Plasma biomarkers of Alzheimer's disease improve prediction of cognitive decline in cognitively unimpaired elderly populations

Olfaction and Plasma Biomarkers of Alzheimer Disease and Neurodegeneration in the Atherosclerosis Risk in Communities Study

BACKGROUND AND OBJECTIVES

Investigation of olfactory impairment, an early manifestation of Alzheimer disease (AD), in relation to plasma biomarkers of AD and neurodegeneration could provide insights into the disease's pathophysiology. Because few such studies based on large, diverse, community-based populations exist, we investigated associations of odor identification ability with plasma biomarkers of AD and other neurodegenerative pathologies in community-dwelling Black and White older adults.

METHODS

This cross-sectional investigation included participants from the Atherosclerosis Risk in Communities study who attended visit 5 (2011-2013) and who completed olfactory testing and brain MRI examinations and had plasma biomarkers measured (namely, amyloid-beta [Aβ]42/Aβ40 ratio, phosphorylated-tau at threonine-181 [p-tau181], p-tau181/Aβ42 ratio, glial fibrillary acidic protein [GFAP], and neurofilament light chain [NfL]). Odor identification ability was measured by the 12-item Sniffin' Sticks test. Separate linear regression models were used to examine the association of continuous olfaction score and olfaction categories (anosmia: score 6; hyposmia: 7-8; moderate-normal: 9-10; good-normal: 11-12) with each biomarker (all were log-transformed), adjusting for sociodemographic and cardiovascular factors, head injury, APOE-ε4 status, and estimated glomerular filtration rate. We further examined whether any observed associations are explained by total and regional brain volumes.

RESULTS

Among 1,545 participants (age: 76 ± 5 years, 60% women, 27% self-reported Black participants), the mean olfaction score was 9.2 ± 2.3; 14% had anosmia. Consistent with our hypotheses, poorer olfactory scores were associated with higher plasma p-tau181 (β per 1-unit lower score: 0.026 [95% CI 0.012-0.040]), p-tau181/Aβ42 (β: 0.027 [95% CI 0.011- 0.044]), GFAP (β: 0.024 [95% CI 0.009-0.040]), and NfL (β: 0.034 [95% CI 0.019-0.050] and lower Aβ42/Aβ40 ratio (β: -0.007 [95% CI -0.015 to 0.000]). Likewise, compared with good-normal olfaction, anosmia showed associations with all biomarker levels indicative of greater neuropathology (e.g., β for plasma p-tau181/Aβ42: 0.235 [95% CI 0.113-0.358] and β for plasma NfL: 0.210 [95% CI 0.102-0.317]), although the association with Aβ42/Aβ40 ratio was not statistically significant (β: -0.054 [95% CI -0.108 to 0.001]). These biomarkers were not significantly associated with hyposmia or moderate-normal olfaction. Smaller medial-temporal lobe volumes partly explained olfaction's link with plasma p-tau181, p-tau181/Aβ42, GFAP, and NfL.

DISCUSSION

Our findings suggest that poor olfaction is associated with multiple AD-related and other neurodegenerative processes. Future studies should investigate how longitudinal changes in both olfaction and biomarkers relate to each other.

Modeling functional connectivity with learning and memory in a mouse model of Alzheimer's disease

Introduction

Functional connectivity (FC) is a metric of how different brain regions interact with each other. Although there have been some studies correlating learning and memory with FC, there have not yet been, to date, studies that use machine learning (ML) to explain how FC changes can be used to explain behavior not only in healthy mice, but also in mouse models of Alzheimer's Disease (AD). Here, we investigated changes in FC and their relationship to learning and memory in a mouse model of AD across disease progression.

Methods

We assessed the APP/PS1 mouse model of AD and wild-type controls at 3-, 6-, and 10-months of age. Using resting state functional magnetic resonance imaging (rs-fMRI) in awake, unanesthetized mice, we assessed FC between 30 brain regions. ML models were then used to define interactions between neuroimaging readouts with learning and memory performance.

Results

In the APP/PS1 mice, we identified a pattern of hyperconnectivity across all three time points, with 47 hyperconnected regions at 3 months, 46 at 6 months, and 84 at 10 months. Notably, FC changes were also observed in the Default Mode Network, exhibiting a loss of hyperconnectivity over time. Modeling revealed functional connections that support learning and memory performance differ between the 6- and 10-month groups.

Discussion

These ML models show potential for early disease detection by identifying connectivity patterns associated with cognitive decline. Additionally, ML may provide a means to begin to understand how FC translates into learning and memory performance.

Enhanced associations between subjective cognitive concerns and blood-based AD biomarkers using a novel EMA approach

BACKGROUND

Subjective cognitive concerns (SCC) have emerged as important early indicators of Alzheimer's disease (AD) risk. Traditional measures of SCC rely on recall-based assessments, which may be limited in capturing real-time fluctuations in cognitive concerns. Ecological Momentary Assessment (EMA) offers a promising alternative by providing real-time data. This study aimed to link SCC assessed via EMA and traditional measures with blood-based AD biomarkers in a diverse, dementia-free, community-based sample based in the Bronx, NY.

METHODS

Einstein Aging Study (EAS) participants underwent in-person, recall-based assessments of SCC during an in-clinic visit. Additionally, EMA SCC assessments were collected once per day over two weeks. Linear regressions were conducted to examine the relationships between SCC variables and plasma biomarkers adjusted for demographics and mild cognitive impairment (MCI) status.

RESULTS

In N = 254 participants, EMA-reported SCCs demonstrated significant associations with AD biomarkers, particularly p-tau181 (β = 0.21, p = 0.001). Further, significant associations remain across both cognitive (cognitively unimpaired vs. MCI) and racial groups. In contrast, traditional SCC measures exhibited limited associations with these biomarkers. The findings highlight the added value of EMA in capturing SCCs that could indicate early ADRD risk.

CONCLUSIONS

EMA provides a more dynamic and potentially sensitive method for detecting early AD risk compared to traditional SCC assessments. These real-time measures could enhance early detection and clinical intervention, particularly in diverse and under-resourced populations. This study underscores the potential of EMA for broad applicability and inclusivity in monitoring AD progression and facilitating early therapeutic interventions.

Age-Related differences in the relationship between sustained attention and associative memory and Memory-Guided inference

Episodic memory enables the encoding and retrieval of novel associations, as well as the bridging across learned associations to draw novel inferences. A fundamental goal of memory science is to understand the factors that give rise to individual and age-related differences in memory-dependent cognition. Variability in episodic memory could arise, in part, from both individual differences in sustained attention and diminished attention in aging. We first report that, relative to young adults (N = 23; M = 20.0 years), older adults (N = 26, M = 68.7 years) demonstrated lower associative memory and memory-guided associative inference performance and that this age-related reduction in associative inference occurs even when controlling for associative memory performance. Next, we confirm these age-related memory differences by using a high-powered, online replication study (young adults: N = 143, M = 26.2 years; older adults N = 133, M = 67.7 years), further demonstrating that age-related differences in memory do not reflect group differences in sustained attention (as assayed by the gradual-onset continuous performance task; gradCPT). Finally, we report that individual differences in sustained attention explain between-person variability in associative memory and inference performance in the present, online young adult sample, but not in the older adult sample. These findings extend understanding of the links between attention and memory in young adults, demonstrating that differences in sustained attention was related to differences in memory-guided inference. By contrast, our data suggest that the present age-related differences in memory-dependent behavior and the memory differences between older adults are due to attention-independent mechanisms.

