Assessment of Variability in the SOMAscan Assay

• Published in: Scientific reports Vol. 7; no. 1; pp. 14248 - 13
• Main Authors: Candia, Julián, Cheung, Foo, Kotliarov, Yuri, Fantoni, Giovanna, Sellers, Brian, Griesman, Trevor, Huang, Jinghe, Stuccio, Sarah, Zingone, Adriana, Ryan, Bríd M., Tsang, John S., Biancotto, Angélique
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.10.2017; Nature Publishing Group
• Subjects: 631/114; 631/337/475; Adult; Aptamers; Aptamers, Nucleotide - metabolism; Blood Proteins - metabolism; Calibration; Clinical trials; Coefficient of variation; Female; Humanities and Social Sciences; Humans; Immunology; Infectious diseases; Information sharing; Laboratories; Male; Mathematical models; Meta-analysis; Middle Aged; multidisciplinary; Plasma; Proteins; Proteomics; Proteomics - methods; Quality control; Reagents; Reproducibility; Reproducibility of Results; Science; Science (multidisciplinary); Statistical analysis; Statistical models
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-14755-5

SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals.