Amyloid Metabolism and Amyloid-Targeting Blood-Based Biomarkers of Alzheimer's Disease

Characteristics of discordance between amyloid positron emission tomography and plasma amyloid-β 42/40 positivity

Various plasma biomarkers for amyloid-β (Aβ) have shown high predictability of amyloid PET positivity. However, the characteristics of discordance between amyloid PET and plasma Aβ42/40 positivity are poorly understood. Thorough interpretation of discordant cases is vital as Aβ plasma biomarker is imminent to integrate into clinical guidelines. We aimed to determine the characteristics of discordant groups between amyloid PET and plasma Aβ42/40 positivity, and inter-assays variability depending on plasma assays. We compared tau burden measured by PET, brain volume assessed by MRI, cross-sectional cognitive function, longitudinal cognitive decline and polygenic risk score (PRS) between PET/plasma groups (PET-/plasma-, PET-/plasma+, PET+/plasma-, PET+/plasma+) using Alzheimer's Disease Neuroimaging Initiative database. Additionally, we investigated inter-assays variability between immunoprecipitation followed by mass spectrometry method developed at Washington University (IP-MS-WashU) and Elecsys immunoassay from Roche (IA-Elc). PET+/plasma+ was significantly associated with higher tau burden assessed by PET in entorhinal, Braak III/IV, and Braak V/VI regions, and with decreased volume of hippocampal and precuneus regions compared to PET-/plasma-. PET+/plasma+ showed poor performances in global cognition, memory, executive and daily-life function, and rapid cognitive decline. PET+/plasma+ was related to high PRS. The PET-/plasma+ showed intermediate changes between PET-/plasma- and PET+/plasma+ in terms of tau burden, hippocampal and precuneus volume, cross-sectional and longitudinal cognition, and PRS. PET+/plasma- represented heterogeneous characteristics with most prominent variability depending on plasma assays. Moreover, IP-MS-WashU showed more linear association between amyloid PET standardized uptake value ratio and plasma Aβ42/40 than IA-Elc. IA-Elc showed more plasma Aβ42/40 positivity in the amyloid PET-negative stage than IP-MS-WashU. Characteristics of PET-/plasma+ support plasma biomarkers as early biomarker of amyloidopathy prior to amyloid PET. Various plasma biomarker assays might be applied distinctively to detect different target subjects or disease stages.

Integration of amyloid-β oligomerization tendency as a plasma biomarker in Alzheimer's disease diagnosis

Introduction

There has been significant development in blood-based biomarkers targeting amyloidopathy of Alzheimer's disease (AD). However, the guidelines for integrating such biomarkers into AD diagnosis are still inadequate. Multimer Detection System-Oligomeric Amyloid-β (MDS-OAβ) as a plasma biomarker detecting oligomerization tendency is available in the clinical practice.

Main text

We suggest how to interpret the results of plasma biomarker for amyloidopathy using MDS-OAβ with neuropsychological test, brain magnetic resonance imaging (MRI), and amyloid PET for AD diagnosis. Combination of each test result differentiates various stages of AD, other neurodegenerative diseases, or cognitive impairment due to the causes other than neurodegeneration.

Discussion

A systematic interpretation strategy could support accurate diagnosis and staging of AD. Moreover, comprehensive use of biomarkers that target amyloidopathy such as amyloid PET on brain amyloid plaque and MDS-OAβ on amyloid-β oligomerization tendency can complement to gain advanced insights on amyloid-β dynamics in AD.

Prediction of amyloid PET positivity via machine learning algorithms trained with EDTA-based blood amyloid-β oligomerization data

Background

The tendency of amyloid-β to form oligomers in the blood as measured with Multimer Detection System-Oligomeric Amyloid-β (MDS-OAβ) is a valuable biomarker for Alzheimer’s disease and has been verified with heparin-based plasma. The objective of this study was to evaluate the performance of ethylenediaminetetraacetic acid (EDTA)-based MDS-OAβ and to develop machine learning algorithms to predict amyloid positron emission tomography (PET) positivity.

