Clinical validation of the PrecivityAD2 blood test: A mass spectrometry-based test with algorithm combining %p-tau217 and Aß42/40 ratio to identify presence of brain amyloid.

BACKGROUND: With the availability of disease-modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment. METHODS: High-throughput, mass spectrometry-based assays were used to measure %p-tau217 and amyloid beta (Aß)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET. RESULTS: The area under the receiver operating characteristic curve (AUC-ROC) for %p-tau217 (0.94) was statistically significantly higher than that for p-tau217 concentration (0.91). The AUC-ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status. DISCUSSION: The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.

Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans.

STUDY OBJECTIVES: Given the established racial disparities in both sleep health and dementia risk for African American populations, we assess cross-sectional and longitudinal associations of self-report sleep duration (SRSD) and daytime sleepiness with plasma amyloid beta (Aß) and cognition in an African American (AA) cohort. METHODS: In a cognitively unimpaired sample drawn from the African Americans Fighting Alzheimer's in Midlife (AA-FAiM) study, data on SRSD, Epworth Sleepiness Scale, demographics, and cognitive performance were analyzed. Aß40, Aß42, and the Aß42/40 ratio were quantified from plasma samples. Cross-sectional analyses explored associations between baseline predictors and outcome measures. Linear mixed-effect regression models estimated associations of SRSD and daytime sleepiness with plasma Aß and cognitive performance levels and change over time. RESULTS: One hundred and forty-seven participants comprised the cross-sectional sample. Baseline age was 63.2 ±â€…8.51 years. 69.6% self-identified as female. SRSD was 6.4 ±â€…1.1 hours and 22.4% reported excessive daytime sleepiness. The longitudinal dataset included 57 participants. In fully adjusted models, neither SRSD nor daytime sleepiness is associated with cross-sectional or longitudinal Aß. Associations with level and trajectory of cognitive test performance varied by measure of sleep health. CONCLUSIONS: SRSD was below National Sleep Foundation recommendations and daytime sleepiness was prevalent in this cohort. In the absence of observed associations with plasma Aß, poorer self-reported sleep health broadly predicted poorer cognitive function but not accelerated decline. Future research is necessary to understand and address modifiable sleep mechanisms as they relate to cognitive aging in AA at disproportionate risk for dementia. CLINICAL TRIAL INFORMATION: Not applicable.

Assessment of a Plasma Amyloid Probability Score to Estimate Amyloid Positron Emission Tomography Findings Among Adults With Cognitive Impairment.

Importance: The diagnostic evaluation for Alzheimer disease may be improved by a blood-based diagnostic test identifying presence of brain amyloid plaque pathology. Objective: To determine the clinical performance associated with a diagnostic algorithm incorporating plasma amyloid-ß (Aß) 42:40 ratio, patient age, and apoE proteotype to identify brain amyloid status. Design, Setting, and Participants: This cohort study includes analysis from 2 independent cross-sectional cohort studies: the discovery cohort of the Plasma Test for Amyloidosis Risk Screening (PARIS) study, a prospective add-on to the Imaging Dementia-Evidence for Amyloid Scanning study, including 249 patients from 2018 to 2019, and MissionAD, a dataset of 437 biobanked patient samples obtained at screenings during 2016 to 2019. Data were analyzed from May to November 2020. Exposures: Amyloid detected in blood and by positron emission tomography (PET) imaging. Main Outcomes and Measures: The main outcome was the diagnostic performance of plasma Aß42:40 ratio, together with apoE proteotype and age, for identifying amyloid PET status, assessed by accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: All 686 participants (mean [SD] age 73.2 [6.3] years; 368 [53.6%] men; 378 participants [55.1%] with amyloid PET findings) had symptoms of mild cognitive impairment or mild dementia. The AUC of plasma Aß42:40 ratio for PARIS was 0.79 (95% CI, 0.73-0.85) and 0.86 (95% CI, 0.82-0.89) for MissionAD. Ratio cutoffs for Aß42:40 based on the Youden index were similar between cohorts (PARIS: 0.089; MissionAD: 0.092). A logistic regression model (LRM) incorporating Aß42:40 ratio, apoE proteotype, and age improved diagnostic performance within each cohort (PARIS: AUC, 0.86 [95% CI, 0.81-0.91]; MissionAD: AUC, 0.89 [95% CI, 0.86-0.92]), and overall accuracy was 78% (95% CI, 72%-83%) for PARIS and 83% (95% CI, 79%-86%) for MissionAD. The model developed on the prospectively collected samples from PARIS performed well on the MissionAD samples (AUC, 0.88 [95% CI, 0.84-0.91]; accuracy, 78% [95% CI, 74%-82%]). Training the LRM on combined cohorts yielded an AUC of 0.88 (95% CI, 0.85-0.91) and accuracy of 81% (95% CI, 78%-84%). The output of this LRM is the Amyloid Probability Score (APS). For clinical use, 2 APS cutoff values were established yielding 3 categories, with low, intermediate, and high likelihood of brain amyloid plaque pathology. Conclusions and Relevance: These findings suggest that this blood biomarker test could allow for distinguishing individuals with brain amyloid-positive PET findings from individuals with amyloid-negative PET findings and serve as an aid for Alzheimer disease diagnosis.

