Diagnostic accuracy of CSF Ab42 and florbetapir PET for Alzheimer's disease

Development and assessment of algorithms for predicting brain amyloid positivity in a population without dementia

BACKGROUND

The accumulation of amyloid-β (Aβ) peptide in the brain is a hallmark of Alzheimer's disease (AD), occurring years before symptom onset. Current methods for quantifying in vivo amyloid load involve invasive or costly procedures, limiting accessibility. Early detection of amyloid positivity in non-demented individuals is crucial for aiding early AD diagnosis and for initiating anti-amyloid immunotherapies at early stages. This study aimed to develop and validate predictive models to identify brain amyloid positivity in non-demented patients, using routinely collected clinical data.

METHODS

Predictive models for amyloid positivity were developed using data from 853 non-demented participants in the MEMENTO cohort. Amyloid levels were measured potentially repeatedly during study course through Positron Emision Tomography or CerebroSpinal Fluid analysis. The probability of amyloid positivity was modelled using mixed-effects logistic regression. Predictors included demographic information, cognitive assessments, visual brain MRI evaluations of hippocampal atrophy and lobar microbleeds, AD-related blood biomarkers (Aβ42/40 and P-tau181), and ApoE4 status. Models were subjected to internal cross-validation and external validation using data from the Amsterdam Dementia Cohort. Performance also was evaluated in a subsample that met the main criteria of the Appropriate Use Recommendations (AUR) for lecanemab.

RESULTS

The most effective model incorporated demographic data, cognitive assessments, ApoE status, and AD-related blood biomarkers, achieving AUCs of 0.82 [95%CI 0.81-0.82] in MEMENTO sample and 0.90 [95%CI 0.86-0.94] in the external validation sample. This model significantly outperformed a reference model based solely on demographic and cognitive data, with an AUC difference in MEMENTO of 0.10 [95%CI 0.10-0.11]. A similar model without ApoE genotype achieved comparable discriminatory performance. MRI markers did not improve model performance. Performances in AUR of lecanemab subsample were comparable.

CONCLUSION

A predictive model integrating demographic, cognitive, and blood biomarker data offers a promising method to help identify amyloid status in non-demented patients. ApoE genotype and brain MRI data were not necessary for strong discriminatory ability, suggesting that ApoE genotyping may be deferred when assessing the risk-benefit ratio of immunotherapies in amyloid-positive patients who desire treatment. The integration of this model into clinical practice could reduce the need for lumbar puncture or PET examinations to confirm amyloid status.

Aβ status assessment in a hypothetical scenario prior to treatment with disease-modifying therapies: Evidence from 10-year real-world experience at university memory clinics

INTRODUCTION

With the advent of disease-modifying therapies, accurate assessment of biomarkers indicating the presence of disease-associated amyloid beta (Aβ) pathology becomes crucial in patients with clinically suspected Alzheimer's disease (AD). We evaluated Aβ levels in cerebrospinal fluid (Aβ CSF) and Aβ levels in positron emission tomography (Aβ PET) biomarkers in a real-world memory-clinic setting to develop an efficient algorithm for clinical use.

METHODS

Patients were evaluated for AD-related Aβ pathology from two independent cohorts (Ludwig Maximilian University [LMU], n = 402, and Medical University of Vienna [MUV], n = 144). Optimal thresholds of CSF biomarkers were deduced from receiver operating characteristic curves and validated against Aβ PET positivity.

RESULTS

In both cohorts, a CSF Aβ42/40 ratio ≥ 7.1% was associated with a low risk of a positive Aβ PET scan (negative predictive value: 94.3%). Implementing two cutoffs revealed 14% to 16% of patients with intermediate results (CSF Aβ42/40 ratio: 5.5%-7.1%), which had a strong benefit from Aβ PET imaging (44%-52% Aβ PET positivity).

DISCUSSION

A two-cutoff approach for CSF Aβ42/40 including Aβ PET imaging at intermediate results provides an effective assessment of Aβ pathology in real-world settings.

Highlights

We evaluated cerebrospinal fluid (CSF) and positron emission tomography (PET) amyloid beta (Aβ) biomarkers for Alzheimer's disease in real-world cohorts.A CSF Aβ 42/40 ratio between 5.5% and 7.1% defines patients at borderline levels.Patients at borderline levels strongly benefit from additional Aβ PET imaging.Two-cutoff CSF Aβ 42/40 and PET will allow effective treatment stratification.

sTREM2 Mediates the Correlation Between BIN1 Gene Polymorphism and Tau Pathology in Alzheimer's Disease

Background

Bridging integrator 1 (BIN1) gene polymorphism has been reported to play a role in the pathological processes of Alzheimer's disease (AD).

Objective

To explore the association of BIN1 loci with neuroinflammation and AD pathology.

Methods

Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 495) was the discovery cohort, and Chinese Alzheimer's Biomarker and LifestylE (CABLE, N = 619) study was used to replicate the results. Two BIN1 gene polymorphism (rs7561528 and rs744373) were included in the analysis. Multiple linear regression model and causal mediation analysis conducted through 10,000 bootstrapped iterations were used to examine the BIN1 loci relationship with cerebrospinal fluid (CSF) AD biomarkers and alternative biomarker of microglial activation microglia-soluble triggering receptor expressed on myeloid cells 2 (sTREM2).

Results

In ADNI database, we found a significant association between BIN1 loci (rs7561528 and rs744373) and levels of CSF phosphorylated-tau (P-tau) (pc = 0.017; 0.010, respectively) and total-tau (T-tau) (pc = 0.011; 0.013, respectively). The BIN1 loci were also correlated with CSF sTREM2 levels (pc = 0.010; 0.008, respectively). Mediation analysis demonstrated that CSF sTREM2 partially mediated the association of BIN1 loci with P-tau (Proportion of rs7561528 : 20.8%; Proportion of rs744373 : 24.8%) and T-tau (Proportion of rs7561528 : 36.5%; Proportion of rs744373 : 43.9%). The analysis in CABLE study replicated the mediation role of rs7561528.

Conclusions

This study demonstrated the correlation between BIN1 loci and CSF AD biomarkers as well as microglia biomarkers. Additionally, the link between BIN1 loci and tau pathology was partially mediated by CSF sTREM2.

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.

Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology

BACKGROUND

Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway.

CONTENT

Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers.

SUMMARY

CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.

Translating blood biomarkers into clinical practice for Alzheimer's disease: Challenges and perspectives

Early and accurate diagnosis of Alzheimer's disease (AD) in clinical practice is urgent with advances in AD treatment. Blood biomarker assays are preferential diagnostic tools for widespread clinical use with the advantages of being less invasive, cost effective, and easily accessible, and they have shown good performance in research cohorts. However, in community-based populations with maximum heterogeneity, great challenges are still faced in diagnosing AD based on blood biomarkers in terms of accuracy and robustness. Here, we analyze these challenges, including the confounding impact of systemic and biological factors, small changes in blood biomarkers, and difficulty in detecting early changes. Furthermore, we provide perspectives on several potential strategies to overcome these challenges for blood biomarkers to bridge the gap from research to clinical practice.

Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease

The A/T/N research framework has been proposed for the diagnosis and prognosis of Alzheimer's disease (AD). However, the spatial distribution of ATN biomarkers and their relationship with cognitive impairment and neuropsychiatric symptoms (NPS) need further clarification in patients with AD. We scanned 83 AD patients and 38 cognitively normal controls who independently completed the mini-mental state examination and Neuropsychiatric Inventory scales. Tau, Aβ, and hypometabolism spatial patterns were characterized using Statistical Parametric Mapping together with [18F]flortaucipir, [18F]florbetapir, and [18F]FDG positron emission tomography. Piecewise linear regression, two-sample t-tests, and support vector machine algorithms were used to explore the relationship between tau, Aβ, and hypometabolism and cognition, NPS, and AD diagnosis. The results showed that regions with tau deposition are region-specific and mainly occurred in inferior temporal lobes in AD, which extensively overlaps with the hypometabolic regions. While the deposition regions of Aβ were unique and the regions affected by hypometabolism were widely distributed. Unlike Aβ, tau and hypometabolism build up monotonically with increasing cognitive impairment in the late stages of AD. In addition, NPS in AD were associated with tau deposition closely, followed by hypometabolism, but not with Aβ. Finally, hypometabolism and tau had higher accuracy in differentiating the AD patients from controls (accuracy = 0.88, accuracy = 0.85) than Aβ (accuracy = 0.81), and the combined three were the highest (accuracy = 0.95). These findings suggest tau pathology is superior over Aβ and glucose metabolism to identify cognitive impairment and NPS. Its results support tau accumulation can be used as a biomarker of clinical impairment in AD.

PET molecular imaging for pathophysiological visualization in Alzheimer's disease

Alzheimer's disease (AD) is the most common dementia worldwide. The exact etiology of AD is unclear as yet, and no effective treatments are currently available, making AD a tremendous burden posed on the whole society. As AD is a multifaceted and heterogeneous disease, and most biomarkers are dynamic in the course of AD, a range of biomarkers should be established to evaluate the severity and prognosis. Positron emission tomography (PET) offers a great opportunity to visualize AD from diverse perspectives by using radiolabeled agents involved in various pathophysiological processes; PET imaging technique helps to explore the pathomechanisms of AD comprehensively and find out the most appropriate biomarker in each AD phase, leading to a better evaluation of the disease. In this review, we discuss the application of PET in the course of AD and summarized radiolabeled compounds with favorable imaging characteristics.

