Prediction of Longitudinal Cognitive Decline in Preclinical Alzheimer Disease Using Plasma Biomarkers

Longitudinal plasma phosphorylated-tau217 and other related biomarkers in a non-demented Alzheimer's risk-enhanced sample

INTRODUCTION

Understanding longitudinal change in key plasma biomarkers will aid in detecting presymptomatic Alzheimer's disease (AD).

METHODS

Serial plasma samples from 424 Wisconsin Registry for Alzheimer's Prevention participants were analyzed for phosphorylated-tau217 (p-tau217; ALZpath) and other AD biomarkers, to study longitudinal trajectories in relation to disease, health factors, and cognitive decline. Of the participants, 18.6% with known amyloid status were amyloid positive (A+); 97.2% were cognitively unimpaired (CU).

RESULTS

In the CU, amyloid-negative (A-) subset, plasma p-tau217 levels increased modestly with age but were unaffected by body mass index and kidney function. In the whole sample, average p-tau217 change rates were higher in those who were A+ (e.g., simple slopes(se) for A+ and A- at age 60 were 0.232(0.028) and 0.038(0.013))). High baseline p-tau217 levels predicted faster preclinical cognitive decline.

DISCUSSION

p-tau217 stands out among markers for its strong association with disease and cognitive decline, indicating its potential for early AD detection and monitoring progression.

HIGHLIGHTS

Phosphorylated-tau217 (p-tau217) trajectories were significantly different in people who were known to be amyloid positive. Subtle age-related trajectories were seen for all the plasma markers in amyloid-negative cognitively unimpaired. Kidney function and body mass index were not associated with plasma p-tau217 trajectories. Higher plasma p-tau217 was associated with faster preclinical cognitive decline.

Ethical Considerations for Identifying Individuals in the Prodromal/Early Phase of Parkinson's Disease: A Narrative Review

The ability to identify individuals in the prodromal phase of Parkinson's disease has improved in recent years, raising the question of whether and how those affected should be informed about the risk of future disease. Several studies investigated prognostic counselling for individuals with isolated REM sleep behavior disorder and have shown that most patients want to receive information about prognosis, but autonomy and individual preferences must be respected. However, there are still many unanswered questions about risk disclosure or early diagnosis of PD, including the impact on personal circumstances, cultural preferences and specific challenges associated with different profiles of prodromal symptoms, genetic testing or biomarker assessments. This narrative review aims to summarize the current literature on prognostic counselling and risk disclosure in PD, as well as highlight future perspectives that may emerge with the development of new biomarkers and their anticipated impact on the definition of PD.

The associations between nutritional status and physical frailty and Alzheimer's disease plasma biomarkers in older cognitively unimpaired adults with positive of amyloid-β PET

BACKGROUND & AIMS

It has been revealed good nutritional status and no physical frailty, which are modifiable lifestyle factors, are linked to less cognitive decline and a lower risk of Alzheimer's disease (AD). We aimed to investigate the associations between nutritional status and physical frailty and plasma AD biomarkers, especially the Tau-associated biomarkers in older cognitively unimpaired (CU) adults with higher β-amyloid (Aβ) burden.

METHODS

The nutritional status and physical frailty were assessed via Mini-Nutritional Assessment Short-Form (MNA-SF) and Fried frailty index. The participants underwent the examination of plasma AD biomarkers and 18F-florbetapir PET scan as well as 18F-MK6240 PET in the validation cohort. Correlation and multiple linear regression analyses were used to investigate the associations between nutritional status and frailty and AD biomarkers.

RESULTS

Two cohorts were included in our study. A total of 129 participants with Aβ-PET positive were enrolled in the development cohort. Multiple linear regression analysis showed MNA-SF scores, normal nutritional status, Fried frailty index scores, frailty and some domains of frailty including weight loss, maximal grip strength and exhaustion were associated with plasma p-Tau-181. Furthermore, weight loss, Fried frailty index scores and frailty were associated with higher Aβ-PET standard uptake value ratio. We further performed subgroup analyses stratified by age, sex and apolipoprotein E ε4 genotype to investigate the beneficial characteristics of nutrition and frailty in the special subgroups. Validation cohort contained 38 Aβ-PET positive participants. MNA-SF scores, normal nutritional status, Fried frailty index scores and frailty were associated with Tau burden evaluated by 18F-MK6240 PET Braak-like stages.

CONCLUSIONS

Our data indicates that normal nutritional status and no physical frailty may be associated with expected trend of plasma AD biomarkers, especially less Tau pathology in older CU adults with Aβ deposition. Adjusting to these characteristics of nutrition and physical frailty may help reduce the risk of AD development.

Plasma amyloid beta X-42/X-40 ratio and cognitive decline in suspected early and preclinical Alzheimer's disease

INTRODUCTION

Blood-based biomarkers are a cost-effective and minimally invasive method for diagnosing the early and preclinical stages of amyloid positivity (AP). Our study aims to investigate our novel immunoprecipitation-immunoassay (IP-IA) as a test for predicting cognitive decline.

METHODS

We measured levels of amyloid beta (Aβ)X-40 and AβX-42 in immunoprecipitated eluates from the DELCODE cohort. Receiver-operating characteristic (ROC) curves, regression analyses, and Cox proportional hazard regression models were constructed to predict AP by Aβ42/40 classification in cerebrospinal fluid (CSF) and conversion to mild cognitive impairment (MCI) or dementia.

RESULTS

We detected a significant correlation between AßX-42/X-40 in plasma and CSF (r = 0.473). Mixed-modeling analysis revealed a substantial prediction of AßX-42/X-40 with an area under the curve (AUC) of 0.81 for AP (sensitivity: 0.79, specificity: 0.74, positive predictive value [PPV]: 0.71, negative predictive value [NPV]: 0.81). In addition, lower AβX-42/X-40 ratios were associated with negative PACC5 slopes, suggesting cognitive decline.

DISCUSSION

Our results suggest that assessing the plasma AβX-42/X-40 ratio via our semiautomated IP-IA is a promising biomarker when examining patients with early or preclinical AD.

HIGHLIGHTS

New plasma Aβ42/Aβ40 measurement using immunoprecipitation-immunoassay Plasma Aβ42/Aβ40 associated with longitudinal cognitive decline Promising biomarker to detect subjective cognitive decline at-risk for brain amyloid positivity.

Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease

BACKGROUND

This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aβ) 42/Aβ40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening.

METHODS

Quantification of plasma pTau217R and Aβ42/Aβ40 employed immunoprecipitation-mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts.

RESULTS

Models integrating pTau217R outperformed Aβ42/Aβ40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R-based models for low amyloid levels reduced PET scans by 70.5% to 78.6%.

DISCUSSION

pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aβ42/Aβ40's range. Combining it with plasma Aβ42/Aβ40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility.

HIGHLIGHTS

Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid-PET Centiloid (CL) across a broad spectrum. Integrating pTau217R with Aβ42/Aβ40 extends the CL prediction upper limit to 89.1 CL. Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals. This model identifies subjects above or below various CL thresholds with high accuracy. pTau217R-based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid.

Diagnostic performance of plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease

BACKGROUND

Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown.

METHODS

We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A +) or negative (A-) according to CSF Aβ1-42/Aβ1-40 ratio. Plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aβ1-42/Aβ1-40 ratio. We analyzed the concordance of pTau217 with CSF amyloidosis.

RESULTS

Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aβ1-42/Aβ1-40 ratio was lower in A + compared to A-. pTau181 and the Aβ1-42/Aβ1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aβ1-42/Aβ1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (× 3.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%.

