The implications of different approaches to define AT(N) in Alzheimer disease

A Computational Monte Carlo Simulation Strategy to Determine the Temporal Ordering of Abnormal Age Onset Among Biomarkers of Alzheimer's Disease

To quantitatively determining the temporal ordering of abnormal age onsets (AAO) among various biomarkers for Alzheimer's disease (AD), we introduced a computational Monte-Carlo simulation (CMCS) to statistically examine such ordering of an AAO pair or over all AAOs. The CMCS 1) simulates longitudinal data, estimates AAO for each iteration, and finally assesses the type-I error of an AAO pair or all AAO ordering. Using hippocampus volume (VHC), cerebral glucose hypometabolic convergence index (HCI), plasma neurofilament light (NfL), mini-mental state exam (MMSE), the auditory verbal learning test-long term memory (AVLT-LTM), short term memory (AVLT-STM) and clinical-dementia rating sum of box scale (CDR-SOB) from 382 mild cognitive impairment converters and non-converters, the CMCS estimated type-I error for the earlier AAO of VHC, AVLT_STM and AVLT_LTM each than MMSE was significant (p<0.002). The type-I error for the overall AAO temporal ordering of VHC ≤ AVLT_STM ≤ AVLT_LTM < HCI ≤ MMSE ≤ CDR-SOB ≤ NfL was p = 0.012. These findings showed that our CMCS is capable of providing statistical inferences for quantifying AAO ordering which has important implications in advancing our understanding of AD.

Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline

BACKGROUND AND OBJECTIVES

Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD).

METHODS

We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker.

RESULT

We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%-19%). N biomarkers were modestly to moderately correlated (range r -0.28 - 0.58). Serum NfL and GFAP correlated most strongly (r 0.58, p < 0.01). T-tau was strongly correlated with p-tau (r 0.89, p < 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11-2.09]; 1.51 [1.05-2.17]; 1.50 [1.04-2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β -0.17 to -0.11, p < 0.05), but only HV remained associated beyond Aβ and p-tau (β -0.13 [SE 0.04]; p < 0.05).

DISCUSSION

In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.

Biofluid Biomarkers of Alzheimer’s Disease: Progress, Problems, and Perspectives

Since the establishment of the biomarker-based A-T-N (Amyloid/Tau/Neurodegeneration) framework in Alzheimer’s disease (AD), the diagnosis of AD has become more precise, and cerebrospinal fluid tests and positron emission tomography examinations based on this framework have become widely accepted. However, the A-T-N framework does not encompass the whole spectrum of AD pathologies, and problems with invasiveness and high cost limit the application of the above diagnostic methods aimed at the central nervous system. Therefore, we suggest the addition of an “X” to the A-T-N framework and a focus on peripheral biomarkers in the diagnosis of AD. In this review, we retrospectively describe the recent progress in biomarkers based on the A-T-N-X framework, analyze the problems, and present our perspectives on the diagnosis of AD.

A Multi-Dimensional Comparison of Alzheimer's Disease Neurodegenerative Biomarkers

BACKGROUND

In the 2018 AT(N) framework, neurodegenerative (N) biomarkers plays an essential role in the research and staging of Alzheimer's disease (AD); however, the different choice of N may result in discordances.

OBJECTIVE

We aimed to compare different potential N biomarkers.

METHODS

We examined these N biomarkers among 1,238 participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) in their 1) diagnostic utility, 2) cross-sectional and longitudinal correlations between different N biomarkers and clinical variables, and 3) the conversion risk of different N profiles.

RESULTS

Six neurodegenerative biomarkers changed significantly from preclinical AD, through prodromal AD to AD dementia stage, thus they were chosen as the candidate N biomarkers: hippocampal volume (HV), 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET), cerebrospinal fluid (CSF), total tau (T-tau), plasma neurofilament light chain (NFL), CSF NFL, and CSF neurogranin (Ng). Results indicated that FDG-PET not only had the greatest diagnostic utility in differentiating AD from controls (area under the curve: FDG-PET, 0.922), but also had the strongest association with cognitive scores. Furthermore, FDG-PET positive group showed the fastest memory decline (hazard ratio: FDG-PET, 3.45), which was also true even in the presence of amyloid-β pathology. Moreover, we observed great discordances between three valuable N biomarkers (FDG-PET, HV, and T-tau).

CONCLUSION

These results underline the importance of using FDG-PET as N in terms of cognitive decline and AD conversion, followed by HV, and could be a great complement to the AT(N) framework.