Blood-based biomarkers of Alzheimer's disease and incident dementia in the community

Evidence regarding the clinical validity of blood biomarkers of Alzheimer's disease (AD) in the general population is limited. We estimated the hazard and predictive performance of six AD blood biomarkers for incident all-cause and AD dementia-the ratio of amyloid-β 42 to amyloid-β 40 and levels of tau phosphorylated at T217 (p-tau217), tau phosphorylated at T181 (p-tau181), total tau, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP)-in a cohort of 2,148 dementia-free older adults from Sweden, who were followed for up to 16 years. In multi-adjusted Cox regression models, elevated baseline levels of p-tau181, p-tau217, NfL, and GFAP were associated with a significantly increased hazard for all-cause and AD dementia, displaying a non-linear dose-response relationship. Elevated concentrations of p-tau181, p-tau217, NfL, and GFAP demonstrated strong predictive performance (area under the curve ranging from 70.9% to 82.6%) for 10-year all-cause and AD dementia, with negative predictive values exceeding 90% but low positive predictive values (PPVs). Combining p-tau217 with NfL or GFAP further improved prediction, with PPVs reaching 43%. Our findings suggest that these biomarkers have the potential to rule out impending dementia in community settings, but they might need to be combined with other biological or clinical markers to be used as screening tools.

Blood-Based β-Amyloid and Phosphorylated Tau (p-Tau) Biomarkers in Alzheimer's Disease: A Systematic Review of Their Diagnostic Potential

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and neuropathological features such as amyloid-β (Aβ) plaques and phosphorylated tau (p-Tau) tangles. Blood-based biomarkers of Aβ and p-Tau have emerged as promising tools for early diagnosis, monitoring, and risk stratification of AD. This systematic review evaluates current evidence on the diagnostic utility of Aβ and p-Tau blood biomarkers in AD. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science for studies published between 2011 and 2024. This review synthesizes findings from 33 peer-reviewed studies to evaluate the diagnostic and prognostic utility of these biomarkers. Results demonstrate that blood Aβ and p-Tau levels strongly correlate with cerebrospinal fluid (CSF) biomarkers and neuroimaging measures of AD pathology. Among the biomarkers analyzed, p-Tau (including p-Tau181 and p-Tau217) consistently exhibited superior diagnostic accuracy, particularly in distinguishing AD from mild cognitive impairment (MCI) and cognitively normal individuals. The combination of Aβ and p-Tau biomarkers further improved diagnostic precision, supporting their complementary roles in AD pathology detection. Despite promising findings, significant heterogeneity among studies underscores the need for assay standardization, validation in diverse populations, and longitudinal research to establish clinical utility. This study concludes that blood-based Aβ and p-Tau biomarkers represent a significant advance in AD diagnostics, offering non-invasive, cost-effective, and scalable solutions for early detection and therapeutic monitoring.

Blood biomarkers differentiate AD-related versus non-AD-related cognitive deficits

INTRODUCTION

The utility of blood-based biomarkers for discriminating Alzheimer's disease (AD)-related versus non-AD-related cognitive deficits in preclinical populations remains poorly understood. Here, we tested the capability of blood markers to detect and discriminate variation in performance across multiple cognitive domains in a cognitively unimpaired sample.

METHODS

Participants (n = 648, aged 69.9 ± 3.8, 71% female) underwent a comprehensive cognitive assessment and assays for plasma-based biomarkers amyloid beta (Aβ)1-42/1-40 by mass spectrometry, phosphorylated tau (p-tau) 181 and 217, p-tau217/Aβ1-42, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL).

RESULTS

Greater p-tau217 was exclusively associated with poorer episodic memory performance (β = -0.11, SE = 0.04, p = .003), and remained so after covarying for NfL. Higher NfL was non-specifically associated with poorer performance across a range of cognitive domains and remained so after covarying for p-tau217.

DISCUSSION

Blood-based biomarkers may differentiate non-AD-related versus AD-related cognitive deficits. This characterization will be important for early intervention and disease monitoring for AD.

HIGHLIGHTS

There is heterogeneity in the causes of cognitive decline in aging. AD-related blood biomarkers may help characterize these causes. Elevated p-tau217 was exclusively associated with poorer episodic memory. Elevated NfL was associated with poorer cognition in a broad range of domains. Blood biomarkers may help differentiate AD- and non-AD-related cognitive deficits.

Plasma protein risk scores for mild cognitive impairment and Alzheimer's disease in the Framingham heart study

INTRODUCTION

It is unclear whether aggregated plasma protein risk scores (PPRSs) could be useful in predicting the risks of mild cognitive impairment (MCI) and Alzheimer's disease (AD).

METHODS

The Cox proportional hazard model with the Least Absolute Shrinkage and Selection Operator penalty was used to build the PPRSs for MCI and AD in 1515 Framingham Heart Study Generation 2 with 1128 proteins measured in plasma at exam 5 (cognitively normal [CN] = 1258, MCI = 129, AD = 128).

RESULTS

MCI PPRS had a hazard ratio (HR) of 6.97 [5.34, 9.12], with a discriminating power (C-index = 82.52%). AD PPRS had a HR of 5.74 [4.67, 7.05] (C-index = 88.15%). Both PPRSs were also significantly associated with cognitive changes, brain atrophy, and plasma AD biomarkers. Proteins in the MCI and AD PPRSs were involved in several pathways related to leukocyte, chemotaxis, immunity, inflammation, and cellular migration.

DISCUSSION

This study suggests that PPRSs serve well to predict the risk of developing MCI and AD as well as cognitive changes and AD-related pathogenesis in the brain.

HIGHLIGHTS

PPRSs were developed for the risk of AD and AD preclinical stage, MCI. PPRSs were developed for MCI and AD associated with cognitive changes, loss of brain volume, and increasing level of plasma AD biomarkers. Leukocyte, chemotaxis, immunity, inflammation, and cellular migration enriched in proteins were identified as being involved in MCI and AD PPRSs.

Optical Coherence Tomography Angiography Retinal Imaging Associations With Burden of Small Vessel Disease and Amyloid Positivity in the Brain

BACKGROUND

Alzheimer disease (AD) and other dementias are associated with vascular changes and amyloid deposition, which may be reflected as density changes in the retinal capillaries. These changes may can be directly visualized and quantified with optical coherence tomography angiography (OCTA), making OCTA a potential noninvasive preclinical biomarker of small vessel disease and amyloid positivity. Our objective was to investigate the feasibility of retinal imaging metrics as noninvasive biomarkers of small vessel disease and amyloid positivity in the brain.

METHODS

We investigated associations between OCTA and neuroimaging and cognitive metrics in 41 participants without dementia from the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center. OCTA metrics included superficial, deep, and full retina capillary density of the fovea, parafovea, and macula as well as the area of the foveal avascular zone (FAZ). Neuroimaging metrics included a high burden of white matter hyperintensity (WMH), presence of cerebral microbleeds (CMB), lacunar infarcts, and amyloid positivity as evidenced on positron emission tomography (PET), whereas cognitive metrics included mini-mental status examination (MMSE) score. We performed generalized estimating equations to account for measurements in each eye while controlling for age and sex to estimate associations between OCTA metrics and neuroimaging and cognitive scores.