CONCLUSION

The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Associations Between Self and Study Partner Report of Cognitive Decline With Regional Tau in a Multicohort Study

BACKGROUND AND OBJECTIVES

Self-reported cognitive decline is an early behavioral manifestation of Alzheimer disease (AD) at the preclinical stage, often believed to precede concerns reported by a study partner. Previous work shows cross-sectional associations with β-amyloid (Aβ) status and self-reported and study partner-reported cognitive decline, but less is known about their associations with tau deposition, particularly among those with preclinical AD.

METHODS

This cross-sectional study included participants from the Anti-Amyloid Treatment in Asymptomatic AD/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration studies (N = 444) and the Harvard Aging Brain Study and affiliated studies (N = 231), which resulted in a cognitively unimpaired (CU) sample of individuals with both nonelevated (Aβ-) and elevated Aβ (Aβ+). All participants and study partners completed the Cognitive Function Index (CFI). Two regional tau composites were derived by averaging flortaucipir PET uptake in the medial temporal lobe (MTL) and neocortex (NEO). Global Aβ PET was measured in Centiloids (CLs) with Aβ+ >26 CL. We conducted multiple linear regression analyses to test associations between tau PET and CFI, covarying for amyloid, age, sex, education, and cohort. We also controlled for objective cognitive performance, measured using the Preclinical Alzheimer Cognitive Composite (PACC).

RESULTS

Across 675 CU participants (age = 72.3 ± 6.6 years, female = 59%, Aβ+ = 60%), greater tau was associated with greater self-CFI (MTL: β = 0.28 [0.12, 0.44], p < 0.001, and NEO: β = 0.26 [0.09, 0.42], p = 0.002) and study partner CFI (MTL: β = 0.28 [0.14, 0.41], p < 0.001, and NEO: β = 0.31 [0.17, 0.44], p < 0.001). Significant associations between both CFI measures and MTL/NEO tau PET were driven by Aβ+. Continuous Aβ showed an independent effect on CFI in addition to MTL and NEO tau for both self-CFI and study partner CFI. Self-CFI (β = 0.01 [0.001, 0.02], p = 0.03), study partner CFI (β = 0.01 [0.003, 0.02], p = 0.01), and the PACC (β = -0.02 [-0.03, -0.01], p < 0.001) were independently associated with MTL tau, but for NEO tau, PACC (β = -0.02 [-0.03, -0.01], p < 0.001) and study partner report (β = 0.01 [0.004, 0.02], p = 0.002) were associated, but not self-CFI (β = 0.01 [-0.001, 0.02], p = 0.10).

DISCUSSION

Both self-report and study partner report showed associations with tau in addition to Aβ. Additionally, self-report and study partner report were associated with tau above and beyond performance on a neuropsychological composite. Stratification analyses by Aβ status indicate that associations between self-reported and study partner-reported cognitive concerns with regional tau are driven by those at the preclinical stage of AD, suggesting that both are useful to collect on the early AD continuum.

Remote and unsupervised digital memory assessments can reliably detect cognitive impairment in Alzheimer's disease

INTRODUCTION

Remote unsupervised cognitive assessments have the potential to complement and facilitate cognitive assessment in clinical and research settings.

METHODS

Here, we evaluate the usability, validity, and reliability of unsupervised remote memory assessments via mobile devices in individuals without dementia from the Swedish BioFINDER-2 study and explore their prognostic utility regarding future cognitive decline.

RESULTS

Usability was rated positively; remote memory assessments showed good construct validity with traditional neuropsychological assessments and were significantly associated with tau-positron emission tomography and downstream magnetic resonance imaging measures. Memory performance at baseline was associated with future cognitive decline and prediction of future cognitive decline was further improved by combining remote digital memory assessments with plasma p-tau217. Finally, retest reliability was moderate for a single assessment and good for an aggregate of two sessions.

DISCUSSION

Our results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers.

HIGHLIGHTS

Remote and unsupervised digital memory assessments are feasible in older adults and individuals in early stages of Alzheimer's disease. Digital memory assessments are associated with neuropsychological in-clinic assessments, tau-positron emission tomography and magnetic resonance imaging measures. Combination of digital memory assessments with plasma p-tau217 holds promise for prognosis of future cognitive decline. Future validation in further independent, larger, and more diverse cohorts is needed to inform clinical implementation.

Alzheimer disease blood biomarkers: considerations for population-level use

In the past 5 years, we have witnessed the first approved Alzheimer disease (AD) disease-modifying therapy and the development of blood-based biomarkers (BBMs) to aid the diagnosis of AD. For many reasons, including accessibility, invasiveness and cost, BBMs are more acceptable and feasible for patients than a lumbar puncture (for cerebrospinal fluid collection) or neuroimaging. However, many questions remain regarding how best to utilize BBMs at the population level. In this Review, we outline the factors that warrant consideration for the widespread implementation and interpretation of AD BBMs. To set the scene, we review the current use of biomarkers, including BBMs, in AD. We go on to describe the characteristics of typical patients with cognitive impairment in primary care, who often differ from the patient populations used in AD BBM research studies. We also consider factors that might affect the interpretation of BBM tests, such as comorbidities, sex and race or ethnicity. We conclude by discussing broader issues such as ethics, patient and provider preference, incidental findings and dealing with indeterminate results and imperfect accuracy in implementing BBMs at the population level.

Progress on early diagnosing Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.

Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease

BACKGROUND AND PURPOSE

A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD.

METHODS

Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5).

RESULTS

Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language.

CONCLUSION

This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.

Fluid biomarkers unveil signatures of pathological aging

Aging is a multifaceted and highly varied process in the brain. Identifying aging biomarkers is one means of distinguishing pathological from physiological aging. The aim of this narrative review is to focus on two new developments in the field of fluid biomarkers and draw attention to this excellent tool for the early detection of potential brain pathologies that delay, alter, or enable physiological aging to become pathological. Pathological aging can lower the threshold for the development of specific diseases such as late-onset epilepsy. Fluid biomarkers can reveal pathological levels at an early stage and thus indicate disease processes in the brain that begin before symptoms develop; they thus differ from physiological aging.

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.

Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients

BACKGROUND

Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI).

METHODS

Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity.

RESULTS

Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity.

CONCLUSIONS

Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.

Plasma p-tau217 predicts cognitive impairments up to ten years before onset in normal older adults

Importance

Positron emission tomography (PET) biomarkers are the gold standard for detection of Alzheimer amyloid and tau in vivo . Such imaging can identify cognitively unimpaired (CU) individuals who will subsequently develop cognitive impartment (CI). Plasma biomarkers would be more practical than PET or even cerebrospinal fluid (CSF) assays in clinical settings.

Objective

Assess the prognostic accuracy of plasma p-tau217 in comparison to CSF and PET biomarkers for predicting the clinical progression from CU to CI.

Design

In a cohort of elderly at high risk of developing Alzheimer's dementia (AD), we measured the proportion of CU individuals who developed CI, as predicted by Aβ (A+) and/or tau (T+) biomarker assessment from plasma, CSF, and PET. Results from each method were compared with (A-T-) reference individuals. Data were analyzed from June 2023 to April 2024.

Setting

Longitudinal observational cohort.

