relatively late stage in the disease process despite mounting evidence showing that a timely diagnosis would result in numerous benefits for patients, families, and society. Moving toward earlier diagnoses in Alzheimer's disease (AD) requires a conscientious and collective effort to implement a global strategy addressing the multiple causes hindering patient engagement at different levels of society. This article describes the design of the Models of Patient Engagement for Alzheimer's Disease project, an ongoing EU-funded public-private multinational initiative that will compare four innovative patient engagement strategies across five European countries regarding their ability to identify individuals with prodromal AD and mild AD dementia, which are "hidden" in their communities and traditionally not found in the typical memory clinic setting. The strategies include an online AD citizen science platform, an open house initiative at the memory clinics, and patient engagement at primary care and diabetologist clinics., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Within-person trajectories of cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease (AD) are not well defined., Methods: We included 467 subjects from the BIOMARKAPD study with at least two serial CSF samples. Diagnoses were subjective cognitive decline (n = 75), mild cognitive impairment (n = 128), and AD dementia (n = 110), and a group of cognitively unimpaired subjects (n = 154) were also included. We measured baseline and follow-up CSF levels of total tau (t-tau), phosphorylated tau (p-tau), YKL-40, and neurofilament light (NfL). Median CSF sampling interval was 2.1 years., Results: CSF levels of t-tau, p-tau, NfL, and YKL-40 were 2% higher per each year of baseline age in controls (P <.001). In AD, t-tau levels were 1% lower (P <.001) and p-tau levels did not change per each year of baseline age. Longitudinally, only NfL (P <.001) and YKL-40 (P <.02) increased during the study period., Discussion: All four CSF biomarkers increase with age, but this effect deviates in AD for t-tau and p-tau., (Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Introduction: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers., Methods: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis., Results: Eight metabolites were associated with amyloid β and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory., Discussion: PFAMs have been found increased and associated with amyloid β burden in CSF and clinical measures., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

Introduction: Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers., Methods: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed., Results: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71)., Discussion: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: There is increasing evidence that dementia risk associated with vascular disorders is age dependent. Large population-based studies of incident dementia are necessary to further elucidate this effect. Therefore, the aim of the present study was to determine the association of vascular disorders with incident dementia in different age groups in a large primary care database., Methods: We included 442,428 individuals without dementia aged ≥ 65 years from the longitudinal primary care Integrated Primary Care Information (IPCI) database. We determined in 6 age groups (from 65-70 to ≥ 90 years) the risk of hypertension, diabetes mellitus, dyslipidemia, stroke, myocardial infarction, heart failure, and atrial fibrillation for all-cause dementia using incidence rate ratios, Cox regression, and Fine and Gray regression models., Results: The mean age at inclusion of the total study sample was 72.4 years, 45.7% of the participants were male, and median follow-up was 3.6 years. During 1.4 million person-years of follow-up, 13,511 individuals were diagnosed with dementia. The risk for dementia decreased with increasing age for all risk factors and was no longer significant in individuals aged ≥ 90 years. Adjusting for mortality as a competing risk did not change the results., Conclusions: We conclude that vascular disorders are no longer a risk factor for dementia at high age. Possible explanations include selective survival of individuals who are less susceptible to the negative consequences of vascular disorders and differences in follow-up time between individuals with and without a vascular disorder. Future research should focus on the identification of other risk factors than vascular disorders, for example, genetic or inflammatory processes, that can potentially explain the strong age-related increase in dementia risk.

Introduction: We investigated relations between amyloid-β (Aβ) status, apolipoprotein E (APOE) ε4, and cognition, with cerebrospinal fluid markers of neurogranin (Ng), neurofilament light (NFL), YKL-40, and total tau (T-tau)., Methods: We included 770 individuals with normal cognition, mild cognitive impairment, and Alzheimer's disease (AD)-type dementia from the EMIF-AD Multimodal Biomarker Discovery study. We tested the association of Ng, NFL, YKL-40, and T-tau with Aβ status (Aβ- vs. Aβ+), clinical diagnosis APOE ε4 carriership, baseline cognition, and change in cognition., Results: Ng and T-tau distinguished between Aβ+ from Aβ- individuals in each clinical group, whereas NFL and YKL-40 were associated with Aβ+ in nondemented individuals only. APOE ε4 carriership did not influence NFL, Ng, and YKL-40 in Aβ+ individuals. NFL was the best predictor of cognitive decline in Aβ+ individuals across the cognitive spectrum., Discussion: Axonal degeneration, synaptic dysfunction, astroglial activation, and altered tau metabolism are involved already in preclinical AD. NFL may be a useful prognostic marker., (Copyright © 2019 the Alzheimer's Association. All rights reserved.)

