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Abstract With the advent of the first generation of disease‐modifying treatments for Alzheimer's disease, it is clearer now more than ever that the field needs to move toward personalized medicine. Pooling data from past trials may help identify subgroups most likely to benefit from specific treatments and thus inform future trial design. In this perspective, we report on our effort to pool data from past Alzheimer's disease trials to identify patients most likely to respond to different treatments. We delineate challenges and hurdles, from our proof‐of‐principle study, for which we requested access to trial datasets from various pharmaceutical companies and encountered obstacles in the process of arranging data‐sharing agreements through legal departments. Six phase I–III trials from three sponsors provided access to their data (total n = 3170), which included demographic information, vital signs, primary and secondary endpoints, and in a small subset, cerebrospinal fluid amyloid (n = 165, 5.2%) and tau (n = 212, 6.7%). Data could be analyzed only within specific data access platforms, limiting potential harmonization with data provided through other platforms. Limited overlap in terms of outcome measures, clinical and biological information hindered analyses. Thus, while it is a commendable advancement that (some) trials now allow researchers to study their data, we conclude that gaining access to past trial datasets is complicated, frustrating the field's communal effort to find the best treatments for the right individuals. We provide a plea to promote harmonization and open access to data, by urging trial sponsors and the academic research community alike to remove barriers to data access and improve collaboration through practicing open science and harmonizing outcome measures, to allow investigators to learn all there is to learn from past failures and successes. HIGHLIGHTS Pooling data from past Alzheimer's disease clinical trials may help identify subgroups most likely to benefit from specific treatments and may help inform future trial design. Accessing past trial datasets is complicated, frustrating the field's communal effort to find the best treatments for the right individuals. We urge trial sponsors and the academic research community to remove data access barriers and improve collaboration through practicing open science and harmonizing outcome measures.

Abstract INTRODUCTION We investigated whether mortality in memory clinic patients changed due to coronavirus disease 2019 (COVID‐19) pandemic. METHODS We included patients from the Amsterdam Dementia Cohort: (1) n = 923 pandemic patients (baseline visit: 2017–2018, follow‐up: until 2021), and (2) n = 830 historical control patients (baseline visit: 2015–2016, follow‐up: until 2019). Groups were well‐balanced. We compared mortality during pandemic with historical control patients using Cox regression. Differences in cause of death between groups were explored using Fisher's exact test. RESULTS Pandemic patients had a higher risk of mortality than historical control patients (hazard ratio [HR] [95% confidence interval {CI}] = 1.34 [1.05–1.70]). Stratified for syndrome diagnosis, the effect remained significant in dementia patients (HR [95% CI] = 1.35 [1.03–1.78]). Excluding patients who died of COVID‐19‐infection, the higher mortality risk in pandemic patients attenuated (HR [95% CI] = 1.24 [0.97–1.58]). Only the difference in cause of death between pandemic patients and historical control patients for death to COVID‐19‐infection (p = 0.001) was observed. CONCLUSION Memory clinic patients had increased mortality risk during COVID‐19 compared to historical control patients, attributable to dementia patients. Highlights We investigated if mortality rates in memory clinic patients changed due to COVID‐19 pandemic. We included patients along the cognitive continuum, including SCD, MCI, and dementia. We used a well‐balanced historical control group. Memory clinic patients had higher risk for mortality during COVID‐19 lockdown. Our results indicate that excess mortality is mainly caused by death to COVID‐19 infection.

Abstract INTRODUCTION Disease‐modifying therapies (DMTs) for Alzheimer's disease (AD) will increase diagnostic demand. A non‐invasive blood‐based biomarker (BBBM) test for detection of amyloid‐β pathology may reduce diagnostic barriers and facilitate DMT initiation. OBJECTIVE To explore heterogeneity in AD care pathways and potential role of BBBM tests. METHODS Survey of 213 healthcare professionals/payers in US/China/UK/Germany/Spain/France and two advisory boards (US/Europe). RESULTS Current diagnostic pathways are heterogeneous, meaning many AD patients are missed while low‐risk patients undergo unnecessary procedures. Confirmatory amyloid testing (cerebrospinal fluid biomarkers/positron emission tomography) is utilized in few patients, resulting in diagnostic/treatment delays. A high negative‐predictive‐value test could streamline the diagnostic pathway by reducing unnecessary procedures in low‐risk patients; supporting confirmatory testing where needed. Imminent approval of DMTs will increase need for fast and reliable AD diagnostic tests. DISCUSSION An easy‐to‐use, accurate, non‐invasive BBBM test for amyloid pathology could guide diagnostic procedures or referral, streamlining early diagnosis and DMT initiation. Highlights This study explored AD care pathways and how BBBM may meet diagnostic demands Current diagnostic pathways are heterogeneous, with country and setting variations Many AD patients are missed, while low‐risk patients undergo unnecessary procedures An easy‐to‐use, accurate, non‐invasive BBBM test for amyloid pathology is needed This test could streamline early diagnosis of amyloid pathology and DMT initiation