Participants

Some 228 participants from the PREVENT-AD cohort were CU at the time of biomarker assessment and had 1 - 10 years of follow-up. Plasma was available from 215 participants, CSF from 159, and amyloid- and tau-PET from 155. Ninety-three participants had assessment using all three methods (main group of interest). Progression to CI was determined by clinical consensus among physicians and neuropsychologists who were blind to plasma, CSF, PET, and MRI findings, as well as APOE genotype.

Exposures

Plasma Aβ 42/40 was measured using IP-MS; CSF Aβ 42/40 using Lumipulse; plasma and CSF p-tau217 using UGOT assay. Aβ-PET employed the 18 F-NAV4694 ligand, and tau-PET used 18 F-flortaucipir.

Main Outcome

Prognostic accuracy of plasma, CSF, and PET biomarkers for predicting the development of CI in CU individuals.

Results

Cox proportional hazard models indicated a greater progression rate in all A+T+ groups compared to A-T-groups (HR = 6.61 [95% CI = 2.06 - 21.17] for plasma, 3.62 [1.49 - 8.81] for CSF and 9.24 [2.34 - 36.43] for PET). The A-T+ groups were small, but also characterized with individuals who developed CI. Plasma biomarkers identified about five times more T+ than PET.

Conclusion and relevance

Plasma p-tau217 assessment is a practical method for identification of persons who will develop cognitive impairment up to 10 years later.

Key Points

Question: Can plasma p-tau217 serve as a prognostic indicator for identifying cognitively unimpaired (CU) individuals at risk of developing cognitive impairments (CI)?Findings: In a longitudinal cohort of CU individuals with a family history of sporadic AD, almost all individuals with abnormal plasma p-tau217 concentrations developed CI within 10 years, regardless of plasma amyloid levels. Similar findings were obtained with CSF p-tau217 and tau-PET. Fluid p-tau217 biomarkers had the main advantage over PET of identifying five times more participants with elevated tau.Meaning: Elevated plasma p-tau217 levels in CU individuals strongly indicate future clinical progression.

Disease staging of Alzheimer's disease using a CSF-based biomarker model

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aβ42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aβ-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics

The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aβ), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.

Associations Between Blood-Based Biomarkers and Cognitive and Functional Trajectories Among Participants of the MEMENTO Cohort

BACKGROUND AND OBJECTIVES

Elevated levels of Alzheimer disease (AD) blood-based biomarkers are associated with accelerated cognitive decline. However, their distinct relationships with specific cognitive and functional domains require further investigation. We aimed at estimating the associations between AD blood-based biomarkers and the trajectories of distinct cognitive and functional domains over a 5-year follow-up period.

METHODS

We conducted a clinic-based prospective study using data from the MEMENTO study, a nationwide French cohort. We selected dementia-free individuals at baseline aged 60 years or older. Baseline measurements of β-amyloid (Aβ) 40 and 42, phosphorylated tau (p-tau181), and neurofilament light chain (NfL) concentrations were obtained using the Simoa HD-X analyzer. Mini-Mental State Examination (MMSE), Free and Cued Selective Reminding Test (FCSRT), animal fluency, Trail Making Tests A and B, Short Physical Performance Battery (SPPB), and Instrumental Activities of Daily Living were administered annually for up to 5 years. We used linear mixed models, adjusted for potential confounders, to model AD biomarkers' relation with cognitive and functional decline.

RESULTS

A total of 1,938 participants were included in this study, with a mean (SD) baseline age of 72.8 (6.6) years, and 62% were women. Higher baseline p-tau181 and NfL were associated with significantly faster decline in most cognitive, physical, and functional outcomes (+1 SD p-tau181: βMMSE = -0.055, 95% CI -0.067 to -0.043, βFCSRT = -0.034, 95% CI -0.043 to -0.025, βfluency = -0.029, 95% CI -0.038 to -0.020, βSPPB = -0.040, 95% CI -0.057 to -0.022, and β4IADL = -0.115, 95% CI 0.091-0.140. +1 SD NfL: βMMSE = -0.039, 95% CI -0.053 to -0.025, βFCSRT = -0.022, 95% CI -0.032 to -0.012, βfluency = -0.014, 95% CI -0.024 to -0.004, and β4IADL = 0.077, 95% CI 0.048-0.105). A multiplicative association of p-tau181 and NfL with worsening cognitive and functional trajectories was evidenced. Lower Aβ42/40 ratio was only associated with slightly faster cognitive decline in FCSRT and semantic fluency (+1 SD: β = 0.011, 95% CI 0.002-0.020, and β = 0.011, 95% CI 0.003-0.020, respectively). These associations were not modified by APOE ε4, sex, nor education level.

DISCUSSION

In a memory clinic sample, p-tau181 and NfL, both independently and jointly, are linked to more pronounced cognitive, physical and functional declines. Blood-based biomarker measurement in AD research may provide useful insights regarding biological processes underlying cognitive, physical, and functional declines in at-risk individuals.

Clinical value of plasma ALZpath pTau217 immunoassay for assessing mild cognitive impairment

BACKGROUND

Among plasma biomarkers for Alzheimer's disease (AD), pTau181 and pTau217 are the most promising. However, transition from research to routine clinical use will require confirmation of clinical performance in prospective cohorts and evaluation of cofounding factors.

METHOD

pTau181 and pTau217 were quantified using, Quanterix and ALZpath, SIMOA assays in the well-characterised prospective multicentre BALTAZAR (Biomarker of AmyLoid pepTide and AlZheimer's diseAse Risk) cohort of participants with mild cognitive impairment (MCI).

RESULTS

Among participants with MCI, 55% were Aβ+ and 29% developed dementia due to AD. pTau181 and pTau217 were higher in the Aβ+ population with fold change of 1.5 and 2.7, respectively. MCI that converted to AD also had higher levels than non-converters, with HRs of 1.38 (1.26 to 1.51) for pTau181 compared with 8.22 (5.45 to 12.39) for pTau217. The area under the curve for predicting Aβ+ was 0.783 (95% CI 0.721 to 0.836; cut-point 2.75 pg/mL) for pTau181 and 0.914 (95% CI 0.868 to 0.948; cut-point 0.44 pg/mL) for pTau217. The high predictive power of pTau217 was not improved by adding age, sex and apolipoprotein E ε4 (APOEε4) status, in a logistic model. Age, APOEε4 and renal dysfunction were associated with pTau levels, but the clinical performance of pTau217 was only marginally altered by these factors. Using a two cut-point approach, a 95% positive predictive value for Aβ+ corresponded to pTau217 >0.8 pg/mL and a 95% negative predictive value at <0.23 pg/mL. At these two cut-points, the percentages of MCI conversion were 56.8% and 9.7%, respectively, while the annual rates of decline in Mini-Mental State Examination were -2.32 versus -0.65.

CONCLUSIONS

Plasma pTau217 and pTau181 both correlate with AD, but the fold change in pTau217 makes it better to diagnose cerebral amyloidosis, and predict cognitive decline and conversion to AD dementia.

Explaining the Variability of Alzheimer Disease Fluid Biomarker Concentrations in Memory Clinic Patients Without Dementia

BACKGROUND AND OBJECTIVES

Patients' comorbidities can affect Alzheimer disease (AD) blood biomarker concentrations. Because a limited number of factors have been explored to date, our aim was to assess the proportion of the variance in fluid biomarker levels explained by the clinical features of AD and by a large number of non-AD-related factors.

