Evaluating the Performance of Different Criteria in Diagnosing AD and Preclinical AD with the Bayesian Latent Class Model.

BACKGROUND: The diagnostic criteria for Alzheimer's disease (AD) should be highly sensitive and specific. Clinicians have varying opinions on the different criteria, including the International Working Group-1 (IWG-1), International Working Group-2 (IWG-2), and AT(N) criteria. Few studies had evaluated the performance of these criteria in diagnosing AD and preclinical AD when the gold standard was absent. METHODS: We estimated and compared the performance of these criteria in diagnosing AD using data from 908 subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Additionally, 622 subjects were selected to evaluate and compare the performance of IWG-2 and AT(N) criteria in diagnosing preclinical AD. A novel approach, Bayesian latent class models with fixed effect dependent, was utilized to estimate the diagnostic accuracy of these criteria in detecting different AD statuses simultaneously. RESULTS: The sensitivity of the IWG-1, IWG-2, and AT(N) criteria in diagnosing AD was 0.850, 0.836, and 0.665. The specificity of these criteria was 0.788, 0.746, and 0.747. The IWG-1 criteria had the highest Youden Index in detecting AD. When diagnosing preclinical AD, the sensitivity of the IWG-2 and AT(N) criteria was 0.797 and 0.955. The specificity of these criteria was 0.922 and 0.720. The IWG-2 criteria had the highest Youden Index. CONCLUSION: IWG-1 was more suitable than the IWG-2 and AT(N) criteria in detecting AD. IWG-2 criteria was more suitable than AT(N) criteria in detecting preclinical AD.

Executive function and cortical thickness in biomarker aMCI.

INTRODUCTION: Memory deficits are the primary symptom in amnestic Mild Cognitive Impairment (aMCI); however, executive function (EF) deficits are common. The current study examined EF in aMCI based upon amyloid status (A+/A-) and regional atrophy in signature areas of Alzheimer's disease (AD). METHOD: Participants included 110 individuals with aMCI (A+ = 66; A- = 44) and 33 cognitively healthy participants (HP). EF was assessed using four neuropsychological assessment measures. The cortical thickness of the AD signature areas was calculated using structural MRI data. RESULTS: A + had greater EF deficits and cortical atrophy relative to A - in the supramarginal gyrus and superior parietal lobule. A - had greater EF deficits relative to HP, but no difference in signature area cortical thickness. DISCUSSION: The current study found that the degree of EF deficits in aMCI are a function of amyloid status and cortical thinning in the parietal cortex.

Explore the Role of Frailty as a Contributor to the Association Between AT(N) Profiles and Cognition in Alzheimer's Disease.

Background: The relationship between Alzheimer's disease (AD)-related pathology and cognition was not exactly consistent. Objective: To explore whether the association between AD pathology and cognition can be moderated by frailty. Methods: We included 1711 participants from the Alzheimer's Disease Neuroimaging Initiative database. Levels of cerebrospinal fluid amyloid-ß, p-tau, and t-tau were identified for AD-related pathology based on the amyloid-ß/tau/neurodegeneration (AT[N]) framework. Frailty was measured using a modified Frailty Index-11 (mFI-11). Regression and interaction models were utilized to assess the relationship among frailty, AT(N) profiles, and cognition. Moderation models analyzed the correlation between AT(N) profiles and cognition across three frailty levels. All analyses were corrected for age, sex, education, and APOEɛ4 status. Results: In this study, frailty (odds ratio [OR] = 1.71, p < 0.001) and AT(N) profiles (OR = 2.00, p < 0.001) were independently associated with cognitive status. The model fit was improved when frailty was added to the model examining the relationship between AT(N) profiles and cognition (p < 0.001). There was a significant interaction between frailty and AT(N) profiles in relation to cognitive status (OR = 1.12, pinteraction = 0.028). Comparable results were obtained when Mini-Mental State Examination scores were utilized as the measure of cognitive performance. The association between AT(N) profiles and cognition was stronger with the levels of frailty. Conclusions: Frailty may diminish patients' resilience to AD pathology and accelerate cognitive decline resulting from abnormal AD-related pathology. In summary, frailty contributes to elucidating the relationship between AD-related pathology and cognitive impairment.