Amyloid pathology in cognitively normal older adults has been associated with low memory performance and cognitive complaints, but findings are conflicting. Using a monozygotic twin design, we further explored this relation. We investigated 199 cognitively normal older adults (96 twin pairs) and assessed cognitive performance, cognitive complaints, and amyloid pathology on positron emission tomography and in the cerebrospinal fluid (CSF). Participants were on average 70.5 (SD = 7.6) years and 114 (57%) were female. Amyloid-positron emission tomography abnormality on visual read and lower CSF amyloid-β 1-42/1-40 ratio were associated with lower Rey visuospatial memory performance (respectively, β = -0.39 [SE = 0.17], p = 0.02 and β = 0.15 [SE = 0.07], p = 0.04). Twin analyses showed that CSF amyloid-β 1-42/1-40 ratio in one twin of a pair could predict visuospatial memory performance in the cotwin (r = 0.20 [SE = 0.10], p = 0.04). Monozygotic twin discordance analyses further showed a probable effect of disease staging on face-name associative memory performance. Our results suggest amyloid aggregation to be associated with lower visuospatial and face-name-associated memory performance in cognitively normal older adults, supporting the view that amyloid pathology leads to memory dysfunction in very early stages of the disease., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Our objective was to determine the optimal approach for assessing amyloid disease in a cognitively normal elderly population. Methods: Dynamic 18 F-flutemetamol PET scans were acquired using a coffee-break protocol (a 0- to 30-min scan and a 90- to 110-min scan) on 190 cognitively normal elderly individuals (mean age, 70.4 y; 60% female). Parametric images were generated from SUV ratio (SUVr) and nondisplaceable binding potential (BP ND ) methods, with cerebellar gray matter as a reference region, and were visually assessed by 3 trained readers. Interreader agreement was calculated using κ-statistics, and semiquantitative values were obtained. Global cutoffs were calculated for both SUVr and BP ND using a receiver-operating-characteristic analysis and the Youden index. Visual assessment was related to semiquantitative classifications. Results: Interreader agreement in visual assessment was moderate for SUVr (κ = 0.57) and good for BP ND images (κ = 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BP ND , with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BP ND were 1.33 (±0.21) and 0.16 (±0.12), respectively. Most of the 35 cases (91%) for which SUVr image assessment was discordant between readers were classified as negative based on semiquantitative measurements. Conclusion: The use of parametric BP ND images for visual assessment of 18 F-flutemetamol in a population with low amyloid burden improves interreader agreement. Implementing semiquantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population., (© 2019 by the Society of Nuclear Medicine and Molecular Imaging.)

Introduction: In this multicenter study on subjective cognitive decline (SCD) in community-based and memory clinic settings, we assessed the (1) incidence of Alzheimer's disease (AD) and non-AD dementia and (2) determinants of progression to dementia., Methods: Eleven cohorts provided 2978 participants with SCD and 1391 controls. We estimated dementia incidence and identified risk factors using Cox proportional hazards models., Results: In SCD, incidence of dementia was 17.7 (95% Poisson confidence interval 15.2-20.3)/1000 person-years (AD: 11.5 [9.6-13.7], non-AD: 6.1 [4.7-7.7]), compared with 14.2 (11.3-17.6) in controls (AD: 10.1 [7.7-13.0], non-AD: 4.1 [2.6-6.0]). The risk of dementia was strongly increased in SCD in a memory clinic setting but less so in a community-based setting. In addition, higher age (hazard ratio 1.1 [95% confidence interval 1.1-1.1]), lower Mini-Mental State Examination (0.7 [0.66-0.8]), and apolipoprotein E ε4 (1.8 [1.3-2.5]) increased the risk of dementia., Discussion: SCD can precede both AD and non-AD dementia. Despite their younger age, individuals with SCD in a memory clinic setting have a higher risk of dementia than those in community-based cohorts., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

ROADMAP is a public-private advisory partnership to evaluate the usability of multiple data sources, including real-world evidence, in the decision-making process for new treatments in Alzheimer's disease, and to advance key concepts in disease and pharmacoeconomic modeling. ROADMAP identified key disease and patient outcomes for stakeholders to make informed funding and treatment decisions, provided advice on data integration methods and standards, and developed conceptual cost-effectiveness and disease models designed in part to assess whether early treatment provides long-term benefit.

It is an open issue whether blood biomarkers serve to diagnose Alzheimer's disease (AD) or monitor its progression over time from prodromal stages. Here, we addressed this question starting from data of the European FP7 IMI-PharmaCog/E-ADNI longitudinal study in amnesic mild cognitive impairment (aMCI) patients including biological, clinical, neuropsychological (e.g., ADAS-Cog13), neuroimaging, and electroencephalographic measures. PharmaCog/E-ADNI patients were classified as "positive" (i.e., "prodromal AD" n = 76) or "negative" (n = 52) based on a diagnostic cut-off of Aβ42/P-tau in cerebrospinal fluid as well as APOE ε 4 genotype. Blood was sampled at baseline and at two follow-ups (12 and 18 months), when plasma amyloid peptide 42 and 40 (Aβ42, Aβ40) and apolipoprotein J (clusterin, CLU) were assessed. Linear Mixed Models found no significant differences in plasma molecules between the "positive" (i.e., prodromal AD) and "negative" groups at baseline. In contrast, plasma Aβ42 showed a greater reduction over time in the prodromal AD than the "negative" aMCI group (p = 0.048), while CLU and Aβ40 increased, but similarly in the two groups. Furthermore, plasma Aβ42 correlated with the ADAS-Cog13 score both in aMCI patients as a whole and the prodromal AD group alone. Finally, CLU correlated with the ADAS-Cog13 only in the whole aMCI group, and no association with ADAS-Cog13 was found for Aβ40. In conclusion, plasma Aβ42 showed disease progression-related features in aMCI patients with prodromal AD.