METHODS

MEMENTO enrolled 2,323 individuals with cognitive complaints or mild cognitive impairment in 26 French memory clinics. Baseline evaluation included clinical and neuropsychological assessments, brain MRI, amyloid-PET, CSF (optional), and blood sampling. Blood biomarker levels were determined using the Simoa-HDX analyzer. We performed linear regression analysis of the clinical features of AD (cognition, AD genetic risk score, and brain atrophy) to model biomarker concentrations. Next, we added covariates among routine biological tests, inflammatory markers, demographic and behavioral determinants, treatments, comorbidities, and preanalytical sample handling in final models using both stepwise selection processes and least absolute shrinkage and selection operator (LASSO).

RESULTS

In total, 2,257 participants were included in the analysis (median age 71.7, 61.8% women, 55.2% with high educational levels). For blood biomarkers, the proportion of variance explained by clinical features of AD was 13.7% for neurofilaments (NfL), 11.4% for p181-tau, 3.0% for Aβ-42/40, and 1.4% for total-tau. In final models accounting for non-AD-related factors, the variance was mainly explained by age, routine biological tests, inflammatory markers, and preanalytical sample handling. In CSF, the proportion of variance explained by clinical features of AD was 24.8% for NfL, 22.3% for Aβ-42/40, 19.8% for total-tau, and 17.2% for p181-tau. In contrast to blood biomarkers, the largest proportion of variance was explained by cognition after adjustment for covariates. The covariates that explained the largest proportion of variance were also the most frequently selected with LASSO. The performance of blood biomarkers for predicting A+ and T+ status (PET or CSF) remained unchanged after controlling for drivers of variance.

DISCUSSION

This comprehensive analysis demonstrated that the variance in AD blood biomarker concentrations was mainly explained by age, with minor contributions from cognition, brain atrophy, and genetics, conversely to CSF measures. These results challenge the use of blood biomarkers as isolated stand-alone biomarkers for AD.

Assessment of the Correlation and Diagnostic Accuracy between Cerebrospinal Fluid and Plasma Alzheimer's Disease Biomarkers: A Comparison of the Lumipulse and Simoa Platforms

We compared the clinical and analytical performance of Alzheimer's disease (AD) plasma biomarkers measured using the single-molecule array (Simoa) and Lumipulse platforms. We quantified the plasma levels of amyloid beta 42 (Aβ42), Aβ40, phosphorylated tau (Ptau181), and total tau biomarkers in 81 patients with mild cognitive impairment (MCI), 30 with AD, and 16 with non-AD dementia. We found a strong correlation between the Simoa and Lumipulse methods. Concerning the clinical diagnosis, Simoa Ptau181/Aβ42 (AUC 0.739, 95% CI 0.592-0.887) and Lumipulse Aβ42 and Ptau181/Aβ42 (AUC 0.735, 95% CI 0.589-0.882 and AUC 0.733, 95% CI 0.567-0.900) had the highest discriminating power. However, their power was significantly lower than that of CSF Aβ42/Aβ40, as measured by Lumipulse (AUC 0.879, 95% CI 0.766-0.992). Simoa Ptau181 and Lumipulse Ptau181/Aβ42 were the markers most consistent with the CSF Aβ42/Aβ40 status (AUC 0.801, 95% CI 0.712-0.890 vs. AUC 0.870, 95% CI 0.806-0.934, respectively) at the ≥2.127 and ≥0.084 cut-offs, respectively. The performance of the Simoa and Lumipulse plasma AD assays is weaker than that of CSF AD biomarkers. At present, the analysed AD plasma biomarkers may be useful for screening to reduce the number of lumbar punctures in the clinical setting.

Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts

Amyloid-beta (Aβ) toxic oligomers are critical early players in the molecular pathology of Alzheimer's disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aβ oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95-1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aβ oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.

Evaluating p-tau217 and p-tau231 as Biomarkers for Early Diagnosis and Differentiation of Alzheimer's Disease: A Narrative Review

The escalating prevalence of Alzheimer's disease (AD) highlights the urgent need to develop reliable biomarkers for early diagnosis and intervention. AD is characterized by the pathological accumulation of amyloid-beta plaques and tau neurofibrillary tangles. Phosphorylated tau (p-tau) proteins, particularly p-tau217 and p-tau231, have been identified as promising biomarker candidates to differentiate the disease progression from preclinical stages. This narrative review is devoted to a critical evaluation of the diagnostic accuracy, sensitivity, and specificity of p-tau217 and p-tau231 levels in the detection of AD, measured in plasma, serum, and cerebrospinal fluid, compared to established biomarkers. Additionally, the efficacy of these markers in distinguishing AD from other neurodegenerative disorders is examined. The significant advances offered by p-tau217 and p-tau231 in AD diagnostics are highlighted, demonstrating their unique utility in early detection and differential diagnosis. This comprehensive analysis not only confirms the excellent diagnostic capabilities of these markers, but also deepens the understanding of the molecular dynamics of AD, contributing to the broader scientific discourse on neurodegenerative diseases. This review is aimed to provide key information for researchers and clinicians across disciplines, filling interdisciplinary gaps and highlighting the role of p-tau proteins in revolutionizing AD research and clinical practice.

Relationship of plasma biomarkers to digital cognitive tests in Alzheimer's disease

INTRODUCTION

A major limitation in Alzheimer's disease (AD) research is the lack of the ability to measure cognitive performance at scale-robustly, remotely, and frequently. Currently, there are no established online digital platforms validated against plasma biomarkers of AD.

METHODS

We used a novel web-based platform that assessed different cognitive functions in AD patients (N = 46) and elderly controls (N = 53) who were also evaluated for plasma biomarkers (amyloid beta 42/40 ratio, phosphorylated tau ([p-tau]181, glial fibrillary acidic protein, neurofilament light chain). Their cognitive performance was compared to a second, larger group of elderly controls (N = 352).

RESULTS

Patients with AD were significantly impaired across all digital cognitive tests, with performance correlating with plasma biomarker levels, particularly p-tau181. The combination of p-tau181 and the single best-performing digital test achieved high accuracy in group classification.

DISCUSSION

These findings show how online testing can now be deployed in patients with AD to measure cognitive function effectively and related to blood biomarkers of the disease.

Highlights

This is the first study comparing online digital testing to plasma biomarkers.Alzheimer's disease patients and two independent cohorts of elderly controls were assessed.Cognitive performance correlated with plasma biomarkers, particularly phosphorylated tau (p-tau)181.Glial fibrillary acidic protein and neurofilament light chain, and less so the amyloid beta 42/40 ratio, were also associated with performance.The best cognitive metric performed at par to p-tau181 in group classification.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Impact of demographics and comorbid conditions on plasma biomarkers concentrations and their diagnostic accuracy in a memory clinic cohort

Plasma biomarkers have emerged as promising tools for identifying amyloid beta (Aβ) pathology. Before implementation in routine clinical practice, confounding factors modifying their concentration beyond neurodegenerative diseases should be identified. We studied the association of a comprehensive list of demographics, comorbidities, medication and laboratory parameters with plasma p-tau181, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) on a prospective memory clinic cohort and studied their impact on diagnostic accuracy for discriminating CSF/amyloid PET-defined Aβ status. Three hundred sixty patients (mean age 66.5 years, 55% females, 53% Aβ positive) were included. Sex, age and Aβ status-adjusted models showed that only estimated glomerular filtration rate (eGFR, standardized β -0.115 [-0.192 to -0.035], p = 0.005) was associated with p-tau181 levels, although with a much smaller effect than Aβ status (0.685 [0.607-0.763], p < 0.001). Age, sex, body mass index (BMI), Charlson comorbidity index (CCI) and eGFR significantly modified GFAP concentration. Age, blood volume (BV) and eGFR were associated with NfL levels. p-tau181 predicted Aβ status with 87% sensitivity and specificity with no relevant increase in diagnostic performance by adding any of the confounding factors. Using two cut-offs, plasma p-tau181 could have spared 62% of amyloid-PET/CSF testing. Excluding patients with chronic kidney disease did not change the proposed cut-offs nor the diagnostic performance. In conclusion, in a memory clinic cohort, age, sex, eGFR, BMI, BV and CCI slightly modified plasma p-tau181, GFAP and NfL concentrations but their impact on the diagnostic accuracy of plasma biomarkers for Aβ status discrimination was minimal.