Aß oligomers peak in early stages of Alzheimer's disease preceding tau pathology.

INTRODUCTION: Soluble amyloid beta (Aß) oligomers have been suggested as initiating Aß related neuropathologic change in Alzheimer's disease (AD) but their quantitative distribution and chronological sequence within the AD continuum remain unclear. METHODS: A total of 526 participants in early clinical stages of AD and controls from a longitudinal cohort were neurobiologically classified for amyloid and tau pathology applying the AT(N) system. Aß and tau oligomers in the quantified cerebrospinal fluid (CSF) were measured using surface-based fluorescence intensity distribution analysis (sFIDA) technology. RESULTS: Across groups, highest Aß oligomer levels were found in A+ with subjective cognitive decline and mild cognitive impairment. Aß oligomers were significantly higher in A+T- compared to A-T- and A+T+. APOE Îµ4 allele carriers showed significantly higher Aß oligomer levels. No differences in tau oligomers were detected. DISCUSSION: The accumulation of Aß oligomers in the CSF peaks early within the AD continuum, preceding tau pathology. Disease-modifying treatments targeting Aß oligomers might have the highest therapeutic effect in these disease stages. Highlights: Using surface-based fluorescence intensity distribution analysis (sFIDA) technology, we quantified Aß oligomers in cerebrospinal fluid (CSF) samples of the DZNE-Longitudinal Cognitive Impairment and Dementia (DELCODE) cohortAß oligomers were significantly elevated in mild cognitive impairment (MCI)Amyloid-positive subjects in the subjective cognitive decline (SCD) group increased compared to the amyloid-negative control groupInterestingly, levels of Aß oligomers decrease at advanced stages of the disease (A+T+), which might be explained by altered clearing mechanisms.

A critical appraisal of blood-based biomarkers for Alzheimer's disease.

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-ß (Aß) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aß1-42, the Aß1-42/Aß1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aß1-42/Aß1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

Estimating Dementia Onset: AT(N) Profiles and Predictive Modeling in Mild Cognitive Impairment Patients.

BACKGROUND: Mild Cognitive Impairment (MCI) usually precedes the symptomatic phase of dementia and constitutes a window of opportunities for preventive therapies. OBJECTIVES: The objective of this study was to predict the time an MCI patient has left to reach dementia and obtain the most likely natural history in the progression of MCI towards dementia. METHODS: This study was conducted on 633 MCI patients and 145 subjects with dementia through 4726 visits over 15 years from Alzheimer Disease Neuroimaging Initiative (ADNI) cohort. A combination of data from AT(N) profiles at baseline and longitudinal predictive modeling was applied. A data-driven approach was proposed for categorical diagnosis prediction and timeline estimation of cognitive decline progression, which combined supervised and unsupervised learning techniques. RESULTS: A reduced vector of only neuropsychological measures was selected for training the models. At baseline, this approach had high performance in detecting subjects at high risk of converting from MCI to dementia in the coming years. Furthermore, a Disease Progression Model (DPM) was built and also verified using three metrics. As a result of the DPM focused on the studied population, it was inferred that amyloid pathology (A+) appears about 7 years before dementia, and tau pathology (T+) and neurodegeneration (N+) occur almost simultaneously, between 3 and 4 years before dementia. In addition, MCI-A+ subjects were shown to progress more rapidly to dementia compared to MCI-A- subjects. CONCLUSION: Based on proposed natural histories and cross-sectional and longitudinal analysis of AD markers, the results indicated that only a single cerebrospinal fluid sample is necessary during the prodromal phase of AD. Prediction from MCI into dementia and its timeline can be achieved exclusively through neuropsychological measures.

Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer's Disease.

BACKGROUND: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-ß (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive. OBJECTIVE: To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology. METHODS: In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains. RESULTS: Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development. CONCLUSIONS: Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-ß and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.

Harmonization and standardization of biofluid-based biomarker measurements for AT(N) classification in Alzheimer's disease.