Abstract Interpretation of axonal damage biomarker Neurofilament Light chain (NfL) concentrations is difficult due to the lack of age‐specific and disease‐specific reference values. We here developed an interactive interface to support interpretation of NfL results in human body fluids. We used NfL values of 1698 individuals without a neurological disorder, aged 19–85 years, and patients with MS and dementias. Percentile regression estimates per diagnosis populate interactive graphs, alongside NfL background information (available on: https://mybiomarkers.shinyapps.io/Neurofilament). This accessible interface provides reference for interpretation of the individual patient results for clinicians. It showcases an adaptable method to support interpretation of age‐dependent biomarkers in neurology.

Abstract The disease trajectory and healthcare requirements of patients with young‐onset dementia (YOD) differ from those of older patients. Accurate data about YOD is crucial to improve diagnosis and optimize care. PRECODE‐GP aims to set up a prospective national database of patients with YOD to gain insight into the occurrence and characteristics of patients with YOD in memory clinics in the Netherlands. The national database includes data from dementia patients aged

Abstract INTRODUCTION Our previous antibody‐based cerebrospinal fluid (CSF) proteomics study showed that Thimet oligopeptidase (THOP1), an amyloid beta (Aβ) neuropeptidase, was increased in mild cognitive impairment with amyloid pathology (MCI‐Aβ+) and Alzheimer's disease (AD) dementia compared with controls and dementia with Lewy bodies (DLB), highlighting the potential of CSF THOP1 as an early specific biomarker for AD. We aimed to develop THOP1 immunoassays for large‐scale analysis and validate our proteomics findings in two independent cohorts. METHODS We developed in‐house CSF THOP1 immunoassays on automated Ella and Simoa platforms. The performance of the different assays were compared using Passing–Bablok regression analysis in a subset of CSF samples from the discovery cohort (n = 72). Clinical validation was performed in two independent cohorts (cohort 1: n = 200; cohort 2: n = 165) using the Ella platform. RESULTS THOP1 concentrations moderately correlated between proteomics analysis and our novel assays (Rho > 0.580). In both validation cohorts, CSF THOP1 was increased in MCI‐Aβ+ (>1.3‐fold) and AD (>1.2‐fold) compared with controls; and between MCI‐Aβ+ and DLB (>1.2‐fold). Higher THOP1 concentrations were detected in AD compared with DLB only when both cohorts were analyzed together. In both cohorts, THOP1 correlated with CSF total tau (t‐tau), phosphorylated tau (p‐tau), and Aβ40 (Rho > 0.540) but not Aβ42. DISCUSSION Validation of our proteomics findings underpins the potential of CSF THOP1 as an early specific biomarker associated with AD pathology. The use of antibody‐based platforms in both the discovery and validation phases facilitated the translation of proteomics findings, providing an additional workflow that may accelerate the development of biofluid‐based biomarkers.

Abstract Introduction We evaluated determinants associated with care partner outcomes along the Alzheimer's disease (AD) stages. Methods We included n = 270 care partners of amyloid‐positive patients in the pre‐dementia and dementia stages of AD. Using linear regression analysis, we examined determinants of four care partner outcomes: informal care time, caregiver distress, depression, and quality of life (QoL). Results More behavioral symptoms and functional impairment in patients were associated with more informal care time and depressive symptoms in care partners. More behavioral symptoms were related with more caregiver distress. Spouse care partners spent more time on informal care and QoL was lower in female care partners. Behavioral problems and subtle functional impairment of the patient predisposed for worse care partner outcomes already in the pre‐dementia stages. Discussion Both patient and care partner determinants contribute to the care partner outcomes, already in early disease stages. This study provides red flags for high care partner burden.

