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Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder affecting 50 million people globally. It is characterized by the presence of extracellular senile plaques and intracellular neurofibrillary tangles, consisting of amyloid-β and hyperphosphorylated tau proteins, respectively. Despite global research efforts, there is currently no cure available, due in part to an incomplete understanding of the disease pathogenesis. Numerous possible mechanisms, or hypotheses, explaining the origins of sporadic or late-onset AD have been proposed, including the amyloid-β, inflammatory, vascular, and infectious hypotheses. However, despite ample evidence, the failure of multiple trial drugs at the clinical stage illuminates the possible pitfalls of these hypotheses. Systems biology is a strategy which aims to elucidate the interactions between parts of a whole. Using this approach, the current paper shows how the four previously mentioned hypotheses of AD pathogenesis can be intricately connected. This approach allows for seemingly contradictory evidence to be unified in a system-focused explanation of sporadic AD development. Within this view, it is seen that infectious agents, such as P. gingivalis, may play a central role. The data presented here shows that when present, P. gingivalis or its virulence factors, such as gingipains, may induce or exacerbate pathologies underlying sporadic AD. This evidence supports the view that infectious agents, and specifically P. gingivalis, may be suitable treatment targets in AD.

BACKGROUND: Magnetic resonance imaging (MRI) has become important in the diagnostic work-up of neurodegenerative diseases. icobrain dm, a CE-labeled and FDA-cleared automated brain volumetry software, has shown potential in differentiating cognitively healthy controls (HC) from Alzheimer's disease (AD) dementia (ADD) patients in selected research cohorts. OBJECTIVE: This study examines the diagnostic value of icobrain dm for AD in routine clinical practice, including a comparison to the widely used FreeSurfer software, and investigates if combined brain volumes contribute to establish an AD diagnosis. METHODS: The study population included HC (n = 90), subjective cognitive decline (SCD, n = 93), mild cognitive impairment (MCI, n = 357), and ADD (n = 280) patients. Through automated volumetric analyses of global, cortical, and subcortical brain structures on clinical brain MRI T1w (n = 820) images from a retrospective, multi-center study (REMEMBER), icobrain dm's (v.4.4.0) ability to differentiate disease stages via ROC analysis was compared to FreeSurfer (v.6.0). Stepwise backward regression models were constructed to investigate if combined brain volumes can differentiate between AD stages. RESULTS: icobrain dm outperformed FreeSurfer in processing time (15-30 min versus 9-32 h), robustness (0 versus 67 failures), and diagnostic performance for whole brain, hippocampal volumes, and lateral ventricles between HC and ADD patients. Stepwise backward regression showed improved diagnostic accuracy for pairwise group differentiations, with highest performance obtained for distinguishing HC from ADD (AUC = 0.914; Specificity 83.0%; Sensitivity 86.3%). CONCLUSION: Automated volumetry has a diagnostic value for ADD diagnosis in routine clinical practice. Our findings indicate that combined brain volumes improve diagnostic accuracy, using real-world imaging data from a clinical setting. ispartof: JOURNAL OF ALZHEIMERS DISEASE vol:83 issue:2 pages:623-639 ispartof: location:Netherlands status: published

Advanced Alzheimer's disease (AD) is characterized by higher noradrenaline metabolite levels that may be associated with AD pathology. The locus coeruleus (LC) is the main site for cerebral noradrenaline synthesis and LC volume loss occurs as early as Braak stage 1. This study investigates the association between noradrenergic turnover and brain morphology, and the modifying effect of AD pathology. The study sample included 77 memory clinic patients (37 cognitively unimpaired and 40 cognitively impaired (mild cognitive impairment or AD dementia)). Cortical thickness and volumetric analyses were performed using FreeSurfer. Cerebrospinal fluid was analyzed for noradrenergic metabolite 3-methoxy-4hydroxyphenylethyleneglycol (MHPG), A beta 42 and phosphorylated tau. Higher MHPG was associated with lower cortical thickness and hippocampal volume at lower, but subthreshold, levels of A beta 42 and at higher p-tau levels. These associations remained significant after adding APOE-E4 or cognitive status as covariates. Our results suggest that greater MHPG together with worse AD pathology contributes to neurodegeneration, possibly before significant amyloidosis. The noradrenergic system may play an important role in early detection of AD-related processes. (C) 2021 The Authors. Published by Elsevier Inc.

The noradrenergic (NE) locus coeruleus (LC) is vulnerable to hyperphosphorylated tau, and dysregulated NE-metabolism is linked to greater tau and disease progression. We investigated whether elevated NE-metabolism alone predicts memory decline or whether concomitant presence of tau and amyloid-β is required. Among 114 memory clinic participants, time trends (max. six years) showed dose-response declines in learning across groups with elevated NE-metabolite 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG) with no, one, or two Alzheimer’s disease biomarkers; and no decline in the low MHPG group. Elevated MHPG is required and sufficient to detect learning declines, supporting a pathophysiologic model including the LC-NE system contributing to initial Alzheimer’s disease-related processes.

Background: With the more widespread use of 18F-radioligand-based amyloid-β (Aβ) PET-CT imaging, we evaluated Aβ binding and the utility of neocortical 18F-Flutemetamol standardized uptake value ratio (SUVR) as a biomarker. Objective: 18F-Flutemetamol SUVR was used to differentiate 1) mild cognitive impairment (MCI) from Alzheimer's disease (AD), and 2) MCI from other non-AD dementias (OD). Methods: 109 patients consecutively recruited from a University memory clinic underwent clinical evaluation, neuropsychological test, MRI and 18F-Flutemetamol PET-CT. The diagnosis was made by consensus of a panel consisting of 1 neuroradiologist and 2 geriatricians. The final cohort included 13 subjective cognitive decline (SCD), 22 AD, 39 MCI, and 35 OD. Quantitative analysis of 16 region-of-interests made by Cortex ID software (GE Healthcare). Results: The global mean 18F-Flutemetamol SUVR in SCD, MCI, AD, and OD were 0.50 (SD-0.08), 0.53 (SD-0.16), 0.76 (SD-0.10), and 0.56 (SD-0.16), respectively, with SUVR in SCD and MCI and OD being significantly lower than AD. Aβ binding in SCD, MCI, and OD was heterogeneous, being 23%, 38.5%, and 42.9% respectively, as compared to 100% amyloid positivity in AD. Using global SUVR, ROC analysis showed AUC of 0.868 and 0.588 in differentiating MCI from AD and MCI from OD respectively.Conclusion: 18F-Flutemetamol SUVR differentiated MCI from AD with high efficacy (high negative predictive value), but much lower efficacy from OD. The major benefit of the test was to differentiate cognitively impaired patients (either SCD, MCI, or OD) without AD-related-amyloid-pathology from AD in the clinical setting, which was under-emphasized in the current guidelines proposed by Amyloid Imaging Task Force.Keywords: 18F-Flutemetamol; Alzheimer’s disease; amyloid; dementia; early-onset Alzheimer’s disease; mild cognitive impairment; positron emission tomography. Refereed/Peer-reviewed

