Measurement and quality control issues in multiplex protein assays: a case study

Abstract

Background: Multiplex arrays are increasingly used for measuring protein biomarkers. Advantages of this approach include specimen conservation, limited sample handling, and decreased time and cost, but the challenges of optimizing assay format for each protein, selecting common dilution factors, and establishing robust quality control algorithms are substantial. Here, we use measurements of 15 protein biomarkers from a large study to illustrate processing, analytic, and quality control issues with multiplexed immunoassays.

Methods: We contracted with ThermoScientific for duplicate measurements of 15 proteins in 2322 participants from a community-based cohort, a plasma control, and recombinant protein controls using 2 custom planar microarrays with 6 (panel A) or 9 (panel B) capture antibodies printed in each well. We selected constituent analytes in each panel based on endogenous concentrations and assay availability. Protocols were standardized for sample processing, storage, and freeze-thaw exposures. We analyzed data for effects of deviations from processing protocols, precision, and bias.

Results: Measurements were within reportable ranges for each of the assays; however, concentrations for 7 of the 15 proteins were not centered on the dose-response curves. An additional freeze-thaw cycle and erroneous sample dilution for a subset of samples produced significantly different results. Measurements with large differences between duplicates were seen to cluster by analyte, plate, and participant. Conventional univariate quality control algorithms rejected many plates. Plate-specific medians of cohort and plasma control data significantly covaried, an observation important for development of alternative quality control algorithms.

Conclusions: Multiplex measurements present difficult challenges that require further analytical and statistical developments.

Fig. 1. Representative dose–response curves

Vertical dotted lines demark the 5th and 95th percentiles of cohort data. Arrows, squares, triangles, and diamonds depict the median values of the plasma control, recombinant protein quality control 1 (QC1), recombinant protein QC2, and recombinant protein QC3, respectively.

Fig. 2. (A), (B), and (C) illustrate the covariance of plate-specific population-normalized cohort means and plasma control means across 66 microplates for 3 representative proteins