The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics

Many drugs that target amyloid-β (Aβ) in Alzheimer disease (AD) have failed to demonstrate clinical efficacy. However, four anti-Aβ antibodies have been shown to mediate the removal of amyloid plaque from brains of patients with AD, and the FDA has recently granted accelerated approval to one of these, aducanumab, using reduction of amyloid plaque as a surrogate end point. The rationale for approval and the extent of the clinical benefit from these antibodies are under intense debate. With the aim of informing this debate, we review clinical trial data for drugs that target Aβ from the perspective of the temporal interplay between the two pathognomonic protein aggregates in AD - Aβ plaques and tau neurofibrillary tangles - and their relationship to cognitive impairment, highlighting differences in drug properties that could affect their clinical performance. On this basis, we propose that Aβ pathology drives tau pathology, that amyloid plaque would need to be reduced to a low level (~20 centiloids) to reveal significant clinical benefit and that there will be a lag between the removal of amyloid and the potential to observe a clinical benefit. We conclude that the speed of amyloid removal from the brain by a potential therapy will be important in demonstrating clinical benefit in the context of a clinical trial.

Detecting amyloid positivity in early Alzheimer's disease using combinations of plasma Aβ42/Aβ40 and p-tau

INTRODUCTION

We studied usefulness of combining blood amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p-tau)217, and neurofilament light (NfL) to detect abnormal brain Aβ deposition in different stages of early Alzheimer's disease (AD).

METHODS

Plasma biomarkers were measured using mass spectrometry (Aβ42/Aβ40) and immunoassays (p-tau217 and NfL) in cognitively unimpaired individuals (CU, N = 591) and patients with mild cognitive impairment (MCI, N = 304) from two independent cohorts (BioFINDER-1, BioFINDER-2).

RESULTS

In CU, a combination of plasma Aβ42/Aβ40 and p-tau217 detected abnormal brain Aβ status with area under the curve (AUC) of 0.83 to 0.86. In MCI, the models including p-tau217 alone or Aβ42/Aβ40 and p-tau217 had similar AUCs (0.86-0.88); however, the latter showed improved model fit. The models were implemented in an online application providing individualized risk assessments (https://brainapps.shinyapps.io/PredictABplasma/).

DISCUSSION

A combination of plasma Aβ42/Aβ40 and p-tau217 discriminated Aβ status with relatively high accuracy, whereas p-tau217 showed strongest associations with Aβ pathology in MCI but not in CU.

Unravelling the Association Between Amyloid-PET and Cerebrospinal Fluid Biomarkers in the Alzheimer's Disease Spectrum: Who Really Deserves an A+?

BACKGROUND

Association between cerebrospinal fluid (CSF)-amyloid-β (Aβ)42 and amyloid-PET measures is inconstant across the Alzheimer's disease (AD) spectrum. However, they are considered interchangeable, along with Aβ 42/40 ratio, for defining 'Alzheimer's Disease pathologic change' (A+).

OBJECTIVE

Herein, we further characterized the association between amyloid-PET and CSF biomarkers and tested their agreement in a cohort of AD spectrum patients.

METHODS

We include ed 23 patients who underwent amyloid-PET, MRI, and CSF analysis showing reduced levels of Aβ 42 within a 365-days interval. Thresholds used for dichotomization were: Aβ 42 <  640 pg/mL (Aβ 42+); pTau >  61 pg/mL (pTau+); and Aβ 42/40 <  0.069 (ADratio+). Amyloid-PET scans were visually assessed and processed by four pipelines (SPMCL, SPMAAL, FSGM, FSWC).

RESULTS

Different pipelines gave highly inter-correlated standardized uptake value ratios (SUVRs) (rho = 0.93-0.99). The most significant findings were: pTau positive correlation with SPMCL SUVR (rho = 0.56, p = 0.0063) and Aβ 42/40 negative correlation with SPMCL and SPMAAL SUVRs (rho = -0.56, p = 0.0058; rho = -0.52, p = 0.0117 respectively). No correlations between CSF-Aβ 42 and global SUVRs were observed. In subregion analysis, both pTau and Aβ 42/40 values significantly correlated with cingulate SUVRs from any pipeline (R2 = 0.55-0.59, p <  0.0083), with the strongest associations observed for the posterior/isthmus cingulate areas. However, only associations observed for Aβ 42/40 ratio were still significant in linear regression models. Moreover, combining pTau with Aβ 42 or using Aβ 42/40, instead of Aβ 42 alone, increased concordance with amyloid-PET status from 74% to 91% based on visual reads and from 78% to 96% based on Centiloids.

CONCLUSION

We confirmed that, in the AD spectrum, amyloid-PET measures show a stronger association and a better agreement with CSF-Aβ 42/40 and secondarily pTau rather than Aβ 42 levels.