The semantic fluency task is a widely used clinical tool in the diagnostic process of Alzheimer's disease. The task requires efficient mapping of the semantic space to produce as many items as possible within a semantic category. We examined whether healthy volunteers (n = 42) and patients with early Alzheimer's disease (24 diagnosed with amnestic Mild Cognitive Impairment and 18 with early Alzheimer's dementia) take advantage of and travel in the semantic space differently. With focus on the animal fluency task, we sought to emulate the detailed structure of the multidimensional semantic space by utilizing word2vec-method from the natural language processing domain. To render the resulting multidimensional semantic space visually comprehensible, we applied a dimensionality reduction algorithm (t-SNE), which enabled a straightforward division of the semantic space into sub-categories. Moving in semantic space was quantified with the number of items created, sub-categories visited, and switches and returns to these sub-categories. Multinomial logistic regression models were used to predict the diagnostic group with these independent variables. We found that returning to a sub-category provided additional information, besides the number of words produced in the task, to differentiate patients with Alzheimer's dementia from both amnestic Mild Cognitive Impairment patients and healthy controls. The results suggest that the frequency of returning to a sub-category may serve as an additional aid for clinicians in diagnosing early Alzheimer's disease. Moreover, our results imply that the combination of word2vec and subsequent t-SNE-visualization may offer a valuable tool for examining the semantic space and its sub-categories.

Background: Wide-ranging functional defects in eye movements have been reported in Alzheimer's disease (AD) dementia. The detection of abnormal eye movements and reading problems may identify persons at risk of AD when clear clinical symptoms are lacking. Objective: To examine whether computer-based eye-tracking (ET) analysis of King-Devick (KD) test results differentiates cognitively healthy persons from persons with minor problems in cognitive testing or diagnosed mild AD. Methods: We recruited 78 participants (57 non-demented, 21 with mild AD) who underwent neurological examination, the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological test battery (CERAD-NB), and a Clinical Dementia Rating (CDR) interview. The non-demented participants were further divided into control (normal CERAD subtests, mean MMSE= 28) and objective mild cognitive impairment (MCI; decline in at least one CERAD memory score, mean MMSE= 27) groups. The KD reading test was performed using computer-based ET. The total time used for the reading test, errors made, fixation and saccade durations, and saccade amplitudes were analyzed. Results: We found significant differences between the control, objective MCI, and AD groups in regard to the mean saccade amplitude (3.58, 3.33, and 3.21 ms, respectively, p < 0.03) and duration (27.1, 25.3, and 24.8 ms, respectively, p < 0.05). The KD error scores in the AD group differed significantly (p < 0.01) from the other groups. Conclusion: Computed ET analysis of the KD test may help detect persons with objective MCI early when clear clinical symptoms are lacking. The portable device for ET is easy to use in primary health care memory clinics.

BACKGROUND: Distinguishing between Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) results in poor diagnostic accuracy. OBJECTIVE: To investigate the utility of electroencephalography (EEG)-based biomarkers in comparison and in addition to established cerebrospinal fluid (CSF) biomarkers in the AD versus FTLD differential diagnosis. METHODS: The study cohort comprised 37 AD and 30 FTLD patients, of which 17 AD and 9 FTLD patients had definite diagnoses. All participants had CSF neurochemical (NCM) biomarker analyses (Aβ1-42, T-tau, P-tau181, and Nf-L) and underwent 19-channel resting-state EEG. From the EEG spectra, dominant frequency peaks were extracted in four regions resulting in four dominant frequencies. This produced eight features (4 NCM + 4 EEG). RESULTS: When NCM and EEG markers were combined, the diagnostic accuracy increased significantly. In the whole group, the accuracy went up from 79% (NCM) to almost 82%, while in the definite group only, it went up from around 85% to almost 95%. Two differences in the occurrence of the dominant EEG frequency were discovered: people lacking a clear dominant peak almost all had definite AD, while people with two peaks more often had FTLD. CONCLUSION: Combining EEG with NCM biomarkers resulted in differential diagnostic accuracies of 82% in clinically diagnosed AD and FTD patients and of 95% in patients having a definite diagnosis, which was significantly better than with EEG or NCM biomarkers alone. This suggests that NCM and EEG markers are complementary, revealing different aspects of the disease and therefore confirms again their relevance in developing additional diagnosis tools. ispartof: JOURNAL OF ALZHEIMERS DISEASE vol:90 issue:4 pages:1739-1747 ispartof: location:Netherlands status: published

Introduction: Individuals in the Alzheimer's disease (AD) continuum with mild cognitive impairment (prodromal AD) are at increased risk to develop dementia. Still, underlying pathophysiological processes remain unclear. We studied whether cerebrospinal fluid (CSF) proteome changes are related to time to clinical progression in prodromal AD.Methods: We measured 671 CSF proteins in 49 prodromal AD individuals (67±7 years old, 22 [45%] female) from the Amsterdam Dementia Cohort. Associations of protein levels with time to dementia onset were tested with Cox regression models, followed by biological pathway enrichment analysis.Results: Eighteen (36%) individuals developed dementia during follow-up. In total, 128 (98%) proteins were associated with a 1.4- to 17-fold increased risk of progression to dementia (all P < .05). These proteins showed enrichment for immune system processes, signal transduction, neuronal death, and neurodevelopmental biology.Discussion: CSF proteome changes related to rate of progression to dementia can be detected in prodromal AD, providing more insight into processes involved in early AD pathophysiology.

Background Quantifying changes in the levels of biological and cognitive markers prior to the clinical presentation of Alzheimer’s disease (AD) will provide a template for understanding the underlying aetiology of the clinical syndrome and, concomitantly, for improving early diagnosis, clinical trial recruitment and treatment assessment. This study aims to characterise continuous changes of such markers and determine their rate of change and temporal order throughout the AD continuum. Methods The methodology is founded on the development of stochastic models to estimate the expected time to reach different clinical disease states, for different risk groups, and synchronise short-term individual biomarker data onto a disease progression timeline. Twenty-seven markers are considered, including a range of cognitive scores, cerebrospinal (CSF) and plasma fluid proteins, and brain structural and molecular imaging measures. Data from 2014 participants in the Alzheimer’s Disease Neuroimaging Initiative database is utilised. Results The model suggests that detectable memory dysfunction could occur up to three decades prior to the onset of dementia due to AD (ADem). This is closely followed by changes in amyloid-β CSF levels and the first cognitive decline, as assessed by sensitive measures. Hippocampal atrophy could be observed as early as the initial amyloid-β accumulation. Brain hypometabolism starts later, about 14 years before onset, along with changes in the levels of total and phosphorylated tau proteins. Loss of functional abilities occurs rapidly around ADem onset. Neurofilament light is the only protein with notable early changes in plasma levels. The rate of change varies, with CSF, memory, amyloid PET and brain structural measures exhibiting the highest rate before the onset of ADem, followed by a decline. The probability of progressing to a more severe clinical state increases almost exponentially with age. In accordance with previous studies, the presence of apolipoprotein E4 alleles and amyloid-β accumulation can be associated with an increased risk of developing the disease, but their influence depends on age and clinical state. Conclusions Despite the limited longitudinal data at the individual level and the high variability observed in such data, the study elucidates the link between the long asynchronous pathophysiological processes and the preclinical and clinical stages of AD.

