ATN classification and clinical progression in subjective cognitive decline: The SCIENCe project

Needs expressed by people with subjective cognitive decline during amyloid PET disclosure consultations: An observational study

OBJECTIVES

We disclosed amyloid PET results to people with subjective cognitive decline (SCD) and analysed audiotaped consultations. The aim was to examine the needs expressed by people with SCD and their care partners during amyloid PET disclosure consultations, and to explore neurologists' communication behaviours surrounding these expressions of need.

METHODS

53 persons with SCD (65 ± 7.6 yrs, 18(34 %) female, MMSE 29 ± 1.4, 14(26 %) amyloid-positive, 10(18.9 %) attended with care partner) who wished to learn their amyloid PET results were included. We audiotaped disclosure consultations (54.7 % face-to-face, 45.3 % telephone). Systematic coding using inductive and deductive elements was performed and followed by thematic analysis by two independent researchers.

RESULTS

We observed 1434 needs expressions, on average 27(±23) per consultation. The needs expressed could be categorized into two main overarching themes: the need to feel known and understood (44 %) and the need to know and understand (56 %). Amyloid-positive persons expressed significantly more needs (t (14.3)= -2.249, p = 0.041), especially regarding the need to know and understand. Neurologists frequently responded with 'providing space' reactions (68.6 %), which often led to continued discussions about people's needs.

CONCLUSION

This study shows that people with SCD receiving their amyloid PET-scan results have a considerable number and variety of needs. Despite of the large variation in the content of these needs, we identified two main themes implying that people with SCD do not only want information, but also want to feel known and understood. Although the average number of expressed needs was higher among people with an amyloid positive scan, people with a negative scan also expressed a variety of needs. Further research is needed to inform guidelines for tailoring amyloid PET disclosure consultations to individual needs, thereby enhancing person-centred care in memory clinic settings.

IMPLICATIONS

People with SCD, care partners, and neurologists can use these results to prepare for amyloid PET disclosure consultations.

Blood biomarkers confirm subjective cognitive decline (SCD) as a distinct molecular and clinical stage within the NIA-AA framework of Alzheimer´s disease

Subjective cognitive decline (SCD) is proposed as an indicator of transitional disease stage 2 in the Alzheimer's disease (AD) continuum. However, molecular and particularly longitudinal fluid biomarker data for this stage are still limited. This study aimed to determine whether blood-based biomarkers in amyloid-positive individuals with SCD (A + SCD) support the notion of stage 2 as a distinct stage between stages 1 and 3 of AD and to identify those at high risk for clinical progression. In a prospective multicenter study (DELCODE) involving 457 participants across the AD continuum, we analyzed plasma phospho-tau 181 (p181) and neurofilament light chain (NfL) and assessed their association with longitudinal cognition, hippocampal atrophy, and AD clinical stage transition. The results showed that baseline plasma p181 levels were elevated and increased more rapidly in A + SCD individuals compared to amyloid-positive cognitively unimpaired (A + CU) individuals (stage 1). NfL levels rose across A + CU, A + SCD, and amyloid-positive mild cognitive impairment (A + MCI, stage 3). In A + SCD, but not in A + CU, higher p181 levels predicted cognitive decline (PACC5) and transition to MCI. In conclusion, plasma p181 provides molecular biomarker evidence supporting A + SCD as a pre-dementia AD stage (stage 2) distinct from A + CU (stage 1) and helps identify individuals at risk for cognitive decline early in the AD continuum.

Radiomics across modalities: a comprehensive review of neurodegenerative diseases

Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational resources required to generate them, they hold significant value in downstream automated processing. For instance, in statistical or machine learning frameworks, radiomic features enhance sensitivity and specificity, making them indispensable for tasks such as diagnosis, prognosis, prediction, monitoring, image-guided interventions, and evaluating therapeutic responses. This review explores the application of radiomics in neurodegenerative diseases, with a focus on Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. While radiomics literature often focuses on magnetic resonance imaging (MRI) and computed tomography (CT), this review also covers its broader application in nuclear medicine, with use cases of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) radiomics. Additionally, we review integrated radiomics, where features from multiple imaging modalities are fused to improve model performance. This review also highlights the growing integration of radiomics with artificial intelligence and the need for feature standardisation and reproducibility to facilitate its translation into clinical practice.

Analyzing heterogeneity in Alzheimer disease using multimodal normative modeling on imaging-based ATN biomarkers

INTRODUCTION

Previous studies have applied normative modeling on a single neuroimaging modality to investigate Alzheimer disease (AD) heterogeneity. We employed a deep learning-based multimodal normative framework to analyze individual-level variation across ATN (amyloid-tau-neurodegeneration) imaging biomarkers.

METHODS

We selected cross-sectional discovery (n = 665) and replication cohorts (n = 430) with available T1-weighted magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). Normative modeling estimated individual-level abnormal deviations in amyloid-positive individuals compared to amyloid-negative controls. Regional abnormality patterns were mapped at different clinical group levels to assess intra-group heterogeneity. An individual-level disease severity index (DSI) was calculated using both the spatial extent and magnitude of abnormal deviations across ATN.

RESULTS

Greater intra-group heterogeneity in ATN abnormality patterns was observed in more severe clinical stages of AD. Higher DSI was associated with worse cognitive function and increased risk of disease progression.

DISCUSSION

Subject-specific abnormality maps across ATN reveal the heterogeneous impact of AD on the brain.

HIGHLIGHTS

Normative modeling examined AD heterogeneity across multimodal imaging biomarkers. Heterogeneity in spatial patterns of gray matter atrophy, amyloid, and tau burden. Higher within-group heterogeneity for AD patients at advanced dementia stages. Patient-specific metric summarized extent of neurodegeneration and neuropathology. Metric is a marker of poor brain health and can monitor risk of disease progression.

Cognitive Performance Among Older Adults with Subjective Cognitive Decline

Objectives: The main objective of this cross-sectional study was to investigate if there are significant differences in cognition between a group of older adults with subjective cognitive decline (SCD) and cognitively intact controls. Methods: An initial sample of 132 older people underwent an extensive neuropsychological evaluation (memory, executive functions, and language) and were classified according to diagnostic criteria. Two groups of 33 subjects each, controls and SCD, were formed using an a priori case-matching procedures in different variables: age, biological sex, years of education, cognitive reserve, and Mini-Mental State Exam. Results: The mean age and standard deviation in the control group were equal to 70.39 ± 4.31 years, while in the SCD group, they were 70.30 ± 4.33 years. The number of males (n = 9) and females (n = 24) was equal in both groups; the means of years of education were also quite similar. SCD participants have a significantly lower mood than the controls. Significant differences between groups were obtained in delayed recall, inhibitory control, and comprehension of sentences not fitted to canonical word order in Spanish. A logistic regression revealed that a lower score on the Stroop's interference condition is associated with a higher likelihood of having SCD. Finally, ROC analysis provided a model that performs better than random chance, and a cut-off score in Stroop's interference condition equal to 49 was suggested for clinically differentiating the two groups. Conclusions: This study highlights that, compared to a matched control group, participants with SCD showed subtle but significant neuropsychological differences.

The impact of cardiorespiratory fitness on Alzheimer's disease biomarkers and their relationships with cognitive decline

INTRODUCTION

Relationships between core Alzheimer's disease (AD) biomarker accumulation and cognitive decline are well-established and the literature generally suggests a favorable relationship of cardiorespiratory fitness (CRF) on AD biomarker accumulation and cognition. Differences in risk of biomarker status conversion or accumulation rates by CRF, or their potential interactive relationships with cognitive decline remain largely unknown.

METHODS

Participants (N=533; MeanAGE=65, 70% female) from the Wisconsin Alzheimer's Disease Research Center and the Wisconsin Registry for Alzheimer's Prevention underwent serial blood draws, and cognitive and imaging assessments (MeanFollow-up=6.0 years). PET imaging of amyloid-β (Aβ) and tau (T) and plasma phosphorylated tau-217 (pTau-217) were used to determine biomarker status (+/-). Sex-specific estimated CRF (eCRF) tertiles were created using a validated equation. Kaplan-Meier survival curves and Cox-proportional hazards models characterized the risk of becoming biomarker-positive. Linear mixed effects models estimated associations between baseline eCRF and core AD biomarker accumulation and whether eCRF modified relationships between biomarker accumulation and cognitive decline. Analyses were stratified by biomarker +/- status.