Towards the Integrative Theory of Alzheimer's Disease: Linking Molecular Mechanisms of Neurotoxicity, Beta-amyloid Biomarkers, and the Diagnosis

INTRODUCTION

A major gap in amyloid-centric theories of Alzheimer's disease (AD) is that even though amyloid fibrils per se are not toxic in vitro, the diagnosis of AD clearly correlates with the density of beta-amyloid (Aβ) deposits. Based on our proposed amyloid degradation toxicity hypothesis, we developed a mathematical model explaining this discrepancy. It suggests that cytotoxicity depends on the cellular uptake of soluble Aβ rather than on the presence of amyloid aggregates. The dynamics of soluble beta-amyloid in the cerebrospinal fluid (CSF) and the density of Aβ deposits is described using a system of differential equations. In the model, cytotoxic damage is proportional to the cellular uptake of Aβ, while the probability of an AD diagnosis is defined by the Aβ cytotoxicity accumulated over the duration of the disease. After uptake, Aβ is concentrated intralysosomally, promoting the formation of fibrillation seeds inside cells. These seeds cannot be digested and are either accumulated intracellularly or exocytosed. Aβ starts aggregating on the extracellular seeds and, therefore, decreases in concentration in the interstitial fluid. The dependence of both Aβ toxicity and aggregation on the same process-cellular uptake of Aβ-explains the correlation between AD diagnosis and the density of amyloid aggregates in the brain.

METHODS

We tested the model using clinical data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI), which included records of beta-amyloid concentration in the cerebrospinal fluid (CSF-Aβ42) and the density of beta-amyloid deposits measured using positron emission tomography (PET). The model predicts the probability of AD diagnosis as a function of CSF-Aβ42 and PET and fits the experimental data at the 95% confidence level.

RESULTS

Our study shows that existing clinical data allows for the inference of kinetic parameters describing beta-amyloid turnover and disease progression. Each combination of CSF-Aβ42 and PET values can be used to calculate the individual's cellular uptake rate, the effective disease duration, and the accumulated toxicity. We show that natural limitations on these parameters explain the characteristic distribution of the clinical dataset for these two biomarkers in the population.

CONCLUSION

The resulting mathematical model interprets the positive correlation between the density of Aβ deposits and the probability of an AD diagnosis without assuming any cytotoxicity of the aggregated beta-amyloid. To the best of our knowledge, this model is the first to mechanistically explain the negative correlation between the concentration of Aβ42 in the CSF and the probability of an AD diagnosis. Finally, based on the amyloid degradation toxicity hypothesis and the insights provided by mathematical modeling, we propose new pathophysiology-relevant biomarkers to diagnose and predict AD.

Amyloid-β PET in Alzheimer's disease: A systematic review and Bayesian meta-analysis

BACKGROUND

In recent years, longitudinal studies of Alzheimer's disease (AD) have been successively concluded. Our aim is to determine the efficacy of amyloid-β (Aβ) PET in diagnosing AD and early prediction of mild cognitive impairment (MCI) converting to AD. By pooling studies from different centers to explore in-depth whether diagnostic performance varies by population type, radiotracer type, and diagnostic approach, thus providing a more comprehensive theoretical basis for the subsequent widespread application of Aβ PET in the clinical setting.

METHODS

Relevant studies were searched through PubMed. The pooled sensitivities, specificities, DOR, and the summary ROC curve were obtained based on a Bayesian random-effects model.

RESULTS

Forty-eight studies, including 5967 patients, were included. Overall, the pooled sensitivity, specificity, DOR, and AUC of Aβ PET for diagnosing AD were 0.90, 0.80, 35.68, and 0.91, respectively. Subgroup analysis showed that Aβ PET had high sensitivity (0.91) and specificity (0.81) for differentiating AD from normal controls but very poor specificity (0.49) for determining AD from MCI. The pooled sensitivity and specificity were 0.84 and 0.62, respectively, for predicting the conversion of MCI to AD. The differences in diagnostic efficacy between visual assessment and quantitative analysis and between 11 C-PIB PET and 18 F-florbetapir PET were insignificant.

CONCLUSIONS

The overall performance of Aβ PET in diagnosing AD is favorable, but the differentiation between MCI and AD patients should consider that some MCI may be at risk of conversion to AD and may be misdiagnosed. A multimodal diagnostic approach and machine learning analysis may be effective in improving diagnostic accuracy.

Design, synthesis, and preliminary evaluation of [18F]-aryl flurosulfates PET radiotracers via SuFEx methods for β-amyloid plaques in Alzheimer's disease

[18F]BAY-94-9172, [18F]AV-45, and [18F]GE-067 were FDA approved positron emission tomography (PET) imaging radiotracer of β-amyloid plaques (Aβ) in Alzheimer's disease (AD). However, the radiochemical synthesis requires multi-step reactions and complex procedure. Recently, a protocol for radiochemical synthesis of sulfur fluoride exchange (SuFEx) using ultrafast 19F/18F isotopic exchange had been reported. We developed three pairs of novel 18F-labeled radiotracers by the "SuFEx" method for PET imaging Aβ plaques. The 18F labeling reaction can be completed quickly (30 s) at room temperature and purified using solid-phase extraction (SPE). The radiochemical purity (RCP) of the products was all greater than 95 %. In vitro fluorescent staining using Aβ-transgenesis mice section preliminary verified the affinity of tracers with Aβ. Competitive binding assay displayed high affinity of tracers for towards artificial Aβ1-42 aggregates (Ki values ranging from 3.53 ± 0.39 to 42.0 ± 4.24 nM). In vivo biodistribution and Micro-PET imaging showed that [18F]-Sulfur Fluoride β-Amyloid ([18F]SFA 1-6) could penetration the blood-brain barrier (BBB) in wild-type mice, and [18F]SFA 5-6 had a high initial brain uptake value (3.65 ± 0.9 % and 5.07 ± 0.1 % ID/g, respectively) and a fast washout (Brain uptake2 min/60 min = 4.15 and 4.61, respectively) from the brain. In vitro autoradiography demonstrated the affinity of the [18F]SFA 5-6 to Aβ plaques in AD human brain tissues. Our results suggested that [18F]SFA maybe a potential PET radiotracers for detecting Aβ in Alzheimer's disease.

Morphometric imaging biomarker identifies Alzheimer's disease even among mixed dementia patients

A definitive diagnosis of Alzheimer's disease (AD), even in the presence of co-morbid neuropathology (occurring in > 50% of AD cases), is a significant unmet medical need that has obstructed the discovery of effective AD therapeutics. An AD-biomarker, the Morphometric Imaging (MI) assay on cultured skin fibroblasts, was used in a double-blind, allcomers (ages 55-90) trial of 3 patient cohorts: AD dementia patients, N = 25, all autopsy confirmed, non-AD dementia patients, N = 21-all autopsy or genetically confirmed; and non-demented control (AHC) patients N = 27. Fibroblasts cells isolated from 3-mm skin punch biopsies were cultured on a 3-D Matrigel matrix with movement dynamics quantified by image analysis. From counts of all aggregates (N) in a pre-defined field image and measures of the average area (A) of aggregates per image, the number-to-area ratios in a natural logarithmic form Ln(A/N) were determined for all patient samples. AD cell lines formed fewer large aggregates (cells clustered together) than non-AD or AHC cell lines. The cut-off value of Ln(A/N) = 6.98 was determined from the biomarker values of non-demented apparently healthy control (AHC) cases. Unequivocal validation by autopsy, genetics, and/or dementia criteria was possible for all 73 patient samples. The samples were collected from multiple centers-four US centers and one center in Japan. The study found no effect of center-to-center variation in fibroblast isolation, cell growth, or cell aggregation values (Ln(A/N)). The autopsy-confirmed MI Biomarker distinguished AD from non-AD dementia (non-ADD) patients and correctly diagnosed AD even in the presence of other co-morbid pathologies at autopsy (True Positive = 25, False Negative = 0, False Positive = 0, True Negative = 21, and Accuracy = 100%. Sensitivity and specificity were calculated as 100% (95% CI = 84 to 100.00%). From these findings, the MI assay appears to detect AD with great accuracy-even with abundant co-morbidity.

Patients with Alzheimer's disease have an increased removal rate of soluble beta-amyloid-42

Senile plaques, which are mostly composed of beta-amyloid peptide, are the main signature of Alzheimer's disease (AD). Two main forms of beta-amyloid in humans are 40 and 42-amino acid, long; the latter is considered more relevant to AD etiology. The concentration of soluble beta-amyloid-42 (Aβ42) in cerebrospinal fluid (CSF-Aβ42) and the density of amyloid depositions have a strong negative correlation. However, AD patients have lower CSF-Aβ42 levels compared to individuals with normal cognition (NC), even after accounting for this correlation. The goal of this study was to infer deviations of Aβ42 metabolism parameters that underlie this difference using data from the Alzheimer's Disease Neuroimaging Initiative cohort. Aβ42 is released to the interstitial fluid (ISF) by cells and is removed by several processes. First, growth of insoluble fibrils by aggregation decreases the concentration of soluble beta-amyloid in the ISF. Second, Aβ42 is physically transferred from the brain to the CSF and removed with the CSF flow. Finally, there is an intratissue removal of Aβ42 ending in proteolysis, which can occur either in the ISF or inside the cells after the peptide is endocytosed. Unlike aggregation, which preserves the peptide in the brain, transfer to the CSF and intratissue proteolysis together represent amyloid removal. Using a kinetic model of Aβ42 turnover, we found that compared to NC subjects, AD patients had dramatically increased rates of amyloid removal. A group with late-onset mild cognitive impairment (LMCI) also exhibited a higher rate of amyloid removal; however, this was less pronounced than in the AD group. Estimated parameters in the early-onset MCI group did not differ significantly from those in the NC group. We hypothesize that increased amyloid removal is mediated by Aβ42 cellular uptake; this is because CSF flow is not increased in AD patients, while most proteases are intracellular. Aβ cytotoxicity depends on both the amount of beta-amyloid internalized by cells and its intracellular conversion into toxic products. We speculate that AD and LMCI are associated with increased cellular amyloid uptake, which leads to faster disease progression. The early-onset MCI (EMCI) patients do not differ from the NC participants in terms of cellular amyloid uptake. Therefore, EMCI may be mediated by the increased production of toxic amyloid metabolites.