Nanoscale imaging of pT217-tau in aged rhesus macaque entorhinal and dorsolateral prefrontal cortex: Evidence of interneuronal trafficking and early-stage neurodegeneration

INTRODUCTION

Tau phosphorylated at threonine-217 (pT217-tau) is a novel fluid-based biomarker that predicts onset of Alzheimer's disease (AD) symptoms, but little is known about how pT217-tau arises in the brain, as soluble pT217-tau is dephosphorylated post mortem in humans.

METHODS

We used multilabel immunofluorescence and immunoelectron microscopy to examine the subcellular localization of early-stage pT217-tau in entorhinal and prefrontal cortices of aged macaques with naturally occurring tau pathology and assayed pT217-tau levels in plasma.

RESULTS

pT217-tau was aggregated on microtubules within dendrites exhibiting early signs of degeneration, including autophagic vacuoles. It was also seen trafficking between excitatory neurons within synapses on spines, where it was exposed to the extracellular space, and thus accessible to cerebrospinal fluid (CSF)/blood. Plasma pT217-tau levels increased across the age span and thus can serve as a biomarker in macaques.

DISCUSSION

These data help to explain why pT217-tau predicts degeneration in AD and how it gains access to CSF and plasma to serve as a fluid biomarker.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-β and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.

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-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 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 Aβ1-42/Aβ1-40 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.

Head-to-head study of diagnostic accuracy of plasma and cerebrospinal fluid p-tau217 versus p-tau181 and p-tau231 in a memory clinic cohort

BACKGROUND AND OBJECTIVE

Phosphorylated tau (p-tau) 217 has recently received attention because it seems more reliable than other p-tau variants for identifying Alzheimer's disease (AD) pathology. Thus, we aimed to compare the diagnostic accuracy of plasma and CSF p-tau217 with p-tau181 and p-tau231 in a memory clinic cohort.

METHODS

The study included 114 participants (CU = 33; MCI = 67; Dementia = 14). The p-tau variants were correlated versus continuous measures of amyloid (A) and tau (T)-PET. The p-tau phospho-epitopes were assessed through: (i) effect sizes (δ) between diagnostic and A ± and T ± groups; (ii) receiver operating characteristic (ROC) analyses in A-PET and T-PET.

RESULTS

The correlations between both plasma and CSF p-tau217 with A-PET and T-PET (r range 0.64-0.83) were stronger than those of p-tau181 (r range 0.44-0.79) and p-tau231 (r range 0.46-0.76). Plasma p-tau217 showed significantly higher diagnostic accuracy than p-tau181 and p-tau231 in (i) differences between diagnostic and biomarker groups (δrange: p-tau217 = 0.55-0.96; p-tau181 = 0.51-0.67; p-tau231 = 0.53-0.71); (ii) ROC curves to identify A-PET and T-PET positivity (AUCaverage: p-tau217 = 0.96; p-tau181 = 0.76; p-tau231 = 0.79). On the other hand, CSF p-tau217 (AUCaverage = 0.95) did not reveal significant differences in A-PET and T-PET AUC than p-tau181 (AUCaverage = 0.88) and p-tau231 (AUCaverage = 0.89).

DISCUSSION

Plasma p-tau217 demonstrated better performance in the identification of AD pathology and clinical phenotypes in comparison with other variants of p-tau in a memory clinic cohort. Furthermore, p-tau217 had comparable performance in plasma and CSF. Our findings suggest the potential of plasma p-tau217 in the diagnosis and screening for AD, which could allow for a decreased use of invasive biomarkers in the future.

The impact of exercise on blood-based biomarkers of Alzheimer's disease in cognitively unimpaired older adults

Physical activity is a promising preventative strategy for Alzheimer's disease: it is associated with lower dementia risk, better cognition, greater brain volume and lower brain beta-amyloid. Blood-based biomarkers have emerged as a low-cost, non-invasive strategy for detecting preclinical Alzheimer's disease, however, there is limited literature examining the effect of exercise (a structured form of physical activity) on blood-based biomarkers. The current study investigated the influence of a 6-month exercise intervention on levels of plasma beta-amyloid (Aβ42, Aβ40, Aβ42/40), phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) chain in cognitively unimpaired older adults, and as a secondary aim, whether blood-based biomarkers related to cognition. Ninety-nine community-dwelling older adults (69.1 ± 5.2) were allocated to an inactive control, or to moderate or high intensity exercise groups where they cycled twice weekly for six months. At baseline and six months (post-intervention), fasted blood was collected and analysed using single molecule array (SIMOA) assays, and cognition was assessed. Results demonstrated no change in levels of any plasma biomarker from pre- to post-intervention. At baseline, higher NfL was associated with poorer cognition (β = -0.33, SE = 0.13, adjusted p = .042). Exploratory analyses indicated higher cardiorespiratory fitness was associated with higher NfL and GFAP levels in apolipoprotein E (APOE) ε4 non-carriers compared to ε4 carriers (NfL, β = -0.43, SE = 0.19, p = .029; GFAP, β = -0.41, SE = 0.20, p = .044), though this association was mediated by body mass index (BMI). These results highlight the importance of considering BMI in analysis of blood-based biomarkers, especially when investigating differences between APOE ε4 carriers and non-carriers. Our results also indicate that longer follow-up periods may be required to observe exercise-induced change in blood-based biomarkers.

Longitudinal associations of serum biomarkers with early cognitive, amyloid and grey matter changes