RESULTS

Associations between OCTA and neuroimaging metrics were restricted to the fovea. OCTA showed decreased capillary density with high burden of WMH in both the superficial ( P = 0.003), deep ( P = 0.004), and full retina ( P = 0.01) in the fovea but not the parafovea or whole macula. Similarly, participants with amyloid PET positivity had significantly decreased capillary density in the superficial fovea ( P = 0.027) and deep fovea ( P = 0.03) but higher density in the superficial parafovea ( P = 0.038). Participants with amyloid PET positivity also had a significantly larger FAZ ( P = 0.031), whereas in those with high WMH burden the difference did not reach statistical significance ( P = 0.075). There was also a positive association between MMSE and capillary density of the full retina within the fovea ( P = 0.037) and in the superficial parafovea ( P = 0.046). No associations were found between OCTA metrics and presence of CMB or presence of lacunar infarcts.

CONCLUSIONS

The associations of lower foveal capillary density with cerebral WMH and amyloid positivity suggest that further research is warranted to evaluate for shared mechanisms of disease between small vessel disease and AD pathologies.

Plasma Biomarkers in the Distinction of Alzheimer's Disease and Frontotemporal Dementia

Plasma biomarkers are promising tools for the screening and diagnosis of dementia in clinical settings. We analyzed plasma levels of Alzheimer's core biomarkers, neurofilament light chain (NfL) and glial fibrillary acid protein (GFAP), through single-molecule Array in 108 patients with Alzheimer's (AD, cerebrospinal fluid with an amyloid+ tau+ neurodegeneration+ profile), 73 patients with frontotemporal dementia (FTD, 24 with genetic diagnosis), and 54 controls. The best area under the curve (AUC) was used to assess the discriminative power. Patients with AD had lower Aß42/40 ratios and NfL levels, along with higher levels of p-tau181 and GFAP, compared with FTD patients. Single biomarkers discriminated well between dementia patients and controls: the Aß42/40 ratio (AUC:0.86) or GFAP (AUC:0.83) was found for AD, and the NfL (AUC:0.84) was found for FTD patients. However, a combination of two (NfL with p-tau181, or the GFAP/NfL ratio, AUCs ~0.87) or three biomarkers (NfL, P-tau181, and Aß42/40 ratio, AUC: 0.90) was required to distinguish between AD and FTD. Biomarker profiles were similar across different FTD phenotypes, except for carriers of PGRN mutations, who had higher levels of NfL than C9orf72 expansion carriers. In our series, NfL alone provided the best distinction between FTD and controls, while a combination of two or three biomarkers was required to obtain good discrimination between AD and FTD.

Hypertension moderates the relationship between plasma beta-amyloid and cognitive impairment: a cross-sectional study in Xi'an, China

Background

Plasma beta-amyloid (Aβ) are important biomarkers for Alzheimer's disease and cognitive impairment (CI), but results are controversial. It remains unclear whether hypertension modulates their relationship. This cross-sectional study investigates whether hypertension moderates the relationship between plasma Aβ and cognitive impairment (CI).

Methods

This cross-sectional study included 1488 subjects ≥ 40 years from rural areas of northwestern China. CI was defined as a Mini-Mental State Examination score lower than the cutoff. Firstly, plasma Aβ40, Aβ42, Aβ42/Aβ40 were analyzed as restricted cubic spline. Then, categories of combined plasma Aβ were created by making bisection of plasma Aβ according to average and combining them as L-Aβ40 and L-Aβ42, H-Aβ40 and L-Aβ42, L-Aβ40 and H-Aβ42, H-Aβ40 and H-Aβ42. Decreased plasma Aβ40 was defined as < 25th percentile. Multivariate logistic regression examined the relationship between plasma Aβ and CI in total population, the hypertension subgroup and the non-hypertension subgroup.

Results

737 participants (49.5%) had hypertension and 189 participants (12.7%) had CI. Simultaneously elevated plasma Aβ40 and Aβ42 was associated with CI in hypertension (H-Aβ40 and H-Aβ42 vs. L-Aβ40 and L-Aβ42, 21.1% vs.10.7%, P = 0.033; OR = 1.984 [95% CI, 1.067-3.691], P = 0.030) but not in the non-hypertension. Decreased plasma Aβ40 was associated with CI in the non-hypertension (14.9% vs. 9.2%, P = 0.026; OR = 1.728 [95% CI, 1.018-2.931], P = 0.043) but not in the hypertension.

Conclusion

Hypertension is an important modulator in the relationship between plasma Aβ and CI. Simultaneously elevated plasma Aβ40 and Aβ42 in the hypertension, and decreased plasma Aβ40 in the non-hypertension, may be risk factors for CI. These findings emphasize the need to consider hypertension in CI detection.

Blood Neurofilament Light Chain and Phospho-Tau 181 in Subjects with Mild Cognitive Impairment Due to Age-Related Hearing Loss

Background: Mild cognitive impairment is increasingly recognized as a precursor to more severe neurodegenerative conditions, particularly in the context of aging. Recent studies have highlighted the intersection of hearing loss and cognitive decline, suggesting that auditory deficits may exacerbate cognitive impairments in older adults, proposing the use of hearing aids to mitigate cognitive decline, and indicating that early intervention in hearing loss could be crucial for preserving cognitive function. The underlying mechanisms of the relationship between hearing and cognitive impairment may involve neuroinflammatory processes and neurodegeneration. Recent studies have evidenced the role of tau proteins and neurofilaments as biomarkers in the onset and progression of neurodegenerative diseases. Methods: We selected 30 subjects with age-related hearing loss, and we evaluated their cognitive status through the administration of screening tests, which also measured neurofilament light chain and phospho-tau 181 serum levels as biomarkers of neurodegeneration. The subjects were re-evaluated six months after the hearing aid fitting. Results: Patients with hearing impairment presented slightly altered results on cognitive tests, typical of a mild cognitive impairment. At the same time, serum levels of neurofilament light chain and phospho-tau 181 were significantly increased compared to the matched control group. After the hearing aids fitting, auditory, cognitive, and serum values results improved. Conclusions: The results of the study highlight the cognitive involvement in patients with hearing impairment and identify neurofilament light chain and phospho-tau 181 as serum biomarkers of neurodegeneration useful in monitoring the pathology.

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.

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.

Unraveling Alzheimer's disease: insights from single-cell sequencing and spatial transcriptomic

Alzheimer's disease (AD) is a neurodegenerative disorder marked by cognitive decline, primarily affecting memory and executive function. This review highlights recent advancements in single-cell sequencing and spatial transcriptomics, which provide detailed insights into the cellular heterogeneity and neuroimmune mechanisms of AD. The review addresses the need for understanding complex cellular interactions to identify novel therapeutic targets and biomarkers. Single-cell sequencing has revolutionized our understanding by mapping gene expression at the individual cell level, revealing distinct microglial and astrocytic states that contribute to neuroinflammation and neurodegeneration. These technologies have uncovered disease-associated microglial subpopulations and gene expression changes linked to AD risk genes, essential for developing targeted therapies. In conclusion, the integration of single-cell and spatial transcriptomics with other omics data is crucial for a comprehensive understanding of AD, paving the way for personalized medicine. Continued interdisciplinary collaboration will be vital in translating these findings into effective treatments, improving patient outcomes.

