CSF biomarkers of Alzheimer's disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts

Brain Metabolic Resilience in Alzheimer's Disease: A Predictor of Cognitive Decline and Conversion to Dementia

OBJECTIVE

Brain atrophy measured by structural imaging has been used to quantify resilience against neurodegeneration in Alzheimer's disease. Considering glucose hypometabolism is another marker of neurodegeneration, we quantified metabolic resilience (MR) based on Fluorodeoxyglucose positron emission tomography (FDG PET) and investigated its clinical implications.

METHODS

We quantified the MR and other resilience metrics, including brain resilience (BR) and cognitive resilience (CR), using partial least squares path modeling from the ADNI database. A linear mixed-effects model and a Cox proportional hazards model were used to identify the impact of each resilience on longitudinal cognitive function and conversion to dementia, respectively.

RESULTS

A total of 848 participants were included in this study. All resilience metrics (CR, BR, and MR) were associated with slower cognitive decline. Results from the ANOVA test, AIC and BIC values showed that the additional inclusion of MR improved the performances of the linear mixed effect models. In survival analysis, all resilience variables were negatively associated with the risk of conversion to dementia. In line with the results of the linear mixed effects models, the additional inclusion of MR into the models with different resilience variables increased the C-index.

CONCLUSION

Relative preservation of brain glucose metabolism is a valuable predictor of future cognitive decline and conversion to dementia, adding value to existing resilience metrics. While the utility of FDG PET in clinical settings is limited by cost and accessibility, it might have potential usefulness as a prognostic marker, especially in a context of resilience.

CSF α-synuclein aggregation is associated with APOE ε4 and progressive cognitive decline in Alzheimer's disease

At autopsy, around half of the Alzheimer's disease (AD) brains exhibit Lewy body pathology, and the main component of Lewy body pathology is α-synuclein aggregates. This study investigated the prevalence of cerebrospinal fluid (CSF) α-synuclein aggregation and its association with demographic factors and cognitive decline among 1619 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), with the test for α-synuclein aggregation by seed amplification assay (SAA). This cohort consisted of 595 cognitively normal (CN) individuals, 765 with mild cognitive impairment (MCI), and 259 with AD dementia. The results showed a higher prevalence of positive α-synuclein aggregation status in the AD dementia group (37.07 %) and the MCI group (22.75 %) compared to CN controls (16.13 %). Additionally, APOE ε4 carriers exhibited a higher prevalence of α-synuclein aggregation compared to non-carriers: 20.12 % for APOE ε4-/- (non-carriers), 24.82 % for APOE ε4 + /-, and 30.92 % for APOE ε4 + /+ . Longitudinally, positive CSF α-synuclein aggregation associated with accelerated cognitive decline, especially in the MCI and AD groups. Notably, positive aggregation status did not significantly affect cognitive trajectories in CN individuals. Moreover, APOE ε4 carriers with positive CSF α-synuclein aggregation experienced more pronounced cognitive decline. This study provides evidence that CSF α-synuclein aggregation is associated with cognitive function and the APOE ε4 allele. These findings suggest that CSF α-synuclein SAA, in combination with APOE ε4 status, could serve as biomarkers for predicting cognitive decline in AD.

Predicting the progression of MCI and Alzheimer's disease on structural brain integrity and other features with machine learning

Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer's disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70-77% accuracy and 61-83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Differential effects of aging, Alzheimer's pathology, and APOE4 on longitudinal functional connectivity and episodic memory in older adults

BACKGROUND

Both aging and Alzheimer's disease (AD) affect brain networks, with early disruptions occurring in regions involved in episodic memory. Few studies have, however, focused on distinguishing region-specific effects of AD-biomarker negative "normal" aging and early amyloid- and tau pathology on functional connectivity. Further, longitudinal studies combining imaging, biomarkers, and cognition are rare.

METHODS

We assessed resting-state functional connectivity (rsFC) strength and graph measures in the episodic memory network including the medial temporal lobe (MTL), posteromedial cortex (PMC), and medial prefrontal cortex alongside cognition over two years. For this preregistered study, we included 100 older adults who were amyloid- and tau-negative using CSF and PET measurements to investigate "normal" aging, and 70 older adults who had longitudinal CSF data available to investigate functional changes related to early AD pathology. All participants were cognitively unimpaired older adults from the PREVENT-AD cohort. We used region of interest (ROI)-to-ROI bivariate correlations, graph analysis, and multiple regression models.

RESULTS

In the amyloid- and tau-negative sample, rsFC strength within PMC, between parahippocampal cortex and inferomedial precuneus, and between posterior hippocampus and inferomedial precuneus decreased over time. Additionally, we observed a longitudinal decrease in global efficiency. Further, there was a steeper longitudinal decrease in rsFC and global efficiency with higher baseline age particularly of parahippocampal-gyrus regions. Further, lower rsFC strength within PMC was associated with poorer longitudinal episodic memory performance. In the sample with available CSF data, a steeper increase in rsFC between anterior hippocampus and superior precuneus was related to higher baseline AD pathology. Higher MTL-PMC rsFC strength was differentially associated with episodic memory trajectories depending on APOE4 genotype.

CONCLUSIONS

Our findings suggest differential effects of aging and AD pathology. Hypoconnectivity within PMC was related to aging and cognitive decline. MTL-PMC hyperconnectivity was related to early AD pathology and cognitive decline in APOE4 carriers. Future studies should investigate more diverse samples, nonetheless, our approach allowed us to identify longitudinal functional changes related to aging and early AD pathology, enhancing cross-sectional research. Hyperconnectivity has been proposed as a mechanism related to early AD pathology before, we now contribute specific functional connections to focus on in future research.

The association between pulse wave velocity and cerebrospinal fluid biomarkers for Alzheimer's disease

We examined the association between arterial stiffness using non-invasive pulse wave velocity (PWV) and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers. We conducted a cross-sectional multivariate logistic regression analysis using established cut-off values for PWV and CSF biomarkers. Of the 739 participants, 69% were female, 84% were White, 12% were Black, and the mean age was 62. After adjustment for potential confounders, participants with high PWV had 94% (OR = 1.94, 95% CI 1.20-3.20) greater odds of AD biomarker positivity for tTau/Aβ42 and 108% (OR = 2.08, 95% Cl, 1.27-3.46) for pTau181/Aβ42. Our results suggest that higher arterial stiffness is associated with AD CSF biomarker positivity.

Plasma phospho-tau217 for Alzheimer's disease diagnosis in primary and secondary care using a fully automated platform

Global implementation of blood tests for Alzheimer's disease (AD) would be facilitated by easily scalable, cost-effective and accurate tests. In the present study, we evaluated plasma phospho-tau217 (p-tau217) using predefined biomarker cutoffs. The study included 1,767 participants with cognitive symptoms from 4 independent secondary care cohorts in Malmö (Sweden, n = 337), Gothenburg (Sweden, n = 165), Barcelona (Spain, n = 487) and Brescia (Italy, n = 230), and a primary care cohort in Sweden (n = 548). Plasma p-tau217 was primarily measured using the fully automated, commercially available, Lumipulse immunoassay. The primary outcome was AD pathology defined as abnormal cerebrospinal fluid Aβ42:p-tau181. Plasma p-tau217 detected AD pathology with areas under the receiver operating characteristic curves of 0.93-0.96. In secondary care, the accuracies were 89-91%, the positive predictive values 89-95% and the negative predictive values 77-90%. In primary care, the accuracy was 85%, the positive predictive values 82% and the negative predictive values 88%. Accuracy was lower in participants aged ≥80 years (83%), but was unaffected by chronic kidney disease, diabetes, sex, APOE genotype or cognitive stage. Using a two-cutoff approach, accuracies increased to 92-94% in secondary and primary care, excluding 12-17% with intermediate results. Using the plasma p-tau217:Aβ42 ratio did not improve accuracy but reduced intermediate test results (≤10%). Compared with a high-performing mass-spectrometry-based assay for percentage p-tau217, accuracies were comparable in secondary care. However, percentage p-tau217 had higher accuracy in primary care and was unaffected by age. In conclusion, this fully automated p-tau217 test demonstrates high accuracy for identifying AD pathology. A two-cutoff approach might be necessary to optimize performance across diverse settings and subpopulations.

Integrative network analysis reveals novel moderators of Aβ-Tau interaction in Alzheimer's disease

BACKGROUND

Although interactions between amyloid-beta and tau proteins have been implicated in Alzheimer's disease (AD), the precise mechanisms by which these interactions contribute to disease progression are not yet fully understood. Moreover, despite the growing application of deep learning in various biomedical fields, its application in integrating networks to analyze disease mechanisms in AD research remains limited. In this study, we employed BIONIC, a deep learning-based network integration method, to integrate proteomics and protein-protein interaction data, with an aim to uncover factors that moderate the effects of the Aβ-tau interaction on mild cognitive impairment (MCI) and early-stage AD.

METHODS

Proteomic data from the ROSMAP cohort were integrated with protein-protein interaction (PPI) data using a Deep Learning-based model. Linear regression analysis was applied to histopathological and gene expression data, and mutual information was used to detect moderating factors. Statistical significance was determined using the Benjamini-Hochberg correction (p < 0.05).

RESULTS

Our results suggested that astrocytes and GPNMB + microglia moderate the Aβ-tau interaction. Based on linear regression with histopathological and gene expression data, GFAP and IBA1 levels and GPNMB gene expression positively contributed to the interaction of tau with Aβ in non-dementia cases, replicating the results of the network analysis.

CONCLUSIONS

These findings suggest that GPNMB + microglia moderate the Aβ-tau interaction in early AD and therefore are a novel therapeutic target. To facilitate further research, we have made the integrated network available as a visualization tool for the scientific community (URL: https://igcore.cloud/GerOmics/AlzPPMap ).