Classification accuracy of blood-based and neurophysiological markers in the differential diagnosis of Alzheimer's disease and frontotemporal lobar degeneration

BACKGROUND

In the last decade, non-invasive blood-based and neurophysiological biomarkers have shown great potential for the discrimination of several neurodegenerative disorders. However, in the clinical workup of patients with cognitive impairment, it will be highly unlikely that any biomarker will achieve the highest potential predictive accuracy on its own, owing to the multifactorial nature of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD).

METHODS

In this retrospective study, performed on 202 participants, we analysed plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and tau phosphorylated at amino acid 181 (p-Tau181) concentrations, as well as amyloid β42 to 40 ratio (Aβ1-42/1-40) ratio, using the ultrasensitive single-molecule array (Simoa) technique, and neurophysiological measures obtained by transcranial magnetic stimulation (TMS), including short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), long-interval intracortical inhibition (LICI), and short-latency afferent inhibition (SAI). We assessed the diagnostic accuracy of combinations of both plasma and neurophysiological biomarkers in the differential diagnosis between healthy ageing, AD, and FTLD.

RESULTS

We observed significant differences in plasma NfL, GFAP, and p-Tau181 levels between the groups, but not for the Aβ1-42/Aβ1-40 ratio. For the evaluation of diagnostic accuracy, we adopted a two-step process which reflects the clinical judgement on clinical grounds. In the first step, the best single biomarker to classify "cases" vs "controls" was NfL (AUC 0.94, p < 0.001), whilst in the second step, the best single biomarker to classify AD vs FTLD was SAI (AUC 0.96, p < 0.001). The combination of multiple biomarkers significantly increased diagnostic accuracy. The best model for classifying "cases" vs "controls" included the predictors p-Tau181, GFAP, NfL, SICI, ICF, and SAI, resulting in an AUC of 0.99 (p < 0.001). For the second step, classifying AD from FTD, the best model included the combination of Aβ1-42/Aβ1-40 ratio, p-Tau181, SICI, ICF, and SAI, resulting in an AUC of 0.98 (p < 0.001).

CONCLUSIONS

The combined assessment of plasma and neurophysiological measures may greatly improve the differential diagnosis of AD and FTLD.

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

Alzheimer's disease related biomarkers in bipolar disorder - A longitudinal one-year case-control study

INTRODUCTION

Bipolar disorder (BD) is a heterogeneous mental disorder characterized by recurrent relapses of affective episodes: Subgroups of patients with BD have cognitive deficits, and an increased risk of dementia.

METHODS

This prospective, longitudinal, one-year follow-up, case-control study investigated biomarkers for AD and neurodegenerative diseases, namely: cerebrospinal fluid (CSF) amyloid beta (Aβ) isoforms and ratios (Aβ42, Aβ40, Aβ38), CSF soluble amyloid precursor protein (sAPP) α and β, CSF total (t-tau) and phosphorylated tau (p-tau), CSF neurofilament-light (NF-L), CSF neurogranin (NG), plasma-isoforms Aβ42 and Aβ40, plasma-tau, plasma-NF-L, and serum S100B, in patients with BD (N = 62, aged 18-60) and gender-and-age-matched healthy control individuals (N = 40). CSF and plasma/serum samples were collected at baseline, during and after an affective episode, if it occurred, and after a year. Data were analyzed in mixed models.

RESULTS

Levels of CSF Aβ42 decreased in patients with BD who had an episode during follow-up (BD-E) (N = 22) compared to patients without an episode (BD-NE) (N = 25) during follow-up (P = 0.002). Stable levels were seen for all other markers in BD-E compared to BD-NE during the one-year follow-up. We found no statistically significant differences between patients with BD and HC at T0 and T3 for Aβ42, Aβ40, Aβ38, Aβ42/38, Aβ42/40, sAPPα, sAPPβ, t-tau, p-tau, p-tau /t-tau, NF-L, NG in CSF and further Aβ40, Aβ42, Aβ42/40, t-tau, NF-L in plasma, S100B in serum, and APOE-status. Furthermore, all 18 biomarkers were stable in HC during the one-year follow-up from T0 to T3.

CONCLUSION

A panel of biomarkers of Alzheimer's and neurodegeneration show no differences between patients with BD and HC. There were abnormalities of amyloid production/clearance during an acute BD episode. The abnormalities mimic the pattern seen in AD namely decreasing CSF Aβ42 and may suggest an association with brain amyloidosis.

Age, sex and APOE-ε4 modify the balance between soluble and fibrillar β-amyloid in non-demented individuals: topographical patterns across two independent cohorts

Amyloid (Aβ) pathology is the earliest detectable pathophysiological event along the Alzheimer's continuum, which can be measured both in the cerebrospinal fluid (CSF) and by Positron Emission Tomography (PET). Yet, these biomarkers identify two distinct Aβ pools, reflecting the clearance of soluble Aβ as opposed to the presence of Aβ fibrils in the brain. An open question is whether risk factors known to increase Alzheimer's' disease (AD) prevalence may promote an imbalance between soluble and deposited Aβ. Unveiling such interactions shall aid our understanding of the biological pathways underlying Aβ deposition and foster the design of effective prevention strategies. We assessed the impact of three major AD risk factors, such as age, APOE-ε4 and female sex, on the association between CSF and PET Aβ, in two independent samples of non-demented individuals (ALFA: n = 320, ADNI: n = 682). We tested our hypotheses both in candidate regions of interest and in the whole brain using voxel-wise non-parametric permutations. All of the assessed risk factors induced a higher Aβ deposition for any given level of CSF Aβ42/40, although in distinct cerebral topologies. While age and sex mapped onto neocortical areas, the effect of APOE-ε4 was prominent in the medial temporal lobe, which represents a target of early tau deposition. Further, we found that the effects of age and APOE-ε4 was stronger in women than in men. Our data indicate that specific AD risk factors affect the spatial patterns of cerebral Aβ aggregation, with APOE-ε4 possibly facilitating a co-localization between Aβ and tau along the disease continuum.

Cerebral amyloid load determination in a clinical setting: interpretation of amyloid biomarker discordances aided by tau and neurodegeneration measurements

BACKGROUND

Alzheimer's disease (AD) diagnosis can be hindered by amyloid biomarkers discordances.

OBJECTIVE

We aim to interpret discordances between amyloid positron emission tomography (Amy-PET) and cerebrospinal fluid (CSF) (Aβ₄₂ and Aβ_42/40), using Amy-PET semiquantitative analysis, [¹⁸F]fluorodeoxyglucose (FDG)-PET pattern, and CSF assays.

METHOD

Thirty-six subjects with dementia or mild cognitive impairment, assessed by neuropsychological tests, structural and functional imaging, and CSF assays (Aβ₄₂, Aβ_42/40, p-tau, t-tau), were retrospectively examined. Amy-PET and FDG-PET scans were analyzed by visual assessment and voxel-based analysis. SUVR were calculated on Amy-PET scans.

RESULTS

Groups were defined basing on the agreement among CSF Aβ₄₂ (A), CSF Aβ_42/40 Ratio (R), and Amy-PET (P) dichotomic results ( ±). In discordant groups, CSF assays, Amy-PET semiquantification, and FDG-PET patterns supported the diagnosis suggested by any two agreeing amyloid biomarkers. In groups with discordant CSF Aβ₄₂, the ratio always agrees with Amy-PET results, solving both false-negative and false-positive Aβ₄₂ results, with Aβ₄₂ levels close to the cut-off in A + R-P- subjects. The A + R + P- group presented high amyloid deposition in relevant areas, such as precuneus, posterior cingulate cortex (PCC) and dorsolateral frontal inferior cortex at semiquantitative analysis.

CONCLUSION

The amyloid discordant cases could be overcome by combining CSF Aβ₄₂, CSF ratio, and Amy-PET results. The concordance of any 2 out of the 3 biomarkers seems to reveal the remaining one as a false result. A cut-off point review could avoid CSF Aβ₄₂ false-negative results. The regional semiquantitative Amy-PET analysis in AD areas, such as precuneus and PCC, could increase the accuracy in AD diagnosis.

Network-constrained technique to characterize pathology progression rate in Alzheimer's disease

Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer’s disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient’s longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer’s Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject’s degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications.

