A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis

Abstract

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 Aβ42 and Aβ40 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 Aβ42/40 ratio.

Results: Plasma Aβ42/40 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 Aβ42/40 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 Aβ42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87-0.93) and accuracy (86%) improved further when Aβ42/40, 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.

Keywords: Alzheimer’s disease; Neurodegeneration, mass spectrometry; Plasma biomarkers.

Conflict of interest statement

All authors are full time employees or advisors to C2N Diagnostics, receive equity or equity options, and contributed to the development of the plasma Aβ42, Aβ40, ApoE analytical platforms and the amyloid probability prediction models. DMH is as an inventor on a patent licensed by Washington University to C2N Diagnostics on the therapeutic use of anti-tau antibodies. C2N Diagnostics has licensed certain anti-tau antibodies to AbbVie for therapeutic development. DMH and RJB co-founded and are on the scientific advisory board of C2N Diagnostics. DMH is on the scientific advisory board of Denali and consults for Genentech, Merck, and Cajal Neuroscience. RJB receives personal fees from Amgen, AC Immune, Eisai, Hoffman-LaRoche, and Janssen Pharmaceuticals outside the submitted work. RJB receives income based on a blood plasma assay licensed by Washington University to C2N Diagnostics and has a patent (“Plasma Based Methods for Determining A-Beta Amyloidosis”) pending with Washington University.

Figures

Fig. 1

Diagnostic Performance Plots, Metrics, and Prediction Parameters for Plasma Biomarkers Measured Using LC-MS/MS. a Plasma Aβ42/40 concentration ratios were lower in amyloid positive than negative participants (n = 414). Scatter-Box-Whisker plot of plasma Aβ42/40 for participants classified as brain amyloid negative or positive. Optimal plasma Aβ42/40 cutoff value (0.0975) = dashed horizontal line; Median = dark horizontal lines; 25th to 75th quartiles = Box; 95% Confidence Interval = Whisker. b In each cohort, plasma Aβ42/40 ratios were consistently lower in amyloid positive than negative participants. Plasma Aβ42/40 ratios separated by brain amyloid status (Blue = Negative; Red = Positive) for each cohort. Dashed horizontal line is the optimal plasma Aβ42/40 cutoff value (0.0975) based on ratio alone (same as dashed line in a). c Amyloid probability scores were higher in amyloid positive than negative participants. A logistic regression model using plasma Aβ42/40 and cohort to generate a model probability score that predicted brain amyloid status. Scatter-Box-Whisker plots of individual probability scores (0.0–1.0) separated by amyloid status. Optimal model-derived probability score that differentiated amyloid positive from negative (0.42) = dashed horizontal line. d Amyloid probability scores derived from a logistic regression model that used plasma Aβ42/40, number of ApoE4 alleles, age and cohort to predict brain amyloid status. Scatter-Box-Whisker plots of individual amyloid probability scores (0.0–1.0) separated by amyloid status. e Receiver Operating Characteristic curves (ROC) plotted using: participants’ plasma Aβ42/40 ratio, ApoE4, age, and cohort (gold plot; AUC-ROC = 0.90 and 95% CI shown in insert); plasma Aβ42/40 and cohort (blue plot; AUC-ROC = 0.86); and only plasma Aβ42/40 (red plot; AUC-ROC = 0.81). For comparison, the insert also shows AUC-ROC and 95% CI for ApoE4 and age (0.82), and ApoE4, age and cohort (0.84). f Four-quadrant plot illustrating the relationship between quantitative PiB SUVR values and plasma Aβ42/40 ratios and cutoff value (dashed vertical line = 0.0975) for two cohorts (n = 103). Cohort 3 used PiB SUVR cutoff = 1.47 (Red (x) and dashed horizontal line), cohort 6 used 1.42 (Blue filled dots (•) and dashed horizontal line). Three false negative plasma Aβ42/40 results in the upper right quadrant. Twenty false positive plasma Aβ42/40 results in the lower left quadrant that may represent participants with elevated risk for converting to amyloid PET positive in the future