Development and validation of a multiplex electrochemiluminescence immunoassay to evaluate dry eye disease in rat tear fluids

Abstract

Dry eye disease (DED) is a challenge in ophthalmology. Rat models represent valuable tools to study the pathophysiology and to develop novel treatments. A major challenge in DED research is detecting multiple biomarkers in a low tear volume sample. Multiplex immunoassays for DED rat research are missing. We have developed a multiplex electrochemiluminescence immunoassay (ECLIA) to detect three biomarkers for DED: MMP-9, IL-17 and ICAM-1. Tears, used as matrix, were collected from six healthy Wistar rats. Assays were run based on the U-Plex Meso Scale Diagnostics (MSD) platform, by two independent operators according to the EMA guideline on bioanalytical method validation. Linear mixed, regression models were fit to perform the statistical analysis on the range of concentrations for the chosen analytes. During optimization, it has observed that incubation time, temperature and agitation affected the robustness of the protocol. ECLIA optimum conditions include the use of antibodies at 0.5 µg/ml concentration and 1 h incubation at room temperature with shaking. Precision met the acceptance criteria in the chosen range: 1062-133 pg/ml for ICAM-1, 275-34.4 pg/ml for IL-17, 1750-219 pg/ml for MMP-9. Accuracy and linearity were acceptable for a broader range. This is the first report of a validated ECLIA that allows measurements of three relevant DED biomarkers in rat tear fluids.

Figure 1

Graph of the data after logarithmic transformation (natural base) versus target concentration after logarithmic transformation (natural base) per analyte, operator, day and plate. N = 6 samples run in duplicates.

Figure 2

Precision—evolution of the repeatability (residual) and intermediate precision (total) CVs per analyte per concentration level. Target concentrations are expressed in pg/ml. N = 6 samples run in duplicates.

Figure 3

Trueness: evolution of recoveries (%) across concentration levels per analyte together with their corresponding 95% confidence intervals. Target concentrations are expressed in pg/ml. N = 6 samples run in duplicates.

Figure 4

Linearity: regression graph and raw data per analyte. N = 6 samples run in duplicates.

Figure 5

Results of the robustness experiments when changing the time between 30 and 90 min, the temperature between 4 and 37 °C and with or without agitation for the three analytes: ICAM-1, IL-17 and MMP-9. N = 6 samples run in duplicates.

Figure 6

ICAM-1—least squares means of the effect of temperature and time on the log transformed results of ICAM-1 showing the interaction between these two factors. Time values are expressed in minutes. N = 6 samples run in duplicates.

Figure 7

MMP-9—least squares means of the effect of time (minutes) on the log transformed results of MMP-9 showing the time factor N = 6 samples run in duplicates.

Figure 8

MMP-9—least squares means of the effect of time (minutes) and agitation on the log transformed results of MMP9 showing the interaction between these two factors. N = 6 samples run in duplicates.

Figure 9

Structure of the immunoassay: a biotinylated capture antibody was coated on the streptavidin plate and after binding of the specific analyte, a primary detection antibody was added and for completion of the immunocomplex, a secondary detection antibody labeled with SULFO-TAG was used to produce the light signal.

Figure 10

Experimental design of all assays runs. It is divided into two different main procedures for checking precision, accuracy and linearity parameters. They were used 6 samples from 6 rats and run in duplicates. Two independent operators run 2 assays each in 2 different days. The conditions were: 1 h of incubation at room temperature with the presence of shaking. Robustness assays were run by one single operator in two different days. In the figure they are listed all the combinations for testing incubation time, incubation temperature and the presence or absence of shaking.