PubMed ID: 32212244 Although cognitive theory of mind (ToM) has been largely studied within neurodegenerative disorders including Alzheimer's disease (AD), studies focusing on affective ToM are relatively limited, yielding inconsistent findings. The current study aimed at investigating affective ToM abilities within different stages of AD (mild AD dementia [ADD], mild cognitive impairment [MCI], and subjective cognitive impairment [SCI]), together with its relationship with neuropsychological functioning. Eighty-one participants were tested with two different ToM tasks (Faux Pas Recognition Test [FPR] and Reading Mind in the Eyes Test [RMET]) and tests of attention, executive functions, episodic memory, and facial recognition. Our results showed two different affective ToM profiles in AD continuum: while ADD group performed poorly on both tasks of ToM, MCI group displayed deteriorated performance on RMET but not on FPR. In addition, ToM performance was significantly related to episodic memory and verbal fluency within the overall sample. These findings suggest that impairment in the decoding process of emotional cues could begin even in the prodromal stage of AD. In contrast, the reasoning process of emotional information, as measured with FPR, could be preserved until the dementia stage. Moreover, the relation of affective ToM with amnestic functions and verbal abilities could provide evidence of a domain-general ToM impairment in AD. This study was supported by BIDEB 2211 Program of The Scientific and Technological Research Council of Turkey (TUBITAK) Publisher's Version

BACKGROUND: A long-term horizon is necessary when the socioeconomic consequences and the potential effects of interventions in Alzheimer's disease (AD) are estimated. OBJECTIVES: To illustrate the potential societal costs of AD across the disease continuum and to illustrate the potential cost-effectiveness of a hypothetical intervention with disease modifying treatment (DMT). METHODS: Based on the Swedish dementia registry, a Markov model was used to simulate a virtual cohort of 100,000 people with mild cognitive impairment (MCI) due to AD (AD-MCI) in Sweden for 40 years starting at the age of 60. A simulated hypothetical intervention assumed a 25% reduction in progression rate during AD-MCI and mild AD-dementia. A comprehensive set of sensitivity analyses was included. RESULTS: The cumulative risk to develop dementia was 96%. The mean simulated survival was 19.0 years. The net present value for a person year with dementia was 252,843 SEK (about 29,500 US$). The cost effectiveness model illustrated how the hypothetical scenario of a 25% reduction in progression to AD-dementia would require 41 AD-MCI patients to be treated to prevent one case of AD-dementia (2,447 avoided AD-dementia cases of 100,000 with AD-MCI). Most scenarios illustrated hypothetical cost effectiveness (based on a willingness to pay level of 600,000 SEK (70,000 US$) per gained QALY), but not cost savings. DISCUSSION: Lifetime societal costs of AD are substantial. A future DMT may be potentially cost-effective given assumed treatment effects and costs, but cost savings are unlikely.

Even though the involvement of serotonin (5-hydroxytryptamine; 5-HT) and its receptors in Alzheimer's disease (AD) is widely accepted, data on the expression and the role of 5-HT7 receptors in AD is relatively limited. Therefore, the objective of the present work was to study the expression of serotonergic 5-HT7 receptors in postmortem samples of AD brains and correlate it with neurotransmitter levels, cognition and behavior. The study population consisted of clinically well-characterized and neuropathologically confirmed AD patients (n = 42) and age-matched control subjects (n = 18). Reverse-transcription quantitative polymerase chain reaction (RT-qPCR) and high-performance liquid chromatography were performed on Brodmann area (BA) 7, BA10, BA22, BA24, hippocampus, amygdala, thalamus and cerebellum to measure mRNA levels of 5-HT7 receptors (HTR7), as well as the concentrations of various monoamine neurotransmitters and their metabolites.Decreased levels of HTR7 mRNA were observed in BA10. A significant association was observed between HTR7 levels in BA10 and BEHAVE-AD cluster B (hallucinations) (rs(28) = 0.444, P < 0.05). In addition, a negative correlation was observed between HTR7 levels in BA10 and both MHPG concentrations in this brain region (rs(45) = -0.311; P < 0.05), and DOPAC levels in the amygdala (rs(42) = -0.311; P < 0.05). Quite surprisingly, no association was found between HTR7 levels and cognitive status. Altogether, this study supports the notion of the involvement of 5-HT7 receptors in psychotic symptoms in AD, suggesting the interest of testing antagonist acting at this receptor to specifically treat psychotic symptoms in this illness.

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 epsilon 4 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. (C) 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

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 epsilon 4 (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. (C) 2018 The Authors. Published by Elsevier Inc.

Mild cognitive impairment (MCI) is a heterogeneous condition with variable outcomes. Improving diagnosis to increase the likelihood that MCI reliably reflects prodromal Alzheimer’s Disease (AD) would be of great benefit for clinical practice and intervention trials. In 230 cognitively normal (CN) and 394 MCI individuals from the Alzheimer’s Disease Neuroimaging Initiative, we studied whether an MCI diagnostic requirement of impairment on at least two episodic memory tests improves 3-year prediction of medial temporal lobe atrophy and progression to AD. Based on external age-adjusted norms for delayed free recall on the Rey Auditory Verbal Learning Test (AVLT), MCI participants were further classified as having normal (AVLT+, above −1 SD, n = 121) or impaired (AVLT -, −1 SD or below, n = 273) AVLT performance. CN, AVLT+, and AVLT- groups differed significantly on baseline brain (hippocampus, entorhinal cortex) and cerebrospinal fluid (amyloid, tau, p-tau) biomarkers, with the AVLT- group being most abnormal. The AVLT- group had significantly more medial temporal atrophy and a substantially higher AD progression rate than the AVLT+ group (51% vs. 16%, p