Methods

The performance of EDTA-based MDS-OAβ in predicting PET positivity was evaluated in 312 individuals with various machine learning models. The models with various combinations of features (i.e., MDS-OAβ level, age, apolipoprotein E4 alleles, and Mini-Mental Status Examination [MMSE] score) were tested 50 times on each dataset.

Results

The random forest model best-predicted amyloid PET positivity based on MDS-OAβ combined with other features with an accuracy of 77.14 ± 4.21% and an F1 of 85.44 ± 3.10%. The order of significance of predictive features was MDS-OAβ, MMSE, Age, and APOE. The Support Vector Machine using the MDS-OAβ value only showed an accuracy of 71.09 ± 3.27% and F−1 value of 80.18 ± 2.70%.

Conclusions

The Random Forest model using EDTA-based MDS-OAβ combined with the MMSE and apolipoprotein E status can be used to prescreen for amyloid PET positivity.

Effect of Time to Detection on the Measured Concentrations of Blood Proteins Associated with Alzheimer’s Disease

Background

For assays using immunomagnetic reduction, a reagent composed of antibody-functionalized magnetic nanoparticles is dispersed in phosphate-buffered saline solution. The real-time signals of alternating-current (ac) magnetic susceptibility, χ_ac, of the reagent are subsequently recorded after mixing the reagent with a biofluid sample. After mixing the reagent and sample, the reduction in χ_ac of the mixture is calculated and used to quantify the concentration of the target biomarker in the sample. The reduction does not occur immediately but rather occurs at some time after mixing. This observation implies that the time elapsed before recording the real-time signals of χ_ac of a reagent-sample mixture needs to be investigated to ensure that the signals are fully recorded. In this work, the effect of time to detection on the measured concentrations of proteins in human plasma after mixing the reagent and sample is examined.

Methods

The proteins analyzed are related to Alzheimer's disease: amyloid β 1–40, amyloid β 1–42, and Tau protein. The investigated times to detection after the mixing the reagent and sample are 0, 20, 30, 40, and 120 min.

Results

The results show that the recording of real-time signals of χ_ac should be conducted within 20 min after mixing the reagent and sample.

Alzheimer’s Disease Biomarkers Revisited From the Amyloid Cascade Hypothesis Standpoint

Alzheimer’s disease (AD) is the most common neurodegenerative disease worldwide. Amyloid beta (Aβ) is one of the proteins which aggregate in AD, and its key role in the disease pathogenesis is highlighted in the amyloid cascade hypothesis, which states that the deposition of Aβ in the brain parenchyma is a crucial initiating step in the future development of AD. The sensitivity of instruments used to measure proteins in blood and cerebrospinal fluid has significantly improved, such that Aβ can now successfully be measured in plasma. However, due to the peripheral production of Aβ, there is significant overlap between diagnostic groups. The presence of pathological Aβ within the AD brain has several effects on the cells and surrounding tissue. Therefore, there is a possibility that using markers of tissue responses to Aβ may reveal more information about Aβ pathology and pathogenesis than looking at plasma Aβ alone. In this manuscript, using the amyloid cascade hypothesis as a starting point, we will delve into how the effect of Aβ on the surrounding tissue can be monitored using biomarkers. In particular, we will consider whether glial fibrillary acidic protein, triggering receptor expressed on myeloid cells 2, phosphorylated tau, and neurofilament light chain could be used to phenotype and quantify the tissue response against Aβ pathology in AD.

Association Plasma Aβ42 Levels with Alzheimer's Disease and Its Influencing Factors in Chinese Elderly Population

BACKGROUND AND PURPOSE

Intracerebral Aβ protein deposition is an important pathological mechanism of Alzheimer's disease (AD) and is one of the indicators of early diagnosis of AD. However, invasive lumbar puncture and Aβ PET are difficult to perform in primary units, resulting delays in early diagnosis of AD. In recent years, it has been found that plasma Aβ can reflect the pathological state of AD in early stage, but the results are not consistent. The objective of this study was to explore the association between plasma Aβ42 levels and AD cognitive impairment and its influencing factors in Chinese elderly population, so as to provide guidance for the clinical application of plasma Aβ42 as a blood biomarker of AD.