Blood-based biomarkers have been extensively evaluated for their diagnostic potential in Alzheimer's disease. However, their relative prognostic and monitoring capabilities for cognitive decline, amyloid-β (Aβ) accumulation and grey matter loss in cognitively unimpaired elderly require further investigation over extended time periods. This prospective cohort study in cognitively unimpaired elderly [n = 185, mean age (range) = 69 (53-84) years, 48% female] examined the prognostic and monitoring capabilities of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), Aβ1-42/Aβ1-40 and phosphorylated tau (pTau)181 through their quantification in serum. All participants underwent baseline Aβ-PET, MRI and blood sampling as well as 2-yearly cognitive testing. A subset additionally underwent Aβ-PET (n = 109), MRI (n = 106) and blood sampling (n = 110) during follow-up [median time interval (range) = 6.1 (1.3-11.0) years]. Matching plasma measurements were available for Aβ1-42/Aβ1-40 and pTau181 (both n = 140). Linear mixed-effects models showed that high serum GFAP and NfL predicted future cognitive decline in memory (βGFAP×Time = -0.021, PFDR = 0.007 and βNfL×Time = -0.031, PFDR = 0.002) and language (βGFAP×Time = -0.021, PFDR = 0.002 and βNfL×Time = -0.018, PFDR = 0.03) domains. Low serum Aβ1-42/Aβ1-40 equally but independently predicted memory decline (βAβ1-42/Aβ1-40×Time = -0.024, PFDR = 0.02). Whole-brain voxelwise analyses revealed that low Aβ1-42/Aβ1-40 predicted Aβ accumulation within the precuneus and frontal regions, high GFAP and NfL predicted grey matter loss within hippocampal regions and low Aβ1-42/Aβ1-40 predicted grey matter loss in lateral temporal regions. Serum GFAP, NfL and pTau181 increased over time, while Aβ1-42/Aβ1-40 decreased only in Aβ-PET-negative elderly. NfL increases associated with declining memory (βNfLchange×Time = -0.030, PFDR = 0.006) and language (βNfLchange×Time = -0.021, PFDR = 0.02) function and serum Aβ1-42/Aβ1-40 decreases associated with declining language function (βAβ1-42/Aβ1-40×Time = -0.020, PFDR = 0.04). GFAP increases associated with Aβ accumulation within the precuneus and NfL increases associated with grey matter loss. Baseline and longitudinal serum pTau181 only associated with Aβ accumulation in restricted occipital regions. In head-to-head comparisons, serum outperformed plasma Aβ1-42/Aβ1-40 (ΔAUC = 0.10, PDeLong, FDR = 0.04), while both plasma and serum pTau181 demonstrated poor performance to detect asymptomatic Aβ-PET positivity (AUC = 0.55 and 0.63, respectively). However, when measured with a more phospho-specific assay, plasma pTau181 detected Aβ-positivity with high performance (AUC = 0.82, PDeLong, FDR < 0.007). In conclusion, serum GFAP, NfL and Aβ1-42/Aβ1-40 are valuable prognostic and/or monitoring tools in asymptomatic stages providing complementary information in a time- and pathology-dependent manner.

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.

Predicting clinical progression trajectories of early Alzheimer's disease patients

BACKGROUND

Models for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring.

METHODS

Prediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures.

RESULTS

The model using clinical features achieved R2 of 0.21 and 0.31 for predicting 2-year cognitive decline in VC 1 and VC 2, respectively. Adding MRI features improved the R2 to 0.29 in VC 1, which employed the same preprocessing pipeline as the TC. Utilizing these model-based predictions for clinical trial enrichment reduced the required sample size by 20% to 49%.

DISCUSSION

Our validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.

Plasma N-terminal containing tau fragments (NTA-tau): a biomarker of tau deposition in Alzheimer's Disease

BACKGROUND

Novel phosphorylated-tau (p-tau) blood biomarkers (e.g., p-tau181, p-tau217 or p-tau231), are highly specific for Alzheimer's disease (AD), and can track amyloid-β (Aβ) and tau pathology. However, because these biomarkers are strongly associated with the emergence of Aβ pathology, it is difficult to determine the contribution of insoluble tau aggregates to the plasma p-tau signal in blood. Therefore, there remains a need for a biomarker capable of specifically tracking insoluble tau accumulation in brain.

METHODS

NTA is a novel ultrasensitive assay targeting N-terminal containing tau fragments (NTA-tau) in cerebrospinal fluid (CSF) and plasma, which is elevated in AD. Using two well-characterized research cohorts (BioFINDER-2, n = 1,294, and BioFINDER-1, n = 932), we investigated the association between plasma NTA-tau levels and disease progression in AD, including tau accumulation, brain atrophy and cognitive decline.

RESULTS

We demonstrate that plasma NTA-tau increases across the AD continuum¸ especially during late stages, and displays a moderate-to-strong association with tau-PET (β = 0.54, p < 0.001) in Aβ-positive participants, while weak with Aβ-PET (β = 0.28, p < 0.001). Unlike plasma p-tau181, GFAP, NfL and t-tau, tau pathology determined with tau-PET is the most prominent contributor to NTA-tau variance (52.5% of total R2), while having very low contribution from Aβ pathology measured with CSF Aβ42/40 (4.3%). High baseline NTA-tau levels are predictive of tau-PET accumulation (R2 = 0.27), steeper atrophy (R2 ≥ 0.18) and steeper cognitive decline (R2 ≥ 0.27) in participants within the AD continuum. Plasma NTA-tau levels significantly increase over time in Aβ positive cognitively unimpaired (βstd = 0.16) and impaired (βstd = 0.18) at baseline compared to their Aβ negative counterparts. Finally, longitudinal increases in plasma NTA-tau levels were associated with steeper longitudinal decreases in cortical thickness (R2 = 0.21) and cognition (R2 = 0.20).

CONCLUSION

Our results indicate that plasma NTA-tau levels increase across the AD continuum, especially during mid-to-late AD stages, and it is closely associated with in vivo tau tangle deposition in AD and its downstream effects. Moreover, this novel biomarker has potential as a cost-effective and easily accessible tool for monitoring disease progression and cognitive decline in clinical settings, and as an outcome measure in clinical trials which also need to assess the downstream effects of successful Aβ removal.

Plasma proteomic profiles predict future dementia in healthy adults

The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.

Monoclonal antibodies for treating early Alzheimer disease-a commentary on recent 'positive' trials

Recent phase 3 randomised controlled trials of amyloid-targeting monoclonal antibodies in people with pre-clinical or early Alzheimer disease have reported positive results, raising hope of finally having disease-modifying drugs. Given their far-reaching implications for clinical practice, the methods and findings of these trials, and the disease causation theory underpinning the mechanism of drug action, need to be critically appraised. Key considerations are the representativeness of trial populations; balance of prognostic factors at baseline; psychometric properties and minimal clinically important differences of the primary efficacy outcome measures; level of study fidelity; consistency of subgroup analyses; replication of findings in similar trials; sponsor role and potential conflicts of interest; consistency of results with disease causation theory; cost and resource estimates; and alternative prevention and treatment strategies. In this commentary, we show shortcomings in each of these areas and conclude that monoclonal antibody treatment for early Alzheimer disease is lacking high-quality evidence of clinically meaningful impacts at an affordable cost.

Top 100 most-cited articles on tau protein: a bibliometric analysis and evidence mapping

Background

Tau, a microtubule-associated protein extensively distributed within the central nervous system (CNS), exhibits close associations with various neurodegenerative disorders. Here, we aimed to conduct a qualitative and quantitative bibliometric study of the top 100 most-cited publications on tau protein and reveal the current research hotspots and future perspectives.

Methods

The relevant literature was retrieved from the Web of Science Core Collection. CiteSpace (v6.2.R4) and VOSviewer (1.6.19) were adopted for bibliometric analysis with statistical and visual analysis.

Results

Citations per article ranged from 615 to 3,123, with a median number of 765.5 times. "Neuroscience" emerged as the most extensively researched subject in this field. The USA has emerged as the leading country, with a publication record (n = 65), total citations (n = 66,543), strong centrality (0.29), and extensive international collaborations. Harvard University (n = 11) and the University of California, San Francisco (n = 11) were the top two institutions in terms of publications. Neuron dominated with 13 articles in the 37 high-quality journals. M. Goedert from the MRC Laboratory of Molecular Biology was the most productive (n = 9) and top co-cited (n = 179) author. The most frequently studied keywords were Alzheimer's disease (n = 38). Future research is anticipated to intensify its focus on the pathogenesis of various tau-related diseases, emphasizing the phosphorylation and structural alterations of tau protein, particularly in Alzheimer's disease.

Conclusion

The pathogenesis of various tau-related diseases, including the phosphorylation and structural alterations of the tau protein, will be the primary focus of future research, with particular emphasis on Alzheimer's disease as a central area of investigation.