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

INTRODUCTION

The prognosis of patients at the pre-dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker-based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population.

METHODS

Disease-progression modeling of longitudinal cognitive scores of pre-dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative.

RESULTS

Of nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model-based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut-offs, inclusion criteria based on biomarker-profile cut-offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns.

DISCUSSION

The biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web-based application for prediction of patients' future cognitive progression is available online.

Is comprehensiveness critical? Comparing short and long format cognitive assessments in preclinical Alzheimer disease

BACKGROUND

Comprehensive testing of cognitive functioning is standard practice in studies of Alzheimer disease (AD). Short-form tests like the Montreal Cognitive Assessment (MoCA) use a "sampling" of measures, administering key items in a shortened format to efficiently assess cognition while reducing time requirements, participant burden, and administrative costs. We compared the MoCA to a commonly used long-form cognitive battery in predicting AD symptom onset and sensitivity to AD neuroimaging biomarkers.

METHODS

Survival, area under the receiver operating characteristic (ROC) curve (AUC), and multiple regression analyses compared the MoCA and long-form measures in predicting time to symptom onset in cognitively normal older adults (n = 6230) from the National Alzheimer's Coordinating Center (NACC) cohort who had, on average, 2.3 ± 1.2 annual assessments. Multiple regression models in a separate sample (n = 416) from the Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) compared the sensitivity of the MoCA and long-form measures to neuroimaging biomarkers including amyloid PET, tau PET, and cortical thickness.

RESULTS

Hazard ratios suggested that both the MoCA and the long-form measures are similarly and modestly efficacious in predicting symptomatic conversion, although model comparison analyses indicated that the long-form measures slightly outperformed the MoCA (HRs > 1.57). AUC analyses indicated no difference between the measures in predicting conversion (DeLong's test, Z = 1.48, p = 0.13). Sensitivity to AD neuroimaging biomarkers was similar for the two measures though there were only modest associations with tau PET (rs = - 0.13, ps < 0.02) and cortical thickness in cognitively normal participants (rs = 0.15-0.16, ps < 0.007).

CONCLUSIONS

Both test formats showed weak associations with symptom onset, AUC analyses indicated low diagnostic accuracy, and biomarker correlations were modest in cognitively normal participants. Alternative assessment approaches are needed to improve how clinicians and researchers monitor cognitive changes and disease progression prior to symptom onset.

Developing the ATX(N) classification for use across the Alzheimer disease continuum

Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.

The human connectome in Alzheimer disease - relationship to biomarkers and genetics

The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.

Taking the A Train? Limited Consistency of Aβ42 and the Aβ42/40 Ratio in the AT(N) Classification

The consistency of cerebrospinal fluid amyloid-β (Aβ)42/40 ratio and Aβ 42 has not been assessed in the AT(N) classification system. We analyzed the classification changes of the dichotomized amyloid status (A+/A-) in 363 patients tested for Alzheimer's disease biomarkers after Aβ 42 was superseded by the Aβ 42/40 ratio. The consistency of Aβ 42 and the Aβ 42/40 ratio was very low. Notably, the proportions of "false" A+T-patients were considerable (74-91%) and corresponded mostly to patients not clinically diagnosed with Alzheimer's disease. Our results suggest that the interchangeability of Aβ 42/40 ratio and Aβ 42 is limited for classifying patients in clinical setting using the AT(N) scheme.

Optimal Combinations of AT(N) Biomarkers to Determine Longitudinal Cognition in the Alzheimer's Disease

Background: National Institute on Aging-Alzheimer's Association (NIA-AA) proposed the AT(N) system based on β-amyloid deposition, pathologic tau, and neurodegeneration, which considered the definition of Alzheimer's disease (AD) as a biological construct. However, the associations between different AT(N) combinations and cognitive progression have been poorly explored systematically. The aim of this study is to compare different AT(N) combinations using recognized biomarkers within the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Methods: A total of 341 participants were classified into cognitively unimpaired (CU; n = 200) and cognitively impaired (CI; n = 141) groups according to the clinical manifestations and neuropsychological tests. Cerebrospinal fluid (CSF) Aβ42 and amyloid-PET ([18F]flutemetamol) were used as biomarkers for A; CSF phosphorylated tau (p-tau) and tau-PET ([18F]flortaucipir) were used as biomarkers for T; CSF total tau (t-tau), hippocampal volume, temporal cortical thickness, [18F]fluorodeoxyglucose (FDG) PET, and plasma neurofilament light (NfL) were used as biomarkers for (N). Binary biomarkers were obtained from the Youden index and publicly available cutoffs. Prevalence of AT(N) categories was compared between different biomarkers within the group using related independent sample non-parametric test. The relationship between AT(N) combinations and 12-year longitudinal cognition was assessed using linear mixed-effects modeling. Results: Among the CU participants, A-T-(N)- was most common. More T+ were detected using p-tau than tau PET (p < 0.05), and more (N)+ were observed using fluid biomarkers (p < 0.001). A+T+(N)+ was more common in the CI group. Tau PET combined with cortical thickness best predicted cognitive changes in the CI group and MRI predicted changes in the CU group. Conclusions: These findings suggest that optimal AT(N) combinations to determine longitudinal cognition differ by cognitive status. Different biomarkers within a specific component for defining AT(N) cannot be used identically. Furthermore, different strategies for discontinuous biomarkers will be an important area for future studies.