BackgroundTo explore the utility of the International Working Group (IWG)-1 criteria in recruitment for Alzheimer's disease (AD) clinical trials, we applied the more recently proposed research diagnostic criteria to individuals enrolled in a randomized controlled prevention trial (RCT) and assessed their disease progression.MethodsThe multinational LipiDiDiet RCT targeted 311 individuals with IWG-1 defined prodromal AD. Based on centrally analyzed baseline biomarkers, participants were classified according to the IWG-2 and National Institute on Aging-Alzheimer's Association (NIA-AA) 2011 and 2018 criteria. Linear mixed models were used to investigate the 2-year change in cognitive and functional performance (Neuropsychological Test Battery NTB Z scores, Clinical Dementia Rating-Sum of Boxes CDR-SB) (criteria x time interactions; baseline score, randomization group, sex, Mini-Mental State Examination (MMSE), and age also included in the models). Cox models adjusted for randomization group, MMSE, sex, age, and study site were used to investigate the risk of progression to dementia over 2 years.ResultsIn total, 88%, 86%, and 69% of participants had abnormal cerebrospinal fluid (CSF) beta -amyloid, total tau, and phosphorylated tau, respectively; 64% had an A+T+N+ profile (CSF available for N=107). Cognitive-functional decline appeared to be more pronounced in the IWG-2 prodromal AD, NIA-AA 2011 high and intermediate AD likelihood, and NIA-AA 2018 AD groups, but few significant differences were observed between the groups within each set of criteria. Hazard ratio (95% CI) for dementia was 4.6 (1.6-13.7) for IWG-2 prodromal AD (reference group no prodromal AD), 7.4 (1.0-54.7) for NIA-AA 2011 high AD likelihood (reference group suspected non-AD pathology SNAP), and 9.4 (1.2-72.7) for NIA-AA 2018 AD (reference group non-Alzheimer's pathologic change). Compared with the NIA-AA 2011 high AD likelihood group (abnormal beta -amyloid and neuronal injury markers), disease progression was similar in the intermediate AD likelihood group (medial temporal lobe atrophy; no CSF available).ConclusionsDespite being less restrictive than the other criteria, the IWG-1 criteria reliably identified individuals with AD pathology. More pragmatic and easily applicable selection criteria might be preferred due to feasibility in certain situations, e.g., in multidomain prevention trials that do not specifically target beta -amyloid/tau pathologies.Trial registrationNetherlands Trial Register, NL1620. Registered on 9 March 2009

BackgroundTo explore the utility of the International Working Group (IWG)-1 criteria in recruitment for Alzheimer's disease (AD) clinical trials, we applied the more recently proposed research diagnostic criteria to individuals enrolled in a randomized controlled prevention trial (RCT) and assessed their disease progression.MethodsThe multinational LipiDiDiet RCT targeted 311 individuals with IWG-1 defined prodromal AD. Based on centrally analyzed baseline biomarkers, participants were classified according to the IWG-2 and National Institute on Aging-Alzheimer's Association (NIA-AA) 2011 and 2018 criteria. Linear mixed models were used to investigate the 2-year change in cognitive and functional performance (Neuropsychological Test Battery NTB Z scores, Clinical Dementia Rating-Sum of Boxes CDR-SB) (criteria x time interactions; baseline score, randomization group, sex, Mini-Mental State Examination (MMSE), and age also included in the models). Cox models adjusted for randomization group, MMSE, sex, age, and study site were used to investigate the risk of progression to dementia over 2 years.ResultsIn total, 88%, 86%, and 69% of participants had abnormal cerebrospinal fluid (CSF) beta -amyloid, total tau, and phosphorylated tau, respectively; 64% had an A+T+N+ profile (CSF available for N=107). Cognitive-functional decline appeared to be more pronounced in the IWG-2 prodromal AD, NIA-AA 2011 high and intermediate AD likelihood, and NIA-AA 2018 AD groups, but few significant differences were observed between the groups within each set of criteria. Hazard ratio (95% CI) for dementia was 4.6 (1.6-13.7) for IWG-2 prodromal AD (reference group no prodromal AD), 7.4 (1.0-54.7) for NIA-AA 2011 high AD likelihood (reference group suspected non-AD pathology SNAP), and 9.4 (1.2-72.7) for NIA-AA 2018 AD (reference group non-Alzheimer's pathologic change). Compared with the NIA-AA 2011 high AD likelihood group (abnormal beta -amyloid and neuronal injury markers), disease progression was similar in the intermediate AD likelihood group (medial temporal lobe atrophy; no CSF available).ConclusionsDespite being less restrictive than the other criteria, the IWG-1 criteria reliably identified individuals with AD pathology. More pragmatic and easily applicable selection criteria might be preferred due to feasibility in certain situations, e.g., in multidomain prevention trials that do not specifically target beta -amyloid/tau pathologies.Trial registrationNetherlands Trial Register, NL1620. Registered on 9 March 2009

Using CSF proteomics, Tijms et al. identify three Alzheimer’s disease subtypes that show: 1) hyperplasticity and increased BACE1 levels; 2) innate immune activation; and 3) blood-brain barrier dysfunction with low BACE1 levels. Future therapeutics may need tailoring to individual disease subtypes., Alzheimer’s disease is biologically heterogeneous, and detailed understanding of the processes involved in patients is critical for development of treatments. CSF contains hundreds of proteins, with concentrations reflecting ongoing (patho)physiological processes. This provides the opportunity to study many biological processes at the same time in patients. We studied whether Alzheimer’s disease biological subtypes can be detected in CSF proteomics using the dual clustering technique non-negative matrix factorization. In two independent cohorts (EMIF-AD MBD and ADNI) we found that 705 (77% of 911 tested) proteins differed between Alzheimer’s disease (defined as having abnormal amyloid, n = 425) and controls (defined as having normal CSF amyloid and tau and normal cognition, n = 127). Using these proteins for data-driven clustering, we identified three robust pathophysiological Alzheimer’s disease subtypes within each cohort showing (i) hyperplasticity and increased BACE1 levels; (ii) innate immune activation; and (iii) blood–brain barrier dysfunction with low BACE1 levels. In both cohorts, the majority of individuals were labelled as having subtype 1 (80, 36% in EMIF-AD MBD; 117, 59% in ADNI), 71 (32%) in EMIF-AD MBD and 41 (21%) in ADNI were labelled as subtype 2, and 72 (32%) in EMIF-AD MBD and 39 (20%) individuals in ADNI were labelled as subtype 3. Genetic analyses showed that all subtypes had an excess of genetic risk for Alzheimer’s disease (all P > 0.01). Additional pathological comparisons that were available for a subset in ADNI suggested that subtypes showed similar severity of Alzheimer’s disease pathology, and did not differ in the frequencies of co-pathologies, providing further support that found subtypes truly reflect Alzheimer’s disease heterogeneity. Compared to controls, all non-demented Alzheimer’s disease individuals had increased risk of showing clinical progression (all P

OBJECTIVEMRI derived hippocampal volume (HV) and amyloid PET may be useful clinical biomarkers for differentiating between geriatric depression and Alzheimer’s Disease (AD). Here we investigated the incremental value of HV and 18F-flutemetmol PET in tandem and sequentially to improve discrimination in unclassified participants.METHODTwo approaches were compared in 41 participants with geriatric depression and 27 participants with probable AD: (1) amyloid and HV combined in one model and (2) HV first and then amyloid.RESULTSBoth HV(χ2(1) = 6.46: p= 0.011) and amyloid (χ2(1) =11.03: p=0.0009) were significant diagnostic predictors of depression (sensitivity: 95%, specificity: 89%). (2) 51% of participants were correctly classified according to clinical diagnosis based on HV alone, increasing to 87% when adding amyloid data (sensitivity: 94%, specificity: 78%).CONCLUSIONHippocampal volume may be a useful gatekeeper for identifying depressed individuals at risk for AD who would benefit from additional amyloid biomarkers when available.