Abstract The key to stopping Alzheimer's disease (AD) lies in the pre‐dementia stages, with the goal to stop AD before dementia has started. We present the rationale and design of the ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) project, which aims to invest in personalized medicine for AD. ABOARD is a Dutch public–private partnership of 32 partners, connecting stakeholders from a scientific, clinical, and societal perspective. The 5‐year project is structured into five work packages on (1) diagnosis, (2) prediction, (3) prevention, (4) patient‐orchestrated care, and (5) communication and dissemination. ABOARD functions as a network organization in which professionals interact cross‐sectorally. ABOARD has a strong junior training program “Juniors On Board.” Project results are shared with society through multiple communication resources. By including relevant partners and involving citizens at risk, patients, and their care partners, ABOARD builds toward a future with personalized medicine for AD. Highlights ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) is a public–private research project executed by 32 partners that functions as a network organization. Together, the project partners build toward a future with personalized medicine for Alzheimer's disease. Although ABOARD is a Dutch consortium, it has international relevance. ABOARD improves diagnosis, prediction, prevention, and patient‐orchestrated care.

Abstract Objective To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition. Methods We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [18F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas. Results Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P

Abstract Background The development of novel diagnostics enables increasingly earlier diagnosis of Alzheimer's disease (AD). Timely diagnosis may benefit patients by reducing their uncertainty regarding the cause of symptoms, yet does not always provide patients with the desired certainty. Objective To examine, using both quantitative and qualitative methods, uncertainty communicated by memory clinic clinicians in post‐diagnostic testing consultations with patients and their caregivers. Methods First, we identified all uncertainty expressions of 22 clinicians in audiotaped post‐diagnostic testing consultations with 78 patients. Second, we statistically explored relationships between patient/clinician characteristics and uncertainty expressions. Third, the transcribed uncertainty expressions were qualitatively analysed, determining the topic to which they pertained, their source and initiator/elicitor (clinicians/patients/caregivers). Results Within 57/78 (73%) consultations, clinicians expressed in total 115 uncertainties, of which 37% elicited by the patient or caregiver. No apparent relationships were found between patient/clinician characteristics and whether or not, and how often clinicians expressed uncertainty. Uncertainty expressions pertained to ten different topics, most frequently patient's diagnosis and symptom progression. Expressed uncertainty was mostly related to the unpredictability of the future and limits to available knowledge. Discussion and conclusions The majority of clinicians openly discussed the limits of scientific knowledge and diagnostic testing with patients and caregivers in the dementia context. Noticeably, clinicians did not discuss uncertainty in about one quarter of consultations. More evidence is needed on the beneficial and/or harmful effects on patients of discussing uncertainty with them. This knowledge can be used to support clinicians to optimally convey uncertainty and facilitate patients' uncertainty management.

Abstract 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 (

Abstract Introduction We aimed to describe clinician‐patient communication in the diagnostic process of memory clinics, specifically clinician behavior known to facilitate knowledgeable participation of patients during consultations. Methods In this multicenter, observational study, we audio‐recorded routine diagnostic consultations of 41 clinicians and 136 patients/caregivers at eight memory clinics. Patients/caregivers completed surveys after each audiotaped consultation. We used a study‐specific coding scheme to categorize communication behavior. Results Clinicians often provided information on (results of) diagnostic testing. They infrequently invited questions and/or checked understanding. Clinician behavior to involve patients in decision‐making about diagnostic testing was limited. Of note, patients/caregivers rarely expressed their information or involvement preferences. Yet, approximately, one quarter of them would have liked to receive more information. Discussion Involving patients more explicitly by means of shared decision‐making could benefit the quality of care provided in memory clinics because it enables clinicians to attune the diagnostic workup to the individual patient's needs.