Tau PET correlates with different Alzheimer's disease-related features compared to CSF and plasma p-tau biomarkers

PET, CSF and plasma biomarkers of tau pathology may be differentially associated with Alzheimer's disease (AD)‐related demographic, cognitive, genetic and neuroimaging markers. We examined 771 participants with normal cognition, mild cognitive impairment or dementia from BioFINDER‐2 (n = 400) and ADNI (n = 371). All had tau‐PET ([¹⁸F]RO948 in BioFINDER‐2, [¹⁸F]flortaucipir in ADNI) and CSF p‐tau181 biomarkers available. Plasma p‐tau181 and plasma/CSF p‐tau217 were available in BioFINDER‐2 only. Concordance between PET, CSF and plasma tau biomarkers ranged between 66 and 95%. Across the whole group, ridge regression models showed that increased CSF and plasma p‐tau181 and p‐tau217 levels were independently of tau PET associated with higher age, and APOEɛ4‐carriership and Aβ‐positivity, while increased tau‐PET signal in the temporal cortex was associated with worse cognitive performance and reduced cortical thickness. We conclude that biofluid and neuroimaging markers of tau pathology convey partly independent information, with CSF and plasma p‐tau181 and p‐tau217 levels being more tightly linked with early markers of AD (especially Aβ‐pathology), while tau‐PET shows the strongest associations with cognitive and neurodegenerative markers of disease progression.

Application of the ATN classification scheme in a population without dementia: Findings from the EPAD cohort

BACKGROUND

We classified non-demented European Prevention of Alzheimer's Dementia (EPAD) participants through the amyloid/tau/neurodegeneration (ATN) scheme and assessed their neuropsychological and imaging profiles.

MATERIALS AND METHODS

From 1500 EPAD participants, 312 were excluded. Cerebrospinal fluid cut-offs of 1000 pg/mL for amyloid beta (Aß)1-42 and 27 pg/mL for p-tau181 were validated using Gaussian mixture models. Given strong correlation of p-tau and t-tau (R2  = 0.98, P < 0.001), neurodegeneration was defined by age-adjusted hippocampal volume. Multinomial regressions were used to test whether neuropsychological tests and regional brain volumes could distinguish ATN stages.

RESULTS

Age was 65 ± 7 years, with 58% females and 38% apolipoprotein E (APOE) ε4 carriers; 57.1% were A-T-N-, 32.5% were in the Alzheimer's disease (AD) continuum, and 10.4% suspected non-Alzheimer's pathology. Age and cerebrovascular burden progressed with biomarker positivity (P < 0.001). Cognitive dysfunction appeared with T+. Paradoxically higher regional gray matter volumes were observed in A+T-N- compared to A-T-N- (P < 0.001).

DISCUSSION

In non-demented individuals along the AD continuum, p-tau drives cognitive dysfunction. Memory and language domains are affected in the earliest stages.

Prediction of future Alzheimer's disease dementia using plasma phospho-tau combined with other accessible measures

A combination of plasma phospho-tau (P-tau) and other accessible biomarkers might provide accurate prediction about the risk of developing Alzheimer's disease (AD) dementia. We examined this in participants with subjective cognitive decline and mild cognitive impairment from the BioFINDER (n = 340) and Alzheimer's Disease Neuroimaging Initiative (ADNI) (n = 543) studies. Plasma P-tau, plasma Aβ42/Aβ40, plasma neurofilament light, APOE genotype, brief cognitive tests and an AD-specific magnetic resonance imaging measure were examined using progression to AD as outcome. Within 4 years, plasma P-tau217 predicted AD accurately (area under the curve (AUC) = 0.83) in BioFINDER. Combining plasma P-tau217, memory, executive function and APOE produced higher accuracy (AUC = 0.91, P < 0.001). In ADNI, this model had similar AUC (0.90) using plasma P-tau181 instead of P-tau217. The model was implemented online for prediction of the individual probability of progressing to AD. Within 2 and 6 years, similar models had AUCs of 0.90-0.91 in both cohorts. Using cerebrospinal fluid P-tau, Aβ42/Aβ40 and neurofilament light instead of plasma biomarkers did not improve the accuracy significantly. The clinical predictions by memory clinic physicians had significantly lower accuracy (4-year AUC = 0.71). In summary, plasma P-tau, in combination with brief cognitive tests and APOE genotyping, might greatly improve the diagnostic prediction of AD and facilitate recruitment for AD trials.