Studies in the field of Alzheimer’s disease (AD) have shown the emergence of biomarkers in biologic fluids that hold great promise for the diagnosis of the disease. A diagnosis of AD at a presymptomatic or early stage may be the key for a successful treatment, with clinical trials currently investigating this. It is anticipated that preventative and therapeutic strategies may be stage-dependent, which means that they have a better chance of success at a very early stage—before critical neurons are lost. Several studies have been investigating the use of cerebrospinal fluid (CSF) and blood as clinical samples for the detection of AD with a number of established core markers, such as amyloid beta (Aβ), total tau (T-tau) and phosphorylated tau (P-tau), being at the center of clinical research interest. The use of oral samples—including saliva and buccal mucosal cells—falls under one of the least-investigated areas in AD diagnosis. Such samples have great potential to provide a completely non-invasive alternative to current CSF and blood sampling procedures. The present work is a thorough review of the results and analytical approaches, including proteomics, metabolomics, spectroscopy and microbiome analyses that have been used for the study and detection of AD using salivary samples and buccal cells. With a few exceptions, most of the studies utilizing oral samples were performed in small cohorts, which in combination with the existence of contradictory results render it difficult to come to a definitive conclusion on the value of oral markers. Proteins such as Aβ, T-tau and P-tau, as well as small metabolites, were detected in saliva and have shown some potential as future AD diagnostics. Future large-cohort studies and standardization of sample preparation and (pre-)analytical factors are necessary to determine the use of these non-invasive samples as a diagnostic tool for AD.

The co-existence of multiple pathologies and proteins is a common feature in the brains of cognitively impaired elderly individuals. Transactive response DNA-binding protein (TDP-43) has been discovered to accumulate in limbic brain regions of a portion of late-onset Alzheimer’s disease (AD) patients, in addition to amyloid-β and τ protein. However, it is not yet known whether the TDP-43 species in the AD brain differ in their composition, when compared among different AD cases and to frontotemporal lobar degeneration cases with TDP-43 inclusions (FTLD-TDP). Furthermore, it is not known whether TDP-43 pathology in AD is related to symptoms of the frontotemporal dementia (FTD) spectrum. In this study, we investigated the molecular pattern of TDP-43 lesions with five different antibodies against different phosphorylated (pTDP-43) and non-phosphorylated TDP-43 epitopes. We analyzed a cohort of 97 autopsy cases, including brains from 20 non-demented individuals, 16 cognitively normal pathologically-defined preclinical AD (p-preAD), 51 neuropathologically-confirmed AD cases and 10 FTLD-TDP cases as positive controls. We observed distinct neuropathological patterns of TDP-43 among AD cases. In 11 neuropathologically-confirmed AD cases we found dystrophic neurites (DNs), neuronal cytoplasmic inclusions (NCIs) and/or neurofibrillary tangle (NFT)-like lesions not only positive for pTDP-43409/410, but also for pTDP-43 phosphorylated at serines 403/404 (pTDP-43403/404) and non-phosphorylated, full-length TDP-43, as seen with antibodies against C-terminal TDP-43 and N-terminal TDP-43. These cases were referred to as ADTDP + FL because full-length TDP-43 was presumably present in the aggregates. FTLD-TDP cases showed a similar molecular TDP-43 pattern. A second pattern, which was not seen in FTLD-TDP, was observed in most of p-preAD, as well as 30 neuropathologically-confirmed AD cases, which mainly exhibited NFTs and NCIs stained with antibodies against TDP-43 phosphorylated at serines 409/410 (pTDP-43409, pTDP-43409/410). Because only phosphorylated C-terminal species of TDP-43 could be detected in the lesions we designated these AD cases as ADTDP + CTF. Ten AD cases did not contain any TDP-43 pathology and were referred to as ADTDP-. The different TDP-43 patterns were associated with clinically typical AD symptoms in 80% of ADTDP + CTF cases, 63,6% of ADTDP + FL and 100% of the ADTDP- cases. On the other hand, clinical symptoms characteristic for FTD were observed in 36,4% of ADTDP + FL, in 16,6% of the ADTDP + CTF, and in none of the ADTDP- cases. Our findings provide evidence that TDP-43 aggregates occurring in AD cases vary in their composition, suggesting the distinction of different molecular patterns of TDP-43 pathology ranging from ADTDP- to ADTDP + CTF and ADTDP + FL with possible impact on their clinical picture, i.e. a higher chance for FTD-like symptoms in ADTDP + FL cases.

Evidences of infectious pathogens in Alzheimer's disease (AD) brains may suggest a deteriorated innate immune system in AD pathophysiology. We previously demonstrated reduced salivary lactoferrin (Lf) levels, one of the major antimicrobial proteins, in AD patients. To assess the clinical utility of salivary Lf for AD diagnosis, we examine the relationship between salivary Lf and cerebral amyloid-β (Aβ) load using amyloid-Positron-Emission Tomography (PET) neuroimaging, in two different cross-sectional cohorts including patients with different neurodegenerative disorders. The diagnostic performance of salivary Lf in the cohort 1 had an area under the curve [AUC] of 0•95 (0•911-0•992) for the differentiation of the prodromal AD/AD group positive for amyloid-PET (PET+) versus healthy group, and 0•97 (0•924-1) versus the frontotemporal dementia (FTD) group. In the cohort 2, salivary Lf had also an excellent diagnostic performance in the health control group versus prodromal AD comparison: AUC 0•93 (0•876-0•989). Salivary Lf detected prodromal AD and AD dementia distinguishing them from FTD with over 87% sensitivity and 91% specificity. Salivary Lf seems to have a very good diagnostic performance to detect AD. Our findings support the possible utility of salivary Lf as a new non-invasive and cost-effective AD biomarker. Instituto de Salud Carlos III (FIS15/00780, FIS18/00118), FEDER, Comunidad de Madrid (S2017/BMD-3700; NEUROMETAB-CM), and CIBERNED (PI2016/01) to E.C.; Spanish Ministry of Economy and Competitiveness (SAF2017-85310-R) to J.L.C., and (PSI2017-85311-P) to M.A.; International Centre on ageing CENIE-POCTEP (0348_CIE_6_E) to M.A.; Instituto de Salud Carlos III (PIE16/00021, PI17/01799), to H.B. This study was supported by Dr. Carro grants from Instituto de Salud Carlos III (FIS15/00780, FIS18/00118), FEDER, Comunidad de Madrid (S2017/BMD-3700; NEUROMETAB-CM), and CIBERNED(PI2016/01). This study was also supported by research grants fromthe Spanish Ministry of Economy and Competitiveness (SAF2017-85310-R to Dr. Cantero, PSI2017-85311-P to Dr. Atienza); International Centre on ageing CENIE-POCTEP (0348_CIE_6_E to Dr. Atienza);and CIBERNED (CB06/05/1111 to Dr. Cantero). Dr. Bueno receives research funding from the Instituto de Salud Carlos III, Spain (PIE16/00021, PI17/01799). The H2H-Spain Study was supported in Spain by grant PIE16/00021 from Instituto Carlos III, Ministry of Science, Innovation and Universities, and additional funds from the Centro Nacional de Investigaciones Cardiovasculares (CNIC). The CNIC is supported by the Ministry of Economy, Industry and Competitiveness and the Pro CNIC Foundation, and is a Severo Ochoa Centre of Excellence (SEV-2015-0505). Sí

