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Comparison of Proteomic Assessment Methods in Multiple Cohort Studies.
Proteomics ( IF 3.4 ) Pub Date : 2020-05-09 , DOI: 10.1002/pmic.201900278
Laura M Raffield 1 , Hong Dang 2 , Katherine A Pratte 3 , Sean Jacobson 3 , Lucas A Gillenwater 3 , Elizabeth Ampleford 4 , Igor Barjaktarevic 5 , Patricia Basta 6 , Clary B Clish 7 , Alejandro P Comellas 8 , Elaine Cornell 9 , Jeffrey L Curtis 10, 11 , Claire Doerschuk 2 , Peter Durda 9 , Claire Emson 12 , Christine M Freeman 10, 11 , Xiuqing Guo 13 , Annette T Hastie 4 , Gregory A Hawkins 14 , Julio Herrera 15 , W Craig Johnson 16 , Wassim W Labaki 10 , Yongmei Liu 17 , Brett Masters 15 , Michael Miller 15 , Victor E Ortega 4 , George Papanicolaou 18 , Stephen Peters 4 , Kent D Taylor 13 , Stephen S Rich 19 , Jerome I Rotter 13 , Paul Auer 20 , Alex P Reiner 21, 22 , Russell P Tracy 9, 23 , Debby Ngo 24 , Robert E Gerszten 25 , Wanda K O'Neal 2 , Russell P Bowler 3 , 1
Affiliation  

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.

中文翻译:


多个队列研究中蛋白质组学评估方法的比较。



新型蛋白质组学平台,例如基于适配体的 SOMAscan 平台,可以有效且经济高效地量化大量蛋白质,并且正在迅速普及。然而,与传统免疫测定的比较仍未得到充分探索,使研究人员不确定何时适合进行交叉测定比较。 SOMAscan 探索了免疫测定结果与相对蛋白质定量的相关性。对于在两个慢性阻塞性肺疾病 (COPD) 队列、COPD 研究 (SPIROMICS) 和 COPDGene 中评估的 63 种蛋白质,使用多种基于规则的医学多重免疫分析和 SOMAscan,Spearman 相关系数范围为 -0.13 至 0.97,中位相关系数约为 0.5,并且各个队列的结果一致。在基于人群的动脉粥样硬化多种族研究中的免疫测定以及 COPDGene 和 SPIROMICS 中的其他测定中观察到类似的范围。基于抗体的 Olink 平台和 SOMAscan 在一小群心肌梗塞患者中的相对定量比较也显示出广泛的相关范围。最后,整合顺式pQTL 数据、质谱适体确认和其他公开可用的数据,以评估与观察到的相关性的关系。蛋白质组学测定之间的相关性表现出广泛的范围,在比较和荟萃分析跨测定和研究的蛋白质组学数据时应仔细考虑。
更新日期:2020-05-09
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