Abstract Introduction To construct a prognostic model based on amyloid positron emission tomography (PET) to predict clinical progression in individual patients with mild cognitive impairment (MCI). Methods We included 411 MCI patients from the Alzheimer's Disease Neuroimaging Initiative. Prognostic models were constructed with Cox regression with demographics, magnetic resonance imaging, and/or amyloid PET to predict progression to Alzheimer's disease dementia. The models were validated in the Amsterdam Dementia Cohort. Results The combined model (Harrell's C = 0.82 [0.78–0.86]) was significantly superior to demographics (β = 0.100, P < .001), magnetic resonance imaging (β = 0.037, P = .011), and PET only models (β = 0.053, P = .003).The models can be used to calculate individualized risk, for example, a female MCI patient (age = 60, APOE ε4 positive, Mini‐Mental State Examination = 25, hippocampal volume = 5.8 cm3, amyloid PET positive) has 35% (19–57) risk in one year and 85% (64–97) risk in three years. Model performances in the Amsterdam Dementia Cohort were reasonable. Discussion The present study facilitates the interpretation of an amyloid PET result in the context of a patient's own characteristics and clinical assessment.

Abstract Background Patients often perceive a lumbar puncture (LP) as an invasive procedure. We aimed to evaluate the impact of a 3‐minute educational animation‐video explaining the LP procedure, on patients’ knowledge, uncertainty, anxiety, and post‐LP complications. Methods We included 203 newly referred memory clinic patients, who were randomly assigned to one of three conditions: (1) home viewing of the video, (2) clinic viewing of the video, or (3) control condition (care as usual). Participants completed questionnaires measuring knowledge as information recall, uncertainty, anxiety, and post‐LP complications, the latter when patients underwent an LP procedure (n = 145). Results Viewing the video increased information recall for both home (P

Abstract Introduction The Dutch Brain Research Registry aims to facilitate online recruitment of participants for brain disease studies. Methods Registrants were primarily recruited through an online social media campaign. The registration process included a short questionnaire, which was subsequently used in the prescreening process to match participants to studies. Results In the first 18 months, 17,218 registrants signed up (58±11 years old, 78% female). Out of 34,696 study invitations that were sent, 36% were accepted by registrants, of which 50% to 84% were finally enrolled, resulting in 10,661 participants in 28 studies. Compared to non‐participants, study participants were more often older, male, more highly educated, retired or unemployed, non‐smoking, healthier, and more often had a family member with dementia. Discussion The Dutch Brain Research Registry facilitates effective matching of participants to brain disease studies. Participant factors related to study enrollment may reflect facilitators or barriers for participation, which is useful for improving recruitment strategies.

Abstract Background Prognostic studies in the context of Alzheimer's disease (AD) mainly predicted time to dementia. However, it is questionable whether onset of dementia is the most relevant outcome along the AD disease trajectory from the perspective of patients and their care partners. Therefore, we aimed to identify the most relevant outcomes from the viewpoint of patients and care partners. Methods We used a two‐step, mixed‐methods approach. As a first step we conducted four focus groups in the Netherlands to elicit a comprehensive list of outcomes considered important by patients (n = 12) and care partners (n = 14) in the prognosis of AD. The focus groups resulted in a list of 59 items, divided into five categories. Next, in an online European survey, we asked participants (n = 232; 99 patients, 133 care partners) to rate the importance of all 59 items (5‐point Likert scale). As participants were likely to rate a large number of outcomes as “important” (4) or “very important” (5), we subsequently asked them to select the three items they considered most important. Results The top‐10 lists of items most frequently mentioned as “most important” by patients and care partners were merged into one core outcome list, comprising 13 items. Both patients and care partners selected outcomes from the category “cognition” most often, followed by items in the categories “functioning and dependency” and “physical health.” No items from the category “behavior and neuropsychiatry” and “social environment” ended up in our core list of relevant outcomes. Conclusion We identified a core list of outcomes relevant to patients and care partner, and found that prognostic information related to cognitive decline, dependency, and physical health are considered most relevant by both patients and their care partners.

Abstract Introduction We evaluated for two novel automated biomarker assays how cerebrospinal fluid (CSF) amyloid beta (Aβ)1– 42‐ratios improved the concordance with amyloid positron emission tomography (PET) positivity compared to Aβ1– 42 alone. Methods We selected 288 individuals from the Amsterdam Dementia Cohort across the Alzheimer's disease clinical spectrum when they had both CSF and amyloid PET visual read available, regardless of diagnosis. CSF Aβ1– 42, phosphorylated tau (p‐tau), and total tau (t‐tau) were measured with Elecsys and Lumipulse assays, and Aβ1–40 with Lumipulse. CSF cut‐points were defined using receiver operating characteristic (ROC) for amyloid PET positivity. Results For both Elecsys and Lumipulse the p‐tau/Aβ1– 42, Aβ1– 42/Aβ1– 40, and t‐tau/Aβ1– 42 ratios showed similarly good concordance with amyloid PET (Elecsys: 93,90,90%; Lumipulse: 94,92,90%) and were higher than Aβ1– 42 alone (Elecsys 85%; Lumipulse 84%). Discussion Biomarker ratios p‐tau/Aβ1– 42, Aβ1– 42/Aβ1– 40, t‐tau/Aβ1– 42 on two automated platforms show similar optimal concordance with amyloid PET in a memory clinic cohort.