Fluid biomarkers are currently measured in cerebrospinal fluid and blood for Alzheimer's disease diagnosis and are promising targets for drug development and for patients' follow-up in clinical trials. These biomarkers have been grouped in an unbiased research framework, the amyloid (Aß), tau, and neurodegeneration (AT[N]) biomarker system to aid patients' early diagnosis and stratification. Metrological approaches relying on mass spectrometry have been used for the development of reference materials and reference measurement procedures. Despite their excellent performances as clinical tools, fluid biomarkers often present an important between-laboratory variation. Standardization efforts were carried out on the biomarkers currently included in the AT(N) classification system, involving the collaboration of national metrology institutes, clinicians, researchers, and in vitro diagnostic providers. This article provides an overview of current activities towards standardization. These reference methods and reference materials may be used for recalibration of immunoassays and the establishment of standardized cutoff values allowing a better stratification of Alzheimer's disease patients. Highlights: The AT(N) biomarker system allows stratifying AD patients on the basis of biomarker profiles.Fluid biomarker measurements often present an important between-laboratory variation preventing the establishment of standardized cutoff values.Overview on the standardization initiatives involving the fluid biomarkers currently included in the AT(N) framework.

Plasma ATN(I) classification and precision pharmacology in Alzheimer's disease.

Evaluating potential therapies for Alzheimer's disease (AD) depends on use of biomarkers for appropriate subject selection and monitoring disease progression. Biomarkers that predict onset of clinical symptoms are particularly important for AD because they enable intervention before irreversible neurodegeneration occurs. The amyloid-ß-tau-neurodegeneration (ATN) classification system is currently used as a biological staging model for AD and is based on three classes of biomarkers evaluating amyloid-ß (Aß), tau pathology and neurodegeneration or neuronal injury. Promising blood-based biomarkers for each of these categories have been identified (Aß42/Aß40 ratio, phosphorylated tau, neurofilament light chain), and this matrix is now being expanded toward an ATN(I) system, where "I" represents a neuroinflammatory biomarker. The plasma ATN(I) system, together with APOE genotyping, offers a basis for individualized evaluation and a move away from the classic "one size fits all" approach toward a biomarker-driven individualisation of therapy for patients with AD.

The clinical application of optimized AT(N) classification in Alzheimer's clinical syndrome (ACS) and non-ACS conditions.

We aimed to assess the utility of AT(N) classification in clinical practice. We measured the cerebrospinal fluid levels of amyloid-ß (Aß) 42, Aß40, phosphorylated tau, total tau, and neurofilament light chain (NfL) in samples from 230 patients with Alzheimer's clinical syndrome (ACS) and 328 patients with non-ACS. The concordance of two A-markers (i.e., Aß42 alone and the Aß42/Aß40 ratio) was not significantly different between the ACS (87.4%) and non-ACS (74.1%) groups. However, the frequency of discordant cases with AAß42-alone+/AAß-ratio- was significantly higher in the non-ACS (23.8%) than in the ACS group (7.4%). The concordance of two N-markers (i.e., total tau and NfL) was 40.4% in the ACS group and 24.4% in the non-ACS group. In the ACS samples, the frequency of biological Alzheimer's disease (i.e., A+T+) in Ntau+ cases was 95% while that in NNfL+ cases was 65%. Reflecting Aß deposition and neurodegeneration more accurately, we recommend the use of AT(N) classification defined by cerebrospinal fluid AAß-ratioTNNfL in clinical practice.

Macular vessel density in the superficial plexus is not associated to cerebrospinal fluid core biomarkers for Alzheimer's disease in individuals with mild cognitive impairment: The NORFACE cohort.