Background: Assessment of human brain atrophy in temporal regions using magnetic resonance imaging (MRI), resting state functional MRI connectivity in the left parietal cortex, and limbic electroencephalographic (rsEEG) rhythms as well as plasma amyloid peptide 42 (Aβ42) has shown that each is a promising biomarker of disease progression in amnestic mild cognitive impairment (aMCI) patients with prodromal Alzheimer's disease (AD). However, the value of their combined use is unknown., Objective: To evaluate the association with cognitive decline and the effect on sample size calculation when using a biomarker composite matrix in prodromal AD clinical trials., Methods: Multicenter longitudinal study with follow-up of 2 years or until development of incident dementia. APOE ɛ4-specific cerebrospinal fluid (CSF) Aβ42/P-tau cut-offs were used to identify aMCI with prodromal AD. Linear mixed models were performed 1) with repeated matrix values and time as factors to explain the longitudinal changes in ADAS-cog13, 2) with CSF Aβ42/P-tau status, time, and CSF Aβ42/P-tau status×time interaction as factors to explain the longitudinal changes in matrix measures, and 3) to compute sample size estimation for a trial implemented with the selected matrices., Results: The best composite matrix included the MRI volumes of hippocampal dentate gyrus and lateral ventricle. This matrix showed the best sensitivity to track disease progression and required a sample size 31% lower than that of the best individual biomarker (i.e., volume of hippocampal dentate gyrus)., Conclusion: Optimal matrices improved the statistical power to track disease development and to measure clinical progression in the short-term period. This might contribute to optimize the design of future clinical trials in MCI.

Auditory "oddball" event-related potentials (aoERPs), resting state functional magnetic resonance imaging (rsfMRI) connectivity, and electroencephalographic (rsEEG) rhythms were tested as longitudinal functional biomarkers of prodromal Alzheimer's disease (AD). Data were collected at baseline and four follow-ups at 6, 12, 18, and 24 months in amnesic mild cognitive impairment (aMCI) patients classified in two groups: "positive" (i.e., "prodromal AD"; n = 81) or "negative" (n = 63) based on a diagnostic marker of AD derived from cerebrospinal samples (Aβ42/P-tau ratio). A linear mixed model design was used to test functional biomarkers for Group, Time, and Group×Time effects adjusted by nuisance covariates (only data until conversion to dementia was used). Functional biomarkers that showed significant Group effects ("positive" versus "negative", p < 0.05) regardless of Time were 1) reduced rsfMRI connectivity in both the default mode network (DMN) and the posterior cingulate cortex (PCC), both also giving significant Time effects (connectivity decay regardless of Group); 2) increased rsEEG source activity at delta (<4 Hz) and theta (4-8 Hz) rhythms and decreased source activity at low-frequency alpha (8-10.5 Hz) rhythms; and 3) reduced parietal and posterior cingulate source activities of aoERPs. Time×Group effects showed differential functional biomarker progression between groups: 1) increased rsfMRI connectivity in the left parietal cortex of the DMN nodes, consistent with compensatory effects and 2) increased limbic source activity at theta rhythms. These findings represent the first longitudinal characterization of functional biomarkers of prodromal AD relative to "negative" aMCI patients based on 5 serial recording sessions over 2 years.

As research evolves in prodromal AD, the need to validate sufficiently sensitive outcome measures, e.g. the Alzheimer's Disease Composite Score (ADCOMS) is clear. In the LipiDiDiet randomized trial in prodromal AD, cognitive decline in the study population was much less than expected in the timeframe studied. While the primary composite endpoint was insufficiently sensitive to detect a difference in the modified intention to treat population, the per-protocol population showed less decline in the active than the control group, indicating better treatment effects with regular product intake. These results were further strengthened by significant benefits on secondary endpoints of cognition and function, and brain atrophy. The present post-hoc analysis investigated whether ADCOMS could detect a difference between groups in the LipiDiDiet population (138 active, 140 control). The estimated mean change in ADCOMS from baseline (standard error) was 0.085 (0.018) in the active and 0.133 (0.018) in the control group; estimated mean treatment difference -0.048 (95% confidence intervals -0.090, -0.007; p=0.023), or 36% less decline in the active group. This suggests ADCOMS identified the cognitive and functional benefits observed previously, confirming the sensitivity of this composite measure., Competing Interests: SBH and NNE report financial compensation for statistical analysis from Danone Nutricia Research. HS reports personal fees from ACImmune and MERCK, outside the submitted work. AMJH and AA are employees of Danone Nutricia Research. PJV reports grants from Inn ovative Medicine Initiative and ZonMw, during the conduct of the study, and non-financial support from GE Healthcare and grants from Biogen, outside the submitted work. AS reports grants from Academy of Finland, during the conduct of the study, and grants from Alzheimerfonden Sweden and Stockholm County Council (ALF), outside the submitted work. MK reports grants from EU Joint Program - Neurodegenerative Disease Research (MIND-AD), during the conduct of the study, and grants from Alzheimerfonden Sweden, Stockholm County Council (ALF), Academy of Finland, Swedish Research Council, Knut and Alice Wallenberg Foundation, Center for Innovative Medicine at Karolinska Institutet, Sweden, and Stiftelsen Stockholms Sjukhem, Sweden, outside the submitted work. TH reports grants from EU FP7 (LipiDiDiet), EU Joint Program - Neurodegenerative Disease Research (MIND-AD), and Danone Nutricia Research (LipiDiDiet Extension), during the conduct of the study. KB has nothing to disclose.