RESULTS

No significant relationships were observed between eCRF and biomarker trajectories. However, those in the high eCRF group who were also Aβ- (HR[95%CI]=0.42[0.20, 0.88]) and pTau-217-(HR[95%CI]=0.45[0.21, 0.97]) at baseline had a significantly lower risk of becoming biomarker-positive. There was a significant attenuation of the detrimental relationship between Aβ accumulation and cognitive decline for those with high eCRF and Aβ+/T+.

DISCUSSION

While CRF did not influence core AD biomarker accumulation trajectories, high CRF did seem to protect against becoming biomarker-positive and attenuate the known deleterious relationship between biomarker accumulation and cognitive decline in Aβ+/T+.

Blood Biomarkers Reflect Dementia Symptoms and Are Influenced by Cerebrovascular Lesions

Dementia blood biomarkers are becoming increasingly important. Various factors, such as ischemic lesions and inflammation, can influence the pathomechanism of dementia. We aimed to evaluate the effects of past stroke lesions on blood biomarkers (BMs). Following approval from the institutional ethics committee, patients who were admitted to the memory clinic and were consented to written documents were enrolled (n = 111, average [standard deviation] age: 74.5 [9.1] years-old). Brain magnetic resonance imaging, cognitive function, and neuropsychological symptoms were analyzed. The amyloid-β 42 (Aβ42)/Aβ40 ratio, phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and Aβ42/p-tau181 ratio were assessed as plasma BMs. The patients were diagnosed with Alzheimer's disease (n = 45), mild cognitive impairment (n = 56), depression (n = 8), and subjective cognitive impairment (n = 4). Bivariate analysis exhibited that all measured BM indicators were significantly associated with cognitive decline in patients without past stroke lesions. Whereas the patients with stroke lesions presented a significant association only between GFAP and cognitive decline (p = 0.0011). Multiple regression analysis showed that NfL significantly correlated with cognitive decline only in patients without stroke lesions (r = 0.4988, p = 0.0003) and with delusion only in those with stroke lesions (r = 0.5492, p = 0.0121). Past stroke lesions should be addressed in the assessment of the correlation between blood biomarkers and cognitive decline in dementia patients.

SCD-plus features and AD biomarkers in cognitively unimpaired samples: A meta-analytic approach for nine cohort studies

INTRODUCTION

Specific features of subjective cognitive decline (SCD-plus) have been proposed to indicate an increased risk of preclinical Alzheimer's disease (AD). However, few studies have examined how these features relate to AD biomarkers in cognitively unimpaired (CU) older adults.

METHODS

Meta-analyses were performed using cross-sectional data from nine cohorts (n = 7219, mean age (SD): 71.17 (5.9), 56.5% female) to determine associations of SCD-plus features with positron emission tomography (PET)- or cerebrospinal fluid (CSF)-derived amyloid beta (Aβ) and tau biomarkers.

RESULTS

Participants with preclinical AD (community-based only) were more likely to fulfill SCD-plus features. The presence of self-reported memory decline, associated concern/worry, and a higher number of fulfilled features were all associated with high Aβ levels. Only the latter was associated with abnormal tau.

DISCUSSION

Simultaneous endorsement of multiple SCD-plus features is a robust indicator of abnormal AD biomarkers in CU older adults, whereas isolated SCD features seem only sensitive to elevated Aβ, supporting their value as early behavioral markers of preclinical AD.

HIGHLIGHTS

About two-tenths of our sample had abnormal amyloid beta (Aβ) levels with evidence of subjective cognitive decline (SCD). Preclinical AD subsamples (community-based) had a higher percentage of participants meeting SCD-plus features. Self-reported memory decline and concern/worry were the sole features associated with high Aβ, but not tau, burden. A higher number of fulfilled SCD-plus features are linked to high Aβ and tau burden. Use of multiple SCD-plus features may help identify early stages of biological AD.

Neuronal and glial dysfunction, white matter hyperintensities and cognition in ageing and Alzheimer's disease

This cross-sectional study examined associations between multiple fluid biomarkers of neuronal and glial dysfunction (plasma neurofilament light chain, CSF growth-associated protein 43 and CSF soluble triggering receptor expressed on myeloid cells 2), total white matter hyperintensity volume and episodic memory and executive function performance in the context of Alzheimer's disease biomarker status. A total of 563 participants (mean age = 71.9 years, standard deviation = 7.2) from the Alzheimer's Disease Neuroimaging Initiative were classified by the amyloid-β/tau/neurodegeneration framework into no Alzheimer's disease pathology (n = 176), suspected non-Alzheimer's disease pathophysiology (n = 87) or Alzheimer's disease continuum (n = 300) groups. Participants completed baseline neuropsychological assessment, plasma/CSF biomarker collection and MRI. Analyses explored the relative contributions of biomarkers to episodic memory and executive function performance and whether relationships varied by amyloid-β/tau/neurodegeneration group status. Across all participants, neurofilament light chain (β ^ = -0.14, P < 0.001) and growth-associated protein 43 (β ^ = -0.13, P < 0.001) were the strongest biomarkers associated with episodic memory performance, such that greater levels were associated with worse episodic memory. There was a group by growth-associated protein 43 interaction with episodic memory: greater growth-associated protein 43 was associated with lower episodic memory performance in participants classified as Alzheimer's disease continuum relative to the no Alzheimer's disease pathology group (β ^ = -0.26, P < 0.001). No robust associations between biomarkers and executive function performance or between soluble triggering receptor expressed on myeloid cells 2, white matter hyperintensity volume and cognition were observed. Biomarkers of neuro-axonal injury and synaptic dysfunction may independently contribute to episodic memory performance across participants with differing amyloid-β/tau/neurodegeneration profiles. Growth-associated protein 43 may predict worse episodic memory performance in participants with greater Alzheimer's disease pathology. These biomarkers of neuronal dysfunction may serve as domain-specific cognitive correlates in the context of Alzheimer's disease biomarker status.

Identification of circulating risk biomarkers for cognitive decline in a large community-based population in Chongqing China

INTRODUCTION

This study aims to investigate the relationship between blood-based pathologies and established risk factors for cognitive decline in the community-based population of Chongqing, a region with significant aging.

METHODS

A total of 26,554 residents aged 50 years and older were recruited. Multinomial logistic regression models were applied to assess the risk factors of cognition levels. Propensity score matching and linear mixed effects models were used to evaluate the relationship between key risk factors and the circulating biomarkers.

RESULTS

Shared and distinct risk factors for MCI and dementia were identified. Age, lower education, medical history of stroke, hypertension, and epilepsy influenced mild cognitive impairment (MCI) progression to dementia. Correlations between key risk factors and circulating neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), amyloid β protein (Aβ)40, and Aβ42/Aβ40 ratio suggest underlying mechanisms contributing to cognitive impairment.

DISCUSSION

The common and distinct risk factors across cognitive decline stages emphasize the need for tailored interventions. The correlations with blood biomarkers provide insights into potential management targets.

HIGHLIGHTS

From a large community-based cohort study on the residents in Chongqing, we have identified that mild cognitive impairment (MCI) and dementia share several common risk factors, including age, female gender, rural living, lower education levels, and a medical history of stroke. However, each condition also has its own unique risk factors. Several factors contribute to the progression of MCI into dementia including age, education levels, occupation, and a medical history of hypertension and epilepsy. We discover the correlations between the risk factors for dementia and blood biomarkers that indicate the presence of axonal damage, glial activation, and Aβ pathology.

Hippocampal Subfield Volume in Relation to Cerebrospinal Fluid Amyloid-ß in Early Alzheimer's Disease: Diagnostic Utility of 7T MRI

INTRODUCTION

Alzheimer's disease (AD) is a neurodegenerative condition characterised by amyloid plaque accumulation and neurofibrillary tangles. Early detection is essential for effective intervention, but current diagnostic methods that enable early diagnosis in clinical practice rely on invasive or costly biomarker scanning. This study aimed to explore the utility of 7T MRI in assessing hippocampal subfield volumes and their correlation with cerebrospinal fluid (CSF) biomarkers in prodromal AD.

METHODS

Fifty-six participants, including AD patients and healthy controls, underwent 7T MRI scanning. Automated segmentation delineated hippocampal subfield volumes, with subsequent normalisation to whole brain volume.