Abstract Background Heightened public awareness about Alzheimer's disease and dementia increases the need for at‐home cognitive self‐testing. We offered Cognitive Online Self‐Test Amsterdam (COST‐A) to independent groups of cognitively normal adults and investigated the robustness of a norm‐score formula and cutoff. Methods Three thousand eighty‐eight participants (mean age ± standard deviation = 61 ± 12 years, 70% female) completed COST‐A and evaluated it. Demographically adjusted norm scores were the difference between expected COST‐A scores, based on age, gender, and education, and actual scores. We applied the resulting norm‐score formula to two independent cohorts. Results Participants evaluated COST‐A to be of adequate difficulty and duration. Our norm‐score formula was shown to be robust: ≈8% of participants in two cognitively normal cohorts had abnormal scores. A cutoff of ‐1.5 standard deviations proved optimal for distinguishing normal from impaired cognition. Conclusion With robust norm scores, COST‐A is a promising new tool for research and clinical practice, providing low cost and minimally invasive remote assessment of cognitive functioning.

Abstract Introduction We investigated relationships among genetic determinants of Alzheimer's disease (AD), amyloid/tau/neurodegenaration (ATN) biomarkers, and risk of dementia. Methods We studied cognitively normal individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort and SCIENCe project. We examined associations between genetic variants and ATN biomarkers, and evaluated their predictive value for incident dementia. A polygenic risk score (PRS) was calculated based on 39 genetic variants. The APOE gene was not included in the PRS and was analyzed separately. Results The PRS and APOE ε4 were associated with amyloid‐positive ATN profiles, and APOE ε4 additionally with isolated increased tau (A–T+N–). A high PRS and APOE ε4 separately predicted AD dementia. Combined, a high PRS increased while a low PRS attenuated the risk associated with ε4 carriers. Discussion Genetic variants beyond APOE are clinically relevant and contribute to the pathophysiology of AD. In the future, a PRS might be used in individualized risk profiling.

Abstract Background We studied to what degree and at whose initiative 25 informational topics, formerly identified as important, are discussed in diagnostic consultations. Methods Audio recordings of clinician–patient consultations of 71 patients and 32 clinicians, collected in eight Dutch memory clinics, were independently content‐coded by two coders. The coding scheme encompassed 25 informational topics. Results Approximately half (Mdn = 12) of the 25 topics were discussed per patient during the diagnostic process, with a higher frequency among individuals receiving a dementia diagnosis (Mdn = 14) compared to others (Mdn = 11). Individual topics ranged from being discussed with 2/71 (3%) to 70/71 (99%) of patients. Patients and/or care partners rarely initiated topic discussion (10%). When they did, they often enquired about one of the least frequently addressed topics. Conclusion Most patients received information on approximately half of the important informational topics. Providing the topic list to patients and care partners beforehand could allow consultation preparation and stimulate participation.

Abstract Introduction Weight loss is associated with higher mortality and progression of cognitive decline, but its associations with magnetic resonance imaging (MRI) changes related to Alzheimer's disease (AD) are unknown. Methods We included 412 patients from the NUDAD project, comprising 129 with AD dementia, 107 with mild cognitive impairment (MCI), and 176 controls. Associations between nutritional status and MRI measures were analyzed using linear regression, adjusted for age, sex, education, cognitive functioning, and cardiovascular risk factors. Results Lower body mass index (BMI), fat mass (FM), and fat free mass index were associated with higher medial temporal atrophy (MTA) scores. Lower BMI, FM, and waist circumference were associated with more microbleeds. Stratification by diagnosis showed that the observed associations with microbleeds were only significant in MCI. Discussion Lower indicators of nutritional status were associated with more MTA and microbleeds, with largest effect sizes in MCI.

