Biases and consistency of different assay methods for neurological biomarkers using Quanterix single-molecule-array technology: A comparative study of the secondary analysis method

Breakthrough technologies such as the Single molecule array (Simoa) technology developed by Quanterix provide higher sensitivity, enabling measurement of central nervous system-abundant proteins in blood. Neurofilament light chain (NfL) and glial fibrillary protein (GFAP) are two proteins that have attracted considerable attention as biomarkers for many neurological conditions. Due to their performance and utility, these biomarkers are available in different Quanterix assays, including singleplex and multiplex assay setups. Limited research has been conducted to evaluate how modifications in assay formulations may impact overall analytical performance and comparability. In this study, we established reference intervals (RI) for plasma NfL and GFAP measured in normative samples from the Canadian Health Measures Survey (CHMS) using the Quanterix Neurology 4-Plex E (N4PE) Advantage. Seven independent comparisons were conducted, each using a total of 80 plasma samples from the CHMS. These samples were divided ( n = 40 each) based on the two N4PE lots previously used to generate RIs. The following Quanterix assay formulations were evaluated in comparison with the N4PE anchor assay: NfL Advantage PLUS (NfL+), GFAP Advantage PLUS (GFAP+), Neurology 2-Plex B Advantage (N2PB), Neurology 2-Plex B Advantage PLUS (N2PB+), Neurology 4-Plex B Advantage (N4PB), Neurology 4-Plex D PLUS (N4PD+), and Neurology 4-Plex E PLUS (N4PE+). Plasma biomarker concentrations were measured using the Quanterix Simoa HD-X analyzer, and the detection was performed as per the manufacturer's specifications. The bias between assays was detected using Spearman correlation analysis and Bland-Altman analysis. Both NfL and GFAP concentrations were tightly correlated between assay formulations with rho > 0.9 and a P -value < 0.0001 for all assay crosses. However, the bias between formulations ranged from 0.5 % to 42.1 %, indicating that data correction may be required to harmonize data generated from different assay formulations. In summary, this study emphasizes the importance of data correction when using different assay methods to ensure data comparability across studies. Additionally, the study findings support the applicability of RIs and suggest that when using RIs, corrections should be made based on the assay-specific bias. Future studies should further expand the sample range, particularly in high-concentration conditions such as acute neurological injury, to comprehensively evaluate the performance of different assay formulations.