RESULTS

Significant differences in hippocampal and subfield volumes were observed in prodromal AD patients, even when they did not exhibit high MTA scores on 3T MRI or show any whole brain volume loss. Additionally, the volume of the entorhinal cortex (ERC) correlated significantly with CSF amyloid-β levels, suggesting ERC's potential as a proxy CSF amyloid-ß measurement. Conversely, no significant associations were found between CSF 181-Phosphorylated-tau or total tau levels and any hippocampal subfield volumes.

DISCUSSION

These findings show the potential use of 7T MRI, particularly in ERC assessment, as a biomarker for early AD identification. Further validation studies are warranted to confirm these results and elucidate the relationship of ERC volume with CSF biomarkers.

Linking higher amyloid beta 1-38 (Aβ(1-38)) levels to reduced Alzheimer's disease progression risk

INTRODUCTION

The beneficial effects of amyloid beta 1-38, or Aβ(1-38), on Alzheimer's disease (AD) progression in humans in vivo remain controversial. We investigated AD patients' cerebrospinal fluid (CSF) Aβ(1-38) and AD progression.

METHODS

Cognitive function and diagnostic change were assessed annually for 3 years in 177 Aβ-positive participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia from the German Center for Neurodegenerative Diseases (DZNE) longitudinal cognitive impairment and dementia study (DELCODE) cohort using the Mini-Mental State Examination (MMSE), Preclinical Alzheimer's Cognitive Composite (PACC), Clinical Dementia Rating (CDR), and National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria. Mixed linear and Cox regression analyses were conducted. CSF was collected at baseline.

RESULTS

Higher Aβ(1-38) levels were associated with slower PACC (p = 0.001) and slower CDR Sum of Boxes (CDR-SB) (p = 0.002) but not MMSE decline. Including Aβ(1-40) beyond Aβ(1-38) in the model confirmed an association of Aβ(1-38) with slower PACC decline (p = 0.005), but not with CDR-SB or MMSE decline. In addition, higher Aβ(1-38) baseline levels were associated with a reduced dementia conversion risk.

DISCUSSION

Further research is needed to understand the role of Aβ(1-38) in AD and its potential for future therapeutic strategies.

HIGHLIGHTS

This study not only replicates but also extends the existing findings on the role of Aβ(1-38) (amyloid beta 1-38) in Alzheimer's disease (AD) in humans in vivo. Higher baseline Aβ(1-38) levels were associated with a decreased risk of conversion to AD dementia in subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Different linear-mixed regression models suggest an association between higher Aβ(1-38) baseline levels and slower Preclinical Alzheimer's Cognitive Composite (PACC) and Clinical Dementia Rating Sum of Boxes (CDR-SB) decline. Including Aβ(1-40) beyond Aβ(1-38) in the model confirmed a link between Aβ(1-38) and PACC decline, but showed no association of Aβ(1-38) on CDR-SB and Mini-Mental State Examination (MMSE) decline. The impact of short Aβ isoforms in AD progression might have been under-investigated These findings underscore the urgent need for additional research on the role of these shorter Aβ peptides in AD, as they may hold key insights for future therapeutic strategies.

Prevalence of subjective cognitive decline and its association with physical health problems among urban community dwelling elderly population in South India

INTRODUCTION

No studies in India have explored subjective cognitive decline (SCD), a hallmark of stage II of preclinical Alzheimer's disease. This study aims to assess the prevalence and correlates of SCD in a South Indian, urban, elderly population.

METHODS

We screened 403 individuals 60 years of age and older using the Subjective Memory Complaints Questionnaire (SMCQ) and measured objective cognition with the Montreal Cognitive Assessment (MoCA). Physical health parameters were evaluated for all participants.

RESULTS

Among the participants, 377 (93.5%) reported subjective memory complaints. Of the 26 individuals without SCD, 15(57.7%) had objective cognitive impairment (MoCA <25). A total of 182 participants (45.2%) were identified with SCD. Higher educational attainment was significantly associated with fewer SCD reports and better cognitive performance (p < 0.001).

DISCUSSION

Subjective cognitive decline (SCD) is highly prevalent among older adults. Screening for SCD can help identify individuals at risk for Alzheimer's disease. SCD assessement combined with cost-effective biomarkers that confirms AD will help individuals to be identified for disease-modifying therapies.

HIGHLIGHTS

Nearly half of older adults population screened has reported subjective cognitive decline (SCD), highlighting the widespread occurrence of SCD in urban South India. Participants with higher educational attainment had significantly fewer memory complaints and performed better on cognitive assessments. SCD was prevalent even among individuals without major comorbid conditions such as diabetes and hypertension and those who were on regular treatment for metabolic and cardiovascular disorders. Identifying subjective cognitive decline (SCD) can facilitate early and accurate diagnosis of cognitive disorders and help delay progression to dementia. This highlights the importance of developing and implementing improved public health strategies to address these challenges. Further longitudinal studies are necessary to explore the progression of SCD to dementia, focusing on the interplay between cognitive health, biomarkers, and educational factors in the Indian population.

Serum β-secretase 1 (sBACE1) activity in subjective cognitive decline: an exploratory study

β-Secretase-1 (BACE1) plays a key role in the regulation of cerebral amyloid-β homeostasis, being involved in amyloidogenic and, as recently found, amyloidolytic pathways. Growing evidence indicates that increased serum BACE1 (sBACE1) activity might represent an early biomarker for Alzheimer's disease. Here, we tested the hypothesis that an increase in sBACE1 activity may already occur in individuals with subjective cognitive decline (SCD). We found that sBACE1 activity was significantly higher in individuals with SCD (n 118) compared to cognitively normal subjects (controls, n 137) (p < 0.001). Moreover, compared with SCD, sBACE1 activity was even higher in patients affected by amnestic (n 179) or non-amnestic mild cognitive impairment (MCI) (n 99) (p < 0.001 and p 0.02, respectively). In all cases, the respective increase in sBACE1 activity was significant after adjustment for possible confounders including age, sex, and comorbidities. We also found a significant sexual dimorphism, with women affected by either type of MCI, but not by SCD, having higher levels of serum BACE1 activity compared to men. These results provide evidence supporting the potential use of sBACE1 activity as tool for blood-based screening of cognitively healthy individuals at clinical risk of MCI and dementia.

Long-term neurobehavioral and neuroimaging outcomes in athletes with prior concussion(s) and head impact exposure

Objective: The long-term health of former athletes with a history of multiple concussions and/or repetitive head impact (RHI) exposure has been of growing interest among the public. The true proportion of dementia cases attributable to neurotrauma and the neurobehavioral profile/sequelae of multiple concussion and RHI exposure among athletes has been difficult to determine. Methods: Across three exposure paradigms (i.e. group comparisons of athletes vs. controls, number of prior concussions, and level of RHI exposure), this review characterizes the prevalence of neurodegenerative/neurological disease, changes in cognitive and psychiatric function, and alterations on neuroimaging. We highlight sources of variability across studies and provide suggested directions for future investigations. Results: The most robust finding reported in the literature suggests a higher level of symptom endorsement (general, psychiatric, and cognitive) among those with a greater history of sport-related concussion from adolescence to older adulthood. Pathological processes (e.g. atrophy, tau deposition, and hypometabolism) may be more likely to occur within select regions (frontal and temporal cortices) and structures (thalamus and hippocampus). However, studies examining concussion(s) and RHI exposure with imaging outcomes have yet to identify consistent associations or evidence of a dose-response relationship or a threshold at which associations are observed. Discussion: Studies have not observed a simple dose-response relationship between multiple concussions and/or RHI exposure with cognitive, psychiatric, or in vivo neurobiological outcomes, particularly at lower levels of play. The relationship between prior concussion and RHI exposure with long-term outcomes in former athletes is complex and likely influenced by -several non-injury-related factors.

Amyloid-related changes in fluency in patients with subjective cognitive decline

INTRODUCTION

We examined semantic and phonemic fluency in individuals with subjective cognitive decline (SCD) in relation to amyloid status and clinical progression.

METHODS

A total of 490 individuals with SCD (62 ± 8 years, 42% female, 28% amyloid-positive, 17% clinical progression) completed annual fluency assessments (mean ± SD follow-up 4.3 ± 2.9 years). Associations between fluency trajectories, amyloid status, and clinical progression were examined with linear mixed models and joint models.

RESULTS

Amyloid-positive individuals declined faster than amyloid-negative individuals on semantic fluency (B = -0.35, p < 0.001), but not on phonemic fluency (B = -0.06, p = 0.218). An annual decline of one word in semantic and phonemic fluency was associated with 22% (hazard ratio [HR] = 1.22, p < 0.001) and 28% (HR = 1.28, p = 0.004) increased risk of clinical progression.