Background: Optical coherence tomography angiography (OCT-A) is a novel method in the dementia field that allows the detection of retinal vascular changes. The comparison of OCT-A measures with established Alzheimer's disease (AD)-related biomarkers is essential to validate the former as a marker of cerebrovascular impairment in the AD continuum. We aimed to investigate the association of macular vessel density (VD) in the superficial plexus quantified by OCT-A with the AT(N) classification based on cerebrospinal fluid (CSF) Aß1-42, p181-tau and t-tau measurements in individuals with mild cognitive impairment (MCI). Materials and methods: Clinical, demographic, ophthalmological, OCT-A and CSF core biomarkers for AD data from the Neuro-ophthalmology Research at Fundació ACE (NORFACE) project were analyzed. Differences in macular VD in four quadrants (superior, nasal, inferior, and temporal) among three AT(N) groups [Normal, Alzheimer and Suspected non-Alzheimer pathology (SNAP)] were assessed in a multivariate regression model, adjusted for age, APOE ε4 status, hypertension, diabetes mellitus, dyslipidemia, heart disease, chronic obstructive pulmonary disease and smoking habit, using the Normal AT(N) group as the reference category. Results: The study cohort comprised 144 MCI participants: 66 Normal AT(N), 45 Alzheimer AT(N) and 33 SNAP AT(N). Regression analysis showed no significant association of the AT(N) groups with any of the regional macular VD measures (all, p > 0.16). The interaction between sex and AT(N) groups had no effect on differentiating VD. Lastly, CSF Aß1-42, p181-tau and t-tau measures were not correlated to VD (all r < 0.13; p > 0.13). Discussion: Our study showed that macular VD measures were not associated with the AT(N) classification based on CSF biomarkers in patients with MCI, and did not differ between AD and other underlying causes of cognitive decline in our cohort.

Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease.

INTRODUCTION: This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. METHODS: Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). RESULTS: AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DISCUSSION: This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

Biomarker A+T-: is this Alzheimer's disease or not? A combined CSF and pathology study.

The biological definition of Alzheimer's disease using CSF biomarkers requires abnormal levels of both amyloid (A) and tau (T). However, biomarkers and corresponding cutoffs may not always reflect the presence or absence of pathology. Previous studies suggest that up to 32% of individuals with autopsy-confirmed Alzheimer's disease show normal CSF p-tau levels in vivo, but these studies are sparse and had small sample sizes. Therefore, in three independent autopsy cohorts, we studied whether or not CSF A+T- excluded Alzheimer's disease based on autopsy. We included 215 individuals, for whom ante-mortem CSF collection and autopsy had been performed, from three cohorts: (i) the Amsterdam Dementia Cohort (ADC) [n = 80, 37 (46%) Alzheimer's disease at autopsy, time between CSF collection and death 4.5 ± 2.9 years]; (ii) the Antwerp Dementia Cohort (DEM) [n = 92, 84 (91%) Alzheimer's disease at autopsy, time CSF collection to death 1.7 ± 2.3 years]; and (iii) the Alzheimer's Disease Neuroimaging Initiative (ADNI) [n = 43, 31 (72%) Alzheimer's disease at autopsy, time CSF collection to death 5.1 ± 2.5 years]. Biomarker profiles were based on dichotomized CSF Aß1-42 and p-tau levels. The accuracy of CSF AT profiles to detect autopsy-confirmed Alzheimer's disease was assessed. Lastly, we investigated whether the concordance of AT profiles with autopsy diagnosis improved when CSF was collected closer to death in 9 (10%) DEM and 30 (70%) ADNI individuals with repeated CSF measurements available. In total, 50-73% of A+T- individuals and 100% of A+T+ individuals had Alzheimer's disease at autopsy. Amyloid status showed the highest accuracy to detect autopsy-confirmed Alzheimer's disease (accuracy, sensitivity and specificity in the ADC: 88%, 92% and 84%; in the DEM: 87%, 94% and 12%; and in the ADNI cohort: 86%, 90% and 75%, respectively). The addition of CSF p-tau did not further improve these estimates. We observed no differences in demographics or degree of Alzheimer's disease neuropathology between A+T- and A+T+ individuals with autopsy-confirmed Alzheimer's disease. All individuals with repeated CSF measurements remained stable in Aß1-42 status during follow-up. None of the Alzheimer's disease individuals with a normal p-tau status changed to abnormal; however, four (44%) DEM individuals and two (7%) ADNI individuals changed from abnormal to normal p-tau status over time, and all had Alzheimer's disease at autopsy. In summary, we found that up to 73% of A+T- individuals had Alzheimer's disease at autopsy. This should be taken into account in both research and clinical settings.

Increased functional connectivity between nucleus basalis of Meynert and amygdala in cognitively intact elderly along the Alzheimer's continuum.