Apolipoprotein E ɛ4-related effects on cognition are limited to the Alzheimer's disease spectrum

Whether the deleterious effects of APOE4 are restricted to the Alzheimer’s disease (AD) spectrum or cause cognitive impairment irrespectively of the development of AD is still a matter of debate, and the focus of this study. Our analyses included APOE4 genotype, neuropsychological variables, amyloid-βeta (Aβ) and Tau markers, FDG-PET values, and hippocampal volumetry data derived from the healthy controls sample of the ADNI database. We formed 4 groups of equal size (n = 30) based on APOE4 carriage and amyloid-PET status. Baseline and follow-up (i.e., 48 months post-baseline) results indicated that Aβ-positivity was the most important factor to explain poorer cognitive performance, while APOE4 only exerted a significant effect in Aβ-positive subjects. Additionally, multiple regression analyses evidenced that, within the Aβ-positive sample, hippocampal volumetry explained most of the variability in cognitive performance for APOE4 carriers. These findings represent a strong support for the so-called preclinical/prodromal hypothesis, which states that the reported differences in cognitive performance between healthy carriers and non-carriers are mainly due to the APOE4’s capability to increase the risk of AD. Moreover, our results reinforce the notion that a synergistic interaction of Aβ and APOE4 elicits a neurodegenerative process in the hippocampus that might be the main cause of impaired cognitive performance.

Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis

Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.

Temporal Correlation of CSF and Neuroimaging in the Amyloid-Tau-Neurodegeneration Model of Alzheimer Disease

OBJECTIVE

To evaluate temporal correlations between CSF and neuroimaging (PET and MRI) measures of amyloid, tau, and neurodegeneration in relation to Alzheimer disease (AD) progression.

METHODS

A total of 371 cognitively unimpaired and impaired participants enrolled in longitudinal studies of AD had both CSF (β-amyloid [Aβ]₄₂, phosphorylated tau₁₈₁, total tau, and neurofilament light chain) and neuroimaging (Pittsburgh compound B [PiB] PET, flortaucipir PET, and structural MRI) measures. The pairwise time interval between CSF and neuroimaging measures was binned into 2-year periods. Spearman correlations identified the time bin when CSF and neuroimaging measures most strongly correlated. CSF and neuroimaging measures were then binarized as biomarker-positive or biomarker-negative using Gaussian mixture modeling. Cohen kappa coefficient identified the time bin when CSF measures best agreed with corresponding neuroimaging measures when determining amyloid, tau, and neurodegeneration biomarker positivity.

RESULTS

CSF Aβ₄₂ and PiB PET showed maximal correlation when collected within 6 years of each other (R ≈ -0.5). CSF phosphorylated tau₁₈₁ and flortaucipir PET showed maximal correlation when CSF was collected 4 to 8 years prior to PET (R ≈ 0.4). CSF neurofilament light chain and cortical thickness showed low correlation, regardless of time interval (R _avg ≈ -0.3). Similarly, CSF total tau and cortical thickness had low correlation, regardless of time interval (R _avg < -0.2).

CONCLUSIONS

CSF Aβ₄₂ and PiB PET best agree when acquired in close temporal proximity, whereas CSF phosphorylated tau precedes flortaucipir PET by 4 to 8 years. CSF and neuroimaging measures of neurodegeneration have low correspondence and are not interchangeable at any time interval.

Use of Alzheimer's Disease Cerebrospinal Fluid Biomarkers in A Tertiary Care Memory Clinic

INTRODUCTION

Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers are promising tools to help identify the underlying pathology of neurocognitive disorders. In this manuscript, we report our experience with AD CSF biomarkers in 262 consecutive patients in a tertiary care memory clinic.

METHODS

We retrospectively reviewed 262 consecutive patients who underwent lumbar puncture (LP) and CSF measurement of AD biomarkers (Aβ1-42, total tau or t-tau, and p-tau181). We studied the safety of the procedure and its impact on patient's diagnosis and management.

RESULTS

The LP allowed to identify underlying AD pathology in 72 of the 121 patients (59%) with early onset amnestic mild cognitive impairment (aMCI) with a high probability of progression to AD; to distinguish the behavioral/dysexecutive variant of AD from the behavioral variant of frontotemporal dementia (bvFTD) in 25 of the 45 patients (55%) with an atypical neurobehavioral profile; to identify AD as the underlying pathology in 15 of the 27 patients (55%) with atypical or unclassifiable primary progressive aphasia (PPA); and to distinguish AD from other disorders in 9 of the 29 patients (31%) with psychiatric differential diagnoses and 19 of the 40 patients (47%) with lesional differential diagnoses (normal pressure hydrocephalus, encephalitis, prion disease, etc.). No major complications occurred following the LP.

INTERPRETATION

Our results suggest that CSF analysis is a safe and effective diagnostic tool in select patients with neurocognitive disorders. We advocate for a wider use of this biomarker in tertiary care memory clinics in Canada.

Statistical estimation and comparison of group-specific bivariate correlation coefficients in family-type clustered studies

Bivariate correlation coefficients (BCCs) are often calculated to gauge the relationship between two variables in medical research. In a family-type clustered design where multiple participants from same units/families are enrolled, BCCs can be defined and estimated at various hierarchical levels (subject level, family level and marginal BCC). Heterogeneity usually exists between subject groups and, as a result, subject level BCCs may differ between subject groups. In the framework of bivariate linear mixed effects modeling, we define and estimate BCCs at various hierarchical levels in a family-type clustered design, accommodating subject group heterogeneity. Simplified and modified asymptotic confidence intervals are constructed to the BCC differences and Wald type tests are conducted. A real-world family-type clustered study of Alzheimer disease (AD) is analyzed to estimate and compare BCCs among well-established AD biomarkers between mutation carriers and non-carriers in autosomal dominant AD asymptomatic individuals. Extensive simulation studies are conducted across a wide range of scenarios to evaluate the performance of the proposed estimators and the type-I error rate and power of the proposed statistical tests. Abbreviations: BCC: bivariate correlation coefficient; BLM: bivariate linear mixed effects model; CI: confidence interval; AD: Alzheimer's disease; DIAN: The Dominantly Inherited Alzheimer Network; SA: simple asymptotic; MA: modified asymptotic.

Repeatability of parametric methods for [18F]florbetapir imaging in Alzheimer's disease and healthy controls: A test-retest study

Accumulation of amyloid beta (Aβ) is one of the pathological hallmarks of Alzheimer's disease (AD), which can be visualized using [¹⁸F]florbetapir positron emission tomography (PET). The aim of this study was to evaluate various parametric methods and to assess their test-retest (TRT) reliability. Two 90 min dynamic [¹⁸F]florbetapir PET scans, including arterial sampling, were acquired (n = 8 AD patient, n = 8 controls). The following parametric methods were used; (reference:cerebellum); Logan and spectral analysis (SA), receptor parametric mapping (RPM), simplified reference tissue model2 (SRTM2), reference Logan (rLogan) and standardized uptake value ratios (SUV_r(50-70)). BP_ND+1, DVR, V_T and SUVr were compared with corresponding estimates (V_T or DVR) from the plasma input reversible two tissue compartmental (2T4k_V_B) model with corresponding TRT values for 90-scan duration. RPM (r² = 0.92; slope = 0.91), Logan (r² = 0.95; slope = 0.84) and rLogan (r² = 0.94; slope = 0.88), and SRTM2 (r² = 0.91; slope = 0.83), SA (r² = 0.91; slope = 0.88), SUVr (r² = 0.84; slope = 1.16) correlated well with their 2T4k_V_B counterparts. RPM (controls: 1%, AD: 3%), rLogan (controls: 1%, AD: 3%) and SUV_r(50-70) (controls: 3%, AD: 8%) showed an excellent TRT reliability. In conclusion, most parametric methods showed excellent performance for [¹⁸F]florbetapir, but RPM and rLogan seem the methods of choice, combining the highest accuracy and best TRT reliability.

CCCDTD5: Clinical role of neuroimaging and liquid biomarkers in patients with cognitive impairment

Since 1989, four Canadian Consensus Conferences on the Diagnosis and Treatment of Dementia (CCCDTDs) have provided evidence-based dementia diagnostic and treatment guidelines for Canadian clinicians and researchers. We present the results from the Neuroimaging and Fluid Biomarkers Group of the 5th CCCDTD (CCCDTD5), which addressed topics chosen by the steering committee to reflect advances in the field and build on our previous guidelines. Recommendations on Imaging and Fluid Biomarker Use from this Conference cover a series of different fields. Prior structural imaging recommendations for both computerized tomography (CT) and magnetic resonance imaging (MRI) remain largely unchanged, but MRI is now more central to the evaluation than before, with suggested sequences described here. The use of visual rating scales for both atrophy and white matter anomalies is now included in our recommendations. Molecular imaging with [18F]-fluorodeoxyglucose ([18F]-FDG) Positron Emisson Tomography (PET) or [99mTc]-hexamethylpropyleneamine oxime/ethylene cysteinate dimer ([99mTc]-HMPAO/ECD) Single Photon Emission Tomography (SPECT), should now decidedly favor PET. The value of [18F]-FDG PET in the assessment of neurodegenerative conditions has been established with greater certainty since the previous conference, and it has now been recognized as a useful biomarker to establish the presence of neurodegeneration by a number of professional organizations around the world. Furthermore, the role of amyloid PET has been clarified and our recommendations follow those from other groups in multiple countries. SPECT with [123I]-ioflupane (DaTscanTM) is now included as a useful study in differentiating Alzheimer's disease (AD) from Lewy body disease. Finally, liquid biomarkers are in a rapid phase of development and, could lead to a revolution in the assessment AD and other neurodegenerative conditions at a reasonable cost. We hope these guidelines will be useful for clinicians, researchers, policy makers, and the lay public, to inform a current and evidence-based approach to the use of neuroimaging and liquid biomarkers in clinical dementia evaluation and management.