Background: Grey matter (GM) atrophy in Alzheimer's disease (AD) is most commonly modeled as a function of time. However, this approach does not take into account inter-individual differences in initial disease severity or changes due to aging. Here, we modeled GM atrophy within individuals across the AD clinical spectrum as a function of time, aging and MMSE, as a proxy for disease severity, and investigated how these models influence estimates of GM atrophy., Methods: We selected 523 individuals from ADNI (100 preclinical AD, 288 prodromal AD, 135 AD dementia) with abnormal baseline amyloid PET/CSF and ≥1 year of MRI follow-up. We calculated total and 90 regional GM volumes for 2281 MRI scans (median [IQR]; 4 [3-5] scans per individual over 2 [1.6-4] years) and used linear mixed models to investigate atrophy as a function of time, aging and decline on MMSE. Analyses included clinical stage as interaction with the predictor and were corrected for baseline age, sex, education, field strength and total intracranial volume. We repeated analyses for a sample of participants with normal amyloid (n = 387) to assess whether associations were specific for amyloid pathology., Results: Using time or aging as predictors, amyloid abnormal participants annually declined -1.29 ± 0.08 points and - 0.28 ± 0.03 points respectively on the MMSE and -12.23 ± 0.47 cm 3 and -8.87 ± 0.34 respectively in total GM volume (p < .001). For the time and age models atrophy was widespread and preclinical and prodromal AD showed similar atrophy patterns. Comparing prodromal AD to AD dementia, AD dementia showed faster atrophy mostly in temporal lobes as modeled with time, while prodromal AD showed faster atrophy in mostly frontoparietal areas as modeled with age (p FDR  < 0.05). Modeling change in GM volume as a function of decline on MMSE, slopes were less steep compared to those based on time and aging (-4.1 ± 0.25 cm 3 per MMSE point decline; p < .001) and showed steeper atrophy for prodromal AD compared to preclinical AD in the right inferior temporal gyrus (p < .05) and compared to AD dementia mostly in temporal areas (p FDR  < 0.05). Associations with time, aging and MMSE remained when accounting for these effects in the other models, suggesting that all measures explain part of the variance in GM atrophy. Repeating analyses in amyloid normal individuals, effects for time and aging showed similar widespread anatomical patterns, while associations with MMSE were largely reduced., Conclusion: Effects of time, aging and MMSE all explained variance in GM atrophy slopes within individuals. Associations with MMSE were weaker than those for time or age, but specific for amyloid pathology. This suggests that at least some of the atrophy observed in time or age models may not be specific to AD., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Early Alzheimer's disease (AD) detection using cerebrospinal fluid (CSF) biomarkers has been recommended as enrichment strategy for trials involving mild cognitive impairment (MCI) patients., Objective: To model a prodromal AD trial for identifying MRI structural biomarkers to improve subject selection and to be used as surrogate outcomes of disease progression., Methods: APOE ɛ4 specific CSF Aβ42/P-tau cut-offs were used to identify MCI with prodromal AD (Aβ42/P-tau positive) in the WP5-PharmaCog (E-ADNI) cohort. Linear mixed models were performed 1) with baseline structural biomarker, time, and biomarker×time interaction as factors to predict longitudinal changes in ADAS-cog13, 2) with Aβ42/P-tau status, time, and Aβ42/P-tau status×time interaction as factors to explain the longitudinal changes in MRI measures, and 3) to compute sample size estimation for a trial implemented with the selected biomarkers., Results: Only baseline lateral ventricle volume was able to identify a subgroup of prodromal AD patients who declined faster (interaction, p = 0.003). Lateral ventricle volume and medial temporal lobe measures were the biomarkers most sensitive to disease progression (interaction, p≤0.042). Enrichment through ventricular volume reduced the sample size that a clinical trial would require from 13 to 76%, depending on structural outcome variable. The biomarker needing the lowest sample size was the hippocampal subfield GC-ML-DG (granule cells of molecular layer of the dentate gyrus) (n = 82 per arm to demonstrate a 20% atrophy reduction)., Conclusion: MRI structural biomarkers can enrich prodromal AD with fast progressors and significantly decrease group size in clinical trials of disease modifying drugs.

Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) Aβ and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/Aβ 42 ( n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures ( n = 100), MCI participants enrolled in the GE067-005 study with [ 18 F]-Flutemetamol PET amyloid measures ( n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF Aβ 42 measurements ( n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/Aβ 42 ( P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen β chain confirmed by immunoassay ( P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid ( P < 0.05) replicating the association with CSF Tau/Aβ 42 . There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF Aβ 42 ( P ≈ 0.05), while both A1AT and clusterin were nominally significantly associated with CSF Aβ 42 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important.

Alzheimer's disease is a heterogeneous disorder. Understanding the biological basis for this heterogeneity is key for developing personalized medicine. We identified atrophy subtypes in Alzheimer's disease dementia and tested whether these subtypes are already present in prodromal Alzheimer's disease and could explain interindividual differences in cognitive decline. First we retrospectively identified atrophy subtypes from structural MRI with a data-driven cluster analysis in three datasets of patients with Alzheimer's disease dementia: discovery data (dataset 1: n = 299, age = 67 ± 8, 50% female), and two independent external validation datasets (dataset 2: n = 181, age = 66 ± 7, 52% female; dataset 3: n = 227, age = 74 ± 8, 44% female). Subtypes were compared on clinical, cognitive and biological characteristics. Next, we classified prodromal Alzheimer's disease participants (n = 603, age = 72 ± 8, 43% female) according to the best matching subtype to their atrophy pattern, and we tested whether subtypes showed cognitive decline in specific domains. In all Alzheimer's disease dementia datasets we consistently identified four atrophy subtypes: (i) medial-temporal predominant atrophy with worst memory and language function, older age, lowest CSF tau levels and highest amount of vascular lesions; (ii) parieto-occipital atrophy with poor executive/attention and visuospatial functioning and high CSF tau; (iii) mild atrophy with best cognitive performance, young age, but highest CSF tau levels; and (iv) diffuse cortical atrophy with intermediate clinical, cognitive and biological features. Prodromal Alzheimer's disease participants classified into one of these subtypes showed similar subtype characteristics at baseline as Alzheimer's disease dementia subtypes. Compared across subtypes in prodromal Alzheimer's disease, the medial-temporal subtype showed fastest decline in memory and language over time; the parieto-occipital subtype declined fastest on executive/attention domain; the diffuse subtype in visuospatial functioning; and the mild subtype showed intermediate decline in all domains. Robust atrophy subtypes exist in Alzheimer's disease with distinct clinical and biological disease expression. Here we observe that these subtypes can already be detected in prodromal Alzheimer's disease, and that these may inform on expected trajectories of cognitive decline.

Background: The oldest-old (subjects aged 90 years and older) population represents the fastest growing segment of society and shows a high dementia prevalence rate of up to 40%. Only a few studies have investigated protective factors for cognitive impairment in the oldest-old. The EMIF-AD 90+ Study aims to identify factors associated with resilience to cognitive impairment in the oldest-old. In this paper we reviewed previous studies on cognitive resilience in the oldest-old and described the design of the EMIF-AD 90+ Study., Methods: The EMIF-AD 90+ Study aimed to enroll 80 cognitively normal subjects and 40 subjects with cognitive impairment aged 90 years or older. Cognitive impairment was operationalized as amnestic mild cognitive impairment (aMCI), or possible or probable Alzheimer's Disease (AD). The study was part of the European Medical Information Framework for AD (EMIF-AD) and was conducted at the Amsterdam University Medical Centers (UMC) and at the University of Manchester. We will test whether cognitive resilience is associated with cognitive reserve, vascular comorbidities, mood, sleep, sensory system capacity, physical performance and capacity, genetic risk factors, hallmarks of ageing, and markers of neurodegeneration. Markers of neurodegeneration included an amyloid positron emission tomography, amyloid β and tau in cerebrospinal fluid/blood and neurophysiological measures., Discussion: The EMIF-AD 90+ Study will extend our knowledge on resilience to cognitive impairment in the oldest-old by extensive phenotyping of the subjects and the measurement of a wide range of potential protective factors, hallmarks of aging and markers of neurodegeneration., Trial Registration: Nederlands Trial Register NTR5867 . Registered 20 May 2016.

Introduction: We developed and validated a clinically applicable decision tree for the use of cerebrospinal fluid biomarkers in the diagnosis of Alzheimer's disease (AD)., Methods: Subjects with probable AD ( n  = 1004) and controls ( n =  442) were included. A decision tree was modeled using Classification And Regression Tree analysis in a training cohort (AD n =  221; controls n =  221) and validated in an independent cohort (AD n  = 783; controls n  = 221). Diagnostic performance was compared to previously defined cutoffs (amyloid β 1-42 < 813 pg/ml; tau>375 pg/ml)., Results: Two cerebrospinal fluid AD biomarker profiles were revealed: the "classical" AD biomarker profile (amyloid β 1-42: 647-803 pg/ml; tau >374 pg/ml) and an "atypical" AD biomarker profile with strongly decreased amyloid β 1-42 (<647 pg/ml) and normal tau concentrations (<374 pg/ml). Compared to previous cutoffs, the decision tree performed better on diagnostic accuracy (86% [84-88] vs 80% [78-83])., Discussion: Two cerebrospinal fluid AD biomarker profiles were identified and incorporated in a readily applicable decision tree, which improved diagnostic accuracy.