Cutting through the noise: A narrative review of Alzheimer's disease plasma biomarkers for routine clinical use

As novel, anti-amyloid therapies have become more widely available, access to timely and accurate diagnosis has become integral to ensuring optimal treatment of patients with early-stage Alzheimer's disease (AD). Plasma biomarkers are a promising tool for identifying AD pathology; however, several technical and clinical factors need to be considered prior to their implementation in routine clinical use. Given the rapid pace of advancements in the field and the wide array of available biomarkers and tests, this review aims to summarize these considerations, evaluate available platforms, and discuss the steps needed to bring plasma biomarker testing to the clinic. We focus on plasma phosphorylated(p)-tau, specifically plasma p-tau217, as a robust candidate across both primary and secondary care settings. Despite the high performance and robustness demonstrated in research, plasma p-tau217, like all plasma biomarkers, can be affected by analytical and pre-analytical variability as well as patient comorbidities, sex, ethnicity, and race. This review also discusses the advantages of the two-point cut-off approach to mitigating these factors, and the challenges raised by the resulting intermediate range measurements, where clinical guidance is still unclear. Further validation of plasma p-tau217 in heterogeneous, real-world cohorts will help to increase confidence in testing and support establishing a standardized approach. Plasma biomarkers are poised to become a more affordable and less invasive alternative to PET and CSF testing. However, understanding the factors that impact plasma biomarker measurement and interpretation is critical prior to their implementation in routine clinical use.

The associations of cerebrospinal fluid ApoE and C1q with Alzheimer's disease biomarkers

BackgroundThe roles of complement 1q (C1q) and Apolipoprotein E (ApoE) in driving Alzheimer's disease (AD) progression might be explained by their associations with neuroinflammation and AD pathology which were previously reported.ObjectiveWe examined the associations of cerebrospinal fluid (CSF) C1q and ApoE with CSF neuroinflammatory biomarkers and AD core biomarkers, as well as explored whether C1q mediated the associations of CSF ApoE with these biomarkers.MethodsHere, we analyzed CSF proteomics data from Alzheimer's Disease Neuroimaging Initiative (ADNI) using two different ADNI proteomics datasets-SomaScan (n = 579)and multiple reaction monitoring (MRM[n = 207]). Linear regression analyses were conducted to explore the association of CSF ApoE and C1q. The mediation model and structural equation model (SEM) were conducted to explore the associations of ApoE and C1q with AD biomarkers.ResultsMultiple linear regression showed that CSF ApoE was positively associated with CSF C1q in total participants and Alzheimer's continuum participants. Mediation analyses indicated that C1q mediated the associations of CSF ApoE with CSF T-tau, P-tau, sTREM2 and GFAP (mediation proportions range from 15.06 to 44.64%; all the p values < 0.05) but not with CSF amyloid-β and progranulin (PGRN). The SEM yielded similar results.ConclusionsOur findings suggest that C1q is linked to ApoE, and it mediates the associations of ApoE with T-tau, P-tau, sTREM2, GFAP, indicating C1q association with ApoE might be involved in AD progression.

Cerebrospinal fluid VGF is associated with the onset and progression of Alzheimer's disease

BackgroundIt remains unclear whether cerebrospinal fluid (CSF) VGF (non-acronymic) is associated with the onset and progression of Alzheimer's disease (AD).ObjectiveTo assess the levels of CSF VGF throughout the AD continuum, and its association with primary AD pathology, cognition, brain atrophy, and brain metabolism.MethodsWe studied a total of 526 individuals including 377 amyloid-positive individuals (76 preclinical AD, 200 prodromal AD, and 101 AD dementia) and 149 amyloid-negative cognitively normal individuals. VGF peptide in CSF was analyzed using mass spectrometry.ResultsWe observed decreased CSF VGF in preclinical, prodromal, and AD dementia individuals than amyloid-negative cognitively normal individuals. Reduced CSF VGF was associated with cognitive decline, hippocampal atrophy, ventricle enlargement, and glucose hypometabolism at baseline, and it predicted a more marked deterioration over time.ConclusionsOur findings support the important contributions of VGF to disease pathogenesis and progression in the early stages of AD. Exploring the biologics modulating VGF might be a promising approach for AD prevention and early treatment.

Navigating the blurred boundary: Neuropathologic changes versus clinical symptoms in Alzheimer's disease, and its consequences for research in genetics

During decades scientists tried to unveil the genetic architecture of Alzheimer's disease (AD), recurring to increasingly larger sample numbers for genome-wide association studies (GWAS) in hope for higher statistical gains. Here, a retrospective look on the most prominent GWAS was performed, focusing on the quality of the diagnosis associated with the used data and databases. Different methods for AD diagnosis (or absence) carry different levels of accuracy and certainty applied to both subsets of cases and controls. Furthermore, the different phenotypes included in these databases were explored, as several incorporate other ageing comorbidities and might be encompassing many confounding agents as well. Age of the samples' donors and origin populations were also investigated as these could be biasing factors in posterior analyses. A tendency for looser diagnostic methods in more recent GWAS was observed, where greater datasets of individuals are analyzed, which may have been hampering the discovery of associated genetic variants. Specifically for AD, a diagnostic method conveying a clinical outcome may be distinct from the disease neuropathological assessment, since the first has a practical perspective that not necessarily needs a confirmation. Due to its properties and complex diagnosis, this work highlights the importance of the neuropathological confirmation of AD (or its absence) in the subjects considered for research purposes to avoid reaching statistically weak and/or misleading conclusions that may trigger further studies with powerless groundwork.

In vivo-measured Lewy body pathology is associated with neuropsychiatric symptoms across the Alzheimer's disease continuum

Intracellular alpha-synuclein aggregates, known as Lewy bodies (LB), are commonly observed in Alzheimer's disease (AD) dementia. Post-mortem studies have shown a higher frequency of neuropsychiatric symptoms among individuals with AD and LB co-pathology. However, the effects of in vivo-measured LB pathology on neuropsychiatric symptoms in AD remain underexplored. This study aimed to evaluate cross-sectional and longitudinal effects of in vivo-measured LB pathology on neuropsychiatric symptoms across the AD continuum. We analyzed data from 1,169 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants had in vivo measures of LB pathology (assessed using an alpha-synuclein seed amplification assay), amyloid-beta (Aβ) and phosphorylated tau (p-tau) levels in cerebrospinal fluid (CSF), and neuropsychiatric symptoms evaluated using the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Logistic and Cox proportional hazards regression models were used to assess cross-sectional and longitudinal effects, respectively, adjusting for age, sex, and cognitive status. Participants had a mean baseline age of 73.05 (SD 7.22) years, 47.13% were women, 426 (36.44%) cognitively unimpaired, and 743 (63.56%) cognitively impaired. In cross-sectional analyses, LB pathology was associated with higher rates of anxiety, apathy, motor disturbances, and appetite disturbances. In longitudinal analyses, LB pathology increased the risk of developing psychosis and anxiety. These effects were independent of Aβ and p-tau. Our results suggest that in vivo-measured LB pathology is closely associated with neuropsychiatric symptoms across the AD continuum. These findings underscore the potential of in vivo LB detection as a marker for identifying individuals at increased risk of neuropsychiatric symptoms, both in clinical trials and in clinical practice.

New approach to specific Alzheimer's disease diagnosis based on plasma biomarkers in a cognitive disorder cohort

BACKGROUND

The validation of a combination of plasma biomarkers and demographic variables is required to establish reliable cut-offs for Alzheimer's disease diagnosis (AD).

METHODS

Plasma biomarkers (Aβ42/Aβ40, p-Tau181, t-Tau, NfL, GFAP), ApoE genotype, and demographic variables were obtained from a retrospective clinical cohort of cognitive disorders (n = 478). These patients were diagnosed as AD (n = 254) or non-AD (n = 224) according to cerebrospinal fluid (CSF) Aβ42/Aβ40 levels. An analysis using a Ridge logistic regression model was performed to predict the occurrence of AD. The predictive performance of the model was assessed using the observations from a training set (70% of the sample) and validated using a test set (30% of the sample) in each group. Optimum cutoffs for the model were evaluated.

RESULTS

The model including plasma Aβ42/Aβ40, p-Tau181, GFAP, ApoE genotype and age was optimal for predicting CSF Aβ42/Aβ40 positivity (AUC .91, sensitivity .86, specificity .82). The model including only plasma biomarkers (Aβ42/Aβ40, p-Tau181, GFAP) provided reliable results (AUC .88, sensitivity .83, specificity .78). Also, GFAP, individually, showed the best performance in discriminating between AD and non-AD groups (AUC .859). The established cut-offs in a three-range strategy performed satisfactorily for the validated predictive model (probability) and individual plasma GFAP (concentration).

CONCLUSIONS

The plasma GFAP levels and the validated predictive model based on plasma biomarkers represent a relevant step toward the development of a potential clinical approach for AD diagnosis, which should be assessed in further research.

Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer's disease continuum

Amyloid-β (Aβ) plaques in conjunction with hyperphosphorylated tau proteins in the form of neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer's disease. It is well-known that the identification of individuals with Aβ positivity could enable early diagnosis. In this work, we aim at capturing the Aβ positivity status in an unbalanced cohort enclosing subjects at different disease stages, exploiting the underlying structural and connectivity disease-induced modulations as revealed by structural, functional, and diffusion MRI. Of note, due to the unbalanced cohort, the outcomes may be guided by those factors rather than amyloid accumulation. The partial views provided by each modality are integrated in the model, allowing to take full advantage of their complementarity in encoding the effects of the Aβ accumulation, leading to an accuracy of 0.762 ± 0.04. The specificity of the information brought by each modality is assessed by post hoc explainability analysis (guided backpropagation), highlighting the underlying structural and functional changes. Noteworthy, well-established biomarker key regions related to Aβ deposition could be identified by all modalities, including the hippocampus, thalamus, precuneus, and cingulate gyrus, witnessing in favor of the reliability of the method as well as its potential in shedding light on modality-specific possibly unknown Aβ deposition signatures.