Matching Clinical Diagnosis and Amyloid Biomarkers in Alzheimer's Disease and Frontotemporal Dementia

BACKGROUND

The aims of this study were to compare the diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values (PPV, NPV) of different cerebrospinal fluid (CSF) amyloid biomarkers and amyloid-Positron Emission Tomography (PET) in patients with a clinical diagnosis of Alzheimer's disease (AD) and Frontotemporal Dementia (FTD); to compare concordance between biomarkers; and to provide an indication of their use and interpretation.

METHODS

We included 148 patients (95 AD and 53 FTD), who underwent clinical evaluation, neuropsychological assessment, and at least one amyloid biomarker (CSF analysis or amyloid-PET). Thirty-six patients underwent both analyses. One-hundred-thirteen patients underwent Apolipoprotein E (ApoE) genotyping.

RESULTS

Amyloid-PET presented higher diagnostic accuracy, sensitivity, and NPV than CSF Aβ_1-42 but not Aβ_42/40 ratio. Concordance between CSF biomarkers and amyloid-PET was higher in FTD patients compared to AD cases. None of the AD patients presented both negative Aβ biomarkers.

CONCLUSIONS

CSF Aβ_42/40 ratio significantly increased the diagnostic accuracy of CSF biomarkers. On the basis of our current and previous data, we suggest a flowchart to guide the use of biomarkers according to clinical suspicion: due to the high PPV of both amyloid-PET and CSF analysis including Aβ_42/40, in cases of concordance between at least one biomarker and clinical diagnosis, performance of the other analysis could be avoided. A combination of both biomarkers should be performed to better characterize unclear cases. If the two amyloid biomarkers are both negative, an underlying AD pathology can most probably be excluded.

Validation of the Alzheimer Disease Dementia Conversion-Related Pattern as an ATN Biomarker of Neurodegeneration

OBJECTIVE

To determine whether the Alzheimer disease (AD) dementia conversion-related pattern (ADCRP) on [¹⁸F]FDG PET can serve as a valid predictor for the development of AD dementia, the individual expression of the ADCRP (subject score) and its prognostic value were examined in patients with mild cognitive impairment (MCI) and biologically defined AD.

METHODS

A total of 269 patients with available [¹⁸F]FDG PET, [¹⁸F]AV-45 PET, phosphorylated and total tau in CSF, and neurofilament light chain in plasma were included. Following the AT(N) classification scheme, where AD is defined biologically by in vivo biomarkers of β-amyloid (Aβ) deposition ("A") and pathologic tau ("T"), patients were categorized to the A-T-, A+T-, A+T+ (AD), and A-T+ groups.

RESULTS

The mean subject score of the ADCRP was significantly higher in the A+T+ group compared to each of the other group (all p < 0.05) but was similar among the latter (all p > 0.1). Within the A+T+ group, the subject score of ADCRP was a significant predictor of conversion to dementia (hazard ratio, 2.02 per z score increase; p < 0.001), with higher predictive value than of alternative biomarkers of neurodegeneration (total tau and neurofilament light chain). Stratification of A+T+ patients by the subject score of ADCRP yielded well-separated groups of high, medium, and low conversion risks.

CONCLUSIONS

The ADCRP is a valuable biomarker of neurodegeneration in patients with MCI and biologically defined AD. It shows great potential for stratifying the risk and estimating the time to conversion to dementia in patients with MCI and underlying AD (A+T+).

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that [¹⁸F]FDG PET predicts the development of AD dementia in individuals with MCI and underlying AD as defined by the AT(N) framework.

Associations of Subsyndromal Symptomatic Depression with Cognitive Decline and Brain Atrophy in Elderly Individuals without Dementia: A Longitudinal Study

BACKGROUND

Subsyndromal symptomatic depression (SSD) is prevalent in older adults. However, it remains unclear whether there are effects of SSD on brain aging outcomes (cognition and brain structures), especially in the presence of Alzheimer's Disease (AD) pathology.

METHODS

A total of 1,188 adults without dementia were recruited from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Participants with SSD were measured using the 15-item Geriatric Depression Scale (GDS-15). In multivariable models, the cross-sectional and longitudinal associations of SSD with brain aging outcomes were explored. We further evaluated whether baseline amyloid-β (Aβ) load modifies the relations between SSD and brain aging outcomes.

RESULTS

SSD at baseline was associated with significantly longitudinal decline in cognition and displayed significantly accelerated atrophy in hippocampus (β = -29.53, p = 0.001) and middle temporal gyrus (β = - 77.82, p = 0.006) among all participants and Aβ-Positive individuals. SSD interacted with baseline Aβ load in predicting longitudinal decline in Mini Mental State Examination (MMSE) (β = - 0.327, p = 0.023), episodic memory (β = -0.065, p = 0.004) and increase in Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS-cog13) (β = 0.754, p = 0.026).

LIMITATIONS

Our study didn't look at AD diagnosis but Aβ status.

CONCLUSIONS

Our findings suggested that older people without dementia with both SSD and a high level of Aβ load may have higher risk of cognitive deterioration and brain atrophy. Therapeutic mitigation of depressive symptoms, especially in those with abnormal Aβ levels, may help delay progressive decline in cognition.

Association of CSF Aβ, amyloid PET, and cognition in cognitively unimpaired elderly adults

OBJECTIVE

To compare CSF β-amyloid (Aβ) and florbetapir PET measurements in cognitively unimpaired (CU) elderly adults in order to detect the earliest abnormalities and compare their predictive effect for cognitive decline.

METHODS

A total of 259 CU individuals were categorized as abnormal (+) or normal (-) on CSF Aβ_1-42/Aβ_1-40 analyzed with mass spectrometry and Aβ PET measured with ¹⁸F-florbetapir. Simultaneous longitudinal measurements of CSF and PET were compared for 39 individuals who were unambiguously Aβ-negative at baseline (CSF-/PET-). We also examined the relationship between baseline CSF/PET group membership and longitudinal changes in CSF Aβ, Aβ PET, and cognition.

RESULTS

The proportions of individuals in each discordant group were similar (8.1% CSF+/PET- and 7.7% CSF-/PET+). Among baseline Aβ-negative (CSF-/PET-) individuals with longitudinal CSF and PET measurements, a larger proportion subsequently worsened on CSF Aβ (odds ratio 4 [95% confidence interval (CI) 1.1, 22.1], p = 0.035) than Aβ PET over 3.5 ± 1.0 years. Compared to CSF-/PET- individuals, CSF+/PET- individuals had faster (estimate 0.009 [95% CI 0.005, 0.013], p < 0.001) rates of Aβ PET accumulation over 4.4 ± 1.7 years, while CSF-/PET+ individuals had faster (estimate -0.492 [95% CI -0.861, -0.123], p = 0.01) rates of cognitive decline over 4.5 ± 1.9 years.

CONCLUSIONS

The proportions of discordant PET and CSF Aβ-positive individuals were similar cross-sectionally. However, unambiguously Aβ-negative (CSF-/PET-) individuals are more likely to show subsequent worsening on CSF than PET, supporting the idea that CSF detects the earliest Aβ changes. In discordant cases, only PET abnormality predicted cognitive decline, suggesting that abnormal Aβ PET changes are a later phenomenon in cognitively normal individuals.

Characterization of Alzheimer Disease Biomarker Discrepancies Using Cerebrospinal Fluid Phosphorylated Tau and AV1451 Positron Emission Tomography

Importance

Fluid and imaging biomarkers of Alzheimer disease (AD) are often used interchangeably, but some biomarkers may reveal earlier stages of disease.

Objective

To characterize individuals with tau abnormality indicated by cerebrospinal fluid (CSF) assay or positron emission tomography (PET).

Design, Setting, and Participants

Between 2010 and 2019, 322 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent CSF and PET assessments of tau pathology. Data-driven, clinically relevant thresholds for CSF phosphorylated tau (P-tau) (≥26.64 pg/mL) and flortaucipir-PET meta-regions of interest (ROI) (standard uptake value ratio ≥1.37) indicated participants' tau status as CSF-/PET-, CSF+/PET-, CSF-/PET+, and CSF+/PET+. Of 1659 ADNI participants with a CSF or flortaucipir assessment, 588 had both measures (1071 were excluded). Among these, 266 were further excluded because they did not have flortaucipir and CSF testing within less than 25 months, leaving 322 for analysis. Of these, 213 were cognitively unimpaired (CU); 98 had mild cognitive impairment (MCI); and 11 had AD dementia.

Main Outcomes and Measures

We compared tau-positive vs tau-negative groups as indicated by either modality or demographic and clinical variables, amyloid β-PET burden, and flortaucipir-PET binding across Braak stage-related ROIs. We also compared 5-year rates of CSF P-tau accumulation and cognitive decline prior to flortaucipir-PET scanning.