Longitudinal progression of blood biomarkers reveals a key role of astrocyte reactivity in preclinical Alzheimer's disease

Defining the progression of blood biomarkers of Alzheimer's disease (AD) is essential for targeting treatments in patients most likely to benefit from early intervention. We delineated the temporal ordering of blood biomarkers a decade prior to the onset of AD symptoms in participants in the Baltimore Longitudinal Study of Aging. We show that increased astrocyte reactivity, assessed by elevated glial fibrillary acidic protein (GFAP) levels is an early event in the progression of blood biomarker changes in preclinical AD. In AD-converters who are initially cognitively unimpaired (N=158, 377 serial plasma samples), higher plasma GFAP levels are observed as early as 10-years prior to the onset of cognitive impairment due to incident AD compared to individuals who remain cognitively unimpaired (CU, N=160, 379 serial plasma samples). Plasma GFAP levels in AD-converters remain elevated 5-years prior to and coincident with the onset of cognitive impairment due to AD. In participants with neuropathologically confirmed AD, plasma GFAP levels are elevated relative to cognitively normal individuals and intermediate in those who remain cognitively unimpaired despite significant AD pathology (asymptomatic AD). Higher plasma GFAP levels at death are associated with greater severity of both neuritic plaques and neurofibrillary tangles. In the 5XFAD transgenic model of AD, we observed greater GFAP levels in the cortex and hippocampus of transgenic mice relative to wild-type prior to the development of cognitive impairment. Reactive astrocytosis, an established biological response to neuronal injury, may be an early initiator of AD pathogenesis and a promising therapeutic target.

Longitudinal Cognitive Decline in Alzheimer Disease Prevention Trials: A Test of Time

The landscape of clinical trials for Alzheimer disease (AD) has undergone significant evolution in the past decade, most notably by the inclusion of individuals at progressively earlier stages of the disease. Recent approvals by the Food and Drug Administration have predominantly centered around individuals with prodromal and mild AD,1,2 signaling a shift toward early intervention. Despite the result of some recent trials,3 there is optimism and hope that treating individuals at preclinical stages could have even greater effects. A major challenge for the feasibility and cost-effectiveness of clinical trials on patients with preclinical AD, however, is the fact that cognitive and functional decline over time is mild. Previous studies have already shown the heterogeneity in sensitivity to longitudinal decline across cognitive tests within early disease stages.4,5.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

Blood Biomarkers of Alzheimer's Disease and Cognition: A Literature Review

Recent advances in blood-based biomarkers of Alzheimer's Disease (AD) show great promise for clinical applications, offering a less invasive alternative to current cerebrospinal fluid (CSF) measures. However, the relationships between these biomarkers and specific cognitive functions, as well as their utility in predicting longitudinal cognitive decline, are not yet fully understood. This descriptive review surveys the literature from 2018 to 2023, focusing on the associations of amyloid-β (Aβ), Total Tau (t-Tau), Phosphorylated Tau (p-Tau), Neurofilament Light (NfL), and Glial Fibrillary Acidic Protein (GFAP) with cognitive measures. The reviewed studies are heterogeneous, varying in design and population (cognitively unimpaired, cognitively impaired, or mixed populations), and show results that are sometimes conflicting. Generally, cognition positively correlates with Aβ levels, especially when evaluated through the Aβ42/Aβ40 ratio. In contrast, t-Tau, p-Tau, Nfl, and GFAP levels typically show a negative correlation with cognitive performance. While p-Tau measures generally exhibit stronger associations with cognitive functions compared to other biomarkers, no single blood marker has emerged as being predominantly linked to a specific cognitive domain. These findings contribute to our understanding of the complex relationship between blood biomarkers and cognitive performance and underscore their potential utility in clinical assessments of cognition.

Qingxin Kaiqiao Fang decreases Tau hyperphosphorylation in Alzheimer's disease via the PI3K/Akt/GSK3β pathway in vitro and in vivo

ETHNOPHARMACOLOGICAL RELEVANCE

Alzheimer's disease (AD) belongs to the category of "senile dementia" in traditional Chinese medicine. AD is associated with brain emptiness or collaterals blocked by phlegm-heat. "Fumanjian" from Jingyue Quanshu treats dementia by promoting qi circulation, alleviating depression, eliminating turbidity, cultivating positivity, and dispelling evil spirits. Qingxin Kaiqiao Fang (QKF), derived from Fumanjian, is effective in treating AD owing to previously mentioned clinical effects. Elucidating the mechanism(s) of action of QKF on AD associated with phlegm-heat may be beneficial for therapeutic management; however, further research is needed.

AIM OF THE STUDY

This study aimed to determine the role of the PI3K/Akt pathway in AD, especially the specific effector protein involved, and explore the efficacy of QKF in treating AD by modulating the PI3K/Akt signal.

MATERIALS AND METHODS

High-performance liquid chromatography-Q-orbitrap-mass spectrometry was used to analyze the chemical components of QKF. Subsequently, APP/PS1 double-transgenic mice were used for behavioral tests, and hematoxylin-eosin and Nissl staining were used to assess the neuroprotective and cognitive effects of QKF. Cerebrospinal fluid pharmacology was used in in vitro validation, and Aβ25-35 was used to induce PC12 cells to establish the AD cell model. Various methods, including immunohistochemistry, Western blotting, quantitative real-time polymerase chain reaction, morphological assay, cell counting kit-8(CCK-8) assay, and terminal deoxynucleotide transferase (TdT)-mediated dUTP nick-end labeling (TUNEL)staining, were used to evaluate the effect of QKF on Tau hyperphosphorylation and anti-apoptosis. These methods also assessed the influence of QKF on the PI3K/Akt/GSK3β pathway involving the mRNA and protein expressions. Finally, the inhibitor - LY294002 was used for reverse validation.

RESULTS

We identified 295 chemical components in the water extract of QKF.QKF improved spatial cognition and learning memory in APP/PS1 mice, protected PC12 cell morphology, improved cell survival, reduced Aβ25-35-induced apoptosis, and inhibited the hyperphosphorylation of Tau protein via the PI3k/Akt/GSK3β signaling pathway. Furthermore, this protective effect of QKF was reduced by LY294002 in vitro.

CONCLUSIONS

QKF can improve spatial cognition, learning, and memory abilities in APP/PS1 mice and protect PC12 cells. Decreasing the Tau hyperphosphorylation in AD exhibits curative efficacy on AD via the PI3K/Akt/GSK3β pathway in vitro and in vivo.