Objective: To estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants., Methods: We conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n = 443], nonfluent [nfvPPA, n = 333], semantic [svPPA, n = 401], and mixed/unclassifiable [n = 74] variants of PPA) from 36 centers, with a measure of amyloid-β pathology (CSF [n = 600], PET [n = 366], and/or autopsy [n = 378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ε4 status was determined using generalized estimating equation models., Results: Amyloid-β positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p < 0.001). Prevalence of amyloid-β positivity increased with age in nfvPPA (from 10% at age 50 years to 27% at age 80 years, p < 0.01) and svPPA (from 6% at age 50 years to 32% at age 80 years, p < 0.001), but not in lvPPA (p = 0.94). Across PPA variants, ApoE ε4 carriers were more often amyloid-β positive (58.0%) than noncarriers (35.0%, p < 0.001). Autopsy data revealed Alzheimer disease pathology as the most common pathologic diagnosis in lvPPA (76%), frontotemporal lobar degeneration-TDP-43 in svPPA (80%), and frontotemporal lobar degeneration-TDP-43/tau in nfvPPA (64%)., Interpretation: This study shows that the current PPA classification system helps to predict underlying pathology across different cohorts and clinical settings, and suggests that age and ApoE genotype should be considered when interpreting amyloid-β biomarkers in PPA patients. Ann Neurol 2018;84:737-748., (© 2018 American Neurological Association.)

Background: In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations., Main Body: Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation., Conclusion: We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

Purpose: Retinal microvasculopathy may reflect small vessel disease in the brain. Here we test the relationships between retinal vascular parameters and small vessel disease, the influence of cardiovascular risk factors on these relationships, and their common genetic background in a monozygotic twin cohort., Methods: We selected 134 cognitively healthy individuals (67 monozygotic twin pairs) aged ≥60 years from the Netherlands Twin Register for the EMIF-AD PreclinAD study. We measured seven retinal vascular parameters averaged over both eyes using fundus images analyzed with Singapore I Vessel Assessment. Small vessel disease was assessed on MRI by a volumetric measurement of periventricular and deep white matter hyperintensities. We calculated associations between RVPs and WMH, estimated intratwin pair correlations, and performed twin-specific analyses on relationships of interest., Results: Deep white matter hyperintensities volume was positively associated with retinal tortuosity in veins (P = 0.004) and fractal dimension in arteries (P = 0.001) and veins (P = 0.032), periventricular white matter hyperintensities volume was positively associated with retinal venous width (P = 0.028). Intratwin pair correlations were moderate to high for all small vessel disease/retinal vascular parameter variables (r = 0.49-0.87, P < 0.001). Cross-twin cross-trait analyses showed that retinal venous tortuosity of twin 1 could predict deep white matter hyperintensities volume of the co-twin (r = 0.23, P = 0.030). Within twin-pair differences for retinal venous tortuosity were associated with within twin-pair differences in deep white matter hyperintensities volume (r = 0.39, P = 0.001)., Conclusions: Retinal arterial fractal dimension and venous tortuosity have associations with deep white matter hyperintensities volume. Twin-specific analyses suggest that retinal venous tortuosity and deep white matter hyperintensities volume have a common etiology driven by both shared genetic factors and unique environmental factors, supporting the robustness of this relationship.

Background: With the shift of research focus towards the pre-dementia stage of Alzheimer's disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) ε4 genotype, can be used to predict amyloid pathology using machine-learning classification., Methods: We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 ± 7.2, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69.1 ± 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 ± 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE ε4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects., Results: In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 ± 0.07 in MCI and an AUC of 0.74 ± 0.08 in CN. In CN, selected features for the classifier included APOE ε4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE ε4 information did not improve after additionally adding imaging measures., Conclusions: Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE ε4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.

