= Emerging. More than 5 years before clinical availability. (29.54%)
= Expected to be clinically available in 1 to 4 years. (38.82%)
= Clinically available now. (31.65%)
MSACL 2020 US : Boslett

MSACL 2020 US Abstract

Topic: Proteomics

Podium Presentation in Room 5 on Wednesday at 16:15 (Chair: Tim Collier)

Characterization of Pre-analytical Variables and their Influence on High-performance Plasma Amyloid-β Biomarkers for Alzheimer’s Disease

James Boslett (Presenter)
University of Pittsburgh

Presenter Bio(s): Dr. Boslett did his graduate training in a cardiovascular physiology lab at the Ohio State University before entering the field of mass spectrometry as a post-doc in Dr. Nathan Yates' lab at the University of Pittsburgh. As a post-doc, Dr. Boslett has trained in both discovery and targeted proteomics assays. Recently, he has focused on the development of plasma amyloid-beta assays using targeted proteomics.

Authors: James Boslett (1), Xuemei Zeng (2), Mary Ganguli (3), Dan Normolle (4), Oscar Lopez (5), Nathan Yates (1)
(1) Department of Cell Biology, School of Medicine, University of Pittsburgh (2) Biomedical Mass Spectrometry Center, University of Pittsburgh (3) Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh (4) Department of Biostatistics, School of Public Health, University of Pittsburgh (5) Department of Neurology, School of Medicine, University of Pittsburgh

Abstract

Introduction: The enhancement of biomarker measurements for Alzheimer’s Disease (AD) is critical for accurate and timely diagnosis of the disease. Currently, positron-emission tomography (PET) imaging and CSF amyloid-beta (Ab) are the gold standard tests for assessing brain amyloid plaque burden. Recently, Nakamura et. al (2018) demonstrated that immunoprecipitation mass spectrometry (IP-MS) measurements of plasma Ab biomarkers show potential clinical utility for predicting brain amyloid-β plaque burden.

We have implemented a robust plasma Ab assay on a low cost benchtop mass spectrometer that is routinely used to identify microorganisms in clinical microbiology labs. In collaboration with the Alzheimer’s Disease Research Center (ADRC) at the University of Pittsburgh, we have analyzed archived samples and evaluated the performance of plasma Ab biomarkers against PET using 11C-labelled Pittsburgh Compound-B (PIB).

Here we present a series of experiments that examine pre-analytical variables including sample collection, handling, and storage. These pre-validations studies were conducted as a first step toward understanding the influence of sample quality on plasma Ab biomarker measurements.

Objectives: To characterize the pre-analytical error introduced by common plasma collection, storage, and handling procedures.

Methods: All plasma Ab biomarkers were measured from 250 uL aliquots of EDTA plasma. The immunoprecipitation procedure was adapted from Nakamura et. al (2018) with minor modifications. Mass spectra were recorded with a Bruker Daltonics Microflex LT in linear positive ion mode. Freeze/thaw effects were evaluated using aliquots of pooled EDTA plasma that were subjected to 1, 2, 3, or 5 freeze-thaw cycles. Intraday and interday variability was evaluated by analyzing three sets of 20 technical replicates on separate days.

Results: Overall, repeat analysis of replicate samples yielded a robust measure of individual Ab peptides with a coefficient of variation (CV) below 10%. Analysis of individual peptide variation demonstrate that both day-to-day variation and freeze-thaw cycles are small but statistically significant sources of variation that contribute to less than 5% of the total variation. The use of the composite biomarker instead of absolute peak areas further minimizes the impact of these pre-analytical variables.

Conclusion: A robust plasma Ab assay has been implemented on a low cost benchtop mass spectrometer. Analysis of archived plasma samples have shown encouraging clinical performance compared to PET imaging with minimal variation due to sample collection, handling or storage procedures.


Financial Disclosure

DescriptionY/NSource
GrantsnoUniversity of Pittsburgh
Salaryno
Board Memberno
Stockno
Expensesno
IP Royaltyno

Planning to mention or discuss specific products or technology of the company(ies) listed above:

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