Abstract INTRODUCTION We examined associations between nutritional biomarkers and clinical progression in individuals with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD)‐type dementia. METHODS We included 528 individuals (64 ± 8 years, 46% F, follow‐up 2.1 ± 0.87 years) with SCD (n = 204), MCI (n = 130), and AD (n = 194). Baseline levels of cholesterol, triglycerides, glucose, homocysteine, folate, vitamin A, B12, E and uridine were measured in blood and S‐adenosylmethionine and S‐adenosylhomocysteine in cerebrospinal fluid. We determined associations between nutritional biomarkers and clinical progression using Cox proportional hazard models. RESULTS Twenty‐two (11%) patients with SCD, 45 (35%) patients with MCI, and 100 (52%) patients with AD showed clinical progression. In SCD, higher levels of low‐density lipoprotein (LDL) cholesterol were associated with progression (hazard ratio [HR] [95% confidence interval (CI)] 1.88 [1.04 to 3.41]). In AD, lower uridine levels were associated with progression (0.79 [0.63 to 0.99]). DISCUSSION Our findings suggest that LDL cholesterol and uridine play a—stage‐dependent—role in the clinical progression of AD.

Abstract Objective To study risk factors for decreasing aβ1–42 concentrations in cerebrospinal fluid (CSF) in cognitively unimpaired individuals with initially normal amyloid and tau markers, and to investigate whether such aβ1–42 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 aβ1–42 and tau and repeated CSF sampling were selected from ADNI. Subject level slopes of aβ1–42 decreases were estimated with mixed models. We tested associations of baseline APP processing markers (BACE1 activity, aβ1–40, aβ1–38 and sAPPβ) and decreasing aβ1–42 levels by including an interaction term between time and APP marker. Associations between decreasing aβ1–42 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 Aβ1–42 levels decreased annually with −4.6 ± 1 pg/mL. Higher baseline BACE1 activity (β(se) = −0.06(0.03), P < 0.05), aβ1–40 (β(se)= −0.11(.03), P < 0.001), and aβ1–38 levels (β(se) = −0.11(0.03), P < 0.001) predicted faster decreasing aβ1–42. The fastest tertile of decreasing aβ1–42 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 aβ1–42 could be among the earliest, pre‐amyloid, pathological changes in Alzheimer's disease.

Abstract Introduction We compared the automated Elecsys and manual Innotest immunoassays for cerebrospinal fluid (CSF) Alzheimer's disease biomarkers in a multicenter diagnostic setting. Methods We collected CSF samples from 137 participants in eight local memory clinics. Amyloid β(1–42) (Aβ42), total tau (t‐tau), and phosphorylated tau (p‐tau) were centrally analyzed with Innotest and Elecsys assays. Concordances between methods were assessed. Results Biomarker results strongly correlated between assays with Spearman's ρ 0.94 for Aβ42, 0.98 for t‐tau, and 0.98 for p‐tau. Using Gaussian mixture modeling, cohort‐specific cut‐points were estimated at 1092 pg/mL for Aβ42, 235 pg/mL for t‐tau, and 24 pg/mL for p‐tau. We found an excellent concordance of biomarker abnormality between assays of 97% for Aβ42 and 96% for both t‐tau and p‐tau. Discussion The high concordances between Elecsys and Innotest in this nonacademic, multicenter cohort support the use of Elecsys for CSF Alzheimer's disease diagnostics and allow conversion of results between methods.

Abstract Introduction Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression. Methods We included 674 patients with SCD (46% female, 64 ± 9 years, Mini–Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts. Results After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8). Discussion We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable.

Abstract Introduction We studied, using a data‐driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. Methods In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types. Results Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%. Discussion Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.

Abstract Introduction Co‐occurrence of cerebrovascular disease and depression led to the “vascular depression hypothesis”. White matter hyperintensities (WMHs) have been associated with depressive symptoms in population‐based studies. We studied the association between small vessel disease and depressive symptoms in a memory clinic population. Methods We included >2000 patients with subjective cognitive decline (SCD), mild cognitive impairment, and Alzheimer's disease (AD). Magnetic resonance imaging was rated for WMHs, lacunes, and microbleeds. Depressive symptoms were assessed using the Geriatric Depression Scale. We performed logistic regression analysis. Results Depressive symptoms were present in AD: 17%; mild cognitive impairment: 25%; and SCD: 23%. SCD patients with WMHs showed higher propensity of depressive symptoms than AD patients with WMHs. AD patients with microbleeds were more likely to have depressive symptoms compared with AD patients without microbleeds (odds ratio = 1.70; 95% confidence interval: 1.08–2.68). Discussion Microbleeds are associated with depressive symptoms in AD, supporting a potential role of cerebral amyloid angiopathy in the occurrence of depressive symptoms in AD.