The abnormal accumulation of pathological proteins and compensatory functional connectivity enhancement of insula subdivisions in mild cognitive impairment

Background

The insula is a critical node of the salience network responsible for initiating network switching, and its dysfunctional connections are linked to the mechanisms of mild cognitive impairment (MCI). This study aimed to explore the changes in functional connectivity (FC) of insular subregions in MCI patients with varying levels of cerebrospinal fluid (CSF) pathological proteins, and to investigate the impact of these proteins on the brain network alterations in MCI.

Methods

Based on CSF Amyloid-beta (Aβ, A) and phosphorylated tau protein (p-tau, T), MCI patients were classified into 54 A-T-, 28 A+T-, and 52 A+T+ groups. Seed-based FC analysis was employed to compare the FC differences of insular subregions across the three groups. Correlation analysis was further conducted to explore the relationship between altered FC and cognitive function. Finally, ROC curve analysis was used to assess the diagnostic value of altered FC of insular subregion in distinguishing between the groups.

Results

In the left ventral anterior insula, left dorsal anterior insula, and bilateral posterior insular subnetworks, both the A+T- and A+T+ groups showed increased FC compared to the A-T- group, with the A+T+ group showing further increased FC compared to the A+T- group. Additionally, FC of the left cerebellar posterior lobe was negatively correlated with RAVLT-learning, and FC of the left middle frontal gyrus was negatively correlated with p-tau levels. Finally, logistic regression analysis demonstrated that multivariable analysis had high sensitivity and specificity in distinguishing between the groups.

Conclusion

This study showed that MCI patients with abnormal CSF pathological protein levels exhibit compensatory increases in FC of insular subregions, which in turn affect cognitive function. Our findings contributed to a better understanding of the pathophysiology and underlying neural mechanisms of MCI.

Large-scale Plasma Proteomic Profiling Unveils Novel Diagnostic Biomarkers and Pathways for Alzheimer's Disease

Alzheimer disease (AD) is a complex neurodegenerative disorder. Proteomic studies have been instrumental in identifying AD-related proteins present in the brain, cerebrospinal fluid, and plasma. This study comprehensively examined 6,905 plasma proteins in more than 3,300 well-characterized individuals to identify new proteins, pathways, and predictive model for AD. With three-stage analysis (discovery, replication, and meta-analysis) we identified 416 proteins (294 novel) associated with clinical AD status and the findings were further validated in two external datasets including more than 7,000 samples and seven previous studies. Pathway analysis revealed that these proteins were involved in endothelial and blood hemostatic (ACHE, SMOC1, SMOC2, VEGFA, VEGFB, SPARC), capturing blood brain barrier (BBB) disruption due to disease. Other pathways were capturing known processes implicated in AD, such as lipid dysregulation (APOE, BIN1, CLU, SMPD1, PLA2G12A, CTSF) or immune response (C5, CFB, DEFA5, FBXL4), which includes proteins known to be part of the causal pathway indicating that some of the identified proteins and pathways are involved in disease pathogenesis. An enrichment of brain and neural pathways (axonal guidance signaling or myelination signaling) indicates that, in fact, blood proteomics capture brain- and disease-related changes, which can lead to the identification of novel biomarkers and predictive models. Machine learning model was employed to identify a set of seven proteins that were highly predictive of both clinical AD (AUC > 0.72) and biomarker-defined AD status (AUC > 0.88), that were replicated in multiple external cohorts as well as with orthogonal platforms. These extensive findings underscore the potential of using plasma proteins as biomarkers for early detection and monitoring of AD, as well as potentially guiding treatment decisions.

Concordance between the updated Elecsys cerebrospinal fluid immunoassays and amyloid positron emission tomography for Alzheimer's disease assessment: findings from the Apollo study

OBJECTIVES

The Apollo study was designed to support the clinical performance verification of the adjusted cutoffs of the Elecsys® β-Amyloid(1-42) (Aβ42) cerebrospinal fluid (CSF) II, β-Amyloid(1-40) (Aβ40) CSF, Phospho-Tau (181P) (pTau) CSF and Total-Tau (tTau) CSF immunoassays (Roche Diagnostics International Ltd) for measuring fresh CSF samples, and assess the concordance of the Elecsys CSF pTau/Aβ42, tTau/Aβ42 and Aβ42/Aβ40 ratios, as well as Aβ42 alone, with amyloid positron emission tomography (PET) visual read status.

METHODS

The primary study endpoint was to assess the concordance of the Elecsys CSF ratios and Aβ42 alone with amyloid PET visual read status using fresh CSF samples collected from individuals with subjective cognitive decline or mild cognitive impairment, handled with a new routine-use pre-analytical procedure and measured with the Elecsys CSF immunoassays. The sample stability after 1- to 13-week storage at -20 °C was also investigated in an exploratory analysis.

RESULTS

Of 108 screened individuals, 91 met the eligibility criteria, of whom 44.0 % were amyloid PET-positive and 56.0 % amyloid PET-negative. Positive percent agreement (PPA) and negative percent agreement, respectively, were 0.800 and 0.882 for pTau/Aβ42, 0.775 and 0.902 for tTau/Aβ42, and 0.950 and 0.824 for Aβ42/Aβ40. For Aβ42, PPA was 0.975 and negative likelihood ratio was 0.039. Overall, 33 samples (36.3 %) were frozen at -20 °C for 1-13 weeks. All concentration recoveries were within 100 ± 10 % when stored at -20 °C for ≤8 weeks.

CONCLUSIONS

Elecsys CSF ratios and Aβ42 alone may be reliable alternatives to amyloid PET for identifying amyloid positivity in clinical practice.

LRRK2-associated parkinsonism with and without in vivo evidence of alpha-synuclein aggregates: longitudinal clinical and biomarker characterization

Among LRRK2-associated parkinsonism cases with nigral degeneration, over two-thirds demonstrate evidence of pathologic alpha-synuclein, but many do not. Understanding the clinical phenotype and underlying biology in such individuals is critical for therapeutic development. Our objective was to compare clinical and biomarker features, and rate of progression over 4 years of follow-up, among LRRK2-associated parkinsonism cases with and without in vivo evidence of alpha-synuclein aggregates. Data were from the Parkinson's Progression Markers Initiative, a multicentre prospective cohort study. The sample included individuals diagnosed with Parkinson disease with pathogenic variants in LRRK2. Presence of CSF alpha-synuclein aggregation was assessed with seed amplification assay. A range of clinician- and patient-reported outcome assessments were administered. Biomarkers included dopamine transporter scan, CSF amyloid-beta1-42, total tau, phospho-tau181, urine bis(monoacylglycerol)phosphate levels and serum neurofilament light chain. Linear mixed-effects (LMMs) models examined differences in trajectory in CSF-negative and CSF-positive groups. A total of 148 LRRK2 parkinsonism cases (86% with G2019S variant), 46 negative and 102 positive for CSF alpha-synuclein seed amplification assay, were included. At baseline, the negative group was older than the positive group [median (inter-quartile range) 69.1 (65.2-72.3) versus 61.5 (55.6-66.9) years, P < 0.001] and a greater proportion were female [28 (61%) versus 43 (42%), P = 0.035]. Despite being older, the negative group had similar duration since diagnosis and similar motor rating scale [16 (11-23) versus 16 (10-22), P = 0.480] though lower levodopa equivalents. Only 13 (29%) of the negative group were hyposmic, compared with 75 (77%) of the positive group. The negative group, compared with the positive group, had higher per cent-expected putamenal dopamine transporter binding for their age and sex [0.36 (0.29-0.45) versus 0.26 (0.22-0.37), P < 0.001]. Serum neurofilament light chain was higher in the negative group compared with the positive group [17.10 (13.60-22.10) versus 10.50 (8.43-14.70) pg/mL; age-adjusted P-value = 0.013]. In terms of longitudinal change, the negative group remained stable in functional rating scale score in contrast to the positive group who had a significant increase (worsening) of 0.729 per year (P = 0.037), but no other differences in trajectory were found. Among individuals diagnosed with Parkinson disease with pathogenic variants in the LRRK2 gene, we found clinical and biomarker differences in cases without versus with in vivo evidence of CSF alpha-synuclein aggregates. LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates as a group exhibit less severe motor manifestations and decline. The underlying biology in LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates requires further investigation.

Considerations in the clinical use of amyloid PET and CSF biomarkers for Alzheimer's disease

Amyloid-β (Aβ) positron emission tomography (PET) imaging and cerebrospinal fluid (CSF) biomarkers are now established tools in the diagnostic workup of patients with Alzheimer's disease (AD), and their use is anticipated to increase with the introduction of new disease-modifying therapies. Although these biomarkers are comparable alternatives in research settings to determine Aβ status, biomarker testing in clinical practice requires careful consideration of the strengths and limitations of each modality, as well as the specific clinical context, to identify which test is best suited for each patient. This article provides a comprehensive review of the pathologic processes reflected by Aβ-PET and CSF biomarkers, their performance, and their current and future applications and contexts of use. The primary aim is to assist clinicians in making better-informed decisions about the suitability of each biomarker in different clinical situations, thereby reducing the risk of misdiagnosis or incorrect interpretation of biomarker results. HIGHLIGHTS: Recent advances have positioned Aβ PET and CSF biomarkers as pivotal in AD diagnosis. It is crucial to understand the differences in the clinical use of these biomarkers. A team of experts reviewed the state of Aβ PET and CSF markers in clinical settings. Differential features in the clinical application of these biomarkers were reviewed. We discussed the role of Aβ PET and CSF in the context of novel plasma biomarkers.