DISCUSSION

Our results indicate that decline in semantic fluency is an early indicator of cognitive deficits in preclinical Alzheimer's disease.

Highlights

Abnormal amyloid burden is associated with decline in semantic fluency.Fluency trajectories are associated with an increased risk of clinical progression.More refined measures are needed to detect the earliest language deficits.

Multi-modal Imaging-based Pseudotime Analysis of Alzheimer progression

Alzheimer's disease (AD) is a neurodegenerative disorder that results in progressive cognitive decline but without any clinically validated cures so far. Understanding the progression of AD is critical for early detection and risk assessment for AD in aging individuals, thereby enabling initiation of timely intervention and improved chance of success in AD trials. Recent pseudotime approach turns cross-sectional data into "faux" longitudinal data to understand how a complex process evolves over time. This is critical for Alzheimer, which unfolds over the course of decades, but the collected data offers only a snapshot. In this study, we tested several state-of-the-art pseudotime approaches to model the full spectrum of AD progression. Subsequently, we evaluated and compared the pseudotime progression score derived from individual imaging modalities and multi-modalities in the ADNI cohort. Our results showed that most existing pseudotime analysis tools do not generalize well to the imaging data, with either flipped progression score or poor separation of diagnosis groups. This is likely due to the underlying assumptions that only stand for single cell data. From the only tool with promising results, it was observed that all pseudotime, derived from either single imaging modalities or multi-modalities, captures the progressiveness of diagnosis groups. Pseudotime from multi-modality, but not the single modalities, confirmed the hypothetical temporal order of imaging phenotypes. In addition, we found that multi-modal pseudotime is mostly driven by amyloid and tau imaging, suggesting their continuous changes along the full spectrum of AD progression.

Counseling and disclosure practices in predictive Alzheimer's disease diagnostics: A scoping review

New possibilities of biomarker-based predictive technologies for Alzheimer's disease (AD) have become more reliable as well as more accessible. Standardized clinical recommendations and guidance for counseling and disclosure in this context are not yet well developed. Our scoping review identified publications from database searches in PubMed, PsycINFO, LIVIVO, and Web of Science. Inclusion criteria were: (1) information or counseling, (2) biomarkers and a type of cognitive impairment or AD, and (3) published between 2005 and 2024. We identified 63 articles and synthesized them along the categories of staged information provision: pre-test counseling, disclosure, and post-disclosure follow-up. Most publications referred to the context of disclosure (48), followed by pre-test counseling (33), and post-disclosure follow-up (31). Some publications referred to all stages of counseling (17). Our findings highlight the need to further develop and specify comprehensive and standardized guidelines for counseling, disclosure, and post-disclosure follow-up in the context of AD biomarker testing. HIGHLIGHTS: New possibilities of biomarker-based predictive technologies for Alzheimer's disease (AD) have become more reliable and also more accessible. However, clinical recommendations and guidance for counseling and disclosure in the context of AD biomarker testing are currently not well developed. We carried out a scoping review with the aim to generate an overview of the scientific literature and guidance available regarding counseling, biomarker test result and dementia risk disclosure, and clinical management prior to and in the course of a biomarker-based diagnosis in early stages of AD. We identified 63 relevant articles. Most publications referred to the context of disclosure (48), followed by pre-test counseling (33), and post-disclosure follow-up (31). Some publications referred to all stages of counseling (17). Our findings highlight the urgent need for national and international consensus guidelines for comprehensive and staged counseling and disclosure practices. While most publications identify relevant ethical challenges posed for counseling practices in the context of AD biomarker testing, they rarely present any practical recommendations for clinicians, on how and what to counsel on a concrete level.

Clinical Diagnoses and Characterization of Patients With Amyloid-Negative Amyloid-Beta, p-Tau, and Neurofilament Light Chain (ATN) Profiles

The novel amyloid-beta, p-Tau, and neurofilament light chain (ATN) classification scheme has become a promising system for clinically detecting and diagnosing Alzheimer's disease (AD). In addition to its utility in Alzheimer's diagnosis and treatment, the ATN framework may also have clinical relevance in identifying non-Alzheimer's pathologies. In this study conducted at Broadlawns Geriatric and Memory Center, 92 amyloid-negative profiles out of 182 patients with an ATN framework were categorized into subjective cognitive impairment (SCI), non-amnestic mild cognitive impairment (non-amnestic MCI), amnestic MCI, Alzheimer's dementia, vascular dementia, mixed dementia, unspecified dementia, or other memory changes based on diagnoses written in the chart. Additionally, other secondary diagnoses were found in the differential, including sleep disorders, anxiety, depressive disorders and grief, and cerebrovascular disease. The results are concordant with our expectations that amyloid-negative ATN profiles are associated with mostly non-Alzheimer's cognitive decline. We were also able to demonstrate that amyloid-negative patients have other secondary neurologic or psychiatric diagnoses related to memory or cognitive changes. However, certain enigmatic patient presentations warrant further scrutiny in the medical chart. It is possible that ATN may pose a risk of misclassification in both Alzheimer and non-Alzheimer pathologies, particularly at early stages. Future work may be required to corroborate findings using other new plasma biomarkers, such as p-Tau217. Overall, we hope that this study will provide options for early detection and future treatment of AD and other neurocognitive disorders. We also anticipate that this work will lead to the recognition of other non-neurocognitive conditions comorbid with such neurocognitive disorders.

Plasma miRNAs across the Alzheimer's disease continuum: Relationship to central biomarkers

INTRODUCTION

MicroRNAs (miRNAs) play important roles in gene expression regulation and Alzheimer's disease (AD) pathogenesis.

METHODS

We investigated the association between baseline plasma miRNAs and central AD biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 803): amyloid, tau, and neurodegeneration (A/T/N). Differentially expressed miRNAs and their targets were identified, followed by pathway enrichment analysis. Machine learning approaches were applied to investigate the role of miRNAs as blood biomarkers.

RESULTS

We identified nine, two, and eight miRNAs significantly associated with A/T/N positivity, respectively. We identified 271 genes targeted by amyloid-related miRNAs with estrogen signaling receptor-mediated signaling among the enriched pathways. Additionally, 220 genes targeted by neurodegeneration-related miRNAs showed enrichment in pathways including the insulin growth factor 1 pathway. The classification performance of demographic information for A/T/N positivity was increased up to 9% with the inclusion of miRNAs.

DISCUSSION

Plasma miRNAs were associated with central A/T/N biomarkers, highlighting their potential as blood biomarkers.

HIGHLIGHTS

We performed association analysis of microRNAs (miRNAs) with amyloid/tau/neurodegeneration (A/T/N) biomarker positivity. We identified dysregulated miRNAs for A/T/N biomarker positivity. We identified Alzheimer's disease biomarker-specific/common pathways related to miRNAs. miRNAs improved the classification for A/T/N positivity by up to 9%. Our study highlights the potential of miRNAs as blood biomarkers.

Cryo-EM structure of Alzheimer's disease tau filaments with PET ligand MK-6240

Positron Emission Tomography (PET) ligands have advanced Alzheimer's disease (AD) diagnosis and treatment. Using autoradiography and cryo-EM, we identify AD brain tissue with elevated tau burden, purify filaments, and determine the structure of second-generation high avidity PET ligand MK-6240 at 2.31 Å resolution, which bound at a 1:1 ratio within the cleft of tau paired-helical filament (PHF), engaging with glutamine 351, lysine 353, and isoleucine 360. This information elucidates the basis of MK-6240 PET in quantifying PHF deposits in AD and may facilitate the structure-based design of superior ligands against tau amyloids.

Differentiation of Alzheimer's disease from other neurodegenerative disorders using chemiluminescence immunoassays measuring cerebrospinal fluid biomarkers

Introduction

Prior research identified four neurochemical cerebrospinal fluid (CSF) biomarkers, Aβ1-42, Aβ1-40, tTau, and pTau(181), as core diagnostic markers for Alzheimer's disease (AD). Determination of AD biomarkers using immunoassays can support differential diagnosis of AD vs. several neuropsychiatric disorders, which is important because the respective treatment regimens differ. Results of biomarker determination can be classified according to the Amyloid/Tau/Neurodegeneration (ATN) system into profiles. Less is known about the clinical performance of chemiluminescence immunoassays (ChLIA) measuring specific biomarkers in CSF samples from patients suffering from neuropsychiatric impairments with various underlying causes.