Abstract Introduction Identification of blood‐based metabolic changes might provide early and easy‐to‐obtain biomarkers. Methods We included 127 Alzheimer's disease (AD) patients and 121 control subjects with cerebrospinal fluid biomarker‐confirmed diagnosis (cutoff tau/amyloid β peptide 42: 0.52). Mass spectrometry platforms determined the concentrations of 53 amine compounds, 22 organic acid compounds, 120 lipid compounds, and 40 oxidative stress compounds. Multiple signatures were assessed: differential expression (nested linear models), classification (logistic regression), and regulatory (network extraction). Results Twenty‐six metabolites were differentially expressed. Metabolites improved the classification performance of clinical variables from 74% to 79%. Network models identified five hubs of metabolic dysregulation: tyrosine, glycylglycine, glutamine, lysophosphatic acid C18:2, and platelet‐activating factor C16:0. The metabolite network for apolipoprotein E (APOE) ε4 negative AD patients was less cohesive compared with the network for APOE ε4 positive AD patients. Discussion Multiple signatures point to various promising peripheral markers for further validation. The network differences in AD patients according to APOE genotype may reflect different pathways to AD.

Abstract Introduction Synaptic membrane formation depends on nutrients that fuel metabolic pathways for the synthesis of constituent phospholipids. Consequently, insufficient availability of such nutrients may restrict membrane formation and contribute to synaptic dysfunction in Alzheimer's disease (AD). We assessed whether blood and cerebrospinal fluid (CSF) concentrations of nutrients related to phospholipid synthesis differ among patients with AD, mild cognitive impairment (MCI), and control subjects. Methods Concentrations of uridine, choline, folate, homocysteine, and other related metabolites were analyzed in paired blood and CSF samples from subjects selected from the Amsterdam Dementia Cohort with AD (n = 150; age, 66 ± 7 years; 37% female), MCI (n = 148; age, 66 ± 8 years; 37% female), and control subjects (n = 148; age, 59 ± 8 years; 38% female). Results Age‐ and gender‐adjusted analysis of variance revealed different concentrations of circulating uridine, choline, and folate and CSF uridine, folate, and homocysteine (all P

Abstract Introduction We studied the effect of long‐term storage at −80°C on cerebrospinal fluid (CSF) biomarker levels. Our approach assumed consistency of mean biomarker levels in a homogenous Alzheimer's disease patient cohort over time. Methods We selected 148 Alzheimer's disease samples that had inclusion dates equally distributed over the years 2001 to 2013 from our biobank. The concentrations of CSF biomarkers, amyloid β1–42 (Aβ1–42), total tau (T‐tau), and phosphorylated tau181 (P‐tau), were measured with one enzyme‐linked immunosorbent assay lot. Results were compared with historical results obtained at biobank inclusion. Results Linear regression analyses showed that the levels of CSF biomarkers, Aβ1–42, T‐tau, and P‐tau, were not related to storage time at −80°C (β = 0.015, 0.048, and 0.0016 pg/mL per day, not significant). However, the differences between remeasured concentrations of Aβ1–42 and concentrations at biobank inclusion measured for more than 30 assay batches increased with increasing time difference. Discussion The levels of CSF biomarkers, Aβ1–42, T‐tau, and P‐tau, did not significantly change during the maximum period of 12 years of storage at −80°C. Batch variation for Aβ1–42 is a factor that should be controlled for when using historical cohorts.

Abstract A lumbar puncture (LP) is performed to obtain cerebrospinal fluid. It is implemented in the clinic on a routine basis to aid the diagnosis of neurologic diseases. This paper accompanies an informative lumbar puncture video that shows the lumbar puncture procedure as routinely performed in the VUmc Alzheimer center based on the consensus guidelines by Engelborghs et al.