Results

Among the 322 study participants, 180 were women (56%), and the mean (SD) age was 73.08 (7.37) years. Two hundred ten participants were CSF-/PET- (65%); 63 were CSF+/PET- (19.5%); 15 were CSF-/PET+ (4.6%); and 34 were CSF+/PET+ (10.5%). Most CSF-/PET+ participants had measures near CSF or PET tau thresholds. The CSF+/PET- participants showed faster 5-year accrual of P-tau and increased flortaucipir-PET binding in early Braak ROIs but similar memory decline compared with CSF-/PET- participants. Tau-positive individuals by either measure showed increased amyloid β-PET burden. All CSF+/PET+ individuals were amyloid-positive, and 26 had MCI or AD dementia (76%). Compared with the CSF-/PET- group, CSF+/PET+ individuals had experienced faster 5-year accrual of CSF P-tau and decline in memory and executive function, resulting in reduced cognitive abilities at the time of flortaucipir-PET assessment.

Conclusions and Relevance

Suprathreshold CSF P-tau without flortaucipir-PET abnormality may indicate a stage of AD development characterized by early tau abnormality without measurable loss in cognitive performance. Persons with both tau CSF and PET abnormality appear to have reduced cognitive capacities resulting from faster antecedent cognitive decline. Elevation of CSF P-tau appears to precede flortaucipir-PET positivity in the progression of AD pathogenesis and related cognitive decline.

Topographical distribution of Aβ predicts progression to dementia in Aβ positive mild cognitive impairment

INTRODUCTION

Abnormal brain amyloid beta (Aβ) is typically assessed in vivo using global concentrations from cerebrospinal fluid and positron emission tomography (PET). However, it is unknown whether the assessment of the topographical distribution of Aβ pathology can provide additional information to identify, among global Aβ positive individuals, those destined for dementia.

METHODS

We studied 260 amnestic mild cognitive impairment (MCI) subjects who were Aβ-PET positive with [18F]florbetapir. Using [18F]florbetapir, we assessed the percentage of voxels sowing Aβ abnormality as well as the standardized uptake value ratio (SUVR) values across brain regions. Regressions tested the predictive effect of Aβ on progression to dementia over 2 years.

RESULTS

Neither global nor regional [18F]florbetapir SUVR concentrations predicted progression to dementia. In contrast, the spatial extent of Aβ pathology in regions comprising the default mode network was highly associated with the development of dementia over 2 years.

DISCUSSION

These results highlight that the regional distribution of Aβ abnormality may provide important complementary information at an individual level regarding the likelihood of Aβ positive MCI to progress to dementia.

A kinetics-based approach to amyloid PET semi-quantification

PURPOSE

To develop and validate a semi-quantification method (time-delayed ratio, TDr) applied to amyloid PET scans, based on tracer kinetics information.

METHODS

The TDr method requires two static scans per subject: one early (~ 0-10 min after the injection) and one late (typically 50-70 min or 90-100 min after the injection, depending on the tracer). High perfusion regions are delineated on the early scan and applied onto the late scan. A SUVr-like ratio is calculated between the average intensities in the high perfusion regions and the late scan hotspot. TDr was applied to a naturalistic multicenter dataset of 143 subjects acquired with [¹⁸F]florbetapir. TDr values are compared to visual evaluation, cortical-cerebellar SUVr, and to the geometrical semi-quantification method ELBA. All three methods are gauged versus the heterogeneity of the dataset.

RESULTS

TDr shows excellent agreement with respect to the binary visual assessment (AUC = 0.99) and significantly correlates with both validated semi-quantification methods, reaching a Pearson correlation coefficient of 0.86 with respect to ELBA.

CONCLUSIONS

TDr is an alternative approach to previously validated ones (SUVr and ELBA). It requires minimal image processing; it is independent on predefined regions of interest and does not require MR registration. Besides, it takes advantage on the availability of early scans which are becoming common practice while imposing a negligible added patient discomfort.

Applying the ATN scheme in a memory clinic population: The ABIDE project

OBJECTIVE

To apply the ATN scheme to memory clinic patients, to assess whether it discriminates patient populations with specific features.

METHODS

We included 305 memory clinic patients (33% subjective cognitive decline [SCD]: 60 ± 9 years, 61% M; 19% mild cognitive impairment [MCI]: 68 ± 9 years, 68% M; 48% dementia: 66 ± 10 years, 58% M) classified for positivity (±) of amyloid (A) ([¹⁸F]Florbetaben PET), tau (T) (CSF p-tau), and neurodegeneration (N) (medial temporal lobe atrophy). We assessed ATN profiles' demographic, clinical, and cognitive features at baseline, and cognitive decline over time.

RESULTS

The proportion of A+T+N+ patients increased with syndrome severity (from 1% in SCD to 14% in MCI and 35% in dementia), while the opposite was true for A-T-N- (from 48% to 19% and 6%). Compared to A-T-N-, patients with the Alzheimer disease profiles (A+T+N- and A+T+N+) were older (both p < 0.05) and had a higher prevalence of APOE ε4 (both p < 0.05) and lower Mini-Mental State Examination (MMSE) (both p < 0.05), memory (both p < 0.05), and visuospatial abilities (both p < 0.05) at baseline. Non-Alzheimer profiles A-T-N+ and A-T+N+ showed more severe white matter hyperintensities (both p < 0.05) and worse language performance (both p < 0.05) than A-T-N-. A linear mixed model showed faster decline on MMSE over time in A+T+N- and A+T+N+ (p = 0.059 and p < 0.001 vs A-T-N-), attributable mainly to patients without dementia.

CONCLUSIONS

The ATN scheme identified different biomarker profiles with overlapping baseline features and patterns of cognitive decline. The large number of profiles, which may have different implications in patients with vs without dementia, poses a challenge to the application of the ATN scheme.

Discordant amyloid-β PET and CSF biomarkers and its clinical consequences

Background

In vivo, high cerebral amyloid-β load has been associated with (i) reduced concentrations of Aβ₄₂ in cerebrospinal fluid and (ii) increased retention using amyloid-β positron emission tomography. Although these two amyloid-β biomarkers generally show good correspondence, ~ 10–20% of cases have discordant results. To assess the consequences of having discordant amyloid-β PET and CSF biomarkers on clinical features, biomarkers, and longitudinal cognitive trajectories.

Methods

We included 768 patients (194 with subjective cognitive decline (SCD), 127 mild cognitive impairment (MCI), 309 Alzheimer’s dementia (AD), and 138 non-AD) who were categorized as concordant-negative (n = 315, 41%), discordant (n = 97, 13%), or concordant-positive (n = 356, 46%) based on CSF and PET results. We compared discordant with both concordant-negative and concordant-positive groups on demographics, clinical syndrome, apolipoprotein E (APOE) ε4 status, CSF tau, and clinical and neuropsychological progression.

Results

We found an increase from concordant-negative to discordant to concordant-positive in rates of APOE ε4 (28%, 55%, 70%, Z = − 10.6, P < 0.001), CSF total tau (25%, 45%, 78%, Z = − 13.7, P < 0.001), and phosphorylated tau (28%, 43%, 80%, Z = − 13.7, P < 0.001) positivity. In patients without dementia, linear mixed models showed that Mini-Mental State Examination and memory composite scores did not differ between concordant-negative (β [SE] − 0.13[0.08], P = 0.09) and discordant (β 0.08[0.15], P = 0.15) patients (P_interaction = 0.19), while these scores declined in concordant-positive (β − 0.75[0.08] patients (P_interaction < 0.001). In patients with dementia, longitudinal cognitive scores were not affected by amyloid-β biomarker concordance or discordance. Clinical progression rates from SCD to MCI or dementia (P = 0.01) and from MCI to dementia (P = 0.003) increased from concordant-negative to discordant to concordant-positive.

Conclusions

Discordant cases were intermediate to concordant-negative and concordant-positive patients in terms of genetic (APOE ε4) and CSF (tau) markers of AD. While biomarker agreement did not impact cognition in patients with dementia, discordant biomarkers are not benign in patients without dementia given their higher risk of clinical progression.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0532-x) contains supplementary material, which is available to authorized users.

Clinical Experience with Cerebrospinal Fluid Aβ42, Total and Phosphorylated Tau in the Evaluation of 1,016 Individuals for Suspected Dementia

Background:

Elevated total tau (tTau), 181-phosphorylated phosphorylated tau (pTau), and low amyloid-β₄₂ (Aβ₄₂) in cerebrospinal fluid (CSF) represent a diagnostic biomarker for Alzheimer’s disease (AD).

Objective:

The goal was to determine the overall accuracy of CSF Aβ₄₂, tTau, pTau, and the Aβ₄₂/total tau index (ATI) in a non-research, clinical setting for the diagnosis of AD.

Methods:

From medical records in 1,016 patients that had CSF studies for dementia over a 12-year period (2005 to 2017), we calculated the sensitivity and specificity of CSF Aβ₄₂, tTau, and pTau and the ATI in relation to the final clinical diagnosis.

Results:

Compared with non-demented patients and patients with other dementias or mild cognitive impairment (MCI), the sensitivity and specificity of the recommended ATI and pTau cut-offs (ATI < 1.0 and pTau >61 pg/ml) for the diagnosis of AD were 0.88 and 0.72, respectively. Similar results were obtained comparing AD with non-demented patients only (0.88, 0.82) and AD with other types of dementia (0.81, 0.77). A subgroup of patients with presumed normal pressure hydrocephalus (n = 154) were biopsied at the time of shunt placement. Using the pathological manifestations of AD as the standard, the sensitivity was 0.83 while the specificity was 0.72.

Conclusions:

In a non-research setting, CSF biomarkers for AD showed a high sensitivity in accordance with previous studies, but modest specificity differentiating AD from other types of dementia or MCI. This study of unselected patients provides a valid and realistic assessment of the diagnostic accuracy of these CSF biomarkers in clinical practice.