In-situ nanozyme catalytic amplification coupled with a universal antibody orientation strategy based electrochemical immunosensor for AD-related biomarker

An in-situ nanozyme signal tag combined with a DNA-mediated universal antibody-oriented strategy was proposed to establish a high-performance immunosensing platform for Alzheimer's disease (AD)-related biomarker detection. Briefly, a Zr-based metal-organic framework (MOF) with peroxidase (POD)-like activity was synthesized to encapsulating the electroactive molecule methylene blue (MB), and subsequently modified with a layer of gold nanoparticles on its surface. This led to the creation of double POD-like activity nanozymes surrounding the MB molecule to form a nanozyme signal tag. A large number of hydroxyl radicals were generated by the nanozyme signal tag with the help of H2O2, which catalyzed MB molecules in situ to achieve efficient signal amplification. Subsequently, a DNA-aptamer-mediated universal antibody-oriented strategy was proposed to enhance the binding efficiency for the antigen (target). Meanwhile, a poly adenine was incorporated at the end of the aptamer, facilitating binding to the gold electrode and providing anti-fouling properties due to the hydrophilicity of the phosphate group. Under optimal conditions, this platform was successfully employed for highly sensitive detection of AD-associated tau protein and BACE1, achieving limits of detection with concentrations of 3.34 fg/mL and 1.67 fg/mL, respectively. It is worth mentioning that in the tau immunosensing mode, 20 clinical samples from volunteers of varying ages were analyzed, revealing significantly higher tau expression levels in the blood samples of elderly volunteers compared to young volunteers. This suggests that the developed strategy holds great promise for early AD diagnosis.

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

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

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

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

Application of blood-based biomarkers of Alzheimer's disease in clinical practice: Recommendations from Taiwan Dementia Society

Blood-based biomarkers (BBM) are potentially powerful tools that assist in the biological diagnosis of Alzheimer's disease (AD) in vivo with minimal invasiveness, relatively low cost, and good accessibility. This review summarizes current evidence for using BBMs in AD, focusing on amyloid, tau, and biomarkers for neurodegeneration. Blood-based phosphorylated tau and the Aβ42/Aβ40 ratio showed consistent concordance with brain pathology measured by CSF or PET in the research setting. In addition, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are neurodegenerative biomarkers that show the potential to assist in the differential diagnosis of AD. Other pathology-specific biomarkers, such as α-synuclein and TAR DNA-binding protein 43 (TDP-43), can potentially detect AD concurrent pathology. Based on current evidence, the working group from the Taiwan Dementia Society (TDS) achieved consensus recommendations on the appropriate use of BBMs for AD in clinical practice. BBMs may assist clinical diagnosis and prognosis in AD subjects with cognitive symptoms; however, the results should be interpreted by dementia specialists and combining biochemical, neuropsychological, and neuroimaging information. Further studies are needed to evaluate BBMs' real-world performance and potential impact on clinical decision-making.

Biomarker Assessment in Parkinson's Disease Dementia and Dementia with Lewy Bodies by the Immunomagnetic Reduction Assay and Clinical Measures

Background

Plasma biomarker assays provide an opportunity to reassess whether Alzheimer's disease, Parkinson's disease dementia (PDD), and dementia with Lewy bodies (DLB) plasma biomarkers are diagnostically useful.

Objective

We hypothesized that immunomagnetic reduction (IMR) of plasma biomarkers could differentiate between patients with PDD and DLB and healthy patients when combined with established clinical testing measures.

Methods

Plasma samples from 61 participants (12 PDD, 12 DLB, 37 controls) were analyzed using IMR to quantify amyloid-β 42 (Aβ42), total tau (t-tau), phosphorylated tau at threonine 181 (p-tau181), and α-synuclein (α-syn). Receiver operating characteristic curve (ROC) analysis was used to obtain sensitivity, specificity, and area under the ROC curve. Biomarker results were combined with clinical measures from the Unified Parkinson's Disease Rating Scale (UPDRS), Montreal Cognitive Assessment, and Hoehn-Yahr stage to optimize diagnostic test performance.

Results

Participants with PDD had higher α-syn than those with DLB and healthy participants and were distinguishable by their biomarker products Aβ42×p-tau181 and Aβ42×α-syn. Patients with DLB had higher p-tau181 than those with PDD and healthy participants and were distinguishable by their concentrations of α-syn×p-tau181. Plasma α-syn plus UPDRS versus either test alone increased sensitivity, specificity, and AUC when healthy patients were compared with those with PDD and DLB. Combined clinical examination scores and plasma biomarker products demonstrated utility in differentiating PDD from DLB when p-tau181 was combined with UPDRS, α-syn was combined with UPDRS, and α-syn×p-tau181 was combined with UPDRS.

Conclusions

In this pilot study, IMR plasma p-tau181 and α-syn may discriminate between PDD and DLB when used in conjunction with clinical testing.

Prognostic value of Alzheimer's disease plasma biomarkers in the oldest-old: a prospective primary care-based study

Background

Blood-based biomarkers offer a promising, less invasive, and more cost-effective alternative for Alzheimer's disease screening compared to cerebrospinal fluid or imaging biomarkers. However, they have been extensively studied only in memory clinic-based cohorts. We aimed to validate them in a more heterogeneous, older patient population from primary care.

Methods

We measured plasma Aβ42/Aβ40, P-tau181, NfL, and GFAP in 1007 individuals without dementia, aged 79-94 years, from the longitudinal, primary care-based German AgeCoDe study. We assessed the association with cognitive decline, disease progression, and the capacity to predict future dementia of the Alzheimer's type (DAT). We also evaluated biomarker dynamics in 305 individuals with a follow-up sample (∼8 years later).

Findings

Higher levels of P-tau181 (HR = 1.32 [95% CI: 1.17-1.51]), NfL (HR = 1.19 [95% CI: 1.03-1.36]), and GFAP (HR = 1.36 [95% CI: 1.22-1.52]), and a lower Aβ42/Aβ40 ratio (HR = 0.80 [95% CI: 0.68-0.95]) were associated with an increased risk of progressing to clinically-diagnosed DAT. Additionally, higher levels of P-tau181 (β = -0.49 [95% CI: -0.71 to 0.26]), NfL (β = -0.29 [95% CI: -0.52 to 0.06]), and GFAP (β = -0.60 [95% CI: -0.83 to 0.38]) were linked to faster cognitive decline. A two-step DAT prediction strategy combining initial MMSE with biomarkers improved the identification of individuals in the prodromal stage for potential treatment eligibility. Biomarker levels changed over time, with increases in P-tau181 (β = 0.19 [95% CI: 0.14-0.25]), NfL (β = 2.88 [95% CI: 2.18-3.59]), and GFAP (β = 8.23 [95% CI: 6.71-9.75]). NfL (β = 2.47 [95% CI: 1.04-3.89]) and GFAP (β = 4.45 [95% CI: 1.38-7.51]) exhibited a faster increase in individuals progressing to DAT.

