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<p>The circulating blood proteome holds immense potential for biomarker discovery and understanding disease mechanisms. Notable advances in mass spectrometry and affinity-based technologies have been made, but data integration across studies and platforms is hindered by the absence of unified analytical standards. This limitation impedes comprehensive exploration of human biology across diverse phenotypes and cohorts as well as the translation of findings into clinical applications. The disparities between datasets, stemming from a combination of factors related to differences in sample collection, pre-analytical handling, measurement methods and instrumentation, further complicate data integration. In this Perspective, we outline key challenges in blood-based proteomics and propose actionable strategies. Central to our recommendations are high-quality, technology-agnostic reference samples, which can bridge disparate datasets and enable robust cross-study comparisons. By fostering interconnected investigations across proteomic technologies, blood sample collections, clinical phenotypes and different populations, these references will accelerate the field and its translation.</p>

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A standardized framework for circulating blood proteomics

  • 期刊论文

  • 发表日期：

    2025年9月23日

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  • Xue Cai,
  • Philipp E. Geyer,
  • Yasset Perez-Riverol,
  • Gilbert S. Omenn,
  • Lianhua Dong,
  • Robert Winkler,
  • Sara Ahadi,
  • Philip Lössl,
  • Xiaobo Yu,
  • Cheng Chang,
  • Markus Ralser,
  • Connie R. Jimenez,
  • Yang Zhao,
  • Yu-Ju Chen,
  • Terence C. W. Poon,
  • Nicolai Bache,
  • Leming Shi,
  • Xinhua Dai,
  • Ziyue Wang,
  • Yi Zhu,
  • Xiang Fang,
  • Jochen M. Schwenk,
  • Jennifer E. Van Eyk,
  • Uwe Völker,
  • Tiannan Guo

摘要

The circulating blood proteome holds immense potential for biomarker discovery and understanding disease mechanisms. Notable advances in mass spectrometry and affinity-based technologies have been made, but data integration across studies and platforms is hindered by the absence of unified analytical standards. This limitation impedes comprehensive exploration of human biology across diverse phenotypes and cohorts as well as the translation of findings into clinical applications. The disparities between datasets, stemming from a combination of factors related to differences in sample collection, pre-analytical handling, measurement methods and instrumentation, further complicate data integration. In this Perspective, we outline key challenges in blood-based proteomics and propose actionable strategies. Central to our recommendations are high-quality, technology-agnostic reference samples, which can bridge disparate datasets and enable robust cross-study comparisons. By fostering interconnected investigations across proteomic technologies, blood sample collections, clinical phenotypes and different populations, these references will accelerate the field and its translation.