Aerobic exercise improves clearance of amyloid-β via the glymphatic system in a mouse model of Alzheimer's Disease

BACKGROUND

Aerobic exercise training can promote the recovery of learning and memory ability in Alzheimer's disease (AD), but the specific mechanism is still unclear. Previous studies have suggested that aquaporin-4 (AQP4)-mediated glymphatic system is an important way to clear β-amyloid (Aβ) in the brain, which is closely related to learning and memory impairment in AD. However, it remains unclear whether AQP4 regulates glymphatic clearance of Aβ which contributes to the beneficial effects of aerobic exercise in AD patients. Here, the goal of this study was to investigate the mechanisms about aerobic exercise whether AQP4 could modulate glymphatic system using APP/PS1 mice.

METHODS

In this study, APP/PS1 AD model mice were treated with aerobic exercise intervention through swimming exercise training for 4 weeks, and the two groups of mice were injected with AQP4 inhibition virus and empty virus, respectively. Their learning and memory abilities were assessed using behavioral tests, such as the Barnes maze and Morris water maze tests. Hippocampus was obtained from sacrificed mice and used for histological analysis. Tracer imaging of the cerebellar medullary pool was used to observed the CSF-ISF exchange, immunohistochemistry was used to detect the level of Aβ plaques in the hippocampus of mice in each group; immunoblotting was used to detect the expression of AQP4 protein; immunofluorescence co-labeling was used to detect the polarization distribution of AQP4; qRT-PCR was used to detect the transcription levels of AQP4 and its anchoring proteins.

RESULTS

The funding showed that APP/PS1 mice have learning and memory impairment, and the glymphatic system is dysfunction. Swimming training can improve the ability of the glymphatic system to clear Aβ deposition in the hippocampus by up-regulating the transcription levels of Lama1 and Dp71 in the hippocampus, reducing the depolarization distribution of AQP4 in the hippocampus, and enhancing the exchange of CSF-ISF. Thus, improves learning and memory impairment in APP/PS1 mice.

CONCLUSIONS

Swimming training can rescue the function of the glymphatic system, increase the CSF-ISF exchange, promote the polarization distribution of AQP4, and reduce the deposition of Aβ in the hippocampus, thereby improving the learning and memory ability of APP/PS1 mice.

Amyloid PET predicts longitudinal functional and cognitive trajectories in a heterogeneous cohort

INTRODUCTION

Amyloid positron emission tomography (PET) is increasingly available for diagnosis of Alzheimer`s disease (AD); however, its practical implications in heterogenous cohorts are debated.

METHODS

Amyloid PET from 890 National Alzheimer`s Coordinating Center participants with up to 10 years post-PET follow up was analyzed. Cox proportional hazards and linear mixed models were used to investigate amyloid burden prediction of etiology and prospective functional status and cognitive decline.

RESULTS

Amyloid positivity was associated with progression from unimpaired to mild cognitive impairment and dementia. Amyloid burden in the unimpaired group was associated with lower initial memory levels and faster decline in memory, language, and global cognition. In the Impaired group, amyloid was associated with lower initial levels and faster decline for memory, language, executive function, and global cognition.

DISCUSSION

Amyloid burden is an important prognostic marker in a clinically heterogeneous cohort. Future work is needed to establish the proportion of decline driven by AD versus non-AD processes in the context of mixed pathology.

HIGHLIGHTS

Our findings highlight the importance of amyloid positron emission tomography (PET) in heterogenous cohorts, including diverse demographics, clinical syndromes, and underlying etiologies. The results also provide evidence that higher amyloid levels were linked to functional progression from unimpaired cognition to mild cognitive impairment (MCI) and from MCI to dementia. In cognitively unimpaired individuals, higher amyloid burden was associated with poorer memory at baseline and subsequent declines in memory, language, and global cognition. Among individuals with cognitive impairment, amyloid burden was associated with worse initial memory, language, executive function, and global cognition, and faster declines over time.

Clinical Importance of Amyloid Beta Implication in the Detection and Treatment of Alzheimer's Disease

The role of amyloid beta peptide (Aβ) in memory regulation has been a subject of substantial interest and debate in neuroscience, because of both physiological and clinical issues. Understanding the dual nature of Aβ in memory regulation is crucial for developing effective treatments for Alzheimer's disease (AD). Moreover, accurate detection and quantification methods of Aβ isoforms have been tested for diagnostic purposes and therapeutic interventions. This review provides insight into the current knowledge about the methods of amyloid beta detection in vivo and in vitro by fluid tests and brain imaging methods (PET), which allow for preclinical recognition of the disease. Currently, the priority in the development of new therapies for Alzheimer's disease has been given to potential changes in the progression of the disease. In light of increasing amounts of data, this review was focused on the diagnostic and therapeutic employment of amyloid beta in Alzheimer's disease.

The impact of kidney function on Alzheimer's disease blood biomarkers: implications for predicting amyloid-β positivity

BACKGROUND

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer's disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity.

METHODS

We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [18F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m2, based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models.

RESULTS

Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values.

CONCLUSIONS

We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

Comparative analysis of Elecsys and ELISA for differentiating amyloid-PET status in a Korean memory clinic based on cerebrospinal fluid biomarkers

BACKGROUND

The adoption of Alzheimer's disease (AD) biomarkers in clinical practice is expected to increase following recent approval of disease-modifying therapies. Fully automated immunoassays, Elecsys platform, offer convenience and enhanced reliability.

OBJECTIVE

This study was performed to evaluate the performance of the Elecsys assay in a Korean clinical setting, comparing its effectiveness to ELISA for detecting amyloid-PET positivity.

METHODS

Cerebrospinal fluid (CSF) Aβ42, pTau181, tTau, pTau181/Aβ42, and tTau/Aβ42 were evaluated using Elecsys kits on a Cobas e 411 analyzer and manual Innotest ELISA with paired frozen samples (n = 118) from subjects with cognitive status ranging from unimpaired to mild cognitive impairment and dementia.

RESULTS

Strong linear correlations were observed between Elecsys- and ELISA-measured Aβ42, pTau181, and tTau levels. Receiver operating characteristic-based cutoff points for pTau181/Aβ42 (0.0252) and tTau/Aβ42 (0.258) in Elecsys demonstrated the highest areas under the curve (0.97 and 0.96) and predictive values (96.6% for both) for detecting amyloid-PET abnormalities. No cases of abnormal amyloid PET status were found without concurrent abnormal CSF biomarkers when considering Elecsys Aβ42 and the pTau181/Aβ42 ratio simultaneously. In addition, previously established cutoffs for combined ratios effectively differentiated amyloid PET status in our samples.

CONCLUSIONS

This study demonstrated the utility of Elecsys-measured CSF AD biomarkers in agreement with amyloid-PET classification in the Korean population. The pTau181/Aβ42 and tTau/Aβ42 ratios were the most accurate in detecting amyloid-PET (+), with Elecsys showing higher accuracy than ELISA. The study also supported the applicability of common cutoffs from Western countries for these biomarkers in our samples.

Altered spatiotemporal consistency and their genetic mechanisms in mild cognitive impairment: a combined neuroimaging and transcriptome study

The Four-dimensional (spatiotemporal) Consistency of local Neural Activities (FOCA) metric was utilized to assess spontaneous whole-brain activity. Despite its application, the genetic underpinnings of FOCA alterations in Alzheimer's Disease (AD)-related Mild Cognitive Impairment (MCI) remain largely unexplored. To elucidate these changes, we analyzed group FOCA differences in 41 MCI patients and 46 controls from the Alzheimer's Disease Neuroimaging Initiative database. Integrating the Allen Human Brain Atlas, we performed transcriptome-neuroimaging spatial association analyses to pinpoint genes correlating with MCI-related FOCA changes. We observed heightened FOCA in the frontal-parietal system and diminished FOCA in the temporal lobe and medium cingulate gyrus among MCI patients. These FOCA alterations were spatially linked to the expression of 384 genes, which were enriched in crucial molecular functions, biological processes, and cellular components of the cerebral cortex, as well as related pathways. These genes were specifically expressed in brain tissue and corticothalamic neurons, particularly during late cortical development. They also connected to various behavioral domains. Furthermore, these genes could form a protein-protein interaction network, supported by 34 hub genes. Our results suggest that local spatiotemporal consistency of spontaneous brain activity in MCI may stem from the complex interplay of a broad spectrum of genes with diverse functional features.

A comprehensive head-to-head comparison of key plasma phosphorylated tau 217 biomarker tests

Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarker for reliable detection of Alzheimer's disease pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET and cognition as outcomes and benchmarked them against CSF biomarker tests. Samples from 998 individuals [mean (range) age 68.5 (20.0-92.5) years, 53% female] from the Swedish BioFINDER-2 cohort, including both cognitively unimpaired and cognitively impaired individuals, were analysed. Plasma p-tau217 was measured with mass spectrometry assays [the ratio between phosphorylated and non-phosphorylated (%p-tau217WashU) and p-tau217WashU] and with immunoassays (p-tau217Lilly, p-tau217Janssen and p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, the US Food and Drug Administration-approved p-tau181/Aβ42Elecsys, and p-tau181Elecsys. All plasma p-tau217 tests exhibited a high ability to detect abnormal Aβ-PET [area under the curve (AUC) range: 0.91-0.96] and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (Pdiff < 0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 0.91 (immunoassays: 0.84-0.87) and a specificity of 0.94 (immunoassays: 0.85-0.89). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (Pdiff < 0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (Pdiff = 0.025). Plasma %p-tau217WashU exhibited stronger associations with all PET load outcomes compared with immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff < 0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff < 0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff < 0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff < 0.014). Among immunoassays, plasma p-tau217Lilly was more associated with Aβ-PET load than plasma p-tau217Janssen (Pdiff < 0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all Pdiff < 0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination) than all immunoassays (R2: %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; Pdiff < 0.024). The main results were replicated in an external cohort from Washington University in St Louis (n = 219). Finally, p-tau217NULISA showed similar performance to other immunoassays in subsets of both cohorts. In summary, both mass spectrometry- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for Alzheimer's disease pathology, whereas some immunoassays might be better suited as triage tests where positive results are confirmed with a second test, which needs to be determined by future reviews incorporating results from multiple cohorts.