Interpretation

Evaluating plasma biomarkers, alongside brief cognitive assessments, might enhance the precision of risk assessment for DAT progression in primary care.

Funding

Alzheimer Forschung Initiative, Bundesministerium für Bildung und Forschung.

Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment

INTRODUCTION

Previous studies have examined the predictive accuracy of plasma amyloid beta (Aβ) biomarkers in clinical cohorts. However, their accuracy for predicting amyloid-positive patients in community-based cohorts is unclear. This study aimed to determine the predictive accuracy of Aβ precursor protein 669-711/Aβ1-42, Aβ1-40/1-42 and their composite biomarkers for brain amyloid deposition or the clinical progression in community-dwelling older adults with mild cognitive impairment (MCI).

METHODS

This prospective cohort study was conducted from August 2015 to September 2019. Subsequently, the participants underwent follow-up cognitive assessments up to 8 years after the start of the study. Blood samples were collected from older adults aged ≥ 65 years with MCI at baseline. Plasma Aβ biomarkers were analyzed using immunoprecipitation-mass spectrometry. The accuracy of plasma biomarkers for brain amyloid status was evaluated using receiver operating characteristic curve analysis. Relationships between comorbidities and plasma Aβ markers were examined using multiple linear regression analysis. Associations of plasma biomarkers with clinical conversion to Alzheimer's disease (AD) dementia were evaluated using Kaplan‒Meier curves.

RESULTS

The participants included 107 patients (57 [53.3%] females, median age: 76.0 [72.0-80.0] years). Plasma biomarkers correlated with cortical amyloid uptake (ρ = 0.667-0.754). The composite biomarker had the best area under the curve (0.943, 95% confidence interval [CI]: 0.901 to 0.985) for predicting amyloid positivity. Apolipoprotein ε4 status showed significant correlations with increased plasma amyloid biomarker levels. Participants with high composite biomarker levels at baseline had a greater risk of conversion to AD dementia (hazard ratio 10.74, 95% CI: 3.51 to 32.84, P < 0.001). The higher composite biomarker was associated with a faster rate of cognitive decline (ρ = -0.575, P < 0.001).

DISCUSSION

Plasma Aβ composite biomarker may serve as a surrogate measure for amyloid deposition and a predictor of disease progression in a community-based cohort.

Highlights

Plasma amyloid beta (Aβ) biomarkers correlated with 11C-Pittsburgh compound B uptake, mainly in the frontal/parietotemporal cortices and posterior cingulate gyrus.The amyloid composite biomarker can predict amyloid positron emission tomography positivity with a high area under the curve of 0.943 in a community-based mild cognitive impairment cohort.The higher amyloid composite biomarker at baseline was significantly associated with worsening Mini-Mental State Examination score and a high risk for developing Alzheimer's disease (AD) dementia over 8 years.The amyloid composite biomarker can predict clinical progression to AD dementia with a high area under the curve of 0.860.Apolipoprotein E ε4 status influenced the plasma Aβ biomarker levels.

Identifying older adults at risk for dementia based on smartphone data obtained during a wayfinding task in the real world

Alzheimer's disease (AD), as the most common form of dementia and leading cause for disability and death in old age, represents a major burden to healthcare systems worldwide. For the development of disease-modifying interventions and treatments, the detection of cognitive changes at the earliest disease stages is crucial. Recent advancements in mobile consumer technologies provide new opportunities to collect multi-dimensional data in real-life settings to identify and monitor at-risk individuals. Based on evidence showing that deficits in spatial navigation are a common hallmark of dementia, we assessed whether a memory clinic sample of patients with subjective cognitive decline (SCD) who still scored normally on neuropsychological assessments show differences in smartphone-assisted wayfinding behavior compared with cognitively healthy older and younger adults. Guided by a mobile application, participants had to find locations along a short route on the medical campus of the Magdeburg university. We show that performance measures that were extracted from GPS and user input data distinguish between the groups. In particular, the number of orientation stops was predictive of the SCD status in older participants. Our data suggest that subtle cognitive changes in patients with SCD, whose risk to develop dementia in the future is elevated, can be inferred from smartphone data, collected during a brief wayfinding task in the real world.

Plasma markers of neurodegeneration, latent cognitive abilities and physical activity in healthy aging

Blood-based biomarkers of neurodegeneration demonstrate great promise for the diagnosis and prognosis of Alzheimer's disease. Ultra-sensitive plasma assays now allow for quantification of the lower concentrations in cognitively unimpaired older adults, making it possible to investigate whether these markers can provide insight also into the early neurodegenerative processes that affect cognitive function and whether the markers are influenced by modifiable risk factors. Adopting an exploratory approach in 93 healthy older adults (65-75 years), we used structural equation modelling to investigate cross-sectional associations between multiple latent cognitive abilities (working memory, episodic memory, spatial and verbal reasoning) and plasma amyloid beta (Aβ42/Aβ40 ratio), phosphorylated-tau 181 (ptau-181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL), as well as the influence of device-measured habitual physical activity on these associations. The results showed that NfL was negatively associated with working memory, and that NfL interacted with moderate-to-vigorous physical activity in its association with episodic memory. The study has thereby demonstrated the potential of neurodegenerative plasma markers for improving understanding of normative cognitive aging and encourages future research to test the hypothesis that high levels of NfL, indicative of white matter pathology, limit the beneficial effect of physical activity on episodic memory in healthy aging.

Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction?

There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ1-42 and Aβ1-40 (used as Aβ42/Aβ40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants' brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors (APOE, single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65-80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance (R² = 0.15) to MRI (R² = 0.18) and cardiovascular measures (R² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction (R² = 0.26 and 0.27). For amyloid positive individuals Aβ42/Aβ40, glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ42/Aβ40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population's socio-demographics, brain and cardiovascular health.

Leptin bioavailability and markers of brain atrophy and vascular injury in the middle age

INTRODUCTION

We investigated the associations of leptin markers with cognitive function and magnetic resonance imaging (MRI) measures of brain atrophy and vascular injury in healthy middle-aged adults.

METHODS

We included 2262 cognitively healthy participants from the Framingham Heart Study with neuropsychological evaluation; of these, 2028 also had available brain MRI. Concentrations of leptin, soluble leptin receptor (sOB-R), and their ratio (free leptin index [FLI]), indicating leptin bioavailability, were measured using enzyme-linked immunosorbent assays. Cognitive and MRI measures were derived using standardized protocols.

RESULTS

Higher sOB-R was associated with lower fractional anisotropy (FA, β = -0.114 ± 0.02, p < 0.001), and higher free water (FW, β = 0.091 ± 0.022, p < 0.001) and peak-width skeletonized mean diffusivity (PSMD, β = 0.078 ± 0.021, p < 0.001). Correspondingly, higher FLI was associated with higher FA (β = 0.115 ± 0.027, p < 0.001) and lower FW (β = -0.096 ± 0.029, p = 0.001) and PSMD (β = -0.085 ± 0.028, p = 0.002).

DISCUSSION

Higher leptin bioavailability was associated with better white matter (WM) integrity in healthy middle-aged adults, supporting the putative neuroprotective role of leptin in late-life dementia risk.