Methods

Chemiluminescence immunoassays (ChLIAs, EUROIMMUN) were used to determine Beta-Amyloid (1-40), Beta-Amyloid (1-42), Total-Tau, and pTau(181) concentrations in precharacterized cerebrospinal fluid (CSF) samples from 219 AD patients, 74 patients with mild cognitive impairment (MCI), and 220 disease control (DC) patients.

Results

83.0% of AD patients had ATN profiles consistent with AD, whereas 85.5% of DC patients and 77.0% of MCI patients had profiles inconsistent with AD. AD patients showed significantly lower amyloid ratio Aβ1-42/Aβ1-40 (mean: 0.07) and significantly higher concentrations of tTau (mean: 901.6 pg/ml) and pTau(181) (mean: 129 pg/ml) compared to DC and MCI patients (all p values < 0.0071).

Discussion

The ChLIAs effectively determined specific biomarkers and can support differential diagnostics of AD. Their quality was demonstrated in samples from 513 patients with cognitive impairments, representing a realistic mix of underlying causes for seeking treatment at a memory clinic.

Amyloid PET disclosure in subjective cognitive decline: Patient experiences over time

INTRODUCTION

We disclosed amyloid positron emission tomography (PET) results in individuals with subjective cognitive decline (SCD) and studied patient experiences and outcomes over a 6-month period.

METHODS

Fifty-seven participants from the Subjective Cognitive Impairment Cohort (SCIENCe) (66 ± 8 years, 21 [37%] F, Mini-Mental State Examination 29 ± 1, 15 [26%] amyloid positive [A+]) completed questionnaires 1 week prior (T0), 1 day after (T1), and 6 months after amyloid PET disclosure (T2). Questionnaires addressed patient-reported experiences and outcomes.

RESULTS

Independent of amyloid status, participants were satisfied with the consultation (scale 1-10; 7.9 ± 1.7) and information provided (scale 1-4; T1: 3.3 ± 0.9, T2: 3.2 ± 0.8). After 6 months, A+ participants reported more information needs (45% vs. 12%, p = 0.02). Independent of amyloid status, decision regret (scale 1-5; A+: 1.5 ± 0.9, A-: 1.4 ± 0.6, p = 0.53) and negative emotions (negative affect, uncertainty, anxiety) were low (all p > 0.15 and Pinteraction > 0.60).

DISCUSSION

Participants with SCD valued amyloid PET disclosure positively, regardless of amyloid status. The need for information after 6 months, which was stronger in A+ individuals, underscores the importance of follow-up.

HIGHLIGHTS

Participants with subjective cognitive decline (SCD) positively valued amyloid positron emission tomography (PET) disclosure. Participants with SCD experienced low levels of decision regret. We did not observe an increase in negative emotions. After 6 months, amyloid-positive individuals wanted more information.

Differential neuropsychiatric associations of plasma biomarkers in older adults with major depression and subjective cognitive decline

Older adults with major depressive disorder (MDD) or early cognitive decline during the subjective cognitive decline (SCD) stage may exhibit neuropsychiatric symptoms such as anxiety, depression, and subtle cognitive impairment. The clinicopathological features and biological mechanisms of MDD differ from those of SCD among older adults; these conditions thus require different treatment strategies. This study enrolled 82 participants above 50 years old with normal cognitive levels from the communities to examine biomarker-behavior correlations between MDD (n = 23) and SCD (n = 23) relative to a normal control (NC) group (n = 36). Multidomain assessments were performed for all participants, including immunomagnetic reduction tests to detect plasma beta-amyloid (Aβ), total tau (Tau), phosphorylated tau-181 (p-Tau181), neurofilament light chain, and glial fibrillary acidic protein (GFAP). This study observed that depressive symptoms in MDD were associated with amyloid pathology (plasma Aβ40 vs. HADS-D: R = 0.45, p = 0.031; Aβ42/Aβ40 vs. HADS-D: R = -0.47, p = 0.024), which was not observed in the NC (group difference p < 0.05). Moreover, cognitive decline in MDD was distinguished by a mixed neurodegenerative process involving amyloid (plasma Aβ42 vs. facial memory test: R = 0.48, p = 0.025), tau (Tau/Aβ42 vs. digit symbol substitution test (DSST): R = -0.53, p = 0.01), and astrocytic injury (plasma GFAP vs. Montreal cognitive assessment score: R = -0.44, p = 0.038; plasma GFAP vs. DSST: R = -0.52, p = 0.014), findings that did not apply to the NC (group difference p < 0.05). Moreover, this study revealed different biomarker-behavior correlations between individuals with SCD and the NC. Compared with the NC, cognitive decline in the SCD group might be unrelated to amyloid pathology and instead might be early manifestations of tau pathology. This study underscores the difference in clinicopathological features between MDD and SCD among older adults, which differ from those of the NC. These findings enhance our understanding of the mechanisms underlying MDD and SCD in older individuals.

Using eZIS to Predict Progression from MCI to Dementia in Three Years

(1) Background: Mild cognitive impairment (MCI) due to Alzheimer's disease (AD) progresses to dementia at a higher annual rate, while other MCIs may remain stable or even improve over time. Discriminating progressive from non-progressive cases of MCI is crucial and challenging. (2) Methods: A retrospective study of individuals with MCI was conducted at a university hospital located in southern Taiwan. The researchers collected demographic data, comorbidities, the scores of cognitive tests, three easy Z-score imaging system (eZIS) indicators (severity, extent, and ratio), Fazekas scale scores, mesial temporal atrophy (MTA) scores, clinical outcomes including deterioration of Cognitive Abilities Screening Instrument, Mini-mental State Examination, Clinical Dementia Rating Sum of Box scores, and the conversion from MCI to dementia. Those who converted to dementia in three years and non-converters were compared by the three eZIS indicators to test the predictive utility, and the clinical outcomes were evaluated by regression and ROC curve analysis. (3) Results: The three eZIS indicators were significantly higher in the group of progressive MCI than in stable MCI. eZIS severity is positively correlated with a deterioration in the scores of the Cognitive Abilities Screening Instrument and Clinical Dementia Rating Sum of Box. eZIS severity is also positively correlated with conversion from MCI to dementia. The AUC for severity is 0.719, and the optimal cutoff value of severity for predicting conversion is 1.22. (4) Conclusions: During three years of follow-up, MCI individuals with greater eZIS severity were significantly associated with worse cognitive assessment scores and a higher conversion rate to dementia.

Machine and deep learning algorithms for classifying different types of dementia: A literature review

The cognitive impairment known as dementia affects millions of individuals throughout the globe. The use of machine learning (ML) and deep learning (DL) algorithms has shown great promise as a means of early identification and treatment of dementia. Dementias such as Alzheimer's Dementia, frontotemporal dementia, Lewy body dementia, and vascular dementia are all discussed in this article, along with a literature review on using ML algorithms in their diagnosis. Different ML algorithms, such as support vector machines, artificial neural networks, decision trees, and random forests, are compared and contrasted, along with their benefits and drawbacks. As discussed in this article, accurate ML models may be achieved by carefully considering feature selection and data preparation. We also discuss how ML algorithms can predict disease progression and patient responses to therapy. However, overreliance on ML and DL technologies should be avoided without further proof. It's important to note that these technologies are meant to assist in diagnosis but should not be used as the sole criteria for a final diagnosis. The research implies that ML algorithms may help increase the precision with which dementia is diagnosed, especially in its early stages. The efficacy of ML and DL algorithms in clinical contexts must be verified, and ethical issues around the use of personal data must be addressed, but this requires more study.

Towards cascading genetic risk in Alzheimer's disease

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.

Tapping the Brakes on New Parkinson Disease Biological Staging

This Viewpoint cautions against the premature adoption and implementation of biological definitions for Parkinson disease proposed in February 2024.

Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup

The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.

Analyzing heterogeneity in Alzheimer Disease using multimodal normative modeling on imaging-based ATN biomarkers

INTRODUCTION

Previous studies have applied normative modeling on a single neuroimaging modality to investigate Alzheimer Disease (AD) heterogeneity. We employed a deep learning-based multimodal normative framework to analyze individual-level variation across ATN (amyloid-tau-neurodegeneration) imaging biomarkers.