Background: A long-term horizon is necessary when the socioeconomic consequences and the potential effects of interventions in Alzheimer’s disease (AD) are estimated. Objectives: To illustrate the potential societal costs of AD across the disease continuum and to illustrate the potential cost-effectiveness of a hypothetical intervention with disease modifying treatment (DMT). Methods: Based on the Swedish dementia registry, a Markov model was used to simulate a virtual cohort of 100,000 people with mild cognitive impairment (MCI) due to AD (AD-MCI) in Sweden for 40 years starting at the age of 60. A simulated hypothetical intervention assumed a 25% reduction in progression rate during AD-MCI and mild AD-dementia. A comprehensive set of sensitivity analyses was included. Results: The cumulative risk to develop dementia was 96%. The mean simulated survival was 19.0 years. The net present value for a person year with dementia was 252,843 SEK (about 29,500 US$). The cost effectiveness model illustrated how the hypothetical scenario of a 25% reduction in progression to AD-dementia would require 41 AD-MCI patients to be treated to prevent one case of AD-dementia (2,447 avoided AD-dementia cases of 100,000 with AD-MCI). Most scenarios illustrated hypothetical cost effectiveness (based on a willingness to pay level of 600,000 SEK (70,000 US$) per gained QALY), but not cost savings. Discussion: Lifetime societal costs of AD are substantial. A future DMT may be potentially cost-effective given assumed treatment effects and costs, but cost savings are unlikely.

The APOE-epsilon 4 genotype is a risk factor for late-onset Alzheimer's disease (AD) as well as vascular pathology. Given the increased risk of blood-brain barrier (BBB) dysfunction and inflammation among APOE-epsilon 4 carriers, we aimed to examine whether BBB dysfunction and inflammation contribute to the relationship between APOE and AD key pathologies, as measured in the cerebrospinal fluid (CSF). We applied bootstrapped regression and path analyses involving Q-albumin CSF/plasma ratio (a BBB/blood-CSF barrier function marker), interleukins (IL-1 beta, IL-6, and IL-12p70; inflammation markers), and CSF p-Tau(181) and amyloid-beta(1-42) (AD pathology markers) of 97 participants (aged 38-83 years) from a university memory clinic. Our results showed that relationship between BBB dysfunction and AD pathology is modulated by IL-6 and these associations appear to be driven by the APOE-epsilon 4 genotype. This suggests that APOE-epsilon 4-related vascular factors are also part of the pathway to AD pathology, in synergy with an elevated immune response, and could become targets for trials focused on delaying AD. (C) 2019 The Author(s). Published by Elsevier Inc.

Alzheimer’s disease (AD) is a progressive neurodegenerative condition marked by a decline in cognitive functions with no validated disease modifying treatment. It is critical for timely treatment to detect AD in its earlier stage before clinical manifestation. Mild cognitive impairment (MCI) is an intermediate stage between cognitively normal older adults and AD. To predict conversion from MCI to probable AD, we applied a deep learning approach, multimodal recurrent neural network. We developed an integrative framework that combines not only cross-sectional neuroimaging biomarkers at baseline but also longitudinal cerebrospinal fluid (CSF) and cognitive performance biomarkers obtained from the Alzheimer’s Disease Neuroimaging Initiative cohort (ADNI). The proposed framework integrated longitudinal multi-domain data. Our results showed that 1) our prediction model for MCI conversion to AD yielded up to 75% accuracy (area under the curve (AUC) = 0.83) when using only single modality of data separately; and 2) our prediction model achieved the best performance with 81% accuracy (AUC = 0.86) when incorporating longitudinal multi-domain data. A multi-modal deep learning approach has potential to identify persons at risk of developing AD who might benefit most from a clinical trial or as a stratification approach within clinical trials.

Introduction: We develop a framework to model disease progression across Alzheimer's disease (AD) and to assess the cost-effectiveness of future disease-modifying therapies (DMTs) for people with mild cognitive impairment (MCI) due to AD.Methods: Using data from the US National Alzheimer's Coordinating Center, we apply survival analysis to estimate transition from predementia to AD dementia and ordered probit regression to estimate transitions across AD dementia stages. We investigate the cost-effectiveness of a hypothetical treatment scenario for people in MCI due to AD.Results: We present an open-access model-based decision-analytic framework. Assuming a modest DMT treatment effect in MCI, we predict extended life expectancy and a reduction in time with AD dementia.Discussion: Any future DMT for AD is expected to pose significant economic challenges across all health-care systems, and decision-analytic modeling will be required to assess costs and outcomes. Further developments are needed to inform these health policy considerations. (C) 2019 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.

Background: Diagnostic research criteria for Alzheimer's disease support the use of biomarkers in the cerebrospinal fluid (CSF) to improve the accuracy of the prognosis regarding progression to dementia for people with mild cognitive impairment (MCI).Objective: The aim of this study was to estimate the potential incremental cost-effectiveness ratio of adding CSF biomarker testing to the standard diagnostic workup to determine the prognosis for patients with MCI.Methods: In an early technology assessment, a mathematical simulation model was built, using available evidence on added prognostic value as well as expert opinion to estimate the incremental costs and quality-adjusted life years (QALYs) of 20,000 virtual MCI patients with (intervention strategy) and without (control strategy) relying on CSF, from a health-care sector perspective and with a 5-year time horizon.Results: Adding the CSF test improved the accuracy of prognosis by 11%. This resulted in an average QALY gain of 0.046 and (sic)432 additional costs per patient, representing an incremental cost-effectiveness ratio of (sic)9,416.Conclusion: The results show the potential of CSF biomarkers in current practice from a health-economics perspective. This result was, however, marked by a high degree of uncertainty, and empirical research is required into the impact of a prognosis on worrying, false-positive/negative prognosis, and stigmatization.