HIGHLIGHTS

Higher leptin bioavailability was related to better preservation of white matter microstructure. Higher leptin bioavailability during midlife might confer protection against dementia. Potential benefits might be even stronger for individuals with visceral obesity. DTI measures might be sensitive surrogate markers of subclinical neuropathology.

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis

BACKGROUND

Precisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology.

METHODS

Longitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer's Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer's Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777-88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels.

RESULTS

Among the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers.

CONCLUSION

A normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term.

TRIAL REGISTRATION

Clinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.

PrecivityAD2™ Blood Test: Analytical Validation of an LC-MS/MS Assay for Quantifying Plasma Phospho-tau217 and Non-Phospho-tau217 Peptide Concentrations That Are Used with Plasma Amyloid-β42/40 in a Multianalyte Assay with Algorithmic Analysis for Detecting Brain Amyloid Pathology

Alzheimer's disease (AD) is a progressive irreversible neurodegenerative disorder that represents a major global public health concern. Traditionally, AD is diagnosed using cerebrospinal fluid biomarker analysis or brain imaging modalities. Recently, less burdensome, more widely available blood biomarker (BBM) assays for amyloid-beta (Aβ42/40) and phosphorylated-tau concentrations have been found to accurately identify the presence/absence of brain amyloid plaques and tau tangles and have helped to streamline AD diagnosis. However, few BBMs have been rigorously analytically validated. Herein, we report the analytical validation of a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) multiplex method for quantifying plasma phosphorylated-tau217 (p-tau217) and non-phosphorylated-tau217 (np-tau217) peptide concentrations. We combined the p-tau217/np-tau217 concentrations ratio (%p-tau217) and the previously validated LC-MS/MS multiplex assay for plasma Aβ42/40 into a new multianalyte assay with algorithmic analysis (MAAA; PrecivityAD2™ test) that identifies brain amyloid status based on brain amyloid positron emission tomography. We found (a) the %p-tau217 assay is precise, accurate, sensitive, and linear over a wide analytical measurement range, and free from carryover and interference; (b) the pre-analytical specimen collection, processing, storage, and shipping conditions that maintain plasma tau peptide stability; and (c) using the measured analytical imprecision for plasma Aβ42/40 and p-tau217/np-tau217 levels in a worst-case scenario model, the PrecivityAD2 test algorithm for amyloid pathology classification changed for only 3.5% of participants from brain amyloid positive to negative, or from negative to positive. The plasma sample preparation and LC-MS/MS methods underlying the PrecivityAD2 test are suitable for use in the clinical laboratory and valid for the test's intended purpose: to aid in the diagnostic evaluation of individuals aged 55 and older with signs or symptoms of mild cognitive impairment or dementia.

Physical function is associated with cognitive status, brain amyloid-beta deposition, and blood biomarkers in Chinese Han population

BACKGROUND

The physical function of elderly individuals reflects whether they have had a history of regular physical activity over the long term. Such indicators have been found to have a certain connection with cognitive function these years. However, there is limited research that associates it with mechanisms such as cerebral Aβ deposition. We aim to investigate this relationship and unveil the underlying mechanisms.

METHOD

Physical function and cognition data of 4189 participants were obtained from the Chinese preclinical Alzheimer's disease study. Participants were divided into six groups according to disease severity. Among them, 1048 participants underwent the positron emission tomography-computed tomography (PET-CT) and plasma biomarker test. Grip strength and gait were combined into a score indicating physical function. Multiple linear regression models and logistic regression models were mainly used to conduct the analysis.

RESULTS

There was a significant positive correlation between physical function and cognitive function (R = 0.48, p < 0.001), independent of sex, age, apolipoprotein E-ε4 genotype, and disease stages (p < 0.001). Physical function was effective in distinguishing individuals with cognitive impairment from those without (AUC = 0.835). Physical function was negatively associated with brain Aβ deposition (p = 0.008) and brain Aβ had an intermediary effect (p < 0.01) on the association between physical function and cognition in women. This association was mainly evident in the lateral parietal, lateral temporal, posterior cingulate, frontal, occipital, and precuneus regions. Physical function was negatively associated with plasma neurofilament light-chain (Nfl) level (p < 0.001).

CONCLUSIONS

Physical function is strongly associated with cognitive function in the Chinese elderly, and brain Aβ deposition partly mediates the linkage in women. Plasma Nfl can be used as a potential target for exercise intervention in cognitive function. Improving physical function will contribute to the alleviation of cognition decline.

Real-world performance of plasma p-tau181 in a heterogeneous memory clinic cohort

OBJECTIVE

In light of clinical trials and disease-modifying therapies, an early identification of patients at-risk of developing Alzheimer's disease (AD) is crucial. Blood-based biomarkers have shown promising results regarding the in vivo detection of the earliest neuropathological changes in AD. Herein, we investigated the ability of plasma p-tau181 to act as a prescreening marker for amyloid positivity in a heterogeneous memory clinic-based cohort.

METHODS

In this retrospective cross-sectional study, we included a total of 115 patients along the clinical AD continuum (mild cognitive impairment [MCI] due to AD, n = 62, probable AD dementia, n = 53). Based on their biomarker status, they were stratified into an amyloid-positive (Aβ+, n = 88) or amyloid-negative cohort (Aβ-, n = 27). Plasma and CSF p-tau181 concentrations were quantified using an ultrasensitive single-molecule array (SIMOA©). Furthermore, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared using DeLong's test for correlated AUC curves.

RESULTS

The median (interquartile range [IQR]) concentration of plasma p-tau181 was significantly higher in Aβ+ patients (3.6 pg/mL [2.5-4.6]), compared with Aβ- patients (1.7 pg/mL [1.2-1.9], p < 0.001). Regarding the distinction between Aβ+ and Aβ- patients and the prediction of amyloid positivity, a high diagnostic accuracy for plasma p-tau181 with an AUC of 0.89 (95% CI = 0.82-0.95) was calculated. Adding the risk factors, age and APOE4, to the model did not significantly improve its performance.

INTERPRETATION

Our findings demonstrate that plasma p-tau181 could be a noninvasive and feasible prescreening marker for amyloid positivity in a heterogeneous clinical AD cohort and therefore help in identifying those who would benefit from more invasive assessment of amyloid pathology.

Machine learning on longitudinal multi-modal data enables the understanding and prognosis of Alzheimer's disease progression

Alzheimer's disease (AD) is a complex pathophysiological disease. Allowing for heterogeneity, not only in disease manifestations but also in different progression patterns, is critical for developing effective disease models that can be used in clinical and research settings. We introduce a machine learning model for identifying underlying patterns in Alzheimer's disease (AD) trajectory using longitudinal multi-modal data from the ADNI cohort and the AIBL cohort. Ten biologically and clinically meaningful disease-related states were identified from data, which constitute three non-overlapping stages (i.e., neocortical atrophy [NCA], medial temporal atrophy [MTA], and whole brain atrophy [WBA]) and two distinct disease progression patterns (i.e., NCA → WBA and MTA → WBA). The index of disease-related states provided a remarkable performance in predicting the time to conversion to AD dementia (C-Index: 0.923 ± 0.007). Our model shows potential for promoting the understanding of heterogeneous disease progression and early predicting the conversion time to AD dementia.

