Purpose: Metabolic related diseases, including diabetes, obesity, and metabolic syndrome, have driven an increased demand for the sensitive measurement of biomarkers linked to these disease states. The expression levels of these biomarkers, produced in the gut, adipose tissue, and the brain, are altered frequently during disease and many can be detected in normal samples such as plasma. Here, we report the development of 34 metabolic assays targeting both traditional and emergent metabolic biomarkers for use in human and rodent samples. Through extensive screening for antibodies with selectivity and high affinity, several best-in-class assays have been developed for key markers such as GLP-1 and glucagon on the U-PLEX platform, which enables flexible multiplexing with a wide range of assays, as well as reduced sample volumes and assay times.
Methods: Unbiased pairwise screening for metabolic targets was performed on U-PLEX plates using biotinylated capture antibodies and SULFO-TAG™ labeled detection antibodies. Feasible antibody pairs were identified and developed using parameters such as dynamic range, sensitivity, specificity, sample recognition, and matrix tolerance. The consequent human and mouse metabolic assays were evaluated for cross-reactivity and interference from both species-specific assays (including 71 human assays and 51 mouse assays) and relevant metabolic analytes that share significant sequence homology. Spike recovery, dilution linearity, and sample recognition were also evaluated in relevant matrices including P800 plasma, EDTA plasma, and serum samples. The precision and accuracy of each assay was determined from at least 25 experimental runs using assay-specific controls. Assay performance was characterized to demonstrate correlation for use on both singleplex and multiplex formats.
Results: Calibration curves for 22 human and 12 mouse metabolic assays demonstrated 3-4 logs of dynamic range and lower limits of detection (LLOD) below 1 pg/mL. Key metabolic assays such as glucagon and GLP-1 featured superior LLODs of 0.13 pM and 0.59 pM, respectively. Control samples for each assay showed expected precision and accuracy, with intra-run %CVs less than 10%, inter-run %CVs less than 25%, and recoveries largely within 80-120% of target concentrations. Dilution linearity and spike recovery studies demonstrated matrix tolerance and accurate quantitation across tested matrices for most of the assays (typically between 80-120%). Non-specific binding between these assays and other biomarker assays tested was generally less than 0.5% (65 other human assays and 46 other mouse biomarker assays). Most of the 34 metabolic assays exhibited minimal cross-reactivity and interference from analytes that share significant sequence homology. All assays showed a good correlation between samples measured on U-PLEX multiplex and streptavidin plates with R2 values greater than 0.95 and slopes between 0.8 and 1.2.
Conclusion: Thirty-four human and rodent assays provide sensitive and reliable measurement of traditional and emergent biomarkers associated with diabetes, obesity, and metabolic syndrome. These metabolic assays can be used in singleplex and multiplex formats and include GLP-1 and glucagon assays with best-in-class sensitivity and specificity. Moreover, these assays can be combined with 65 human or 46 mouse assays in a species-specific manner, enabling researchers and drug developers to make simultaneous measurements of metabolic analytes combined with a variety of biomarkers relevant to other biological areas.
Christopher Shelburne– Gaithersburg, Maryland
David Cheo– Gaithersburg, Maryland
Pu Liu– Gaithersburg, Maryland
Jose Rodriguez-Nieves– Gaithersburg, Maryland
Jon Buhrman– Rockville, Maryland
Laure Moller– Rockville, Maryland
Svetlana Krepkiy– Gaithersburg, Maryland
Simon Kwong– Gaithersburg, Maryland
Sripriya Ranganathan– Gaithersburg, Maryland
Ilia Davydov– Gaithersburg, Maryland
David Stewart– Meso Scale Discovery, Rockville, Maryland
Jeff Debad– Rockville, Maryland
Jacob Wohlstadter– Rockville, Maryland
Chris Shelburne– Scientist, Meso Scale Discovery, Gaithersburg, MD