The PrecivityAD™ test: Accurate and reliable LC-MS/MS assays for quantifying plasma amyloid beta 40 and 42 and apolipoprotein E proteotype for the assessment of brain amyloidosis.

BACKGROUND: There is an unmet need for an accessible, less invasive, cost-effective method to facilitate clinical trial enrollment and aid in clinical Alzheimer's disease (AD) diagnosis. APOE genotype affects the clearance and deposition of amyloid-beta (Aß) with APOE4 carriers having increased risk while APOE2 alleles appear to be protective. Lower plasma Aß42/40 correlates with brain amyloidosis. In response, C2N has developed the PrecivityAD™ test; plasma LC-MS/MS assays for Aß isoform quantitation and qualitative APOE isoform-specific proteotyping. METHODS: In accord with CLIA standards, we developed and validated assay performance: precision, accuracy, linearity, limit of detection (LoD), interferences. RESULTS: Within-day precision varied from 1.5-3.0% (Aß40) and 2.5-8.4% (Aß42). Total (within-lab) variability was 2.7-7.7% (Aß40) and 3.1-9.5% (Aß42). Aß40 quantitation was linear from 10 to 1780 pg/mL; Aß42 was linear from 2 to 254 pg/mL. LoD was 11 and 2 pg/mL for Aß40 and Aß42, respectively. APOE proteotypes were 100% concordant with genotype, while LoD (fM) was much lower than APOE concentrations observed in plasma (mM). CONCLUSIONS: The PrecivityAD™ assays are precise, accurate, sensitive, and linear over a wide analytical range, free from significant interferences, and suitable for use in the clinical laboratory.

A blood-based diagnostic test incorporating plasma Aß42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis.

BACKGROUND: The development of blood-based biomarker tests that are accurate and robust for Alzheimer's disease (AD) pathology have the potential to aid clinical diagnosis and facilitate enrollment in AD drug trials. We developed a high-resolution mass spectrometry (MS)-based test that quantifies plasma Aß42 and Aß40 concentrations and identifies the ApoE proteotype. We evaluated robustness, clinical performance, and commercial viability of this MS biomarker assay for distinguishing brain amyloid status. METHODS: We used the novel MS assay to analyze 414 plasma samples that were collected, processed, and stored using site-specific protocols, from six independent US cohorts. We used receiver operating characteristic curve (ROC) analyses to assess assay performance and accuracy for predicting amyloid status (positive, negative, and standard uptake value ratio; SUVR). After plasma analysis, sites shared brain amyloid status, defined using diverse, site-specific methods and cutoff values; amyloid PET imaging using various tracers or CSF Aß42/40 ratio. RESULTS: Plasma Aß42/40 ratio was significantly (p < 0.001) lower in the amyloid positive vs. negative participants in each cohort. The area under the ROC curve (AUC-ROC) was 0.81 (95% CI = 0.77-0.85) and the percent agreement between plasma Aß42/40 and amyloid positivity was 75% at the optimal (Youden index) cutoff value. The AUC-ROC (0.86; 95% CI = 0.82-0.90) and accuracy (81%) for the plasma Aß42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87-0.93) and accuracy (86%) improved further when Aß42/40, ApoE4 copy number and participant age were included in the model. CONCLUSIONS: This mass spectrometry-based plasma biomarker test: has strong diagnostic performance; can accurately distinguish brain amyloid positive from amyloid negative individuals; may aid in the diagnostic evaluation process for Alzheimer's disease; and may enhance the efficiency of enrolling participants into Alzheimer's disease drug trials.