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Accessible and cost-effective diagnostic tools are urgently needed to accurately quantify blood biomarkers to support early diagnosis of Alzheimer's disease (AD). In this study, we investigated the ability of plasma amyloid-beta (Aβ)42/Aβ40 ratio measured by an antibody-free mass-spectrometric (MS) method, ABtest-MS, to detect early pathological changes of AD.This cohort study included data from the baseline and 2-year follow-up visits from the Fundació ACE Healthy Brain Initiative (FACEHBI) study. Plasma Aβ42/Aβ40 was measured with ABtest-MS and compared toThe FACEHBI cohort at baseline included 200 healthy individuals with subjective cognitive decline (SCD), of which 36 (18%) were Aβ-PET positive. Plasma Aβ42/Aβ40 levels were significantly lower in Aβ-PET positive individuals (median [interquartile range, IQR], 0.215 [0.203-0.236]) versus Aβ-PET negative subjects (median [IQR], 0.261 [0.244-0.279]) (P.001). Plasma Aβ42/Aβ40 was significantly correlated with Aβ-PET levels (rho = -0.390; P.001) and identified Aβ-PET status with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI], 0.80-0.93). A cutoff for the Aβ42/Aβ40 ratio of 0.241 (maximum Youden index) yielded a sensitivity of 86.1% and a specificity of 80.5%. These findings were cross-validated in an independent DPUK-Korean cohort (AUC 0.86 [95% CI 0.77-0.95]). Lower plasma Aβ42/Aβ40 ratio was associated with worse episodic memory performance and increased brain atrophy. Plasma Aβ42/Aβ40 at baseline predicted clinical conversion to mild cognitive impairment and longitudinal changes in amyloid deposition and brain atrophy at 2-year follow-up.This study suggests that plasma Aβ42/Aβ40, as determined by this MS-based assay, has potential value as an accurate and cost-effective tool to identify individuals in the earliest stages of AD, supporting its implementation in clinical trials, preventative strategies and clinical practice.

We developed models for individualized risk prediction of cognitive decline in mild cognitive impairment (MCI) using plasma biomarkers of β-amyloid (Aβ), tau and neurodegeneration. A total of 573 patients with MCI from the Swedish BioFINDER study and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were included in the study. The primary outcomes were longitudinal cognition and conversion to Alzheimer’s disease (AD) dementia. A model combining tau phosphorylated at threonine 181 (P-tau181) and neurofilament light (NfL), but not Aβ42/Aβ40, had the best prognosis performance of all models (area under the curve = 0.88 for 4-year conversion to AD in BioFINDER, validated in ADNI), was stronger than a basic model of age, sex, education and baseline cognition, and performed similarly to cerebrospinal fluid biomarkers. A publicly available online tool for individualized prognosis in MCI based on our combined plasma biomarker models is introduced. Combination of plasma biomarkers may be of high value to identify individuals with MCI who will progress to AD dementia in clinical trials and in clinical practice. This study shows that combinations of blood-based biomarkers can be used to predict cognitive decline and dementia due to Alzheimer’s disease in patients with mild cognitive impairment. Biomarkers for tau and neurodegeneration provided accurate prognosis of decline and conversion over four years.

Background We assessed the feasibility of plasma Aβ42/Aβ40 determined using a novel liquid chromatography-mass spectrometry method (LC-MS) as a useful biomarker of PET status in a Korean cohort from the DPUK Study. Methods A total of 580 participants belonging to six groups, Alzheimer’s disease dementia (ADD, n = 134), amnestic mild cognitive impairment (aMCI, n = 212), old controls (OC, n = 149), young controls (YC, n = 15), subcortical vascular cognitive impairment (SVCI, n = 58), and cerebral amyloid angiopathy (CAA, n = 12), were included in this study. Plasma Aβ40 and Aβ42 were quantitated using a new antibody-free, LC-MS, which drastically reduced the sample preparation time and cost. We performed receiver operating characteristic (ROC) analysis to develop the cutoff of Aβ42/Aβ40 and investigated its performance predicting centiloid-based PET positivity (PET+). Results Plasma Aβ42/Aβ40 were lower for PET+ individuals in ADD, aMCI, OC, and SVCI (p < 0.001), but not in CAA (p = 0.133). In the group of YC, OC, aMCI, and ADD groups, plasma Aβ42/Aβ40 predicted PET+ with an area under the ROC curve (AUC) of 0.814 at a cutoff of 0.2576. When adding age, APOE4, and diagnosis, the AUC significantly improved to 0.912. Conclusion Plasma Aβ42/Aβ40, as measured by this novel LC-MS method, showed good discriminating performance based on PET positivity.