BACKGROUND: A growing body of research reported the degeneration of the basal forebrain (BF) cholinergic system in the early course of Alzheimer's disease (AD). However, functional changes of the BF in asymptomatic individuals along the Alzheimer's continuum remain unclear. METHODS: A total of 229 cognitively intact participants were included from the Alzheimer's Disease Neuroimaging Initiative dataset and further divided into four groups based on the "A/T" profile using amyloid and tau positron emission tomography (PET). All A-T+ subjects were excluded. One hundred and seventy-three subjects along the Alzheimer's continuum (A-T-, A+ T-, A+ T+) were used for further study. The seed-based functional connectivity (FC) maps of the BF subregions (Ch1-3 and Ch4 [nucleus basalis of Meynert, NBM]) with whole-brain voxels were constructed. Analyses of covariance to detect the between-group differences and to further investigated the relations between FC values and AD biomarkers or cognition. RESULTS: We found increased FC between right Ch4 and bilateral amygdala among three groups, and the FC value could well distinguish between the A-T- group and the Alzheimer's continuum groups. Furthermore, increased FC between the Ch4 and amygdala was associated with higher pathological burden reflected by amyloid and tau PET in the entire population as well as better logistic memory function in A + T+ group. CONCLUSION: Our study demonstrated the NBM functional connectivity increased in cognitively normal elderly along the Alzheimer's continuum, which indicated a potential compensatory mechanism to counteract pathological changes in AD and maintain intact cognitive function.

Elevation of plasma phosphorylated tau181 during neurological illnesses affecting consciousness and kidney dysfunction.

Introduction: Phosphorylated tau (p-tau)181 has become a promising blood-based Alzheimer's disease (AD) biomarker. We studied the agreement of plasma p-tau181 and cerebrospinal fluid (CSF) markers in patients with alteration of consciousness (AOC). Methods: Plasma and CSF were simultaneously collected in participants presenting with AOC. Plasma p-tau181 was measured using the single-molecule array. CSF biomarkers were classified according to the amyloid/tau/neurodegeneration (AT[N]) framework. Results: Among participants enrolled, the median (interquartile range) age was 57 (28.5-75) years and 5.8% had AD. Plasma p-tau181 yielded area under the curve of 0.85 and showed moderate correlation with CSF p-tau181 (Rho = 0.42, P < .001). Using the historical cut-point, many non-AD participants had elevated plasma p-tau181 resulting in a specificity of 0.57. Plasma p-tau181 correlated with the glomerular filtration rate (Rho = -0.52, P < .001). Among A- participants with elevated plasma p-tau181, 42% had kidney dysfunction. Discussion: Plasma p-tau181 showed inadequate specificity in patients with AOC partially attributable to concomitant kidney dysfunction.

Residual reserve index modifies the effect of amyloid pathology on fluorodeoxyglucose metabolism: Implications for efficiency and capacity in cognitive reserve.

Background: The residual approach to measuring cognitive reserve (using the residual reserve index) aims to capture cognitive resilience conferred by cognitive reserve, but may be confounded by factors representing brain resilience. We sought to distinguish between brain and cognitive resilience by comparing interactions between the residual reserve index and amyloid, tau, and neurodegeneration ["AT(N)"] biomarkers when predicting executive function. We hypothesized that the residual reserve index would moderate at least one path from an AT(N) biomarker to executive function (consistent with cognitive resilience), as opposed to moderating a path between two AT(N) biomarkers (suggestive of brain resilience). Methods: Participants (N = 332) were from the Alzheimer's Disease Neuroimaging Initiative. The residual reserve index represented the difference between observed and predicted memory performance (a positive residual reserve index suggests higher cognitive reserve). AT(N) biomarkers were: CSF ß-amyloid1-42/ß-amyloid1-40 (A), plasma phosphorylated tau-181 (T), and FDG metabolism in AD-specific regions ([N]). AT(N) biomarkers (measured at consecutive time points) were entered in a sequential mediation model testing the indirect effects from baseline amyloid to executive function intercept (third annual follow-up) and slope (baseline to seventh follow-up), via tau and/or FDG metabolism. The baseline residual reserve index was entered as a moderator of paths between AT(N) biomarkers (e.g., amyloid-tau), and paths between AT(N) biomarkers and executive function. Results: The residual reserve index interacted with amyloid pathology when predicting FDG metabolism: the indirect effect of amyloid → FDG metabolism → executive function intercept and slope varied as a function of the residual reserve index. With lower amyloid pathology, executive function performance was comparable at different levels of the residual reserve index, but a higher residual reserve index was associated with lower FDG metabolism. With higher amyloid pathology, a higher residual reserve index predicted better executive function via higher FDG metabolism. Conclusion: The effect of the residual reserve index on executive function performance via FDG metabolism was consistent with cognitive resilience. This suggests the residual reserve index captures variation in cognitive reserve; specifically, neural efficiency, and neural capacity to upregulate metabolism to enhance cognitive resilience in the face of greater amyloid pathology. Implications for future research include the potential bidirectionality between neural efficiency and amyloid accumulation.