The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.

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

Highlights • Multimodal MRI AD classification models were pre-trained on AD patients and controls. • Generalisation of these models was tested on a multi-centre memory clinic data set. • AD scores were assigned to AD patients, MCI patients and memory complainers. • Anatomical MRI performed better than diffusion MRI and resting state fMRI. • Combining imaging modalities did not improve the results over anatomical MRI only., Anatomical magnetic resonance imaging (MRI), diffusion MRI and resting state functional MRI (rs-fMRI) have been used for Alzheimer’s disease (AD) classification. These scans are typically used to build models for discriminating AD patients from control subjects, but it is not clear if these models can also discriminate AD in diverse clinical populations as found in memory clinics. To study this, we trained MRI-based AD classification models on a single centre data set consisting of AD patients (N = 76) and controls (N = 173), and used these models to assign AD scores to subjective memory complainers (N = 67), mild cognitive impairment (MCI) patients (N = 61), and AD patients (N = 61) from a multi-centre memory clinic data set. The anatomical MRI scans were used to calculate grey matter density, subcortical volumes and cortical thickness, the diffusion MRI scans were used to calculate fractional anisotropy, mean, axial and radial diffusivity, and the rs-fMRI scans were used to calculate functional connectivity between resting state networks and amplitude of low frequency fluctuations. Within the multi-centre memory clinic data set we removed scan site differences prior to applying the models. For all models, on average, the AD patients were assigned the highest AD scores, followed by MCI patients, and later followed by SMC subjects. The anatomical MRI models performed best, and the best performing anatomical MRI measure was grey matter density, separating SMC subjects from MCI patients with an AUC of 0.69, MCI patients from AD patients with an AUC of 0.70, and SMC patients from AD patients with an AUC of 0.86. The diffusion MRI models did not generalise well to the memory clinic data, possibly because of large scan site differences. The functional connectivity model separated SMC subjects and MCI patients relatively good (AUC = 0.66). The multimodal MRI model did not improve upon the anatomical MRI model. In conclusion, we showed that the grey matter density model generalises best to memory clinic subjects. When also considering the fact that grey matter density generally performs well in AD classification studies, this feature is probably the best MRI-based feature for AD diagnosis in clinical practice.

Introduction: Apolipoprotein E (APOE) epsilon 4 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 beta(A beta) pathology. Methods: We included 3451 A beta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon 4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE epsilon 4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in A beta+ cognitively normal and A beta+ mild cognitive impairment (P

Introduction Dementia is one of the greatest health challenges the world will face in the coming decades, as it is one of the principal causes of disability and dependency among older people. Economic modelling is used widely across many health conditions to inform decisions on health and social care policy and practice. The aim of this literature review is to systematically identify, review and critically evaluate existing health economics models in dementia. We included the full spectrum of dementia, including Alzheimer's disease (AD), from preclinical stages through to severe dementia and end of life. This review forms part of the Real world Outcomes across the Alzheimer's Disease spectrum for better care: multimodal data Access Platform (ROADMAP) project. Methods and analysis Electronic searches were conducted in Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, Economic Literature Database, NHS Economic Evaluation Database, Cochrane Central Register of Controlled Trials, Cost Effectiveness Analysis Registry, Research Papers in Economics, Database of Abstracts of Reviews of Effectiveness, Science Citation Index, Turning Research Into Practice and Open Grey for studies published between January 2000 and the end of June 2017. Two reviewers will independently assess each study against predefined eligibility criteria. A third reviewer will resolve any disagreement. Data will be extracted using a predefined data extraction form following best practice. Study quality will be assessed using the Phillips checklist for decision analytic modelling. A narrative synthesis will be used. Ethics and dissemination The results will be made available in a scientific peer-reviewed journal paper, will he presented at relevant conferences and will also be made available through the ROADMAP project.

Background: AD is a progressive neurodegenerative disorder that is associated with the accumulation of two different insoluble protein aggregates, Aβ plaques and hyperphosphorylated tau. This study aimed to investigate the optimal acquisition and quantification of [18F]AV45 and [18F]AV1451 to image Aβ and tau, respectively, in subjects with AD. Fifteen subjects with early stage AD underwent a T1-weighted structural MRI and two dynamic PET scans to image Aβ (60 min, [18F]AV45) and tau (120 min, [18F]AV1451). Both dynamic BPND and static SUVR outcome measures were calculated and compared for 12 out of 15 subjects who completed 60 min of the Aβ PET scan and at least 110 min of the tau PET scan. The SRTM and reference Logan graphical analysis were applied to the dynamic data to estimate regional BPND values and SUVR ratios from the static data. Optimal acquisition windows were explored for both the dynamic and static acquisitions. In addition, the spatial correlation between regional Aβ and tau signals was explored. Results: Both the SRTM and graphical analysis methods showed a good fit to the dynamic data for both Aβ and tau dynamic PET scans. Mean regional BPND estimates became stable 30 min p.i. for [18F]AV45 and 80 min p.i. for [18F]AV1451. Time stability analysis of static SUVR data showed that the outcome measure starts to become stable for scan windows of 30–50 min p.i. for [18F]AV45 and 80–100 min p.i. for [18F]AV1451. The results from these time windows correlated well with the results from the full dynamic analysis for both tracers (R2 = 0.74 for [18F]AV45 and R2 = 0.88 for [18F]AV1451). There was a high correlation between amyloid uptake estimate using both dynamic analysis methods in thalamus and tau uptake in thalamus, hippocampus and amygdala. Conclusions: Short static PET scans at appropriate time windows provided SUVR values which were in reasonable agreement with BPND values calculated from dynamic scans using SRTM and reference Logan. These simplified methods may be appropriate for classification and intervention studies, although caution should be employed when considering interventional studies where blood flow and extraction could change.

