- June 24, 2025
Topic/Product:
AQ, Immunology, Inflammation
Disease Area:
Sample Type:
Abstract
Highly multiplexed profiling of biomarkers associated with inflammatory, autoimmune and infectious diseases can aid in identification of new diagnostic and therapeutic strategies. Previously, we developed the NULISAseq Inflammation Panel 250-plex assay on the Argo HT platform for relative quantitation of key cytokines, chemokines, and proteins involved in inflammation and immune response.
Absolute quantification (AQ) of analytes in mass concentration units (pg/mL) can be valuable in translational and clinical settings for biomarker validation, disease stratification and monitoring of treatment responses. However, conventional immunoassay quantification involves constructing multi-point calibration curves for each analyte, reducing available wells on the assay plate for samples and adding costs. To address this challenge, we developed a novel approach requiring a single calibrator sample to derive absolute concentrations of samples using a proprietary algorithm.
Here, we report analytical characterization of the Inflammation Panel AQ assay, enabling AQ of 157 analytes simultaneously with minimal sample input and high throughput. Precision and reproducibility assessments demonstrated 5.97% intra-plate and 3.09% inter-plate median CV across 157 AQ targets. With variance component analysis, total median CV was 8.35% across different reagent lots and instruments. Limits of quantification determination demonstrated a wide dynamic range with 9 logs across all targets and upto 6 logs for individual targets. Additionally, >90% of targets showed >50% detectability and >50% quantifiability in a cohort of healthy and diseased plasma (n=119) and serum (n=53) samples.
In summary, the NULISAseq Inflammation Panel AQ provides absolute quantification of >150 analytes to enable discovery of key targets for immunology research.
Authors & Affiliations
Xiao-Jun Ma1, Chan Ho Park1, Alissa O’ Connor1, Tianyang Evan Bai1, Cheng Xie1, Joanne Beer1, Natalia Sherina2, Alexander Van Sant Tsoi2, Dionysis Nikolopoulos2, Niyati Jhaveri1, Dwight Kuo1, Bingqing Zhang1, Yiyuan Yin1, Ioannis Paradis2, Yuling Luo1
1Alamar Biosciences Inc., Fremont, California, USA; 2Karolinska Institute, Stockholm, Sweden