Differential diagnosis of mild cognitive impairment of Alzheimer's disease by Simoa p-tau181 measurements with matching plasma and CSF

Alzheimer's disease (AD) is characterized by a long preclinical phase. Although late-stage AD/dementia may be robustly differentiated from cognitively normal individuals by means of a clinical evaluation, PET imaging, and established biofluid biomarkers, disease differentiation between cognitively normal and various subtypes of mild cognitive impairment (MCI) remains a challenging task. Differential biomarkers for early-stage AD diagnosis with accessible biofluid samples are urgently needed. Misfolded phosphorylated tau aggregates (p-tau) are present in multiple neurodegenerative diseases known as "tauopathies", with the most common being AD. P-tau181 is a well-established p-tau biomarker to differentiate AD dementia from non-AD pathology. However, it is unclear if p-tau181 is capable of diagnosing MCI, an early AD stage, from cognitively normal subjects, or if it can discriminate MCI subtypes amnestic MCI (aMCI) from non-amnestic MCI (naMCI). Here we evaluated the capability of p-tau181 in diagnosing MCI from cognitively normal subjects and discriminating aMCI from naMCI subtypes. We collected matching plasma and CSF samples of a clinically diagnosed cohort of 35 cognitively normal, 34 aMCI, 17 naMCI, and 31 AD dementia cases (total 117 participants) with supplemental CSF Aβ42 and total tau AD biomarker levels and performed Simoa p-tau181 assays. The diagnostic capabilities of Simoa p-tau181 assays to differentiate these cohorts were evaluated. We found (i) p-tau181 can robustly differentiate MCI or aMCI from cognitively normal cohorts with matching plasma and CSF samples, but such differentiation is weaker in diagnosing naMCI from cognitively normal groups, (ii) p-tau181 is not capable of differentiating aMCI from naMCI cohorts, and (iii) either factor of Aβ or total tau burden markedly improved differentiation power to diagnose aMCI from cognitively normal group. Plasma and CSF p-tau181 levels may serve as a promising biomarker for diagnosing aMCI from normal controls in the preclinical phase. But more robust new biomarkers are needed to differentiate naMCI from cognitively normal cases or to discriminate between MCI subtypes, aMCI from naMCI.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach

Background

The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points.

Objective

To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach.

Methods

We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline.

Results

We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways.

Conclusions

Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

Translating NIA-AA criteria into usual practice: Report from the ReDeMa Project

INTRODUCTION

Biomarker-informed criteria were proposed for the diagnosis of Alzheimer's disease (AD) by the National Institute on Aging and the Alzheimer's Association (NIA-AA) in 2011; however, the adequacy of this criteria has not been sufficiently evaluated.

METHODS

ReDeMa (Red de Demencias de Madrid) is a regional cohort of patients attending memory and neurology clinics. Core cerebrospinal fluid biomarkers were obtained, NIA-AA diagnostic criteria were considered, and changes in diagnosis and management were evaluated.

RESULTS

A total of 233 patients were analyzed (mean age 70 years, 50% women, 73% AD). The diagnostic language was modified significantly, with a majority assumption of NIA-AA definitions (69%). Confidence in diagnosis increased from 70% to 92% (p < 0.0005) and management was changed in 71% of patient/caregivers. The influence of neurologist's age or expertise on study results was minimal.

DISCUSSION

The NIA-AA criteria are adequate and utile for usual practice in memory and neurology clinics, improving diagnostic confidence and significantly modifying patient management.

HIGHLIGHTS

Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers increase diagnostic certainty regardless of the neurologist.AD CSF biomarkers lead to changes in disease management .Biomarker-enriched, 2011 NIA-AA diagnostic criteria are adequate for usual practice.

Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status

BACKGROUND

Although cerebrospinal fluid (CSF) amyloid-β42 peptide (Aβ42) and phosphorylated tau (p-tau) and blood p-tau are valuable for differential diagnosis of Alzheimer's disease (AD) from cognitively normal (CN) there is a lack of validated biomarkers for mild cognitive impairment (MCI).

OBJECTIVE

This study sought to determine how plasma and CSF protein markers compared in the characterization of MCI and AD status.

METHODS

This cohort study included Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 75 proteins measured commonly in plasma and CSF (257 total, 46 CN, 143 MCI, and 68 AD). Logistic regression, least absolute shrinkage and selection operator (LASSO) and Random Forest (RF) methods were used to identify the protein candidates for the disease classification.

RESULTS

We observed that six plasma proteins panel (APOE, AMBP, C3, IL16, IGFBP2, APOD) outperformed the seven CSF proteins panel (VEGFA, HGF, PRL, FABP3, FGF4, CD40, RETN) as well as AD markers (CSF p-tau and Aβ42) to distinguish the MCI from AD [area under the curve (AUC) = 0.75 (plasma proteins), AUC = 0.60 (CSF proteins) and AUC = 0.56 (CSF p-tau and Aβ42)]. Also, these six plasma proteins performed better than the CSF proteins and were in line with CSF p-tau and Aβ42 in differentiating CN versus MCI subjects [AUC = 0.89 (plasma proteins), AUC = 0.85 (CSF proteins) and AUC = 0.89 (CSF p-tau and Aβ42)]. These results were adjusted for age, sex, education, and APOEϵ4 genotype.

CONCLUSIONS

This study suggests that the combination of 6 plasma proteins can serve as an effective marker for differentiating MCI from AD and CN.

Plasma Biomarkers as Predictors of Progression to Dementia in Individuals with Mild Cognitive Impairment

Background

Blood-based biomarkers (BBMs) are of growing interest in the field of Alzheimer's disease (AD) and related dementias.

Objective

This study aimed to assess the ability of plasma biomarkers to 1) predict disease progression from mild cognitive impairment (MCI) to dementia and 2) improve the predictive ability of magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) measures when combined.

Methods

We used data from the Alzheimer's Disease Neuroimaging Initiative. Machine learning models were trained using the data from participants who remained cognitively stable (CN-s) and with Dementia diagnosis at 2-year follow-up visit. The models were used to predict progression to dementia in MCI individuals. We assessed the performance of models with plasma biomarkers against those with CSF and MRI measures, and also in combination with them.

Results

Our models with plasma biomarkers classified CN-s individuals from AD with an AUC of 0.75±0.03 and could predict conversion to dementia in MCI individuals with an AUC of 0.64±0.03 (17.1% BP, base prevalence). Models with plasma biomarkers performed better when combined with CSF and MRI measures (CN versus AD: AUC of 0.89±0.02; MCI-to-AD: AUC of 0.76±0.03, 21.5% BP).

Conclusions

Our results highlight the potential of plasma biomarkers in predicting conversion to dementia in MCI individuals. While plasma biomarkers could improve the predictive ability of CSF and MRI measures when combined, they also show the potential to predict non-progression to AD when considered alone. The predictive ability of plasma biomarkers is crucially linked to reducing the costly and effortful collection of CSF and MRI measures.

Plasma phosphorylated tau-217 exhibits sex-specific prognostication of cognitive decline and brain atrophy in cognitively unimpaired adults

INTRODUCTION

Accumulating evidence indicates disproportionate tau burden and tau-related clinical progression in females. However, sex differences in plasma phosphorylated tau (p-tau)217 prediction of subclinical cognitive and brain changes are unknown.

METHODS

We measured baseline plasma p-tau217, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) in 163 participants (85 cognitively unimpaired [CU], 78 mild cognitive impairment [MCI]). In CU, linear mixed effects models examined sex differences in plasma biomarker prediction of longitudinal domain-specific cognitive decline and brain atrophy. Cognitive models were repeated in MCI.

RESULTS

In CU females, baseline plasma p-tau217 predicted verbal memory and medial temporal lobe trajectories such that trajectories significantly declined once p-tau217 concentrations surpassed 0.053 pg/ml, a threshold that corresponded to early levels of cortical amyloid aggregation in secondary amyloid positron emission tomography analyses. CU males exhibited similar rates of cognitive decline and brain atrophy, but these trajectories were not dependent on plasma p-tau217. Plasma GFAP and NfL exhibited similar female-specific prediction of medial temporal lobe atrophy in CU. Plasma p-tau217 exhibited comparable prediction of cognitive decline across sex in MCI.

DISCUSSION

Plasma p-tau217 may capture earlier Alzheimer's disease (AD)-related cognitive and brain atrophy hallmarks in females compared to males, possibly reflective of increased susceptibility to AD pathophysiology.