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

Objective: To compare the diagnostic accuracy of CSF biomarkers and amyloid PET for diagnosing early-stage Alzheimer disease (AD). Methods: From the prospective, longitudinal BioFINDER study, we included 122 healthy elderly and 34 patients with mild cognitive impairment who developed AD dementia within 3 years (MCI-AD). β-Amyloid (Aβ) deposition in 9 brain regions was examined with [18F]-flutemetamol PET. CSF was analyzed with INNOTEST and EUROIMMUN ELISAs. The results were replicated in 146 controls and 64 patients with MCI-AD from the Alzheimer's Disease Neuroimaging Initiative study. Results: The best CSF measures for identifying MCI-AD were Aβ42/total tau (t-tau) and Aβ42/hyperphosphorylated tau (p-tau) (area under the curve [AUC] 0.93–0.94). The best PET measures performed similarly (AUC 0.92–0.93; anterior cingulate, posterior cingulate/precuneus, and global neocortical uptake). CSF Aβ42/t-tau and Aβ42/p-tau performed better than CSF Aβ42 and Aβ42/40 (AUC difference 0.03–0.12, p < 0.05). Using nonoptimized cutoffs, CSF Aβ42/t-tau had the highest accuracy of all CSF/PET biomarkers (sensitivity 97%, specificity 83%). The combination of CSF and PET was not better than using either biomarker separately. Conclusions: Amyloid PET and CSF biomarkers can identify early AD with high accuracy. There were no differences between the best CSF and PET measures and no improvement when combining them. Regional PET measures were not better than assessing the global Aβ deposition. The results were replicated in an independent cohort using another CSF assay and PET tracer. The choice between CSF and amyloid PET biomarkers for identifying early AD can be based on availability, costs, and doctor/patient preferences since both have equally high diagnostic accuracy. Classification of evidence: This study provides Class III evidence that amyloid PET and CSF biomarkers identify early-stage AD equally accurately.

This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) amyloid-β142, tau, and phosphorylated tau in the diagnostic evaluation of patients with mild cognitive impairment (MCI). The recommendations were developed by a multidisciplinary working group and based on the available evidence and consensus from focused group discussions for 1) prediction of clinical progression to Alzheimer's disease (AD) dementia, 2) cost-effectiveness, 3) interpretation of results, and 4) patient counseling. The working group recommended using CSF AD biomarkers in the diagnostic workup of MCI patients, after prebiomarker counseling, as an add-on to clinical evaluation to predict functional decline or conversion to AD dementia and to guide disease management. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Furthermore, the working group provided recommendations for interpretation of ambiguous CSF biomarker results and for pre- and post-biomarker counseling. Abstract: This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) amyloid-beta(1-42), tau, and phosphorylated tau in the diagnostic evaluation of patients with mild cognitive impairment (MCI). The recommendations were developed by a multidisciplinary working group and based on the available evidence and consensus from focused group discussions for 1) prediction of clinical progression to Alzheimer's disease (AD) dementia, 2) cost-effectiveness, 3)interpretation of results, and 4) patient counseling. The working group recommended using CSF AD biomarkers in the diagnostic workup of MCI patients, after prebiomarker counseling, as an add-on to clinical evaluation to predict functional decline or conversion to AD dementia and to guide disease management. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Furthermore, the working group provided recommendations for interpretation of ambiguous CSF biomarker results and for pre-and post-biomarker counseling. (C) 2016 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.

Background Little is known of possible associations between Alzheimer's disease (AD) biomarkers and instrumental activities of daily living (IADL) change over time. Objective The present study seeks to identify relationships between baseline imaging and fluid biomarker profiles, and decline in IADL utilizing data collated from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Methods Generalized estimating equations analysis, adjusted for cognitive deterioration, was applied to a cohort of 509 individuals from all stages of ADNI, including 156 healthy controls, 189 early mild cognitive impairment (MCI) patients and 164 MCI patients. Results A significant correlation was found between baseline biomarkers, specifically CSF Aβ and FDG PET, and IADL change over a 3-year period in individuals with MCI. Importantly, comparable correlations between presence of pathological biomarker levels and temporal decline in both functional and cognitive performance were also noted. Discussion We show that distinct baseline biomarkers may predict latent changes in IADL. Our results necessitate a revision of the commonly held view upholding cognitive changes as the predominant endpoint measure associated with presence of abnormal baseline biomarkers.

Biomarkers for the diagnosis of Alzheimer's disease (AD) are not yet validated for use in clinical settings. We aim to provide a methodological framework for their systematic validation, by reference to that developed for oncology biomarkers. As for this discipline, the steps for the systematic validation of AD biomarkers need to target analytical validity, clinical validity, and clinical utility. However, the premises are different from oncology: the nature of disease (neurodegeneration vs. cancer), the purpose (improve diagnosis in clinically affected vs. screening preclinical individuals), and the target population (mild cognitive impairment patients referring to memory clinics vs. general population) lead to important differences, influencing both the design of validation studies and the use of selected biomarkers. This framework is applied within a wider initiative to assess the current available evidence on the clinical validity of biomarkers for AD, for the final aim to identify gaps and research priorities, and to inform coordinated research efforts boosting AD biomarkers research.

Neurodegenerative brain changes can affect the functional connectivity strength between nodes of the default-mode network (DMN), which may underlie changes in cognitive performance. It remains unclear how the functional connectivity strength of DMN nodes differs from healthy to pathological aging and whether these changes are cognitively relevant. We used resting-state functional magnetic resonance imaging to investigate the functional connectivity strength across five DMN nodes in 25 healthy controls (HC), 28 subjective cognitive decline (SCD) participants, and 25 prodromal Alzheimer's disease (AD) patients. After identifying the ventral medial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), retrosplenial cortex (RSC), inferior parietal lobule, and the hippocampus we investigated the functional strength between DMN nodes using temporal network modeling. Functional coupling of the vmPFC and PCC in prodromal AD patients was disrupted. This vmPFC-PCC coupling correlated positively with memory performance in prodromal AD. Furthermore, the hippocampus de-coupled from posterior DMN nodes in SCD and prodromal AD patients. There was no coupling between the hippocampus and the anterior DMN. Additional mediation analyses indicated that the RSC enables communication between the hippocampus and DMN regions in HC but none of the other two groups. These results suggest an anterior-posterior disconnection and a hippocampal de-coupling from posterior DMN nodes with disease progression. Hippocampal de-coupling already occurring in SCD may provide valuable information for the development of a functional biomarker.

The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.

Cerebrospinal fluid (CSF) biomarkers may support the diagnosis of Alzheimer's disease (AD). We studied if the diagnostic power of AD CSF biomarker concentrations, i.e., Aβ42, total tau (t-tau), and phosphorylated tau (p-tau), is affected by differences in lateral ventricular volume (VV), using CSF biomarker data and magnetic resonance imaging (MRI) scans of 730 subjects, from 13 European Memory Clinics. We developed a Matlab-algorithm for standardized automated segmentation analysis of T1 weighted MRI scans in SPM8 for determining VV, and computed its ratio with total intracranial volume (TIV) as proxy for total CSF volume. The diagnostic power of CSF biomarkers (and their combination), either corrected for VV/TIV ratio or not, was determined by ROC analysis. CSF Aβ42 levels inversely correlated to VV/TIV in the whole study population (Aβ42: r=-0.28; p42 alone (AUC: 0.75 versus 0.81) or in combination with t-tau (AUC: 0.81 versus 0.91). In conclusion, differences in VV may be an important confounder in interpreting CSF Aβ42 levels.