Agreement of cerebrospinal fluid biomarkers and amyloid-PET in a multicenter study

Core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers have shown incomplete agreement with amyloid-positron emission tomography (PET). Our goal was to analyze the agreement between AD CSF biomarkers and amyloid-PET in a multicenter study. Retrospective multicenter study (5 centers). Participants who underwent both CSF biomarkers and amyloid-PET scan within 18 months were included. Clinical diagnoses were made according to latest diagnostic criteria by the attending clinicians. CSF Amyloid Beta1-42 (Aβ1-42, A), phosphorliated tau 181 (pTau181, T) and total tau (tTau, N) biomarkers were considered normal (-) or abnormal ( +) according to cutoffs of each center. Amyloid-PET was visually classified as positive/negative. Agreement between CSF biomarkers and amyloid-PET was analyzed by overall percent agreement (OPA). 236 participants were included (mean age 67.9 years (SD 9.1), MMSE score 24.5 (SD 4.1)). Diagnoses were mild cognitive impairment or dementia due to AD (49%), Lewy body dementia (22%), frontotemporal dementia (10%) and others (19%). Mean time between tests was 5.1 months (SD 4.1). OPA between single CSF biomarkers and amyloid-PET was 74% for Aβ1-42, 75% for pTau181, 73% for tTau. The use of biomarker ratios improved OPA: 87% for Aβ1-42/Aβ1-40 (n = 155), 88% for pTau181/Aβ1-42 (n = 94) and 82% for tTau/Aβ1-42 (n = 160). A + T + N + cases showed the highest agreement between CSF biomarkers and amyloid-PET (96%), followed by A-T-N- cases (89%). Aβ1-42/Aβ1-40 was a better marker of cerebral amyloid deposition, as identified by amyloid tracers, than Aβ1-42 alone. Combined biomarkers in CSF predicted amyloid-PET result better than single biomarkers.

Associations of tau, Aβ, and brain volume of the Papez circuit with cognition in Alzheimer's disease

This study aimed to investigate the cross-sectional associations between regional Alzheimer's disease (AD) biomarkers, including tau, β-amyloid (Aβ), and brain volume, within the Papez circuit, and neuropsychological functioning across the preclinical and clinical spectrum of AD. We utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including 251 Aβ-positive participants. Participants were categorized into three groups based on the Clinical Dementia Rating (CDR): 73 individuals with preclinical AD (CDR = 0), 114 with prodromal AD (CDR = 0.5), and 64 with clinical AD dementia (CDR ≥ 1). Linear regression analyses, adjusted for age, gender, and education years, were employed to evaluate the associations between five regions of interest (the hippocampus, para-hippocampus, entorhinal cortex, posterior cingulate cortex, and thalamus) and five neuropsychological tests across the three imaging modalities. In the preclinical stage of AD, flortaucipir PET was associated with impaired global cognition and episodic memory (range standardized β = 0.255-0.498, p < 0.05 corrected for multiple comparisons), while florbetapir PET and brain volume were marginally related to global cognition (range standardized β = 0.221-0.231, p < 0.05). In the clinical stages of AD (prodromal and dementia), both increased flortaucipir uptake and decreased brain volume were significantly associated with poorer global neuropsychological and episodic memory performance (range standardized β = 0.222-0.621, p < 0.05, most regions of interest survived correction for multiple comparisions). However, a slight relationship was observed between florbetapir uptake and poorer global cognitive function. The regions most affected by flortaucipir PET were the hippocampus, para-hippocampus, and posterior cingulate cortex. During the clinical stages, the hippocampus and entorhinal cortex exhibited the most significant volumetric changes. Tau PET and brain volume measurements within the Papez circuit are more sensitive indicators of early cognitive deficits in AD than Aβ PET. Furthermore, during the clinical stages of AD, both flortaucipir PET and brain volume of the Papez circuit are closely correlated with cognitive decline. These findings underscore the importance of integrating multiple biomarkers for the comprehensive evaluation of AD pathology and its impact on cognition.

A head-to-head comparison of plasma biomarkers to detect Alzheimer's disease in a memory clinic

INTRODUCTION

Blood-based biomarkers for Alzheimer's disease (AD) have been widely studied, but direct comparisons of several biomarkers in clinical settings remain limited.

METHODS

In this cross-sectional study, plasma biomarkers from 197 participants in the BIODEGMAR cohort (Hospital del Mar, Barcelona) were analyzed. Participants were classified based on AD cerebrospinal fluid (CSF) core biomarkers. We assessed the ability of plasma p-tau181, p-tau217, p-tau231, t-tau, and Aβ42/40 to classify Aβ pathology status.

RESULTS

Plasma p-tau biomarkers had a greater diagnostic performance and larger effect sizes compared to t-tau and Aβ42/40 assays in detecting Aβ pathology. Among them, plasma p-tau217 consistently outperformed the others, demonstrating superior area under the curves. Furthermore, p-tau217 showed the strongest correlation between plasma and CSF levels, underscoring its potential as a reliable surrogate for CSF biomarkers.

DISCUSSION

Several plasma biomarkers, targeting different epitopes and using different platforms, demonstrated high performance in detecting AD in a memory clinic setting.

HIGHLIGHTS

Plasma p-tau biomarkers demonstrated higher diagnostic performance and larger effect sizes than t-tau and Aβ42/40 assays in detecting Alzheimer's disease. Among the p-tau biomarkers, p-tau217 assays consistently outperformed the others, providing superior classification of Aβ pathology status across different phosphorylation sites. p-tau217 assays showed the strongest correlation between plasma and CSF levels, indicating its potential as a reliable surrogate for CSF biomarkers. Several plasma p-tau biomarkers can be used in a specialized memory clinic to accurately detect Alzheimer's disease.

Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?

INTRODUCTION

Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict cognitive worsening.

METHODS

We selected cognitively normal and MCI participants from the Alzheimer's Disease Neuroimaging Initiative dataset and categorized them on total tau/amyloid beta 1-42 ratios. ML was applied to predict the 3-year conversion with standard clinical data (SCD), assess the model's accuracy, and identify the role of cerebrospinal fluid (CSF) biomarkers in this approach. Shapley Additive Explanations (SHAP) analysis was carried out to explore the automated decisional process.

RESULTS

The model achieved 84% accuracy across the entire cohort, 86% in patients with negative CSF, and 88% in individuals with AD-like CSF. SHAP analysis identified differences between CSF-positive and -negative patients in predictors of conversion and cut-offs.

CONCLUSIONS

The approach yielded good prediction accuracy using SCD. However, CSF-based categorizations are needed to improve predictive accuracy.

HIGHLIGHTS

Machine learning algorithms can predict cognitive decline with standard and routinely used clinical data. Classification according to cerebrospinal fluid biomarkers enhances prediction accuracy. Different cut-offs could be applied to neuropsychological tests to predict conversion.

Neuroimaging Predictors of Cognitive Resilience against Alzheimer's Disease Pathology

OBJECTIVE

Some individuals demonstrate greater cognitive resilience-the ability to maintain cognitive performance despite adverse brain-related changes-through as yet unknown mechanisms. We examined whether cortical thickness in several brain regions confers resilience against cognitive decline in amyloid-positive adults by moderating the effects of thinner cortex in Alzheimer's disease (AD)-related brain regions and of higher levels of tau.

METHODS

Amyloid-positive participants from the Alzheimer's Disease Neuroimaging Initiative with relevant imaging data were included (n = 160, observations = 473). Risk factors included an AD brain signature and cerebrospinal fluid phosphorylated tau. Cognitive measures were episodic memory and executive function composites. Mixed effects models tested whether region-specific cortical thickness moderated relationships between markers of AD risk and memory or executive function.

RESULTS

Cross-sectionally, thicker cortex in 8 regions minimized the negative impact of thinner cortex/smaller volume in AD signature regions on executive function. Longitudinally, higher baseline thickness in a composite of these 8 regions predicted less memory decline (p = 0.007) and weakened negative effects of phosphorylated tau on memory decline (p = 0.014), independent of baseline cognition and risk markers.

INTERPRETATION

We identified 8 cortical regions that appear to confer cognitive resilience cross-sectionally and longitudinally in the face of established indicators of AD pathology. Brain regions fostering executive function may enable compensation in later memory performance and confer cognitive resilience against effects of phosphorylated tau and AD-related cortical changes. These "resilience" regions suggest the value of focusing on brain regions beyond only those determined to be AD-related and may partially explain variability in AD-related cognitive trajectories. ANN NEUROL 2025.

Ultrasensitive SERS nanoprobe-based multiplexed digital sensing platform for the simultaneous quantification of Alzheimer's disease biomarkers

Alzheimer's disease (AD) is a severe neurodegenerative disease that requires early diagnosis to manage its progression. Although the simultaneous detection of multiple AD biomarkers is expected to facilitate early assessment of AD risk, the lack of multiplexed sensing platforms for accurately quantifying multiple AD biomarkers remains a challenge. Here, we present a multiplexed digital sensing platform based on bumpy core-shell (BCS) surface-enhanced Raman spectroscopy (SERS) nanoprobes for ultrasensitive, quantitative, and simultaneous detection of Aβ42 and Aβ40 as AD biomarkers, enabling the accurate determination of the Aβ42/Aβ40 ratio. We synthesized BCS SERS nanoprobes with distinct Raman reporters to generate unique, intense, and reproducible SERS signals, offering single-nanoparticle sensitivity and quantification capabilities. These nanoprobes were subsequently employed in SERS-based immunoassays combined with digital SERS analysis for multiplexed quantification. The proposed platform accurately and quantitatively detected Aβ42 and Aβ40 across a range of five orders of magnitude, with a limit of detection of 8.7× 10-17 g/mL (1.9 × 10-17 M) for Aβ42 and 1.0 × 10-15 g/mL (2.3 × 10-16 M) for Aβ40, surpassing the performance of conventional enzyme-linked immunosorbent assays. Based on the exclusive detection of Aβ42 and Aβ40 using distinct SERS nanoprobes, the proposed sensing platform can also accurately quantify Aβ42 and Aβ40 at clinically relevant levels in both cerebrospinal fluid and blood plasma. Therefore, this sensing platform can be used to accurately and reliably determine the Aβ42/Aβ40 ratio, thus serving as an effective tool for the early diagnosis of AD.