ADAMANT: a placebo-controlled randomized phase 2 study of AADvac1, an active immunotherapy against pathological tau in Alzheimer's disease

Alzheimer's disease (AD) pathology is partly characterized by accumulation of aberrant forms of tau protein. Here we report the results of ADAMANT, a 24-month double-blinded, parallel-arm, randomized phase 2 multicenter placebo-controlled trial of AADvac1, an active peptide vaccine designed to target pathological tau in AD (EudraCT 2015-000630-30). Eleven doses of AADvac1 were administered to patients with mild AD dementia at 40 μg per dose over the course of the trial. The primary objective was to evaluate the safety and tolerability of long-term AADvac1 treatment. The secondary objectives were to evaluate immunogenicity and efficacy of AADvac1 treatment in slowing cognitive and functional decline. A total of 196 patients were randomized 3:2 between AADvac1 and placebo. AADvac1 was safe and well tolerated (AADvac1 n = 117, placebo n = 79; serious adverse events observed in 17.1% of AADvac1-treated individuals and 24.1% of placebo-treated individuals; adverse events observed in 84.6% of AADvac1-treated individuals and 81.0% of placebo-treated individuals). The vaccine induced high levels of IgG antibodies. No significant effects were found in cognitive and functional tests on the whole study sample (Clinical Dementia Rating-Sum of the Boxes scale adjusted mean point difference -0.360 (95% CI -1.306, 0.589)), custom cognitive battery adjusted mean z-score difference of 0.0008 (95% CI -0.169, 0.172). We also present results from exploratory and post hoc analyses looking at relevant biomarkers and clinical outcomes in specific subgroups. Our results show that AADvac1 is safe and immunogenic, but larger stratified studies are needed to better evaluate its potential clinical efficacy and impact on disease biomarkers.

Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group

In 2018, the US National Institute on Aging and the Alzheimer's Association proposed a purely biological definition of Alzheimer's disease that relies on biomarkers. Although the intended use of this framework was for research purposes, it has engendered debate and challenges regarding its use in everyday clinical practice. For instance, cognitively unimpaired individuals can have biomarker evidence of both amyloid β and tau pathology but will often not develop clinical manifestations in their lifetime. Furthermore, a positive Alzheimer's disease pattern of biomarkers can be observed in other brain diseases in which Alzheimer's disease pathology is present as a comorbidity. In this Personal View, the International Working Group presents what we consider to be the current limitations of biomarkers in the diagnosis of Alzheimer's disease and, on the basis of this evidence, we propose recommendations for how biomarkers should and should not be used for diagnosing Alzheimer's disease in a clinical setting. We recommend that Alzheimer's disease diagnosis be restricted to people who have positive biomarkers together with specific Alzheimer's disease phenotypes, whereas biomarker-positive cognitively unimpaired individuals should be considered only at-risk for progression to Alzheimer's disease.

Characterization of Alzheimer's tau biomarker discordance using plasma, CSF, and PET

BACKGROUND

We aimed to investigate the tau biomarker discrepancies of Alzheimer's disease (AD) using plasma tau phosphorylated at threonine 181 (p-tau181), cerebrospinal fluid (CSF) p-tau181, and AV1451 positron emission tomography (PET).

METHODS

In the Alzheimer's Disease Neuroimaging Initiative, 724 non-demented participants were categorized into plasma/CSF and plasma/PET groups. Demographic and clinical variables, amyloid-β (Aβ) burden, flortaucipir-PET binding in Braak regions of interest (ROIs), longitudinal changes in clinical outcomes, and conversion risk were compared.