Comparison of different MRI-based morphometric estimates for defining neurodegeneration across the Alzheimer's disease continuum

BACKGROUND

Several neurodegeneration (N) metrics using structural MRI are used for the purpose of Alzheimer's disease (AD)-related staging, including hippocampal volume, global atrophy, and an "AD signature" composite consisting of thickness or volumetric estimates derived from regions impacted early in AD. This study sought to determine if less user-intensive estimates of global atrophy and hippocampal volume were equivalent to a thickness-based AD signature from FreeSurfer for defining N across the AD continuum (i.e., individuals who are amyloid-positive (A+)).

METHODS

Cognitively unimpaired (CU) late middle-aged and older adults, as well as A+ mild cognitive impairment (MCI) and A+ AD dementia individuals, with available CSF and structural MRI scan <1.5 years apart, were selected for the study (n = 325, mean age = 62). First, in a subsample of A+ AD dementia and matched biomarker-negative (i.e., A- and tau tangle pathology (T)-) CU controls (n = 40), we examined ROC characteristics and identified N cut-offs using Youden's J for neurofilament light chain protein (NfL) and each of three MRI-based measures: a thickness-based AD signature from FreeSurfer, hippocampal volume (using FIRST), and a simple estimate of global atrophy (the ratio of intracranial CSF segmented volume to brain tissue volume, using SPM12). Based on the results from the ROC analyses, we then examined the concordance between NfL N positivity and N positivity for each MRI-based metric using Cohen's Kappa in the remaining subsample of 285 individuals. Finally, in the full sample (n = 325), we examined the relationship between the four measures of N and group membership across the AD continuum using Kruskal-Wallis tests and Cliff's deltas.

RESULTS

The three MRI-based metrics and CSF NfL similarly discriminated between the A-T- CU (n = 20) and A+ AD (n = 20) groups (AUCs ≥0.885; ps < 0.001). Using the cut-off values derived from the ROCs to define N positivity, there was weak concordance between NfL and all three MRI-derived metrics of N in the subsample of 285 individuals (Cohen's Kappas ≤0.429). Finally, the three MRI-based measures of N and CSF NfL showed similar associations with AD continuum group (i.e., Kruskal-Wallis ps < 0.001), with relatively larger effect sizes noted when comparing the A-T- CU to the A+ MCI (Cliff's deltas ≥0.741) and A+ AD groups (Cliff's deltas ≥0.810) than to the A+T- CU (Cliff's deltas = 0.112-0.298) and A + T+ CU groups (Cliff's deltas = 0.212-0.731).

CONCLUSIONS

These findings suggest that the three MRI-based morphometric estimates and CSF NfL similarly differentiate individuals across the AD continuum on N status. In many applications, a simple estimate of global atrophy may be preferred as an MRI marker of N across the AD continuum given its methodological robustness and ease of calculation when compared to hippocampal volume or a cortical thickness AD signature.

The Past and the Future of Alzheimer's Disease Fluid Biomarkers

Following the development of the first methods to measure the core Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers total-tau (T-tau), phosphorylated tau (P-tau) and the 42 amino acid form of amyloid-β (Aβ₄₂), there has been an enormous expansion of this scientific research area. Today, it is generally acknowledged that these biochemical tests reflect several central pathophysiological features of AD and contribute diagnostically relevant information, also for prodromal AD. In this article in the 20th anniversary issue of the Journal of Alzheimer’s Disease, we review the AD biomarkers, from early assay development to their entrance into diagnostic criteria. We also summarize the long journey of standardization and the development of assays on fully automated instruments, where we now have high precision and stable assays that will serve as the basis for common cut-off levels and a more general introduction of these diagnostic tests in clinical routine practice. We also discuss the latest expansion of the AD CSF biomarker toolbox that now also contains synaptic proteins such as neurogranin, which seemingly is specific for AD and predicts rate of future cognitive deterioration. Last, we are at the brink of having blood biomarkers that may be implemented as screening tools in the early clinical management of patients with cognitive problems and suspected AD. Whether this will become true, and whether it will be plasma Aβ₄₂, the Aβ_42/40 ratio, or neurofilament light, or a combination of these, remains to be established in future clinical neurochemical studies.

Modeling grey matter atrophy as a function of time, aging or cognitive decline show different anatomical patterns in Alzheimer's disease

Background

Grey matter (GM) atrophy in Alzheimer's disease (AD) is most commonly modeled as a function of time. However, this approach does not take into account inter-individual differences in initial disease severity or changes due to aging. Here, we modeled GM atrophy within individuals across the AD clinical spectrum as a function of time, aging and MMSE, as a proxy for disease severity, and investigated how these models influence estimates of GM atrophy.

Methods

We selected 523 individuals from ADNI (100 preclinical AD, 288 prodromal AD, 135 AD dementia) with abnormal baseline amyloid PET/CSF and ≥1 year of MRI follow-up. We calculated total and 90 regional GM volumes for 2281 MRI scans (median [IQR]; 4 [3–5] scans per individual over 2 [1.6–4] years) and used linear mixed models to investigate atrophy as a function of time, aging and decline on MMSE. Analyses included clinical stage as interaction with the predictor and were corrected for baseline age, sex, education, field strength and total intracranial volume. We repeated analyses for a sample of participants with normal amyloid (n = 387) to assess whether associations were specific for amyloid pathology.

Results

Using time or aging as predictors, amyloid abnormal participants annually declined −1.29 ± 0.08 points and − 0.28 ± 0.03 points respectively on the MMSE and −12.23 ± 0.47 cm³ and −8.87 ± 0.34 respectively in total GM volume (p < .001). For the time and age models atrophy was widespread and preclinical and prodromal AD showed similar atrophy patterns. Comparing prodromal AD to AD dementia, AD dementia showed faster atrophy mostly in temporal lobes as modeled with time, while prodromal AD showed faster atrophy in mostly frontoparietal areas as modeled with age (p_FDR < 0.05). Modeling change in GM volume as a function of decline on MMSE, slopes were less steep compared to those based on time and aging (−4.1 ± 0.25 cm³ per MMSE point decline; p < .001) and showed steeper atrophy for prodromal AD compared to preclinical AD in the right inferior temporal gyrus (p < .05) and compared to AD dementia mostly in temporal areas (p_FDR < 0.05). Associations with time, aging and MMSE remained when accounting for these effects in the other models, suggesting that all measures explain part of the variance in GM atrophy. Repeating analyses in amyloid normal individuals, effects for time and aging showed similar widespread anatomical patterns, while associations with MMSE were largely reduced.

Conclusion

Effects of time, aging and MMSE all explained variance in GM atrophy slopes within individuals. Associations with MMSE were weaker than those for time or age, but specific for amyloid pathology. This suggests that at least some of the atrophy observed in time or age models may not be specific to AD.

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Modeling atrophy as a function of time or aging show similar anatomical patterns.

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GM atrophy as a function of time or aging seems nonspecific for amyloid pathology.

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GM atrophy as a function of MMSE shows involvement of different anatomical patterns.

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Atrophy modeled based on time or age was steeper than modeled based on MMSE.

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Atrophy patterns based on MMSE were specific for amyloid pathology.

Fluid and PET biomarkers for amyloid pathology in Alzheimer's disease

Alzheimer's disease (AD) is characterized by amyloid plaques and tau pathology (neurofibrillary tangles and neuropil threads). Amyloid plaques are primarily composed of aggregated and oligomeric β-amyloid (Aβ) peptides ending at position 42 (Aβ42). The development of fluid and PET biomarkers for Alzheimer's disease (AD), has allowed for detection of Aβ pathology in vivo and marks a major advancement in understanding the role of Aβ in Alzheimer's disease (AD). In the recent National Institute on Aging and Alzheimer's Association (NIA-AA) Research Framework, AD is defined by the underlying pathology as measured in patients during life by biomarkers (Jack et al., 2018), while clinical symptoms are used for staging of the disease. Therefore, sensitive, specific and robust biomarkers to identify brain amyloidosis are central in AD research. Here, we discuss fluid and PET biomarkers for Aβ and their application.

Appropriate use criteria for lumbar puncture and cerebrospinal fluid testing in the diagnosis of Alzheimer's disease

INTRODUCTION

The Alzheimer's Association convened a multidisciplinary workgroup to develop appropriate use criteria to guide the safe and optimal use of the lumbar puncture procedure and cerebrospinal fluid (CSF) testing for Alzheimer's disease pathology detection in the diagnostic process.

METHODS

The workgroup, experienced in the ethical use of lumbar puncture and CSF analysis, developed key research questions to guide the systematic review of the evidence and developed clinical indications commonly encountered in clinical practice based on key patient groups in whom the use of lumbar puncture and CSF may be considered as part of the diagnostic process. Based on their expertise and interpretation of the evidence from systematic review, members rated each indication as appropriate or inappropriate.

RESULTS

The workgroup finalized 14 indications, rating 6 appropriate and 8 inappropriate.

DISCUSSION

In anticipation of the emergence of more reliable CSF analysis platforms, the manuscript offers important guidance to health-care practitioners and suggestions for implementation and future research.

Accurate risk estimation of β-amyloid positivity to identify prodromal Alzheimer's disease: Cross-validation study of practical algorithms

INTRODUCTION

The aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity.

METHODS

The algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ₄₂/Aβ₄₀, tau, and neurofilament light.