Plasma pTau181 enhances the prediction of future clinical decline in amyloid-positive mild cognitive impairment

Abstract

Plasma pTau181, a marker of amyloid and tau burden, was evaluated as a prognostic predictor of clinical decline and Alzheimer's disease (AD) progression of amyloid-positive (Aβ+) patients with mild cognitive impairment (MCI). The training cohort for constructing the Bayesian prediction models comprised 135 Aβ+ MCI clinical trial placebo subjects. Performance was evaluated in two validation cohorts. An 18-month ≥1 increase in the Clinical Dementia Rating Sum of Boxes was the clinical decline criterion. Baseline plasma pTau181 concentration matched clinical assessments' prediction performance. Adding pTau181 to clinical assessments significantly improved the prediction of an 18-month clinical decline and the 36-month progression from Aβ+ MCI to AD. The area under the receiver operating characteristic curve for the latter increased from 71.8% to 79%, and the hazard ratio for time-to-progression improved from 2.26 to 3.11 (p < 0.0001). Baseline plasma pTau181 has the potential for identifying Aβ+ MCI subjects with faster clinical decline over time.

Highlights

This study assessed pTau181 as a prognostic predictor of 18-month clinical decline and extended progression to Alzheimer's disease (AD) in amyloid-positive patients with mild cognitive impairment (Aβ+ MCI).The research findings underscore the promise of baseline plasma pTau181 as a screening tool for identifying Aβ+ MCI individuals with accelerated clinical decline within a standard 18-month clinical trial period. The predictive accuracy is notably enhanced when combined with clinical assessments.Similar positive outcomes were noted in forecasting the extended progression of Aβ+ MCI subjects to AD.

Cognitive Impairment in the Primary Care Clinic

Cognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment.

miR-519a-3p, found to regulate cellular prion protein during Alzheimer's disease pathogenesis, as a biomarker of asymptomatic stages

Clinical relevance of miRNAs as biomarkers is growing due to their stability and detection in biofluids. In this, diagnosis at asymptomatic stages of Alzheimer's disease (AD) remains a challenge since it can only be made at autopsy according to Braak NFT staging. Achieving the objective of detecting AD at early stages would allow possible therapies to be addressed before the onset of cognitive impairment. Many studies have determined that the expression pattern of some miRNAs is dysregulated in AD patients, but to date, none has been correlated with downregulated expression of cellular prion protein (PrPC) during disease progression. That is why, by means of cross studies of miRNAs up-regulated in AD with in silico identification of potential miRNAs-binding to 3'UTR of human PRNP gene, we selected miR-519a-3p for our study. Then, in vitro experiments were carried out in two ways. First, we validated miR-519a-3p target on 3'UTR-PRNP, and second, we analyzed the levels of PrPC expression after using of mimic technology on cell culture. In addition, RT-qPCR was performed to analyzed miR-519a-3p expression in human cerebral samples of AD at different stages of disease evolution. Additionally, samples of other neurodegenerative diseases such as other non-AD tauopathies and several synucleinopathies were included in the study. Our results showed that miR-519a-3p overlaps with PRNP 3'UTR in vitro and promotes downregulation of PrPC. Moreover, miR-519a-3p was found to be up-regulated exclusively in AD samples from stage I to VI, suggesting its potential use as a novel label of preclinical stages of the disease.

Physical exercise, cognition, and brain health in aging

Exercise training is an important strategy to counteract cognitive and brain health decline during aging. Evidence from systematic reviews and meta-analyses supports the notion of beneficial effects of exercise in cognitively unimpaired and impaired older individuals. However, the effects are often modest, and likely influenced by moderators such as exercise training parameters, sample characteristics, outcome assessments, and control conditions. Here, we discuss evidence on the impact of exercise on cognitive and brain health outcomes in healthy aging and in individuals with or at risk for cognitive impairment and neurodegeneration. We also review neuroplastic adaptations in response to exercise and their potential neurobiological mechanisms. We conclude by highlighting goals for future studies, including addressing unexplored neurobiological mechanisms and the inclusion of under-represented populations.

Longitudinal assessment of plasma biomarkers for early detection of cognitive changes in subjective cognitive decline

Background

Individuals experiencing subjective cognitive decline (SCD) are at an increased risk of developing mild cognitive impairment and dementia. Early identification of SCD and neurodegenerative diseases using biomarkers may help clinical decision-making and improve prognosis. However, few cross-sectional and longitudinal studies have explored plasma biomarkers in individuals with SCD using immunomagnetic reduction.

Objective

To identify plasma biomarkers for SCD.

Methods

Fifty-two participants [38 with SCD, 14 healthy controls (HCs)] underwent baseline assessments, including measurements of plasma Aβ42, Aβ40, t-tau, p-tau, and α-synuclein using immunomagnetic reduction (IMR) assays, cognitive tests and the Mini-Mental State Examination (MMSE). Following initial cross-sectional analysis, 39 individuals (29 with SCD, 10 HCs) entered a longitudinal phase for reassessment of these biomarkers and the MMSE. Biomarker outcomes across different individual categories were primarily assessed using the area under the receiver operating characteristic (ROC) curve. The SCD subgroup with an MMSE decline over one point was compared to those without such a decline.

Results

Higher baseline plasma Aβ1-42 levels significantly discriminated participants with SCD from HCs, with an acceptable area under the ROC curve (AUC) of 67.5% [95% confidence interval (CI), 52.7-80.0%]. However, follow-up and changes in MMSE and IMR data did not significantly differ between the SCD and HC groups (p > 0.05). Furthermore, lower baseline plasma Aβ1-42 levels were able to discriminate SCD subgroups with and without cognitive decline with a satisfied performance (AUC, 75.0%; 95% CI, 55.6-89.1%). At last, the changes in t-tau and Aβ42 × t-tau could differentiate between the two SCD subgroups (p < 0.05).

Conclusion

Baseline plasma Aβ42 may help identify people with SCD and predict SCD progression. The role of plasma Aβ42 levels as well as their upward trends from baseline in cases of SCD that progress to mild cognitive impairment and Alzheimer's disease require further investigation.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting

Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

Novel Biomarkers for Alzheimer's Disease: Plasma Neurofilament Light and Cerebrospinal Fluid

Neurodegenerative disorders such as Alzheimer's disease (AD) represent an increasingly significant public health concern. As clinical diagnosis faces challenges, biomarkers are becoming increasingly important in research, trials, and patient assessments. While biomarkers like amyloid-β peptide, tau proteins, CSF levels (Aβ, tau, and p-tau), and neuroimaging techniques are commonly used in AD diagnosis, they are often limited and invasive in monitoring and diagnosis. For this reason, blood-based biomarkers are the optimal choice for detecting neurodegeneration in brain diseases due to their noninvasiveness, affordability, reliability, and consistency. This literature review focuses on plasma neurofilament light (NfL) and CSF NfL as blood-based biomarkers used in recent AD diagnosis. The findings revealed that the core CSF biomarkers of neurodegeneration (T-tau, P-tau, and Aβ42), CSF NFL, and plasma T-tau were strongly associated with Alzheimer's disease, and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer's disease. Elevated levels of plasma and cerebrospinal fluid NfL were linked to decreased [18F]FDG uptake in corresponding brain areas. In participants with Aβ positivity (Aβ+), NfL correlated with reduced metabolism in regions susceptible to Alzheimer's disease. In addition, CSF NfL levels correlate with brain atrophy and predict cognitive changes, while plasma total tau does not. Plasma P-tau, especially in combination with Aβ42/Aβ40, is promising for symptomatic AD stages. Though not AD-exclusive, blood NfL holds promise for neurodegeneration detection and assessing treatment efficacy. Given the consistent levels of T-tau, P-tau, Aβ42, and NFL in CSF, their incorporation into both clinical practice and research is highly recommended.