RESULTS

Across different tau biomarker groups, the proportion of participants with a discordant profile varied (plasma+/CSF- 15.6%, plasma-/CSF+ 15.3%, plasma+/PET- 22.4%, and plasma-/PET+ 6.1%). Within the plasma/CSF categories, we found an increase from concordant-negative to discordant to concordant-positive in the frequency of Aβ pathology or cognitive impairment, rates of cognitive decline, and risk of cognitive conversion. However, the two discordant categories (plasma+/CSF- and plasma-/CSF+) showed comparable performances, resulting in similarly reduced cognitive capacities. Regarding plasma/PET categories, as expected, PET-positive individuals had increased Aβ burden, elevated flortaucipir retention in Braak ROIs, and accelerated cognitive deterioration than concordant-negative persons. Noteworthy, discordant participants with normal PET exhibited reduced flortaucipir uptake in Braak stage ROIs and slower rates of cognitive decline, relative to those PET-positive. Therefore, individuals with PET abnormality appeared to have advanced tau pathological changes and poorer cognitive function, regardless of the plasma status. Furthermore, these results were found only in individuals with Aβ pathology.

CONCLUSIONS

Our results indicate that plasma and CSF p-tau181 abnormalities associated with amyloidosis occur simultaneously in the progression of AD pathogenesis and related cognitive decline, before tau-PET turns positive.

Cerebral amyloid-β load is associated with neurodegeneration and gliosis: Mediation by p-tau and interactions with risk factors early in the Alzheimer's continuum

INTRODUCTION

The association between cerebral amyloid-β accumulation and downstream CSF biomarkers is not fully understood, particularly in asymptomatic stages.

METHODS

In 318 cognitively unimpaired participants, we assessed the association between amyloid-β PET (Centiloid), and cerebrospinal fluid (CSF) biomarkers of several pathophysiological pathways. Interactions by Alzheimer's disease risk factors (age, sex and APOE-ε4), and the mediation effect of tau and neurodegeneration were also investigated.

RESULTS

Centiloids were positively associated with CSF biomarkers of tau pathology (p-tau), neurodegeneration (t-tau, NfL), synaptic dysfunction (neurogranin) and neuroinflammation (YKL-40, GFAP, sTREM2), presenting interactions with age (p-tau, t-tau, neurogranin) and sex (sTREM2, NfL). Most of these associations were mediated by p-tau, except for NfL. The interaction between sex and amyloid-β on sTREM2 and NfL was also tau-independent.

DISCUSSION

Early amyloid-β accumulation has a tau-independent effect on neurodegeneration and a tau-dependent effect on neuroinflammation. Besides, sex has a modifier effect on these associations independent of tau.

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect-especially with a clear relationship to dose-can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to "de-risk" the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer's disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease

Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.

Current advances in plasma and cerebrospinal fluid biomarkers in Alzheimer's disease

PURPOSE OF REVIEW

This review provides a concise overview of recent advances in cerebrospinal fluid (CSF) and blood-based biomarkers of Alzheimer's disease lesions.

RECENT FINDINGS

Important recent advances for CSF Alzheimer's disease biomarkers include the introduction of fully automated assays, the development and implementation of certified reference materials for CSF Aβ42 and a unified protocol for handling of samples, which all support reliability and availability of CSF Alzheimer's disease biomarkers. Aβ deposition can be detected using Aβ42/Aβ40 ratio in both CSF and plasma, though a much more modest change is seen in plasma. Tau aggregation can be detected using phosphorylated tau (P-tau) at threonine 181 and 217 in CSF, with similar accuracy in plasma. Neurofilament light (NfL) be measured in CSF and shows similar diagnostic accuracy in plasma. Though total tau (T-tau) can also be measured in plasma, this measure is of limited clinical relevance for Alzheimer's disease in its current immunoassay format.

SUMMARY

Alzheimer's disease biomarkers, including Aβ, P-tau and NfL can now be reliably measured in both CSF and blood. Plasma-based measures of P-tau show particular promise, with potential applications in both clinical practice and in clinical trials.

Adding cognition to AT(N) models improves prediction of cognitive and functional decline

INTRODUCTION

This study sought to determine whether adding cognition to a model with Alzheimer's disease biomarkers based on the amyloid, tau, and neurodegeneration/neuronal injury-AT(N)-biomarker framework predicts rates of cognitive and functional decline in older adults without dementia.

METHODS

The study included 465 participants who completed amyloid positron emission tomography, cerebrospinal fluid phosphorylated tau, structural magnetic resonance imaging, and serial neuropsychological testing. Using the AT(N) framework and a newly validated cognitive metric as the independent variables, we used linear mixed effects models to examine a 4-year rate of change in cognitive and functional measures.

RESULTS

The inclusion of baseline cognitive status improved model fit in predicting rate of decline in outcomes above and beyond biomarker variables. Specifically, those with worse cognitive functioning at baseline had faster rates of memory and functional decline over a 4-year period, even when accounting for AT(N).

DISCUSSION

Including a newly validated measure of baseline cognition may improve clinical prognosis in non-demented older adults beyond the use of AT(N) biomarkers alone.

Replication study of plasma proteins relating to Alzheimer's pathology

INTRODUCTION

This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis.

