Plasma Aβ42/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study

Background: To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer’s disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. Methods: We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. Results: Eighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779–0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden’s cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913–0.100). Conclusions: Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer’s disease

Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity

Background: Early detection of β-amyloid (Aβ) accumulation, a major biomarker for Alzheimer's disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) Aβ for predicting Aβ deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma Aβ is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma Aβ and CSF Aβ levels for Aβ PET positivity. Methods: We recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed. Results: When predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p < 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added. Conclusion: Plasma Aβ might be a useful predictor of Aβ deposition on PET status as much as CSF Aβ, particularly when considered with clinical information such as APOE genotype and cognitive stage

Individualized prognosis of cognitive decline and dementia in mild cognitive impairment based on plasma biomarker combinations

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

Detecting amyloid positivity in early Alzheimer's disease using combinations of plasma Aβ42/Aβ40 and p-tau

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

Plasma Aβ42/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study

Background: To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer’s disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. Methods: We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. Results: Eighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779–0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden’s cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913–0.100). Conclusions: Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer’s disease

Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity

BackgroundEarly detection of β-amyloid (Aβ) accumulation, a major biomarker for Alzheimer’s disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) Aβ for predicting Aβ deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma Aβ is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma Aβ and CSF Aβ levels for Aβ PET positivity.MethodsWe recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed.ResultsWhen predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p &lt; 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added.ConclusionPlasma Aβ might be a useful predictor of Aβ deposition on PET status as much as CSF Aβ, particularly when considered with clinical information such as APOE genotype and cognitive stage

The global Alzheimer's Association round robin study on plasma amyloid β methods

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