Introduction Blood‐based assays to measure brain amyloid beta (Aβ) deposition are an attractive alternative to the cerebrospinal fluid (CSF)–based assays currently used in clinical settings. In this study, we examined different blood‐based assays to measure Aβ and how they compare among centers and assays. Methods Aliquots from 81 plasma samples were distributed to 10 participating centers. Seven immunological assays and four mass‐spectrometric methods were used to measure plasma Aβ concentrations. Results Correlations were weak for Aβ42 while Aβ40 correlations were stronger. The ratio Aβ42/Aβ40 did not improve the correlations and showed weak correlations. Discussion The poor correlations for Aβ42 in plasma might have several potential explanations, such as the high levels of plasma proteins (compared to CSF), sensitivity to pre‐analytical sample handling and specificity, and cross‐reactivity of different antibodies. Different methods might also measure different pools of plasma Aβ42. We, however, hypothesize that greater correlations might be seen in future studies because many of the methods have been refined during completion of this study.

Key Points Question How well does plasma amyloid-β 42/40 (Aβ42/40), measured using 8 different assays, detect brain Aβ pathology in the early stages of Alzheimer disease? Findings In this study, including 408 participants from 2 independent cohorts (BioFINDER and Alzheimer Disease Neuroimaging Initiative), plasma Aβ42/40 quantified using certain mass spectrometry–based methods showed better discriminative accuracy than immunoassays when identifying individuals with abnormal intracerebral Aβ status according to cerebrospinal fluid Aβ42/40 levels and Aβ positron emission tomography. Meaning Certain mass spectrometry–based plasma tests might have sufficient performance to detect brain Aβ pathology in Alzheimer disease., This cross-sectional study compares the performance of plasma amyloid-β 42/40 (Aβ42/40) measured using 8 different Aβ assays and methods in detecting abnormal brain Aβ status in patients with early Alzheimer disease., Importance Blood-based tests for brain amyloid-β (Aβ) pathology are needed for widespread implementation of Alzheimer disease (AD) biomarkers in clinical care and to facilitate patient screening and monitoring of treatment responses in clinical trials. Objective To compare the performance of plasma Aβ42/40 measured using 8 different Aβ assays when detecting abnormal brain Aβ status in patients with early AD. Design, Setting, and Participants This study included 182 cognitively unimpaired participants and 104 patients with mild cognitive impairment from the BioFINDER cohort who were enrolled at 3 different hospitals in Sweden and underwent Aβ positron emission tomography (PET) imaging and cerebrospinal fluid (CSF) and plasma collection from 2010 to 2014. Plasma Aβ42/40 was measured using an immunoprecipitation-coupled mass spectrometry developed at Washington University (IP-MS-WashU), antibody-free liquid chromatography MS developed by Araclon (LC-MS-Arc), and immunoassays from Roche Diagnostics (IA-Elc); Euroimmun (IA-EI); and Amsterdam University Medical Center, ADx Neurosciences, and Quanterix (IA-N4PE). Plasma Aβ42/40 was also measured using an IP-MS–based method from Shimadzu in 200 participants (IP-MS-Shim) and an IP-MS–based method from the University of Gothenburg (IP-MS-UGOT) and another immunoassay from Quanterix (IA-Quan) among 227 participants. For validation, 122 participants (51 cognitively normal, 51 with mild cognitive impairment, and 20 with AD dementia) were included from the Alzheimer Disease Neuroimaging Initiative who underwent Aβ-PET and plasma Aβ assessments using IP-MS-WashU, IP-MS-Shim, IP-MS-UGOT, IA-Elc, IA-N4PE, and IA-Quan assays. Main Outcomes and Measures Discriminative accuracy of plasma Aβ42/40 quantified using 8 different assays for abnormal CSF Aβ42/40 and Aβ-PET status. Results A total of 408 participants were included in this study. In the BioFINDER cohort, the mean (SD) age was 71.6 (5.6) years and 49.3% of the cohort were women. When identifying participants with abnormal CSF Aβ42/40 in the whole cohort, plasma IP-MS-WashU Aβ42/40 showed significantly higher accuracy (area under the receiver operating characteristic curve [AUC], 0.86; 95% CI, 0.81-0.90) than LC-MS-Arc Aβ42/40, IA-Elc Aβ42/40, IA-EI Aβ42/40, and IA-N4PE Aβ42/40 (AUC range, 0.69-0.78; P

Introduction: We studied usefulness of combining blood amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p-tau)217, and neurofilament light (NfL) to detect abnormal brain Aβ deposition in different stages of early Alzheimer's disease (AD). Methods: Plasma biomarkers were measured using mass spectrometry (Aβ42/Aβ40) and immunoassays (p-tau217 and NfL) in cognitively unimpaired individuals (CU, N = 591) and patients with mild cognitive impairment (MCI, N = 304) from two independent cohorts (BioFINDER-1, BioFINDER-2). Results: In CU, a combination of plasma Aβ42/Aβ40 and p-tau217 detected abnormal brain Aβ status with area under the curve (AUC) of 0.83 to 0.86. In MCI, the models including p-tau217 alone or Aβ42/Aβ40 and p-tau217 had similar AUCs (0.86–0.88); however, the latter showed improved model fit. The models were implemented in an online application providing individualized risk assessments (https://brainapps.shinyapps.io/PredictABplasma/). Discussion: A combination of plasma Aβ42/Aβ40 and p-tau217 discriminated Aβ status with relatively high accuracy, whereas p-tau217 showed strongest associations with Aβ pathology in MCI but not in CU.