RESULTS

Aβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini-Mental State Examination, and APOE (area under the receiver operating characteristics curve = 0.81 [0.77-0.85] to 0.83 [0.79-0.87]). When validated, the models performed almost identical in Alzheimer's Disease Neuroimaging Initiative (area under the receiver operating characteristics curve = 0.80-0.82) and within different age, subjective cognitive decline, and mild cognitive impairment populations. Plasma Aβ₄₂/Aβ₄₀ improved the models slightly.

DISCUSSION

The algorithms are implemented on http://amyloidrisk.com where the individual probability of being Aβ positive can be calculated. This is useful in the workup of prodromal Alzheimer's disease and can reduce the number needed to screen in Alzheimer's disease trials.

Quantitative Systems Pharmacology Model for Alzheimer Disease Indicates Targeting Sphingolipid Dysregulation as Potential Treatment Option

Alzheimer disease (AD) is a devastating neurodegenerative disorder with high unmet medical need. Drug development is hampered by limited understanding of the disease and its driving factors. Quantitative Systems Pharmacology (QSP) modeling provides a comprehensive quantitative framework to evaluate the relevance of biological mechanisms in the context of disease and to predict the efficacy of novel treatments. Here, we report a QSP model for AD with a particular focus on investigating the relevance of dysregulation of cholesterol and sphingolipids. We show that our model captures the modulation of several biomarkers in subjects with AD, as well as the response to pharmacological interventions. We evaluate the impact of targeting the sphingosine-1-phosphate 5 receptor (S1PR5) as a potential novel treatment option for AD, and model predictions increase our confidence in this novel disease pathway. Future applications for the QSP model are in validation of further targets and identification of potential treatment response biomarkers.

Data driven diagnostic classification in Alzheimer's disease based on different reference regions for normalization of PiB-PET images and correlation with CSF concentrations of Aβ species

Positron emission tomography (PET) neuroimaging with the Pittsburgh Compound_B (PiB) is widely used to assess amyloid plaque burden. Standard quantification approaches normalize PiB-PET by mean cerebellar gray matter uptake. Previous studies suggested similar pons and white-matter uptake in Alzheimer's disease (AD) and healthy controls (HC), but lack exhaustive comparison of normalization across the three regions, with data-driven diagnostic classification.

We aimed to compare the impact of distinct reference regions in normalization, measured by data-driven statistical analysis, and correlation with cerebrospinal fluid (CSF) amyloid β (Aβ) species concentrations.

243 individuals with clinical diagnosis of AD, HC, mild cognitive impairment (MCI) and other dementias, from the Biomarkers for Alzheimer's/Parkinson's Disease (BIOMARKAPD) initiative were included. PiB-PET images and CSF concentrations of Aβ₃₈, Aβ₄₀ and Aβ₄₂ were submitted to classification using support vector machines. Voxel-wise group differences and correlations between normalized PiB-PET images and CSF Aβ concentrations were calculated.

Normalization by cerebellar gray matter and pons yielded identical classification accuracy of AD (accuracy-96%, sensitivity-96%, specificity-95%), and significantly higher than Aβ concentrations (best accuracy 91%). Normalization by the white-matter showed decreased extent of statistically significant multivoxel patterns and was the only method not outperforming CSF biomarkers, suggesting statistical inferiority. Aβ₃₈ and Aβ₄₀ correlated negatively with PiB-PET images normalized by the white-matter, corroborating previous observations of correlations with non-AD-specific subcortical changes in white-matter. In general, when using the pons as reference region, higher voxel-wise group differences and stronger correlation with Aβ₄₂, the Aβ₄₂/Aβ₄₀ or Aβ₄₂/Aβ₃₈ ratios were found compared to normalization based on cerebellar gray matter.

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Direct multivariate comparison of distinct reference regions in normalization of PET amyloid markers

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Using the pons as ROI, higher voxel-wise group differences emerge

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Using the pons as ROIs stronger correlation with Aβ₄₂, the Aβ₄₂/Aβ₄₀ or Aβ₄₂/Aβ₃₈ ratios were found.

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Evidence for statistical inferiority of CSF biomarkers

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Aβ₃₈ and Aβ₄₀ correlated negatively with PiB-PET white-matter normalized images.

New PET markers for the diagnosis of dementia

PURPOSE OF REVIEW

To present the new PET markers that could become in the coming years, relevant to advanced clinical approaches to dementia diagnosis, drug trials, and treatment strategies and discuss their advantages and limitations.

RECENT FINDINGS

The most advanced new PET tracers are the markers of the amyloid plaques, the τ compounds and the tracers of the translocator protein as markers of neuroinflammation. The main advantages but also the weaknesses of each of these markers are discussed. The main pitfall remains the heterogeneity of the available results that cast doubt to a rapid introduction of these new ligands in clinical practice.

SUMMARY

With the advent of biomarkers in clinical management and findings of molecular neuroimaging studies in the evaluation of patients with suspected dementia, the impact of functional neuroimaging has increased considerably these last years and has been integrated into many clinical guidelines in the field of dementia. In addition to conventional single PET brain perfusion and dopaminergic neurotransmission, 18F-fluorodeoxyglucose (18F-FDG) PET is used in advanced diagnosis procedures. Furthermore, new tracers are being developed to quantify key neuropathological features in the brain tissue as highly specific diagnosis is crucial to comply with the global medical and public health objectives in this domain. A strategic road map for further developments, adapted from the approach to cancer biomarkers, should be proposed so as to optimize the rationale of the PET-based molecular diagnosis of Alzheimer's disease and related disorders.

An Algorithm for Preclinical Diagnosis of Alzheimer's Disease

Almost all Alzheimer's disease (AD) therapeutic trials have failed in recent years. One of the main reasons for failure is due to designing the disease-modifying clinical trials at the advanced stage of the disease when irreversible brain damage has already occurred. Diagnosis of the preclinical stage of AD and therapeutic intervention at this phase, with a perfect target, are key points to slowing the progression of the disease. Various AD biomarkers hold enormous promise for identifying individuals with preclinical AD and predicting the development of AD dementia in the future, but no single AD biomarker has the capability to distinguish the AD preclinical stage. A combination of complimentary AD biomarkers in cerebrospinal fluid (Aβ₄₂, tau, and phosphor-tau), non-invasive neuroimaging, and genetic evidence of AD can detect preclinical AD in the in-vivo ante mortem brain. Neuroimaging studies have examined region-specific cerebral blood flow (CBF) and microstructural changes in the preclinical AD brain. Functional MRI (fMRI), diffusion tensor imaging (DTI) MRI, arterial spin labeling (ASL) MRI, and advanced PET have potential application in preclinical AD diagnosis. A well-validated simple framework for diagnosis of preclinical AD is urgently needed. This article proposes a comprehensive preclinical AD diagnostic algorithm based on neuroimaging, CSF biomarkers, and genetic markers.

Cerebrospinal fluid biomarkers measured by Elecsys assays compared to amyloid imaging

INTRODUCTION

Levels of amyloid β peptide 42 (Aβ42), total tau, and phosphorylated tau-181 are well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, but variability in manual plate-based assays has limited their use. We examined the relationship between CSF biomarkers, as measured by a novel automated immunoassay platform, and amyloid positron emission tomography.

METHODS

CSF samples from 200 individuals underwent separate analysis for Aβ42, total tau, and phosphorylated tau-181 with automated Roche Elecsys assays. Aβ40 was measured with a commercial plate-based assay. Positron emission tomography with Pittsburgh Compound B was performed less than 1 year from CSF collection.

RESULTS

Ratios of CSF biomarkers (total tau/Aβ42, phosphorylated tau-181/Aβ42, and Aβ42/Aβ40) best discriminated Pittsburgh Compound B-positive from Pittsburgh Compound B-negative individuals.

DISCUSSION

CSF biomarkers and amyloid positron emission tomography reflect different aspects of Alzheimer's disease brain pathology, and therefore, less-than-perfect correspondence is expected. Automated assays are likely to increase the utility of CSF biomarkers.

Clinical utility of amyloid PET imaging with (18)F-florbetapir: a retrospective study of 100 patients

BACKGROUND AND OBJECTIVE

Amyloid-positron emission tomography (PET) imaging (API) detects amyloid-beta pathology early in the course of Alzheimer's disease (AD) with high sensitivity and specificity. (18)F-florbetapir (Amyvid) is an amyloid-binding PET ligand with a half-life suitable for clinical use outside of the research setting. How API affects patient investigation and management in the 'real-world' arena is unknown. To address this, we retrospectively documented the effect of API in patients in the memory clinic.

METHODS

We reviewed the presenting clinical features, the pre-API and post-API investigations, diagnosis and outcomes for the first 100 patients who had API as part of their routine work-up at the Imperial Memory Centre, a tertiary referral clinic in the UK National Health Service.

RESULTS

API was primarily used to investigate patients with atypical clinical features (56 cases) or those that were young at onset (42 cases). MRI features of AD did not always predict positive API (67%), and 6 of 23 patients with MRIs reported as normal were amyloid-PET positive. There were significantly more cases categorised as non-AD dementia post-API (from 11 to 23). Patients investigated when API was initially available had fewer overall investigations and all patients had significantly fewer investigations in total post-API.

CONCLUSIONS

API has a clear impact on the investigation of young-onset or complex dementia while reducing the overall burden of investigations. It was most useful in younger patients, atypical presentations or individuals with multiple possible causes of cognitive impairment.