METHODS

We selected cross-sectional discovery (n = 665) and replication cohorts (n = 430) with available T1-weighted MRI, amyloid and tau PET. Normative modeling estimated individual-level abnormal deviations in amyloid-positive individuals compared to amyloid-negative controls. Regional abnormality patterns were mapped at different clinical group levels to assess intra-group heterogeneity. An individual-level disease severity index (DSI) was calculated using both the spatial extent and magnitude of abnormal deviations across ATN.

RESULTS

Greater intra-group heterogeneity in ATN abnormality patterns was observed in more severe clinical stages of AD. Higher DSI was associated with worse cognitive function and increased risk of disease progression.

DISCUSSION

Subject-specific abnormality maps across ATN reveal the heterogeneous impact of AD on the brain.

Disease progression modeling with temporal realignment: An emerging approach to deepen knowledge on chronic diseases

The recent development of the first disease-modifying drug for Alzheimer's disease represents a major advancement in dementia treatment. Behind this breakthrough is a quarter century of research efforts to understand the disease not by a particular symptom at a given moment, but by long-term sequential changes in multiple biomarkers. Disease progression modeling with temporal realignment (DPM-TR) is an emerging computational approach proposed with this biomarker-based disease concept. By integrating short-term clinical observations of multiple disease biomarkers in a data-driven manner, DPM-TR provides a way to understand the progression of chronic diseases over decades and predict individual disease stages more accurately. DPM-TR has been developed primarily in the area of neurodegenerative diseases but has recently been extended to non-neurodegenerative diseases, including chronic obstructive pulmonary, autoimmune, and ophthalmologic diseases. This review focuses on opportunities for DPM-TR in clinical practice and drug development and discusses its current status and challenges.

Alzheimer's disease: part 2 - the present

Based on my work as a clinical neurologist with more than 50 years of experience in caring for patients with Alzheimer's disease (AD), I focus, in this review article, on the disease's two fundamental aspects for the doctor: diagnosis and treatment. The 1984 diagnostic criteria had been stable for more than a quarter of a century when it was replaced in 2011. Since then, there have been many discoveries, especially of biomarkers that have a heavy impact on the diagnosis of AD. Recently, AD biomarkers have become available in plasma, which certainly will cause a major change in the diagnosis of biological AD, a term that still needs care and information to society before being used in clinical practice. Three monoclonal antibodies against β-amyloid peptide have also been recently approved, and two of these have shown a small but statistically significant effect on clinical outcome. These monoclonal antibodies have had a greater effect on the reduction of amyloid plaques in the brain assessed by positron emission tomography (PET), and on the concentration of biomarkers in the cerebrospinal fluid (β-amyloid peptide with 42 amino acids and hyperphosphorylated tau protein) than in the neuropsychological and functional assessments. Even this small clinical effect will be encouraging for the development of new research, particularly helped by the greater ease of diagnosis and monitoring of the evolution of AD pathophysiology with plasma biomarkers. Recently, new diagnostic criteria for AD were presented by the Alzheimer's Association, causing controversy about their use in clinical practice.

The clinical importance of suspected non-Alzheimer disease pathophysiology

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

Cognitive trajectories preluding the onset of different dementia entities: a descriptive longitudinal study using the NACC database

OBJECTIVE

To describe the 10-year preclinical cognitive trajectories of older, non-demented individuals towards the onset of the four most prevalent types of dementia, i.e., Alzheimer's disease(AD), Lewy body(LBD), vascular(VD) and frontotemporal dementia(FTD).

METHODS

Our analysis focused on data from older (≥ 60years) NACC (National Alzheimer's Coordinating Center) participants. Four distinct presymptomatic dementia groups (AD-LBD-VD-FTD) and a comparison group of cognitively unimpaired(CU) participants were formed. Comprehensive cognitive assessments involving verbal episodic memory, semantic verbal fluency, confrontation naming, mental processing speed - attention and executive function - cognitive flexibility were conducted at baseline and on an approximately yearly basis. Descriptive analyses (adjusted general linear models) were performed to determine and compare the yearly cognitive scores of each group throughout the follow-up. Exploratory analyses were conducted to estimate the rates of cognitive decline.

RESULTS

There were 3343 participants who developed AD, 247 LBD, 108 FTD, 155 VD and 3398 composed the CU group. Participants with AD performed worse on episodic memory than those with VD and LBD for about 3 to 4 years prior to dementia onset (the FTD group documented an intermediate course). Presymptomatic verbal fluency and confrontation naming trajectories differentiated quite well between the FTD group and the remaining dementia entities. Participants with incident LBD and VD performed worse than those with AD on executive functions and mental processing speed-attention since about 5 years prior to the onset of dementia, and worse than those with FTD more proximally to the diagnosis of the disorder.

CONCLUSIONS

Heterogeneous cognitive trajectories characterize the presymptomatic courses of the most prevalent dementia entities.

The Taxonomy of Subjective Cognitive Decline: Proposal and First Clinical Evidence from the Geneva Memory Clinic Cohort

INTRODUCTION

Subjective cognitive decline (SCD) is characterized by subjective cognitive concerns without objective cognitive impairment and is considered a risk factor for cognitive decline and dementia. However, most SCD patients will not develop neurodegenerative disorders, yet they may suffer from minor psychiatric, neurological, or somatic comorbidities. The aim of the present study was to provide a taxonomy of the heterogeneous SCD entity and to conduct a preliminary validation using data from a memory clinic sample.

METHODS

Participants were fifty-five SCD individuals consecutively recruited at the Geneva Memory Center. Based on clinical reports, they were classified into three clinically pre-defined subgroups: (i) those with psychological or psychiatric comorbidities (Psy), (ii) those with somatic comorbidities (SomCom), (iii) and those with no apparent cause (NAC). Baseline demographics, clinical, cognitive, and biomarker differences among the SCD subgroups were assessed. Longitudinal cognitive changes (average 3 years follow-up) were modeled using a linear mixed model.

RESULTS

Out of the 55 SCD cases, 16 were SomCom, 18 Psy, and 21 NAC. 47% were female, mean age was 71 years. We observed higher frequency of APOE ε4 carriers in NAC (53%) compared to SomCom (14%) and Psy (0%, p = 0.023) and lower level of plasma Aβ42 in NAC (6.8 ± 1.0) compared to SomCom (8.4 ± 1.1; p = 0.031). SomCom subjects were older (74 years) than Psy (67 years, p = 0.011), and had greater medial temporal lobe atrophy (1.0 ± 1.0) than Psy (0.2 ± 0.6) and NAC (0.4 ± 0.5, p = 0.005). SomCom has worse episodic memory performances (14.5 ± 3.5) than Psy (15.8 ± 0.4) and NAC (15.8 ± 0.7, p = 0.032). We observed a slightly steeper, yet not statistically significant, cognitive decline in NAC (β = -0.48) compared to Psy (β = -0.28) and SomCom (β = -0.24).

CONCLUSIONS

NAC features a higher proportion of APOE ε4 carriers, lower plasma Aβ42 and a trend towards steeper cognitive decline than SomCom and Psy. Taken together, these findings suggest that NACs are at higher risk of cognitive decline due to AD. The proposed clinical taxonomy might be implemented in clinical practice to identify SCD at higher risk. However, such taxonomy should be tested on an independent cohort with a larger sample size.

Future perspective and clinical applicability of the combined use of plasma phosphorylated tau 181 and neurofilament light chain in Subjective Cognitive Decline and Mild Cognitive Impairment

We aimed to assess diagnostic accuracy of plasma p-tau181 and NfL separately and in combination in discriminating Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) patients carrying Alzheimer's Disease (AD) pathology from non-carriers; to propose a flowchart for the interpretation of the results of plasma p-tau181 and NfL. We included 43 SCD, 41 MCI and 21 AD-demented (AD-d) patients, who underwent plasma p-tau181 and NfL analysis. Twenty-eight SCD, 41 MCI and 21 AD-d patients underwent CSF biomarkers analysis (Aβ1-42, Aβ1-42/1-40, p-tau, t-tau) and were classified as carriers of AD pathology (AP+) it they were A+/T+ , or non-carriers (AP-) when they were A-, A+/T-/N-, or A+/T-/N+ according to the A/T(N) system. Plasma p-tau181 and NfL separately showed a good accuracy (AUC = 0.88), while the combined model (NfL + p-tau181) showed an excellent accuracy (AUC = 0.92) in discriminating AP+ from AP- patients. Plasma p-tau181 and NfL results were moderately concordant (Coehn's k = 0.50, p < 0.001). Based on a logistic regression model, we estimated the risk of AD pathology considering the two biomarkers: 10.91% if both p-tau181 and NfL were negative; 41.10 and 76.49% if only one biomarker was positive (respectively p-tau18 and NfL); 94.88% if both p-tau181 and NfL were positive. Considering the moderate concordance and the risk of presenting an underlying AD pathology according to the positivity of plasma p-tau181 and NfL, we proposed a flow chart to guide the combined use of plasma p-tau181 and NfL and the interpretation of biomarker results to detect AD pathology.