METHODS

Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively.

RESULTS

Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis.

DISCUSSION

Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Frequency of Biologically Defined Alzheimer Disease in Relation to Age, Sex, APOE ε4, and Cognitive Impairment

OBJECTIVE

To assess the frequency of biologically defined Alzheimer disease (AD) in relation to age, sex, APOE ε4, and clinical diagnosis in a prospective cohort study evaluated with amyloid-PET and tau-PET.

METHODS

We assessed cognitively unimpaired (CU) elderly (n = 166), patients with amnestic mild cognitive impairment (n = 77), and patients with probable AD dementia (n = 62) who underwent evaluation by dementia specialists and neuropsychologists in addition to amyloid-PET with [18F]AZD4694 and tau-PET with [18F]MK6240. Individuals were grouped according to their AD biomarker profile. Positive predictive value for biologically defined AD was assessed in relation to clinical diagnosis. Frequency of AD biomarker profiles was assessed using logistic regressions with odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

The clinical diagnosis of probable AD dementia demonstrated good agreement with biologically defined AD (positive predictive value 85.2%). A total of 7.88% of CU were positive for both amyloid-PET and tau-PET. Frequency of biologically defined AD increased with age (OR 1.14; p < 0.0001) and frequency of APOE ε4 allele carriers (single ε4: OR 3.82; p < 0.0001; double ε4: OR 17.55, p < 0.0001).

CONCLUSION

Whereas we observed strong, but not complete, agreement between clinically defined probable AD dementia and biomarker positivity for both β-amyloid and tau, we also observed that biologically defined AD was not rare in CU elderly. Abnormal tau-PET was almost exclusively observed in individuals with abnormal amyloid-PET. Our results highlight that even in tertiary care memory clinics, detailed evaluation by dementia specialists systematically underestimates the frequency of biologically defined AD and related entities.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that biologically defined AD (abnormal amyloid PET and tau PET) was observed in 85.2% of people with clinically defined AD and 7.88% of CU elderly.

Comparing ATN-T designation by tau PET visual reads, tau PET quantification, and CSF PTau181 across three cohorts

PURPOSE

To compare rates of tau biomarker positivity (T-status) per the 2018 Alzheimer's Disease (AD) Research Framework derived from [¹⁸F]flortaucipir (FTP) PET visual assessment, FTP quantification, and cerebrospinal fluid (CSF) phosphorylated Tau-181 (PTau181).

METHODS

We included 351 subjects with varying clinical diagnoses from three cohorts with available FTP PET and CSF PTau181 within 18 months. T-status was derived from (1) FTP visual assessment by two blinded raters; (2) FTP standardized uptake value ratio (SUVR) quantification from a temporal meta-ROI (threshold: SUVR ≥1.27); and (3) Elecsys® Phospho-Tau (181P) CSF (Roche Diagnostics) concentrations (threshold: PTau181 ≥ 24.5 pg/mL).

RESULTS

FTP visual reads yielded the highest rates of T+, while T+ by SUVR increased progressively from cognitively normal (CN) through mild cognitive impairment (MCI) and AD dementia. T+ designation by CSF PTau181 was intermediate between FTP visual reads and SUVR values in CN, similar to SUVR in MCI, and lower in AD dementia. Concordance in T-status between modality pairs ranged from 68 to 76% and varied by clinical diagnosis, being highest in patients with AD dementia. In discriminating Aβ + MCI and AD subjects from healthy controls and non-AD participants, FTP visual assessment was most sensitive (0.96) but least specific (0.60). Specificity was highest with FTP SUVR (0.91) with sensitivity of 0.89. Sensitivity (0.73) and specificity (0.72) were balanced for PTau181.

CONCLUSION

The choice of tau biomarker may differ by disease stage and research goals that seek to maximize sensitivity or specificity. Visual interpretations of tau PET enhance sensitivity compared to quantification alone, particularly in early disease stages.

Alzheimer's disease profiled by fluid and imaging markers: tau PET best predicts cognitive decline