METHODS

This is a cross-sectional study based on the community population. Plasma samples were collected from 604 healthy controls (HC), 508 mild cognitive impairment (MCI) and 202 dementia with Alzheimer's type (DAT) patients from three cities. We analyzed the correlation between plasma Aβ42 levels and cognitive function and the influence of confounding factors on the relationship between plasma Aβ42 levels and AD. The independent influencing factors of plasma Aβ42 levels were determined by covariance and linear regression analysis.

RESULTS

Our results suggest that there is a special linear relationship between plasma Aβ42 and cognitive impairment of AD in Chinese elderly population, with Aβ42 levels slightly decreased in early AD and significantly increased in moderate-to-severe AD (P<0.01). There are many factors influencing the association between plasma Aβ42 levels and AD cognitive impairment, and sample source, gender and BMI are independent influencing factors of plasma Aβ42.

CONCLUSION

This indentifies that plasma Aβ42 may be a peripheral biomarker for AD screening in Chinese elderly population, but it is necessary to establish standardized detection methods and establish different demarcation criteria for various influencing factors.

Plasma Amyloid-β Oligomerization Tendency Predicts Amyloid PET Positivity

Purpose

Among other emerging amyloid-targeting blood-based biomarkers, Multimer Detection System-Oligomeric Amyloid-β (MDS-OAβ) measures dynamic changes in concentration of oligomeric amyloid-β (OAβ), which is considered the main pathogenic culprit of Alzheimer’s disease (AD), in plasma after spiking with synthetic amyloid-β (Aβ). We aimed to investigate the predictability of MDS-OAβ on amyloid positron emission tomography (PET) positivity.

Patients and Methods

A total of 96 subjects who visited Seoul National University Bundang Hospital for medical check-up complaining of cognitive decline and had undergone extensive medical assessment were recruited. Amyloid statuses were dichotomized into positive or negative based on visual assessment of amyloid PET. Plasma OAβ concentration was measured by MDS-OAβ. In the previous validation study, 0.78ng/mL was established as the cut-off value and the plasma OAβ concentration higher than or equal to the cut-off value was defined as MDS-OAβ positive.

Results

MDS-OAβ positivity could discriminate amyloid PET positivity with the AUC value of 0.855 (95% CI 0.776–0.933). Adding MDS-OAβ positivity to prediction models including age, MMSE score, and APOE ε4 status improved performance up to the AUC value of 0.926 (95% CI 0.871–0.980).

Conclusion

The Aβ oligomerization tendency in plasma could predict amyloid PET positivity with high performance, and, when it is combined with age, MMSE score, and APOE ε4 status, predictability was improved substantially. This suggests the potential of MDS-OAβ as a useful initial stage test in the clinical and research fields of AD.

Graphene oxide improves postoperative cognitive dysfunction by maximally alleviating amyloid beta burden in mice

Rationale: Graphene oxide (GO) based nanomaterials have shown potential for the diagnosis and treatment of amyloid-β (Aβ)-related diseases, mainly on Alzheimer's disease (AD). However, these nanomaterials have limitations. How GO is beneficial to eliminate Aβ burden, and its physiological function in Aβ-related diseases, still needs to be investigated. Moreover, postoperative cognitive dysfunction (POCD) is an Aβ-related common central nervous system complication, however, nanomedicine treatment is lacking.

Methods: To evaluate the effects of GO on Aβ levels, HEK293T-APP-GFP and SHSY5Y-APP-GFP cells are established. Intramedullary fixation surgery for tibial fractures under inhalation anesthesia is used to induce dysfunction of fear memory in mice. The fear memory of mice is assessed by fear conditioning test.

Results: GO treatment maximally alleviated Aβ levels by simultaneously reducing Aβ generation and enhancing its degradation through inhibiting β-cleavage of amyloid precursor protein (APP) and improving endosomal Aβ delivery to lysosomes, respectively. In postoperative mice, the hippocampal Aβ levels were significantly increased and hippocampal-dependent fear memory was impaired. However, GO administration significantly reduced hippocampal Aβ levels and improved the cognitive function of the postoperative mice.

Conclusion: GO improves fear memory of postoperative mice by maximally alleviating Aβ accumulation, providing new evidence for the application of GO-based nanomedicines in Aβ-related diseases.