Cerebral Amyloidosis in Individuals with Subjective Cognitive Decline: From Genetic Predisposition to Actual Cerebrospinal Fluid Measurements

The possible relationship between Subjective Cognitive Decline (SCD) and dementia needs further investigation. In the present study, we explored the association between specific biomarkers of Alzheimer's Disease (AD), amyloid-beta 42 (Aβ42) and Tau with the odds of SCD using data from two ongoing studies. In total, 849 cognitively normal (CN) individuals were included in our analyses. Among the participants, 107 had available results regarding cerebrospinal fluid (CSF) Aβ42 and Tau, while 742 had available genetic data to construct polygenic risk scores (PRSs) reflecting their genetic predisposition for CSF Aβ42 and plasma total Tau levels. The associations between AD biomarkers and SCD were tested using logistic regression models adjusted for possible confounders such as age, sex, education, depression, and baseline cognitive test scores. Abnormal values of CSF Aβ42 were related to 2.5-fold higher odds of SCD, while higher polygenic loading for Aβ42 was associated with 1.6-fold higher odds of SCD. CSF Tau, as well as polygenic loading for total Tau, were not associated with SCD. Thus, only cerebral amyloidosis appears to be related to SCD status, either in the form of polygenic risk or actual CSF measurements. The temporal sequence of amyloidosis being followed by tauopathy may partially explain our findings.

The relation of a cerebrospinal fluid profile associated with Alzheimer's disease with cognitive function and neuropsychiatric symptoms in sporadic cerebral amyloid angiopathy

BACKGROUND

Patients with sporadic cerebral amyloid angiopathy (sCAA) frequently report cognitive or neuropsychiatric symptoms. The aim of this study is to investigate whether in patients with sCAA, cognitive impairment and neuropsychiatric symptoms are associated with a cerebrospinal fluid (CSF) biomarker profile associated with Alzheimer's disease (AD).

METHODS

In this cross-sectional study, we included participants with sCAA and dementia- and stroke-free, age- and sex-matched controls, who underwent a lumbar puncture, brain MRI, cognitive assessments, and self-administered and informant-based-questionnaires on neuropsychiatric symptoms. CSF phosphorylated tau, total tau and Aβ42 levels were used to divide sCAA patients in two groups: CAA with (CAA-AD+) or without a CSF biomarker profile associated with AD (CAA-AD-). Performance on global cognition, specific cognitive domains (episodic memory, working memory, processing speed, verbal fluency, visuoconstruction, and executive functioning), presence and severity of neuropsychiatric symptoms, were compared between groups.

RESULTS

sCAA-AD+ (n=31; mean age: 72 ± 6; 42%, 61% female) and sCAA-AD- (n=23; 70 ± 5; 42% female) participants did not differ with respect to global cognition or type of affected cognitive domain(s). The number or severity of neuropsychiatric symptoms also did not differ between sCAA-AD+ and sCAA-AD- participants. These results did not change after exclusion of patients without prior ICH.

CONCLUSIONS

In participants with sCAA, a CSF biomarker profile associated with AD does not impact global cognition or specific cognitive domains, or the presence of neuropsychiatric symptoms.

Real-word application of the AT(N) classification and disease-modifying treatment eligibility in a hospital-based cohort

BACKGROUND AND OBJECTIVES

The AT(N) classification system stratifies patients based on biomarker profiles, including amyloid-beta deposition (A), tau pathology (T), and neurodegeneration (N). This study aims to apply the AT(N) classification to a hospital-based cohort of patients with cognitive decline and/or dementia, within and outside the Alzheimer's disease (AD) continuum, to enhance our understanding of the multidimensional aspects of AD and related disorders. Furthermore, we wish to investigate how many cases from our cohort would be eligible for the available disease modifying treatments, such as aducanemab and lecanemab.

METHODS

We conducted a retrospective evaluation of 429 patients referred to the Memory Center of IRCCS San Raffaele Hospital in Milan. Patients underwent clinical/neuropsychological assessments, lumbar puncture, structural brain imaging, and positron emission tomography (FDG-PET). Patients were stratified according to AT(N) classification, group comparisons were performed and the number of eligible cases for anti-β amyloid monoclonal antibodies was calculated.

RESULTS

Sociodemographic and clinical features were similar across groups. The most represented group was A + T + N + accounting for 38% of cases, followed by A + T - N + (21%) and A - T - N + (20%). Although the clinical presentation was similar, the A + T + N + group showed more severe cognitive impairment in memory, language, attention, executive, and visuospatial functions compared to other AT(N) groups. Notably, T + patients demonstrated greater memory complaints compared to T -  cases. FDG-PET outperformed MRI and CT in distinguishing A + from A -  patients. Although 61% of the observed cases were A + , only 17% of them were eligible for amyloid-targeting treatments.

DISCUSSION

The AT(N) classification is applicable in a real-world clinical setting. The classification system provided insights into clinical management and treatment strategies. Low cognitive performance and specific regional FDG-PET hypometabolism at diagnosis are highly suggestive for A + T + or A - T + profiles. This work provides also a realistic picture of the proportion of AD patients eligible for disease modifying treatments emphasizing the need for early detection.

Alzheimer disease biomarkers are associated with decline in subjective memory, attention, and spatial navigation ability in clinically normal adults

OBJECTIVE

Subtle changes in memory, attention, and spatial navigation abilities have been associated with preclinical Alzheimer disease (AD). The current study examined whether baseline AD biomarkers are associated with self- and informant-reported decline in memory, attention, and spatial navigation.

METHOD

Clinically normal (Clinical Dementia Rating Scale (CDR®) = 0) adults aged 56-93 (N = 320) and their informants completed the memory, divided attention, and visuospatial abilities (which assesses spatial navigation) subsections of the Everyday Cognition Scale (ECog) annually for an average of 4 years. Biomarker data was collected within (±) 2 years of baseline (i.e., cerebrospinal fluid (CSF) p-tau181/Aβ42 ratio and hippocampal volume). Clinical progression was defined as CDR > 0 at time of final available ECog.

RESULTS

Self- and informant-reported memory, attention, and spatial navigation significantly declined over time (ps < .001). Baseline AD biomarkers were significantly associated with self- and informant-reported decline in cognitive ability (ps < .030), with the exception of p-tau181/Aβ42 ratio and self-reported attention (p = .364). Clinical progression did not significantly moderate the relationship between AD biomarkers and decline in self- or informant-reported cognitive ability (ps > .062). Post-hoc analyses indicated that biomarker burden was also associated with self- and informant-reported decline in total ECog (ps < .002), and again clinical progression did not significantly moderate these relationships (ps > .299).

CONCLUSIONS

AD biomarkers at baseline may indicate risk of decline in self- and informant-reported change in memory, attention, and spatial navigation ability. As such, subjectively reported decline in these domains may have clinical utility in tracking the subtle cognitive changes associated with the earliest stages of AD.

Risk of conversion to mild cognitive impairment or dementia among subjects with amyloid and tau pathology: a systematic review and meta-analysis

BACKGROUND

Measurement of beta-amyloid (Aβ) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination.

METHODS

A systematic search of prospective and retrospective studies investigating the association of Aβ and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature.

RESULTS

A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled (n= 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aβ42 or Aβ42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aβ exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]).

CONCLUSIONS

Identifying Aβ-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aβ, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aβ decreases with age.

TRIAL REGISTRATION

The study was registered in PROSPERO (ID: CRD42021288100).

Blood levels of glial fibrillary acidic protein for predicting clinical progression to Alzheimer's disease in adults without dementia: a systematic review and meta-analysis protocol

BACKGROUND

There is urgent clinical need to identify reliable prognostic biomarkers that predict the progression of dementia symptoms in individuals with early-phase Alzheimer's disease (AD) especially given the research on and predicted applications of amyloid-beta (Aβ)-directed immunotherapies to remove Aβ from the brain. Cross-sectional studies have reported higher levels of cerebrospinal fluid and blood glial fibrillary acidic protein (GFAP) in individuals with AD-associated dementia than in cognitively unimpaired individuals. Further, recent longitudinal studies have assessed the prognostic potential of baseline blood GFAP levels as a predictor of future cognitive decline in cognitively unimpaired individuals and in those with mild cognitive impairment (MCI) due to AD. In this systematic review and meta-analysis, we propose analyzing longitudinal studies on blood GFAP levels to predict future cognitive decline.