We developed models for individualized risk prediction of cognitive decline in mild cognitive impairment (MCI), using plasma biomarkers of β-amyloid (Aβ), tau, and neurodegeneration. We included MCI patients from the Swedish BioFINDER study (n=148) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI; n=86 for model selection; n=425 for prognostic validation). The primary outcomes were longitudinal cognition and conversion to AD dementia, predicted by plasma Aβ42/Aβ40, P-tau181, and neurofilament light (NfL). A model which included P-tau181 and NfL, but not Aβ42/Aβ40, had the best performance (AUC=0.88 for four-year conversion to AD in BioFINDER, validated in ADNI). The prognostic ability of plasma biomarkers was stronger than a basic model of age, sex, education, and baseline cognition and similar to cerebrospinal fluid biomarkers. Plasma biomarkers, in particular P-tau181 and NfL, may be of high value to identify MCI individuals who will progress to AD dementia in clinical trials and in clinical practice.

APPswe/PS1dE9 and Tg2576 are very common transgenic mouse models of Alzheimer's disease (AD), used in many laboratories as tools to research the mechanistic process leading to the disease. In order to augment our knowledge about the amyloid-β (Aβ) isoforms present in both transgenic mouse models, we have developed two chromatographic methods, one acidic and the other basic, for the characterization of the Aβ species produced in the brains of the two transgenic mouse models. After immunoprecipitation and micro-liquid chromatography-electrospray ionization mass spectrometry/mass spectrometry, 10 species of Aβ, surprisingly all of human origin, were detected in the brain of Tg2576 mouse, whereas 39 species, of both murine and human origin, were detected in the brain of the APP/PS1 mouse. To the best of our knowledge, this is the first study showing the identification of such a high number of Aβ species in the brain of the APP/PS1 transgenic mouse, whereas, in contrast, a much lower number of Aβ species were identified in the Tg2576 mouse. Therefore, this study brings to light a relevant phenotypic difference between these two popular mice models of AD.

This work was prompted by the finding that Aβ1-17 (Aβ17) appeared to be the second-most abundant cerebrospinal fluid (CSF) Aβ fragment, after Aβ40. We developed an ELISA to quantify levels of Aβ17 directly accessible in plasma (DA17), recovered from the proteomic plasma matrix (RP17) and associated with the cellular pellet (CP17) that remained after plasma collection. Then, we used a sample of 19 healthy control (HC), 27 mild cognitive impairment (MCI), and 17 mild Alzheimer's disease (AD) patients to explore the association of the diagnostic groups with those direct markers, their ratios or the ratios with their Aβ40 or Aβ42 counterparts. After dichotomization (d) for the median of the sample population, logistic regression analysis showed that in the AD versus HC subgroup, subjects with a dDA/CP17 higher than the median had a significantly greater risk of being AD than those with marker levels equal to or below the median (odds ratio OR; 95% confidence interval; 17.21; 1.42-208.81). Subjects with dRP17/42 below the median had an increased likelihood of being MCI (20.00; 1.17-333.33) or AD (40.00; 1.87-1000) versus being HC, than those with dRP17/42 higher than the median. Although the confidence intervals are wide, these findings suggest that assessment of Aβ17 may increase the diagnostic performance of blood-based Aβ tests which might be developed into minimally invasive first-step screening tests for people with increased risk for AD.

It is well known that several Aβ species, including Aβ40 and Aβ42, are present in cerebrospinal fluid (CSF). Experimental results suggest that these species could play a role in Alzheimer's disease and might also have diagnostic significance. In the present work, the canine CSF β-amyloid species profile has been identified by matrix-assisted laser desorption and ionization–time-of-flight/time of flight mass spectrometry (MALDI-TOF/TOF) analysis after immunoprecipitation with different Aβ-specific antibodies. The results show that species arising from combined β- and γ-secretase activities in humans, such as Aβ1–33, Aβ1–34, Aβ1–37, Aβ1–38, Aβ1–39, Aβ1–40, and Aβ1–42, are also present in dogs. Species arising from combined α- and β-secretase activities, as well as other Aβ-degrading enzymes, are also present in both human and canine CSF, with the exception of Aβ1–13, Aβ1–14, and Aβ1–18, which are not detected in dogs. A large number of species truncated at Glu-3 and Glu-11 have also been detected. To our knowledge, this work describes a most complete Aβ species profile from canine CSF. The similarities between the canine and human CSF Aβ profile reinforce the dog as a highly appropriate animal model for research in Alzheimer's disease.