For early detection of Alzheimer's disease, it is important to find biomarkers with predictive value for disease progression and clinical manifestations, such as cognitive decline. Individuals can now be profiled based on their biomarker status for Aβ42 (A) or tau (T) deposition and neurodegeneration (N). The aim of this study was to compare the cerebrospinal fluid (CSF) and imaging (PET/MR) biomarkers in each ATN category and to assess their ability to predict longitudinal cognitive decline. A subset of 282 patients, who had had at the same time PET investigations with amyloid-β and tau tracers, CSF sampling, and structural MRI (18% within 13 months), was selected from the ADNI dataset. The participants were grouped by clinical diagnosis at that time: cognitively normal, subjective memory concern, early or late mild cognitive impairment, or AD. Agreement between CSF (amyloid-β-1-42(A), phosphorylated-Tau181(T), total-Tau(N)), and imaging (amyloid-β PET (florbetaben and florbetapir)(A), tau PET (flortaucipir)(T), hippocampal volume (MRI)(N)) positivity in ATN was assessed with Cohen's Kappa. Linear mixed-effects models were used to predict decline in the episodic memory. There was moderate agreement between PET and CSF for A biomarkers (Kappa = 0.39-0.71), while only fair agreement for T biomarkers (Kappa ≤ 0.40, except AD) and discordance for N biomarkers across all groups (Kappa ≤ 0.14) was found. Baseline PET tau predicted longitudinal decline in episodic memory irrespective of CSF p-Tau181 positivity (p ≤ 0.02). Baseline PET tau and amyloid-β predicted decline in episodic memory (p ≤ 0.0001), but isolated PET amyloid-β did not. Isolated PET Tau positivity was only observed in 2 participants (0.71% of the sample). While results for amyloid-β were similar using CSF or imaging, CSF and imaging results for tau and neurodegeneration were not interchangeable. PET tau positivity was superior to CSF p-Tau181 and PET amyloid-β in predicting cognitive decline in the AD continuum within 3 years of follow-up.

ATN incorporating cerebrospinal fluid neurofilament light chain detects frontotemporal lobar degeneration

INTRODUCTION

The ATN framework provides an in vivo diagnosis of Alzheimer's disease (AD) using cerebrospinal fluid (CSF) biomarkers of pathologic amyloid plaques (A), tangles (T), and neurodegeneration (N). ATN is rarely evaluated in pathologically confirmed patients and its poor sensitivity to suspected non-Alzheimer's pathophysiologies (SNAP), including frontotemporal lobar degeneration (FTLD), leads to misdiagnoses. We compared accuracy of ATN (ATN_TAU ) using CSF total tau (t-tau) to a modified strategy (ATN_NfL ) using CSF neurofilament light chain (NfL) in an autopsy cohort.

METHODS

ATN_TAU and ATN_NfL were trained in an independent sample and validated in autopsy-confirmed AD (n = 67) and FTLD (n = 27).

RESULTS

ATN_NfL more accurately identified FTLD as SNAP (sensitivity = 0.93, specificity = 0.94) than ATN_TAU (sensitivity = 0.44, specificity = 0.97), even in cases with co-occurring AD and FTLD. ATN_NfL misclassified fewer AD and FTLD as "Normal" (2%) than ATN_TAU (14%).

DISCUSSION

ATN_NfL is a promising diagnostic strategy that may accurately identify both AD and FTLD, even when pathologies co-occur.

Discordant Alzheimer's neurodegenerative biomarkers and their clinical outcomes

OBJECTIVE

In the 2018 ATN framework, Alzheimer's neurodegenerative biomarkers comprised cerebrospinal fluid (CSF) total tau, 18 F-fluorodeoxyglucose-positron emission tomography, and brain atrophy. We aimed to assess the clinical outcomes of having discordant Alzheimer's neurodegenerative biomarkers.

METHODS

A total of 721 non-demented individuals from the Alzheimer's Disease Neuroimaging Initiative database were included and then further categorized into concordant-negative, discordant, and concordant-positive groups. Demographic distributions of the groups were compared. Longitudinal changes in clinical outcomes and risk of conversion were assessed using linear mixed-effects models and multivariate Cox proportional hazard models, respectively.

RESULTS

Discordant group was intermediate to concordant-negative and concordant-positive groups in terms of APOE ε4 positivity, CSF amyloid-beta, and phosphorylated tau. Compared with concordant-negative group, discordant group deteriorated faster in cognitive scores (Mini-Mental State Examination, the Clinical Dementia Rating Scale-Sum of Boxes, and the Functional Activities Questionnaire) and demonstrated greater rates of atrophy in brain structures (hippocampus, entorhinal cortex, and whole brain), and concordant-positive group performed worse over time than discordant group. Moreover, the risk of cognitive decline increased from concordant-negative to discordant to concordant-positive. The results from longitudinal analyses were validated in A+T+, cognitively normal, and mild cognitive impairment individuals, and were also validated by applying different cutoffs and neurodegenerative biomarkers.

INTERPRETATION

Discordant neurodegenerative status denotes a stage of cognitive function which is intermediate between concordant-negative and concordant-positive. Identification of discordant cases would provide insights into intervention and new therapy approaches, particularly in A+T+ individuals. Moreover, this work may be a complement to the ATN scheme.