The ratio of plasma pTau217 to Aβ42 outperforms individual measurements in detecting brain amyloidosis

IMPORTANCE

Early detection of brain amyloidosis (Aβ+) is pivotal for diagnosing Alzheimer's disease (AD) and optimizing patient management, especially in light of emerging treatments. While plasma biomarkers are promising, their combined diagnostic value through specific ratios remains underexplored.

OBJECTIVE

To evaluate the diagnostic accuracy of plasma pTau isoform (pTau181 and pTau217) to Aβ42 ratios in detecting Aβ+ status.

DESIGN SETTING AND PARTICIPANTS

This study included 423 participants from the multicenter prospective ALZAN cohort, recruited for cognitive complaints. Aβ+ status was determined using cerebrospinal fluid (CSF) biomarkers. Validation of the key findings was performed in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, where Aβ+ status was determined using PET imaging.

EXPOSURES

Plasma biomarkers (pTau181, pTau217, Aβ40, Aβ42) were measured using immunoassays and mass spectrometry, with specific ratios calculated. In the ALZAN cohort, the impact of confounding factors such as age, renal function, ApoE4 status, body mass index, and the delay between blood collection and processing was also evaluated to assess their influence on biomarker concentrations and diagnostic performance.

MAIN OUTCOMES AND MEASURES

The primary outcome was the diagnostic performance of plasma biomarkers and their ratios for detecting Aβ+ status. Secondary outcomes included the proportion of patients classified as low, intermediate, or high risk for Aβ+ using a two-cutoff approach.

RESULTS

The pTau181/Aβ42 ratio matched the diagnostic performance of pTau217 with AUC of 0.911 (0.880-0.936). The pTau217/Aβ42 ratio demonstrated the highest diagnostic accuracy in the ALZAN cohort, with an AUC of 0.927 (0.898-0.950), outperforming individual biomarkers. Both ratios effectively mitigated confounding factors, such as variations in renal function, and were particularly excellent in identifying Aβ+ status in individuals with early cognitive decline. Validation in the ADNI cohort confirmed these findings, with consistent performance across different measurement methods. The two-cutoff workflow using pTau217/Aβ42 reduced the intermediate-risk zone from 16% to 8%, enhancing stratification for clinical decision-making.

CONCLUSIONS AND RELEVANCE

The pTau217/Aβ42 ratio offers superior diagnostic accuracy for detecting Aβ+ compared to individual biomarkers and reduces diagnostic uncertainty. These findings highlight the clinical utility of plasma biomarker ratios for early AD detection, paving the way for broader implementation in clinical and research settings.

Updated Appropriate Use Criteria for Amyloid and Tau PET: A Report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup

The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. Methods: The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities. Results: For amyloid PET, 7 scenarios were rated as appropriate, 2 as uncertain, and 8 as rarely appropriate. For tau PET, 5 scenarios were rated as appropriate, 6 as uncertain, and 6 as rarely appropriate. Conclusion: AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease.

sTREM2 in discordant CSF Aβ42 and p-tau181

INTRODUCTION

Little is known about the factors underpinning discordant cerebrospinal fluid (CSF) amyloid beta (Aβ)42 versus p-tau181/Aβ42 or CSF Aβ42 versus Aβ positron emission tomography (PET).

METHODS

We stratified 570 non-demented Alzheimer's Disease Neuroimaging Initiative (ADNI) participants by Aβ PET and further by CSF Aβ42 or p-tau181/Aβ42. We used analysis of covariance testing adjusting for covariates, followed by Tukey post hoc pairwise comparisons, to compare CSF soluble triggering receptor expressed on myeloid cells-2 (sTREM2) across four participant groups: CSF+ Aβ42 with CSF- p-tau/Aβ42, CSF- Aβ42 with CSF+ p-tau/Aβ42, and concordant CSFAβ42/CSFp-tau/Aβ42. We also compared sTREM2 across discordant and concordant CSFAβ42/PET.

RESULTS

Regardless of Aβ PET status, CSF+Aβ42 with CSF-p-tau/Aβ42 had lower sTREM2 than CSF-Aβ42 with CSF+p-tau/Aβ42. CSF sTREM2 was similarly also associated with discordant CSF Aβ42 /PET.

DISCUSSION

Our study suggests the potential roles of sTREM2 in discordant CSF Aβ42 and p-tau181/Aβ42 and discordant CSFAβ42/PET. Low- and high-CSF sTREM2 may affect the accuracy of p-tau181/Aβ42 during the clinical work-up of AD.

Highlights

17% of non-demented older adults had discordant CSF Aβ42 versus p-tau181/Aβ42.sTREM2 differed between discordant cases of CSF Aβ42 versus p-tau181/Aβ42.20% of non-demented older adults had discordant CSF Aβ42 versus Aβ PET.sTREM2 also differed between discordant cases of CSF Aβ42 versus Aβ PET.p-tau181/Aβ42 may miss 6.7% of PET+ non-demented older adults with low sTREM2.

Real-life reliability of plasma pTau181, Aβ42/Aβ40, and pTau181/Aβ42 measured by Lumipulse G600II in predicting cerebrospinal fluid amyloid status

BACKGROUND

Alzheimer's disease (AD) is the most common neurodegenerative dementia, with diagnosis traditionally reliant on clinical criteria. Cerebrospinal fluid (CSF) biomarkers like pTau181 and Aβ42/Aβ40 ratio significantly improve diagnostic accuracy but are invasive. Plasma biomarkers measured by automated assays offer a non-invasive alternative.

OBJECTIVE

To evaluate the diagnostic performance of plasma pTau181, Aβ42/Aβ40, and pTau181/Aβ42 ratios in predicting CSF amyloid status in a real-life clinical setting.

METHODS

Data from consecutive patients whose plasma and CSF samples sent to our laboratory between March and October 2022, were retrospectively analyzed. Plasma and CSF pTau181, Aβ42, and Aβ40 levels were measured using the Lumipulse G600II platform. CSF amyloid status was classified as amyloid-positive (A+) or amyloid-negative (A-) based on the Aβ42/Aβ40 ratio. Statistical analyses included Spearman correlation, receiver operating characteristic (ROC) curves, and multivariate logistic regression to evaluate biomarker performance.

RESULTS

Among 165 individuals (83 females), 29.1% were classified as A+. Significant correlations were found between plasma and CSF biomarkers, with the highest for the pTau181/Aβ42 ratio (ρ=0.620, p < 0.0001). ROC analysis showed the pTau181/Aβ42 ratio had the highest diagnostic performance (AUC 0.818), followed by pTau181 (AUC 0.794) and Aβ42/Aβ40 (AUC 0.775). Combining plasma biomarkers in age-adjusted models improved diagnostic accuracy (AUC up to 0.846).

CONCLUSIONS

Plasma biomarkers measured by the Lumipulse G600II platform show strong potential in predicting CSF amyloid status and possibly reduces the need for lumbar punctures. These findings support the potential use of plasma assays in the early diagnosis of AD. Anyway, further validations in larger multicenter cohorts are mandatory.

ADNI Biomarker Core: A review of progress since 2004 and future challenges

BACKGROUND

We describe the Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core major activities from October 2004 to March 2024, including biobanking ADNI cerebrospinal fluid (CSF), plasma, and serum biofluid samples, biofluid analyses for Alzheimer's disease (AD) biomarkers in the Biomarker Core and various non-ADNI laboratories, and continuous assessments of pre-analytics.

RESULTS

Validated immunoassay and mass spectrometry-based assays were performed in CSF with a shift to plasma, a more accessible biofluid, as qualified assays became available. Performance comparisons across different CSF and plasma AD biomarker measurement platforms have enriched substantially the ADNI participant database enabling method performance determinations for AD pathology detection and longitudinal assessments of disease progression.

DISCUSSION

Close collaboration with academic and industrial partners in the validation and implementation of AD biomarkers for early detection of disease pathology in treatment trials and ultimately in clinical practice is a key factor for the success of the work done in the Biomarker Core.

HIGHLIGHTS

Describe ADNI Biomarker Core biobanking and sample distribution from 2007 to 2024. Discuss validated mass spectrometry and immunoassay methods for ADNI biofluid analyses. Review collaborations with academic and industrial partners to detect AD and progression. Discuss major challenges, and progress to date, for co-pathology detection. Implementation in the ATN scheme: co-pathology and modeling disease progression.

Overview of Alzheimer's Disease Neuroimaging Initiative and future clinical trials

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to optimize and validate biomarkers for clinical trials while sharing all data and biofluid samples with the global scientific community. ADNI has been instrumental in standardizing and validating amyloid beta (Aβ) and tau positron emission tomography (PET) imaging. ADNI data were used for the US Food and Drug Administration (FDA) approval of the Fujirebio and Roche Elecsys cerebrospinal fluid diagnostic tests. Additionally, ADNI provided data for the trials of the FDA-approved treatments aducanumab, lecanemab, and donanemab. More than 6000 scientific papers have been published using ADNI data, reflecting ADNI's promotion of open science and data sharing. Despite its enormous success, ADNI has some limitations, particularly in generalizing its data and findings to the entire US/Canadian population. This introduction provides a historical overview of ADNI and highlights its significant accomplishments and future vision to pioneer "the clinical trial of the future" focusing on demographic inclusivity. HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) introduced a novel model for public-private partnerships and data sharing. It successfully validated amyloid and Tau PET imaging, as well as CSF and plasma biomarkers, for diagnosing Alzheimer's disease. ADNI generated and disseminated vital data for designing AD clinical trials.