METHODS

This study will include prospective and retrospective cohort studies that assessed blood GFAP levels as a prognostic factor and any prediction models that incorporated blood GFAP levels in cognitively unimpaired individuals or those with MCI. The primary outcome will be conversion to MCI or AD in cognitively unimpaired individuals or conversion to AD in individuals with MCI. Articles from PubMed and Embase will be extracted up to December 31, 2023, without language restrictions. An independent dual screening of abstracts and potentially eligible full-text reports will be conducted. Data will be dual-extracted using the CHeck list for critical appraisal, data extraction for systematic Reviews of prediction Modeling Studies (CHARMS)-prognostic factor, and CHARMS checklists, and we will dual-rate the risk of bias and applicability using the Quality In Prognosis Studies and Prediction Study Risk-of-Bias Assessment tools. We will qualitatively synthesize the study data, participants, index biomarkers, predictive model characteristics, and clinical outcomes. If appropriate, random-effects meta-analyses will be performed to obtain summary estimates. Finally, we will assess the body of evidence using the Grading of Recommendation, Assessment, Development, and Evaluation Approach.

DISCUSSION

This systematic review and meta-analysis will comprehensively evaluate and synthesize existing evidence on blood GFAP levels for prognosticating presymptomatic individuals and those with MCI to help advance risk-stratified treatment strategies for early-phase AD.

TRIAL REGISTRATION

PROSPERO CRD42023481200.

Comparison of plasma biomarkers and amyloid PET for predicting memory decline in cognitively unimpaired individuals

BACKGROUND

We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals.

METHODS

We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E (APOE) ε4 genotype, amyloid PET, and plasma amyloid beta (Aβ)42/40, phosphorylated tau (p-tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p-tau217. The outcome was a change in a memory composite measure.

RESULTS

All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p-tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person-level prediction intervals were wide.

DISCUSSION

Plasma p-tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.

Modifiable dementia risk factors and AT(N) biomarkers: findings from the EPAD cohort

Introduction

Modifiable risk factors account for a substantial proportion of Alzheimer's disease (AD) cases and we currently have a discrete AT(N) biomarker profile for AD biomarkers: amyloid (A), p-tau (T), and neurodegeneration (N). Here, we investigated how modifiable risk factors relate to the three hallmark AT(N) biomarkers of AD.

Methods

Participants from the European Prevention of Alzheimer's Dementia (EPAD) study underwent clinical assessments, brain magnetic resonance imaging, and cerebrospinal fluid collection and analysis. Generalized additive models (GAMs) with penalized regression splines were modeled in the AD Workbench on the NTKApp.

Results

A total of 1,434 participants were included (56% women, 39% APOE ε4+) with an average age of 65.5 (± 7.2) years. We found that modifiable risk factors of less education (t = 3.9, p < 0.001), less exercise (t = 2.1, p = 0.034), traumatic brain injury (t = -2.1, p = 0.036), and higher body mass index (t = -4.5, p < 0.001) were all significantly associated with higher AD biomarker burden.

Discussion

This cross-sectional study provides further support for modifiable risk factors displaying neuroprotective associations with the characteristic AT(N) biomarkers of AD.

Assessment of immunoprecipitation with subsequent immunoassays for the blood-based diagnosis of Alzheimer's disease

The Aβ42/40 ratio and the concentration of phosphorylated Tau181 in blood plasma represent attractive biomarkers for Alzheimer's disease. As a means for reducing potential matrix effects, which may interfere with plasma immunoassays, we have previously developed a pre-analytical sample workup by semi-automated immunoprecipitation. Here we test the compatibility of pre-analytical immunoprecipitations with automated Aβ1-40, Aβ1-42 and phosphorylated Tau181 immunoassays on the Lumipulse platform and compare the diagnostic performance of the respective immunoprecipitation immunoassay approaches with direct plasma measurements. 71 participants were dichotomized according to their Aβ42/40 ratios in cerebrospinal fluid into the diagnostic groups amyloid-positive (n = 32) and amyloid-negative (n = 39). The plasma Aβ1-42/1-40 ratio and phosphorylated Tau181 levels were determined on the Lumipulse G600II platform (Fujirebio) by direct measurements in EDTA-plasma or after Aβ- or Tau-immunoprecipitation, respectively. Pre-analytical immunoprecipitation of Aβ turned out to be compatible with the Lumipulse Aβ assays and resulted in a numerical, yet statistically not significant increase in the area under the ROC curve for plasma Aβ1-42/1-40. Additionally, we observed a significant increase in the standardised effect size (Cohen's D). Pre-analytical immunoprecipitation of Tau resulted in increased differences between the diagnostic groups in terms of median and mean phosphorylated Tau 181 levels. Furthermore, we observed a greater Cohen's d (p < 0.001) and a larger area under the ROC curve (p = 0.038) after Tau-IP. Our preliminary findings in a small, preselected sample indicate that pre-analytical immunoprecipitation may have the potential to improve the diagnostic performance of plasma biomarker immunoassays for Aβ1-42/1-40 and phosphorylated Tau181 to predict brain amyloid deposition.

Degeneration of the cholinergic system in individuals with subjective cognitive decline: A systematic review

BACKGROUND

Subjective cognitive decline (SCD) is a risk factor for future cognitive impairment and dementia. It is uncertain whether the neurodegeneration of the cholinergic system is already present in SCD individuals. We aimed to review the current evidence about the association between SCD and biomarkers of degeneration in the cholinergic system.

METHOD

Original articles were extracted from three databases: Pubmed, Web of Sciences, and Scopus, in January 2023. Two researchers screened the studies independently.

RESULTS

A total of 11 research articles were selected. SCD was mostly based on amnestic cognitive complaints. Cholinergic system biomarkers included neuroimaging markers of basal forebrain volume, functional connectivity, transcranial magnetic stimulation, or biofluid. The evidence showed associations between basal forebrain atrophy, poorer connectivity of the cholinergic system, and SCD CONCLUSIONS: Degenerative changes in the cholinergic system can be present in SCD. Subjective complaints may help when identifying individuals with brain changes that are associated with cognitive impairment. These findings may have important implications in targeting individuals that may benefit from cholinergic-target treatments at very early stages of neurodegenerative diseases.

A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers

AIMS

The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values.

METHODS

We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aβ(1-42), Aβ(1-42)/Aβ(1-40) ratio, tTau, and pTau.

RESULTS

The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia.

CONCLUSION

We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.

Plasma pTau-217 and N-terminal tau (NTA) enhance sensitivity to identify tau PET positivity in amyloid-β positive individuals

INTRODUCTION

We set out to identify tau PET-positive (A+T+) individuals among amyloid-beta (Aβ) positive participants using plasma biomarkers.

METHODS

In this cross-sectional study we assessed 234 participants across the AD continuum who were evaluated by amyloid PET with [18 F]AZD4694 and tau-PET with [18 F]MK6240 and measured plasma levels of total tau, pTau-181, pTau-217, pTau-231, and N-terminal tau (NTA-tau). We evaluated the performances of plasma biomarkers to predict tau positivity in Aβ+ individuals.

RESULTS

Highest associations with tau positivity in Aβ+ individuals were found for plasma pTau-217 (AUC [CI95% ] = 0.89 [0.82, 0.96]) and NTA-tau (AUC [CI95% ] = 0.88 [0.91, 0.95]). Combining pTau-217 and NTA-tau resulted in the strongest agreement (Cohen's Kappa = 0.74, CI95%  = 0.57/0.90, sensitivity = 92%, specificity = 81%) with PET for classifying tau positivity.

DISCUSSION

The potential for identifying tau accumulation in later Braak stages will be useful for patient stratification and prognostication in treatment trials and in clinical practice.

HIGHLIGHTS

We found that in a cohort without pre-selection pTau-181, pTau-217, and NTA-tau showed the highest association with tau PET positivity. We found that in Aβ+ individuals pTau-217 and NTA-tau showed the highest association with tau PET positivity. Combining pTau-217 and NTA-tau resulted in the strongest agreement with the tau PET-based classification.