Heylen Dries, Pusparum Murih, Kuliesius Jurgis, Wilson Jim, Park Young-Chan, Jamiołkowski Jacek, D'Onofrio Valentino, Valkenborg Dirk, Aerts Jan, Ertaylan Gökhan, Hooyberghs Jef
Data Science Institute, Theory Lab, Hasselt University, 3590 Diepenbeek, Belgium.
Flemish Institute for Technological Research (VITO), Mol, Belgium.
Brief Bioinform. 2024 Nov 22;26(1). doi: 10.1093/bib/bbae657.
Proteomics stands as the crucial link between genomics and human diseases. Quantitative proteomics provides detailed insights into protein levels, enabling differentiation between distinct phenotypes. OLINK, a biotechnology company from Uppsala, Sweden, offers a targeted, affinity-based protein measurement method called Target 96, which has become prominent in the field of proteomics. The SCALLOP consortium, for instance, contains data from over 70.000 individuals across 45 independent cohort studies, all sampled by OLINK. However, when independent cohorts want to collaborate and quantitatively compare their target 96 protein values, it is currently advised to include 'identical biological bridging' samples in each sampling run to perform a reference sample normalization, correcting technical variations across measurements. Such a 'biological bridging sample' approach requires each of the involved cohorts to resend their biological bridging samples to OLINK to run them all together, which is logistically challenging, costly and time-consuming. Hence alternatives are searched and an evaluation of the current state of the art exposes the need for a more robust method that allows all OLINK Target 96 studies to compare proteomics data accurately and cost-efficiently. To meet these goals we developed the Synthetic Plasma Pool Cohort Correction, the 'SPOC correction' approach, based on the use of an OLINK-composed synthetic plasma sample. The method can easily be implemented in a federated data-sharing context which is illustrated on a sepsis use case.
蛋白质组学是基因组学与人类疾病之间的关键纽带。定量蛋白质组学能深入了解蛋白质水平，从而区分不同的表型。瑞典乌普萨拉的生物技术公司OLINK提供了一种基于亲和的靶向蛋白质测量方法，称为Target 96，该方法在蛋白质组学领域已崭露头角。例如，SCALLOP联盟包含来自45项独立队列研究的7万多名个体的数据，所有样本均由OLINK采集。然而，当独立队列想要合作并定量比较其Target 96蛋白质值时，目前建议在每次采样过程中纳入“相同的生物桥接”样本，以进行参考样本归一化，校正测量中的技术差异。这种“生物桥接样本”方法要求每个参与的队列将其生物桥接样本重新发送给OLINK，以便一起进行检测，这在后勤方面具有挑战性，成本高昂且耗时。因此，人们在寻找替代方法，对当前技术水平的评估表明，需要一种更强大的方法，使所有OLINK Target 96研究能够准确且经济高效地比较蛋白质组学数据。为了实现这些目标，我们基于使用OLINK合成的血浆样本，开发了合成血浆池队列校正方法，即“SPOC校正”方法。该方法可以轻松地在联合数据共享环境中实施，脓毒症用例对此进行了说明。
