| Literature DB >> 32386347 |
Laura M Raffield1, Hong Dang2, Katherine A Pratte3, Sean Jacobson3, Lucas A Gillenwater3, Elizabeth Ampleford4, Igor Barjaktarevic5, Patricia Basta6, Clary B Clish7, Alejandro P Comellas8, Elaine Cornell9, Jeffrey L Curtis10,11, Claire Doerschuk2, Peter Durda9, Claire Emson12, Christine M Freeman10,11, Xiuqing Guo13, Annette T Hastie4, Gregory A Hawkins14, Julio Herrera15, W Craig Johnson16, Wassim W Labaki10, Yongmei Liu17, Brett Masters15, Michael Miller15, Victor E Ortega4, George Papanicolaou18, Stephen Peters4, Kent D Taylor13, Stephen S Rich19, Jerome I Rotter13, Paul Auer20, Alex P Reiner21,22, Russell P Tracy9,23, Debby Ngo24, Robert E Gerszten25, Wanda K O'Neal2, Russell P Bowler3.
Abstract
Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.Entities:
Keywords: antibody microarrays; biomarkers; multiplexings
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Year: 2020 PMID: 32386347 PMCID: PMC7425176 DOI: 10.1002/pmic.201900278
Source DB: PubMed Journal: Proteomics ISSN: 1615-9853 Impact factor: 3.984