Interactions between mild depressive symptoms and amyloid pathology on the trajectory of neurodegeneration, cognitive decline, and risk of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) was driven by the interplay between modifiable environmental factors and β-amyloid (Aβ) pathology. We aimed to investigate the interaction effects of mild depressive symptoms (MDS) with Aβ on AD development.

METHODS

Longitudinal data of 1746 non-demented adults (mean age = 73 years, female = 53 %, maximum = 10 years) were derived from the Alzheimer's Disease Neuroimaging Initiative cohort. MDS was separately defined by the baseline status, longitudinal latent class, and average intensity during follow-up. Amyloid-positive (A+) status was determined based on cerebrospinal fluid levels of β-amyloid. Regression models were employed to analyze the interactive effects of MDS with A+ on cognitive decline, neurodegeneration, and AD incidence.

RESULTS

Individuals with both A+ status and MDS at baseline experienced the fastest neurodegeneration (p < 0.01), cognitive decline (p < 0.05), and a higher risk of developing AD (HR = 5.23, p < 0.001). Furthermore, A+ participants with the trajectory of increasing depressive symptoms demonstrated more pronounced neurodegeneration (p < 0.001), cognitive decline (p < 0.01), and elevated risk of AD (HR = 10.45, p < 0.001). Finally, A+ status in combination with a higher average intensity of depressive symptoms was associated with faster brain atrophy (p < 0.01) and brain metabolism decline (p < 0.05), cognitive decline (p < 0.05), and higher AD risk (HR = 13.99, p < 0.001).

CONCLUSION

These findings emphasized that the MDS-Aβ interaction relationship should be considered in risk stratification, prediction, and early management of neurodegeneration and cognitive decline in the pre-dementia stage.

Cerebrospinal fluid Visinin-like protein-1 was associated with the relationship of body mass index with Alzheimer's disease pathology and cognition in non-demented elderly

Background

The relationship and mechanisms between body mass index (BMI) and cognition are complex and inconclusive. Additionally, the role of neuronal calcium dysfunction, reflected by cerebrospinal fluid (CSF) Visinin-like protein 1 (VILIP-1), in the mechanisms linked with BMI and Alzheimer's disease (AD) has not been investigated.

Objective

To investigate the relationship between CSF VILIP-1, BMI, and AD pathologies in non-demented elderly at early stages of AD.

Methods

Baseline CSF AD core biomarkers (amyloid-β42 [Aβ42], phosphorylated tau [P-tau], and total tau [T-tau]) were measured for 1201 non-demented participants, selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, among whom 128 had measurements of CSF VILIP-1. Multivariate linear regression, causal mediation analyses, and linear mixed effects models were conducted to detect these associations.

Results

The average age of participants was 72.6. CSF VILIP-1 was decreased in A+/TN- (A-positive/T- and N- negative) group and elevated in A-/TN + (A-negative/T- or N-positive) and A+/TN + groups, as compared with A-/TN- group. In total participants, BMI was negatively related to CSF P-tau, T-tau, P-tau/Aβ42 and T-tau/Aβ42. Noticeable associations were also presented between CSF VILIP-1 and AD core biomarkers, but not with Aβ42 after stratification by A/T/N scheme. Furthermore, the influences of BMI on CSF tau pathology were mediated by CSF VILIP-1. Higher baseline CSF VILIP-1 correspond to faster longitudinal cognitive decline.

Conclusions

Our findings indicated that CSF VILIP-1 changed dynamically and might be a key mediator in the associations between BMI and tau pathology, providing new insights into understanding the mechanisms underlying BMI-related cognitive deficits in non-demented elderly.

Updated appropriate use criteria for amyloid and tau PET: A report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup

INTRODUCTION

The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET.

METHODS

The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities.

RESULTS

For amyloid PET, seven scenarios were rated as appropriate, two as uncertain, and eight as rarely appropriate. For tau PET, five scenarios were rated as appropriate, six as uncertain, and six as rarely appropriate.

DISCUSSION

AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease.

HIGHLIGHTS

A multidisciplinary workgroup convened by the Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging updated the appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. The goal of these updated AUC is to assist clinicians in identifying clinical scenarios in which amyloid or tau PET may be useful for guiding the diagnosis and management of patients who have, or are at risk for, cognitive decline These updated AUC are intended for dementia specialists who spend a significant proportion of their clinical effort caring for patients with cognitive complaints, as well as serve as a general reference for a broader audience interested in implementation of amyloid and tau PET in clinical practice.

Fast Declining Prediction in Alzheimer's Disease from Early Clinical Assessment

INTRODUCTION

The heterogenicity in Alzheimer's Disease (AD) progression hinders individual prognosis. The present work is an observational 2-year longitudinal study in patients with mild cognitive impairment due to AD (n = 52, with positive CSF biomarkers). The aim of this study is to predict which patients are at risk of fast progression. For this, 3 neuropsychological tests based on different domains (clinical dementia, cognition, delayed memory) and the sum of them were used.

METHODS

The tests were performed at diagnosis time (T1) and two years after the diagnosis time (T2). Then, the corresponding progression models were developed using each individual test and their sum as a variable response.

RESULTS

As a result, the model based on cognition status to predict fast decline (differences in the Z score (T2-T1) <1.5 were considered fast declining) provided satisfactory performance (AUC 0.74, 83.3% of sensibility and 70.2% of specificity); the models based on clinical dementia and delayed memory to predict fast declining showed low AUC and sensitivity. Nevertheless, the model based on the sum of the 3 tests showed the highest AUC (0.79), low sensitivity (63.6%), and high specificity.

CONCLUSION

The developed progression models could provide useful information to clinicians and AD patients regarding their fast/normal decline in general or specific domains.

A whole-brain functional connectivity model of Alzheimer's disease pathology

INTRODUCTION

Alzheimer's disease (AD) is characterized by the presence of two proteinopathies, amyloid and tau, which have a cascading effect on the functional and structural organization of the brain.

METHODS

In this study, we used a supervised machine learning technique to build a model of functional connections that predicts cerebrospinal fluid (CSF) p-tau/Aβ42 (the PATH-fc model). Resting-state functional magnetic resonance imaging (fMRI) data from 289 older adults in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were utilized for this model.

RESULTS

We successfully derived the PATH-fc model to predict the ratio of p-tau/Aβ42 as well as cognitive functioning in older adults across the spectrum of healthy and pathological aging. However, the in-sample fit magnitude was low, indicating a need for further model development.

DISCUSSION

Our pathology-based model of functional connectivity included representation from multiple canonical networks of the brain with intra-network connectivity associated with low pathology and inter-network connectivity associated with higher levels of pathology.

HIGHLIGHTS

Whole-brain functional connectivity model (PATH-fc) is linked to AD pathophysiology. The PATH-fc model predicts performance in multiple domains of cognitive functioning. The PATH-fc model is a distributed model including representation from all canonical networks.

Interval-specific likelihood ratios and probability-based models for interpreting combined CSF biomarkers for Alzheimer's disease

BACKGROUND

In Alzheimer's disease (AD) diagnosis, a cerebrospinal fluid (CSF) biomarker panel is commonly interpreted with binary cutoff values. However, these values are not generic and do not reflect the disease continuum. We explored the use of interval-specific likelihood ratios (LRs) and probability-based models for AD using a CSF biomarker panel.

METHODS

CSF biomarker (Aβ1-42, tTau and pTau181) data for both a clinical discovery cohort of 241 patients (measured with INNOTEST) and a clinical validation cohort of 129 patients (measured with EUROIMMUN), both including AD and non-AD dementia/cognitive complaints were retrospectively retrieved in a single-center study. Interval-specific LRs for AD were calculated and validated for univariate and combined (Aβ1-42/tTau and pTau181) biomarkers, and a continuous bivariate probability-based model for AD, plotting Aβ1-42/tTau versus pTau181 was constructed and validated.

RESULTS

LR for AD increased as individual CSF biomarker values deviated from normal. Interval-specific LRs of a combined biomarker model showed that once one biomarker became abnormal, LRs increased even further when another biomarker largely deviated from normal, as replicated in the validation cohort. A bivariate probability-based model predicted AD with a validated accuracy of 88% on a continuous scale.

CONCLUSIONS

Interval-specific LRs in a combined biomarker model and prediction of AD using a continuous bivariate biomarker probability-based model, offer a more meaningful interpretation of CSF AD biomarkers on a (semi-)continuous scale with respect to the post-test probability of AD across different assays and cohorts.

Alzheimer's disease biomarkers and their current use in clinical research and practice

While blood-based tests are readily available for various conditions, including cardiovascular diseases, type 2 diabetes, and common cancers, Alzheimer's disease (AD) and other neurodegenerative diseases lack an early blood-based screening test that can be used in primary care. Major efforts have been made towards the investigation of approaches that may lead to minimally invasive, cost-effective, and reliable tests capable of measuring brain pathological status. Here, we review past and current technologies developed to investigate biomarkers of AD, including novel blood-based approaches and the more established cerebrospinal fluid and neuroimaging biomarkers of disease. The utility of blood as a source of AD-related biomarkers in both clinical practice and interventional trials is discussed, supported by a comprehensive list of clinical trials for AD drugs and interventions that list biomarkers as primary or secondary endpoints. We highlight that identifying individuals in early preclinical AD using blood-based biomarkers will improve clinical trials and the optimization of therapeutic treatments as they become available. Lastly, we discuss challenges that remain in the field and address new approaches being developed, such as the examination of cargo packaged within extracellular vesicles of neuronal origin isolated from peripheral blood.

