Comparison of Proteomic Assessment Methods in Multiple Cohort Studies

蛋白质组学 定量蛋白质组学 队列 相关性 医学 计算生物学 多路复用 慢性阻塞性肺病 蛋白质组 斯皮尔曼秩相关系数 生物信息学 肿瘤科 内科学 生物 统计 数学 遗传学 几何学 基因
作者
Laura M. Raffield,Hong Dang,Katherine Pratte,Sean Jacobson,Lucas A. Gillenwater,Elizabeth Ampleford,Igor Barjaktarević,Patricia V. Basta,Clary B. Clish,Alejandro P. Comellas,Elaine Cornell,Jeffrey L. Curtis,Claire M. Doerschuk,Peter Durda,Claire Emson,Christine M. Freeman,Xiuqing Guo,Annette T. Hastie,Gregory A. Hawkins,Julio E. Herrera
出处
期刊:Proteomics [Wiley]
卷期号:20 (12) 被引量:148
标识
DOI:10.1002/pmic.201900278
摘要

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.
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