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

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

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

Plasma biomarkers for Alzheimer's and related dementias: A review and outlook for clinical neuropsychology

Recent technological advances have improved the sensitivity and specificity of blood-based biomarkers for Alzheimer's disease and related dementias. Accurate quantification of amyloid-ß peptide, phosphorylated tau (pTau) isoforms, as well as markers of neurodegeneration (neurofilament light chain [NfL]) and neuro-immune activation (glial fibrillary acidic protein [GFAP] and chitinase-3-like protein 1 [YKL-40]) in blood has allowed researchers to characterize neurobiological processes at scale in a cost-effective and minimally invasive manner. Although currently used primarily for research purposes, these blood-based biomarkers have the potential to be highly impactful in the clinical setting - aiding in diagnosis, predicting disease risk, and monitoring disease progression. Whereas plasma NfL has shown promise as a non-specific marker of neuronal injury, plasma pTau181, pTau217, pTau231, and GFAP have demonstrated desirable levels of sensitivity and specificity for identification of individuals with Alzheimer's disease pathology and Alzheimer's dementia. In this forward looking review, we (i) provide an overview of the most commonly used blood-based biomarkers for Alzheimer's disease and related dementias, (ii) discuss how comorbid medical conditions, demographic, and genetic factors can inform the interpretation of these biomarkers, (iii) describe ongoing efforts to move blood-based biomarkers into the clinic, and (iv) highlight the central role that clinical neuropsychologists may play in contextualizing and communicating blood-based biomarker results for patients.

[On the road to biological blood diagnosis of Alzheimer's disease?]

The growing number of people suffering from Alzheimer's disease (AD) represents a major public health problem. The diagnosis of AD is multidisciplinary and involves the use of amyloid and tau biomarkers measured in cerebrospinal fluid. Recent advances in analytical techniques now allow us to measure these biomarkers in blood. Blood biomarkers offer particularly promising potential for early, minimally invasive detection of AD, as well as for differential diagnosis of dementia and patient follow-up. The aim of this review is to provide an overview of current and candidate blood biomarkers for AD, their informative value, and their potential to be integrated into clinical practice in the near future.

Cognitive and functional performance and plasma biomarkers of early Alzheimer's disease in Down syndrome

INTRODUCTION

People with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer's disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials.

METHODS

This large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual-motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25-81 years).

RESULTS

In general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory.

DISCUSSION

Plasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest.

Highlights

Plasma Alzheimer's disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome.Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities.Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance.Plasma biomarkers show potential for tracking early stages of AD symptomology.

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

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

Circulating biomarkers of inflammaging and Alzheimer's disease to track age-related trajectories of dementia: Can we develop a clinically relevant composite combination?

Alzheimer's disease (AD) is a rapidly growing global concern due to a consistent rise of the prevalence of dementia which is mainly caused by the aging population worldwide. An early diagnosis of AD remains important as interventions are plausibly more effective when started at the earliest stages. Recent developments in clinical research have focused on the use of blood-based biomarkers for improve diagnosis/prognosis of neurodegenerative diseases, particularly AD. Unlike invasive cerebrospinal fluid tests, circulating biomarkers are less invasive and will become increasingly cheaper and simple to use in larger number of patients with mild symptoms or at risk of dementia. In addition to AD-specific markers, there is growing interest in biomarkers of inflammaging/neuro-inflammaging, an age-related chronic low-grade inflammatory condition increasingly recognized as one of the main risk factor for almost all age-related diseases, including AD. Several inflammatory markers have been associated with cognitive performance and AD development and progression. The presence of senescent cells, a key driver of inflammaging, has also been linked to AD pathogenesis, and senolytic therapy is emerging as a potential treatment strategy. Here, we describe blood-based biomarkers clinically relevant for AD diagnosis/prognosis and biomarkers of inflammaging associated with AD. Through a systematic review approach, we propose that a combination of circulating neurodegeneration and inflammatory biomarkers may contribute to improving early diagnosis and prognosis, as well as providing valuable insights into the trajectory of cognitive decline and dementia in the aging population.

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

BACKGROUND

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

METHODS

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

RESULTS

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

DISCUSSION

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

Path integration deficits are associated with phosphorylated tau accumulation in the entorhinal cortex

Alzheimer's disease is a devastating disease that is accompanied by dementia, and its incidence increases with age. However, no interventions have exhibited clear therapeutic effects. We aimed to develop and characterize behavioural tasks that allow the earlier identification of signs preceding dementia that would facilitate the development of preventative and therapeutic interventions for Alzheimer's disease. To this end, we developed a 3D virtual reality task sensitive to the activity of grid cells in the entorhinal cortex, which is the region that first exhibits neurofibrillary tangles in Alzheimer's disease. We investigated path integration (assessed by error distance) in a spatial navigation task sensitive to grid cells in the entorhinal cortex in 177 volunteers, aged 20-89 years, who did not have self-reported dementia. While place memory was intact even in old age, path integration deteriorated with increasing age. To investigate the relationship between neurofibrillary tangles in the entorhinal cortex and path integration deficit, we examined a mouse model of tauopathy (P301S mutant tau-overexpressing mice; PS19 mice). At 6 months of age, PS19 mice showed a significant accumulation of phosphorylated tau only in the entorhinal cortex, associated with impaired path integration without impairments in spatial cognition. These data are consistent with the idea that path integration deficit is caused by the accumulation of phosphorylated tau in the entorhinal cortex. This method may allow the early identification of individuals likely to develop Alzheimer's disease.

Comparative methods for quantifying plasma biomarkers in Alzheimer's disease: Implications for the next frontier in cerebral amyloid angiopathy diagnostics

Plasma amyloid beta (Aβ) and tau are emerging as accessible biomarkers for Alzheimer's disease (AD). However, many assays exist with variable test performances, highlighting the need for a comparative assessment to identify the most valid assays for future use in AD and to apply to other settings in which the same biomarkers may be useful, namely, cerebral amyloid angiopathy (CAA). CAA is a progressive cerebrovascular disease characterized by deposition of Aβ40 and Aβ42 in cortical and leptomeningeal vessels. Novel immunotherapies for AD can induce amyloid-related imaging abnormalities resembling CAA-related inflammation. Few studies have evaluated plasma biomarkers in CAA. Identifying a CAA signature could facilitate diagnosis, prognosis, and a safer selection of patients with AD for emerging immunotherapies. This review evaluates studies that compare the diagnostic test performance of plasma biomarker techniques in AD and cerebrovascular and plasma biomarker profiles of CAA; it also discusses novel hypotheses and future avenues for plasma biomarker research in CAA.