The CSF p-tau/β-amyloid 42 ratio correlates with brain structure and fibrillary β-amyloid deposition in cognitively unimpaired individuals at the earliest stages of pre-clinical Alzheimer's disease

CSF concentrations of β-amyloid 42 (Aβ42) and phosphorylated tau (p-tau) are well-established biomarkers of Alzheimer's disease and have been studied in relation to several neuropathological features both in patients and in cognitively unimpaired individuals. The CSF p-tau/Aβ42 ratio, a biomarker combining information from both pathophysiological processes, has emerged as a promising tool for monitoring disease progression, even at pre-clinical stages. Here, we studied the association between the CSF p-tau/Aβ42 ratio with downstream markers of pre-clinical Alzheimer's disease progression including brain structure, glucose metabolism, fibrillary Aβ deposition and cognitive performance in 234 cognitively unimpaired individuals, who underwent cognitive testing, a lumbar puncture, MRI, 18F-fluorodeoxyglucose and 18F-flutemetamol PET scanning. We evaluated both main effects and interactions with Alzheimer's disease risk factors, such as older age, female sex and the apoliporoptein E (APOE)-ɛ4 allele, in a priori defined regions of interest and further examined the associations on the whole-brain using voxel-wise regressions. In addition, as the association between CSF Alzheimer's disease biomarkers and brain structure and function may be non-linear, we tested the interaction between the CSF p-tau/Aβ42 ratio and stages of pre-clinical Alzheimer's disease defined using the amyloid (A) and tau (T) classification. We found significantly positive associations between CSF p-tau/Aβ42 and both cortical Aβ deposition and regional grey matter volume while no effect was observed for brain metabolism. A significant interaction with age indicated that, for the same level of CSF p-tau/Aβ42, older individuals displayed both increased Aβ deposition and lower grey matter volume, in widespread cortical areas. In addition, we found that women compared with men had a greater Aβ fibrillary accumulation in midline cortical areas and inferior temporal regions, for the same level of the CSF biomarker. The impact of CSF p-tau/Aβ42 on grey matter volume was modulated by AT stages, with A+T+ individuals displaying significantly less positive associations in areas of early atrophy in the Alzheimer's continuum. Finally, we found that sex and APOE-ɛ4 modulated the association between the CSF biomarker and episodic memory as well as abstract reasoning, respectively. Our data indicate that the CSF p-tau/Aβ42 ratio is strongly associated with multiple downstream neuropathological events in cognitively unimpaired individuals and may thus serve as a potent biomarker to investigate the earliest changes in pre-clinical Alzheimer's disease. Given that its impact on both Aβ deposition and grey matter volume is modulated by specific risk factors, our results highlight the need to take into account such predisposing variables in both clinical practice and prevention trials.

Lumipulse-Measured Cerebrospinal Fluid Biomarkers for the Early Detection of Alzheimer Disease

BACKGROUND AND OBJECTIVES

CSF biomarkers of Aβ42 and phosphorylated tau (p-tau181) are used clinically for the detection of Alzheimer disease (AD) pathology during life. CSF biomarker validation studies have largely used clinical diagnoses and/or amyloid PET imaging as the reference standard. The few existing CSF-to-autopsy studies have been restricted to late-stage AD. This CSF-to-autopsy study investigated associations between CSF biomarkers of AD and AD neuropathologic changes among brain donors who had normal cognition at the time of lumbar puncture (LP).

METHODS

This was a retrospective study of brain donors from the National Alzheimer's Coordinating Center who had normal cognition at the time of LP and who had measurements of CSF Aβ42 and p-tau181 performed with Lumipulse assays. All brain donors were from Washington University Knight ADRC. Staging of AD neuropathologic change (ADNC) was made based on National Institute on Aging-Alzheimer's Association criteria. For this study, participants were divided into 2 categories: "AD-" (no AD/low ADNC) and "AD+" (intermediate/high ADNC). Accuracy of each biomarker for discriminating AD status was evaluated using area under the curve (AUC) statistics generated using predicted probabilities from binary logistic regressions that controlled for age, sex, APOE ε4, and interval between LP and death.

RESULTS

The average age at LP was 79.3 years (SD = 5.6), and the average age at death was 87.1 years (SD = 6.5). Of the 49 brain donors, 24 (49%) were male and 47 (95.9%) were White. 20 (40.8%) had autopsy-confirmed AD. The average interval from LP until death was 7.76 years (SD = 4.31). CSF p-tau181/Aβ42 was the optimal predictor of AD, having excellent discrimination accuracy (AUC = 0.97, 95% CI 0.94-1.00, p = 0.003). CSF p-tau181 alone had the second-best discrimination accuracy (AUC = 0.92, 95% CI 0.84-1.00, p = 0.001), followed by CSF Aβ42 alone (AUC = 0.92, 95% CI 0.85-1.00, p = 0.007), while CSF t-tau had the numerically lowest discrimination accuracy (AUC = 0.87, 95% CI 0.76-0.97, p = 0.005). Effects remained after controlling for prevalent comorbid neuropathologies. CSF p-tau181/Aβ42 was strongly associated with CERAD ratings of neuritic amyloid plaque scores and Braak staging of NFTs.

DISCUSSION

This study supports Lumipulse-measured CSF Aβ42 and p-tau181 and, particularly, the ratio of p-tau181 to Aβ42, for the early detection of AD pathophysiologic processes.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that Lumipulse measures of p-tau181/Aβ42 in the CSF accurately discriminated cognitively normal participants with and without Alzheimer disease neuropathologic change.

Timing of Alzheimer's disease biomarker progressions: A two-decade observational study from the Alzheimer's Disease Neuroimaging Initiative (ADNI)

INTRODUCTION

Alzheimer's Disease Neuroimaging Initiative (ADNI) has been pivotal in identifying and refining Alzheimer's disease (AD) biomarkers for clinical trials. This study leverages longitudinal data from participants who have progressed to amyloid-positivity during their study participation to track evolution of biomarkers and cognitive function.

METHODS

We modeled AD biomarker (positron emission tomography [PET], structural, cerebrospinal fluid [CSF], cognition) trajectories before and after observed amyloid-positivity onset time to detect time at which each biomarker had detectable trajectory changes.

RESULTS

Analysis of a sub-cohort of the 20-year ADNI study (N = 90) recapitulated Alzheimer's progression beginning with amyloid alterations -4.8 to -5.3 years relative to amyloid-positivity, succeeded by neurodegeneration (t = -4.0 to -4.1 years), and CSF tau (t = -0.4 to -0.5 years). Cognitive decline was observed to significantly correspond with emergence of amyloid-positivity (t = 0.2 to 2.4 years).

DISCUSSION

Our results corroborate temporal progression curves of AD biomarkers, providing insights on earliest detectable changes in objective and subjective cognitive function assessments.

Memory consolidation, temporal and parietal atrophy, and metabolism in amyloid-β positive and negative mild cognitive impairment

BACKGROUND

Alzheimer's disease (AD) is classically characterized by alterations in memory consolidation. With the advent of diagnostic biomarkers, some patients clinically diagnosed with AD display biomarkers inconsistent with the diagnosis.

OBJECTIVE

We aimed to explore differences in memory consolidation and neurodegeneration of the temporal and parietal lobes as a function of amyloid-β status in amnestic mild cognitive impairment (aMCI).

METHODS

We examined differences in memory consolidation and neurodegeneration between patients diagnosed with amyloid-β positive aMCI (Aβ+ N = 78), amyloid-β negative aMCI (Aβ- N = 48), and healthy participants (HP; N = 41), within a well-characterized clinical cohort.

RESULTS

Aβ+ exhibited more pronounced consolidation impairments compared to Aβ-, while Aβ- faced more consolidation challenges than HP. Both Aβ+ and Aβ- were similar in hippocampal volume and entorhinal thickness, but Aβ+ had thinner inferior parietal cortex than Aβ-. Using 18F-fluoro-deoxyglucose-positron emission tomography, metabolism in both temporal and parietal regions was lower in Aβ+ relative to Aβ-.

CONCLUSIONS

These findings suggest pathologies other than AD likely contribute to memory consolidation difficulties in aMCI, and neurodegeneration of the parietal cortex in combination with hypometabolism may contribute to more pronounced consolidation problems in Aβ+.

Heterogeneity of cerebral atrophic rate in mild cognitive impairment and its interactive association with proteins related to microglia activity on longitudinal cognitive changes

BACKGROUND

Heterogeneity of cerebral atrophic rate commonly exists in mild cognitive impairment (MCI), which may be associated with microglia-involved neuropathology and have an influence on cognitive outcomes.

OBJECTIVE

We aim to explore the heterogeneity of cerebral atrophic rate among MCI and its association with plasma proteins related to microglia activity, with further investigation of their interaction effects on long-term cognition.

SUBJECTS

A total of 630 MCI subjects in the ADNI database were included, of which 260 subjects were available with baseline data on plasma proteins.

METHODS

Group-based multi-trajectory modeling (GBMT) was used to identify the latent classes with heterogeneous cerebral atrophic rates. Associations between latent classes and plasma proteins related to microglia activity were investigated with generalized linear models. Linear mixed effect models (LME) were implemented to explore the interaction effects between proteins related to microglia activity and identified latent classes on longitudinal cognitive changes.

RESULTS

Two latent classes were identified and labeled as the slow-atrophy class and the fast-atrophy class. Associations were found between such heterogeneity of atrophic rates and plasma proteins related to microglia activity, especially AXL receptor tyrosine kinase (AXL), CD40 antigen (CD40), and tumor necrosis factor receptor-like 2 (TNF-R2). Interaction effects on longitudinal cognitive changes showed that higher CD40 was associated with faster cognitive decline in the slow-atrophy class and higher AXL or TNF-R2 was associated with slower cognitive decline in the fast-atrophy class.

CONCLUSIONS

Heterogeneity of atrophic rates at the MCI stage is associated with several plasma proteins related to microglia activity, which show either protective or adverse effects on long-term cognition depending on the variability of atrophic rates.