Behavioural variant frontotemporal dementia (bvFTD) is characterized by behavioural and social cognitive disturbances, while various psychiatric and neurodegenerative disorders may have similar clinical symptoms. Since neurodegenerative disorders are eventually progressive, whereas primary psychiatric disorders are not, this study aimed to investigate whether the change in clinical symptoms over time differed between groups and which biomarkers predicted rate of decline. Disease trajectories (median follow-up = 3 years) of frontal and stereotyped behaviour, general and frontal cognitive functioning, and social cognition were examined in bvFTD (n = 34), other neurodegenerative (n = 28) and primary psychiatric disorders (n = 43), all presenting with late-onset frontal lobe syndrome (45-75 years), using linear mixed models. To gain more insight in underlying pathological processes driving disease progression, we studied the association of baseline cerebrospinal fluid (CSF) (neurofilament light (NfL) and YKL-40 levels, phosphotau 181 to total tau ratio) and neuroimaging markers with disease trajectories. Frontal behavioural symptoms (e.g., disinhibition, apathy) worsened over time in bvFTD, whereas they improved in psychiatric disorders and remained stable in other neurodegenerative disorders. General and frontal cognitive decline was observed in bvFTD and other neurodegenerative disorders, but not in psychiatric disorders. None of the groups showed change in stereotypy and social cognition. For all diagnostic groups, higher CSF NfL levels were associated with faster frontal cognitive decline. A modest association was observed between caudate volume and stereotyped behaviour. Tracking frontal behavioural symptoms and cognition has potential to distinguish bvFTD from other disorders. CSF NfL levels seem to be associated with decline in frontal cognitive functioning., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Risk factors for cognitive decline might depend on chronological age. The aim of the study was to explore the age dependency of risk factors for cognitive decline in cognitively healthy subjects aged 55-85 years at baseline., Methods: We included 2527 cognitively healthy subjects from the Longitudinal Aging Study Amsterdam (LASA). Median follow-up was 9.1 (IQR: 3.2-19.0) years. The association of genetic and cardiovascular risk factors, depressive symptoms, inflammation markers and lifestyle risk factors with decline in MMSE and memory function was tested using spline regression analyses., Results: Subjects were on average 70.1 (SD 8.8) years old at baseline. Based on a spline regression model, we divided our sample in three age groups: ≤70 years (young-old), > 70-80 years (old) and > 80 years (oldest-old). The association of LDL cholesterol, homocysteine, hypertension, history of stroke, depressive symptoms, interleukin-6, a1-antichymotrypsin, alcohol use and smoking with cognitive decline significantly differed between the age groups. In general, the presence of these risk factors was associated with less cognitive decline in the oldest-old group compared to the young-old and old group., Conclusions: The negative effect of various risk factors on cognitive decline decreases with higher age. A combination of epidemiological factors, such as the selection towards healthier subjects during follow-up, but also risk factor specific features, for example ensuring the cerebral blood flow in case of hypertension, explain this diminished association at higher age. It is important to take these age differences into account when applying preventive strategies to avert cognitive decline.

Background: Amyloid pathology is the pathological hallmark in Alzheimer's disease (AD) and can precede clinical dementia by decades. So far it remains unclear how amyloid pathology leads to cognitive impairment and dementia. To design AD prevention trials it is key to include cognitively normal subjects at high risk for amyloid pathology and to find predictors of cognitive decline in these subjects. These goals can be accomplished by targeting twins, with additional benefits to identify genetic and environmental pathways for amyloid pathology, other AD biomarkers, and cognitive decline., Methods: From December 2014 to October 2017 we enrolled cognitively normal participants aged 60 years and older from the ongoing Manchester and Newcastle Age and Cognitive Performance Research Cohort and the Netherlands Twins Register. In Manchester we included single individuals, and in Amsterdam monozygotic twin pairs. At baseline, participants completed neuropsychological tests and questionnaires, and underwent physical examination, blood sampling, ultrasound of the carotid arteries, structural and resting state functional brain magnetic resonance imaging, and dynamic amyloid positron emission tomography (PET) scanning with [ 18 F]flutemetamol. In addition, the twin cohort underwent lumbar puncture for cerebrospinal fluid collection, buccal cell collection, magnetoencephalography, optical coherence tomography, and retinal imaging., Results: We included 285 participants, who were on average 74.8 ± 9.7 years old, 64% female. Fifty-eight participants (22%) had an abnormal amyloid PET scan., Conclusions: A rich baseline dataset of cognitively normal elderly individuals has been established to estimate risk factors and biomarkers for amyloid pathology and future cognitive decline.

Objective: To study risk factors for decreasing a β 1-42 concentrations in cerebrospinal fluid (CSF) in cognitively unimpaired individuals with initially normal amyloid and tau markers, and to investigate whether such a β 1-42 decreases are associated with subsequent decline in cognition and other biomarkers of Alzheimer's disease., Methods: Cognitively normal subjects ( n = 83, 75 ± 5 years, 35(42%) female) with normal CSF a β 1-42 and tau and repeated CSF sampling were selected from ADNI. Subject level slopes of a β 1-42 decreases were estimated with mixed models. We tested associations of baseline APP processing markers (BACE1 activity, a β 1-40 , a β 1-38 and sAPP β ) and decreasing a β 1-42 levels by including an interaction term between time and APP marker. Associations between decreasing a β 1-42 levels and clinical decline (i.e., progression to mild cognitive impairment or dementia, MMSE, memory functioning) and biological decline (tau, hippocampal volume, glucose processing and amyloid PET) over a time period of 8-10 years were assessed., Results: A β 1-42 levels decreased annually with -4.6 ± 1 pg/mL. Higher baseline BACE1 activity ( β (se) = -0.06(0.03), P < 0.05), a β 1-40 ( β (se)= -0.11(.03), P < 0.001), and a β 1-38 levels ( β (se) = -0.11(0.03), P < 0.001) predicted faster decreasing a β 1-42 . The fastest tertile of decreasing a β 1-42 rates was associated with subsequent pathophysiological processes: 11(14%) subjects developed abnormal amyloid levels after 3 ± 1.7 years, showed increased risk for clinical progression (Hazard Ratio[95CI] = 4.8[1.1-21.0]), decreases in MMSE, glucose metabolism and hippocampal volume, and increased CSF tau and amyloid aggregation on PET (all P < 0.05)., Interpretation: Higher APP processing and fast decreasing a β 1-42 could be among the earliest, pre-amyloid, pathological changes in Alzheimer's disease.

Background: There is an urgent need for novel, noninvasive biomarkers to diagnose Alzheimer's disease (AD) in the predementia stages and to predict the rate of decline. Therefore, we set up the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study. In this report we describe the design of the study, the methods used and the characteristics of the participants., Methods: Participants were selected from existing prospective multicenter and single-center European studies. Inclusion criteria were having normal cognition (NC) or a diagnosis of mild cognitive impairment (MCI) or AD-type dementia at baseline, age above 50 years, known amyloid-beta (Aβ) status, availability of cognitive test results and at least two of the following materials: plasma, DNA, magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF). Targeted and untargeted metabolomic and proteomic analyses were performed in plasma, and targeted and untargeted proteomics were performed in CSF. Genome-wide SNP genotyping, next-generation sequencing and methylation profiling were conducted in DNA. Visual rating and volumetric measures were assessed on MRI. Baseline characteristics were analyzed using ANOVA or chi-square, rate of decline analyzed by linear mixed modeling., Results: We included 1221 individuals (NC n = 492, MCI n = 527, AD-type dementia n = 202) with a mean age of 67.9 (SD 8.3) years. The percentage Aβ+ was 26% in the NC, 58% in the MCI, and 87% in the AD-type dementia groups. Plasma samples were available for 1189 (97%) subjects, DNA samples for 929 (76%) subjects, MRI scans for 862 (71%) subjects and CSF samples for 767 (63%) subjects. For 759 (62%) individuals, clinical follow-up data were available. In each diagnostic group, the APOE ε4 allele was more frequent amongst Aβ+ individuals (p < 0.001). Only in MCI was there a difference in baseline Mini Mental State Examination (MMSE) score between the A groups (p < 0.001). Aβ+ had a faster rate of decline on the MMSE during follow-up in the NC (p < 0.001) and MCI (p < 0.001) groups., Conclusions: The characteristics of this large cohort of elderly subjects at various cognitive stages confirm the central roles of Aβ and APOE ε4 in AD pathogenesis. The results of the multimodal analyses will provide new insights into underlying mechanisms and facilitate the discovery of new diagnostic and prognostic AD biomarkers. All researchers can apply for access to the EMIF-AD MBD data by submitting a research proposal via the EMIF-AD Catalog.

Introduction: Apolipoprotein E (APOE) ε4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid β (Aβ) pathology., Methods: We included 3451 Aβ+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE ε4 prevalence in relation to age, sex, education, and geographical location., Results: The APOE ε4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Aβ+ cognitively normal and Aβ+ mild cognitive impairment (P < .05) but not in Aβ+ AD dementia (P = .66). The prevalence was highest in Northern Europe but did not vary by sex or education., Discussion: The APOE ε4 prevalence in AD was higher than that in previous studies, which did not require presence of Aβ pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location., (Copyright © 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

We investigated whether amyloid-β (Aβ) and tau affected cognition in cognitively normal (CN) individuals, and whether norms for neuropsychological tests based on biomarker-negative individuals would improve early detection of dementia. We included 907 CN individuals from 8 European cohorts and from the Alzheimer's disease Neuroimaging Initiative. All individuals were aged above 40, had Aβ status and neuropsychological data available. Linear mixed models were used to assess the associations of Aβ and tau with five neuropsychological tests assessing memory (immediate and delayed recall of Auditory Verbal Learning Test, AVLT), verbal fluency (Verbal Fluency Test, VFT), attention and executive functioning (Trail Making Test, TMT, part A and B). All test except the VFT were associated with Aβ status and this influence was augmented by age. We found no influence of tau on any of the cognitive tests. For the AVLT Immediate and Delayed recall and the TMT part A and B, we calculated norms in individuals without Aβ pathology (Aβ- norms), which we validated in an independent memory-clinic cohort by comparing their predictive accuracy to published norms. For memory tests, the Aβ- norms rightfully identified an additional group of individuals at risk of dementia. For non-memory test we found no difference. We confirmed the relationship between Aβ and cognition in cognitively normal individuals. The Aβ- norms for memory tests in combination with published norms improve prognostic accuracy of dementia.

Upon publication of this article [1], it was noticed that there were some inconsistencies in Tables 1, 2 and 3. Some of the superscript letters were incorrectly assigned. Please see below the correct tables.