The AT(N) system for describing biological changes in Alzheimer's disease: a plain language summary.

WHAT IS THIS SUMMARY ABOUT?: This is a plain language summary of an article published in Nature Reviews Neurology. It explains how Alzheimer's disease is diagnosed. It also looks at whether a newer way to assess people with Alzheimer's disease could help improve how the condition is diagnosed, monitored, and treated. WHY IS THIS IMPORTANT?: Alzheimer's disease is a long-term progressive brain disease that leads to difficulties with thinking and memory. It is a progressive condition, which means it gets worse over time. Biological changes occur in the brain of people with Alzheimer's disease. This includes a build-up of toxic protein clusters called amyloid plaques and tau tangles, gradual damage to the brain cells (neurodegeneration), and brain shrinkage due to loss of neurons. It is often due to multiple factors and doctors usually diagnose Alzheimer's disease by looking at a person's symptoms and ruling out other causes of dementia. However, research shows that people diagnosed in this way do not always have the biological changes in the brain that are related to Alzheimer's disease. This means that some people may be misdiagnosed. Additionally, there may be a delay in the appearance of Alzheimer's symptoms, by which point changes in the brain may be severe. For example, people with Alzheimer's disease show biological changes in the brain, years before symptoms appear. WHAT ARE THE KEY TAKEAWAYS?: An assessment of biological changes in the brain, by measuring substances that indicate disease progress (biomarkers), may offer a fuller picture of a person's Alzheimer's disease, how advanced it is, and which treatments are likely to work best. A recently developed classification scheme known as the AT(N) system provides a way to assess and describe the biological changes in amyloid (A), tau (T), and neurodegeneration (N) that occur in people with Alzheimer's disease. The goal is to include biomarker testing in clinical practice to help physicians and practitioners diagnose, monitor, and treat people with Alzheimer's disease more effectively. The AT(N) system is being used for various purposes in clinical studies, and has the potential to assist physicians and practitioners in early detection, accurate diagnosis, staging, and treatment selection for people with Alzheimer's disease.

Brain Atrophy and Clinical Characterization of Adults With Mild Cognitive Impairment and Different Cerebrospinal Fluid Biomarker Profiles According to the AT(N) Research Framework of Alzheimer's Disease.

Introduction: This study aimed to evaluate, in adults with mild cognitive impairment (MCI), the brain atrophy that may distinguish between three AT(N) biomarker-based profiles, and to determine its clinical value. Methods: Structural MRI (sMRI) was employed to evaluate the volume and cortical thickness differences in MCI patients with different AT(N) profiles, namely, A-T-(N)-: normal AD biomarkers; A+T-(N)-: AD pathologic change; and A+T+(N)+: prodromal AD. Sensitivity and specificity of these changes were also estimated. Results: An initial atrophy in medial temporal lobe (MTL) areas was found in the A+T-(N)- and A+T+(N)+ groups, spreading toward the parietal and frontal regions in A+T+(N)+ patients. These structural changes allowed distinguishing AT(N) profiles within the AD continuum; however, the profiles and their pattern of neurodegeneration were unsuccessful to determine the current clinical status. Conclusion: sMRI is useful in the determination of the specific brain structural changes of AT(N) profiles along the AD continuum, allowing differentiation between MCI adults with or without pathological AD biomarkers.

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-ß 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.