Stability and reproducibility of proteomic profiles in epidemiological studies: comparing the Olink and SOMAscan platforms

Danielle E. Haslam, Jun Li, Simon T. Dillon, Xuesong Gu, Yin Cao, Oana A. Zeleznik, Naoko Sasamoto, Xuehong Zhang, A. Heather Eliassen, Liming Liang, Meir J. Stampfer, Samia Mora, Zsu Zsu Chen, Kathryn L. Terry, Robert E. Gerszten, Frank B. Hu, Andrew T. Chan, Towia A. Libermann, Shilpa N. Bhupathiraju

Research output: Contribution to journalArticlepeer-review

Abstract

Limited data exist on the performance of high-throughput proteomics profiling in epidemiological settings, including the impact of specimen collection and within-person variability over time. Thus, the Olink (972 proteins) and SOMAscan7Kv4.1 (7322 proteoforms of 6596 proteins) assays were utilized to measure protein concentrations in archived plasma samples from the Nurses’ Health Studies and Health Professionals Follow-Up Study. Spearman's correlation coefficients (r) and intraclass correlation coefficients (ICCs) were used to assess agreement between (1) 42 triplicate samples processed immediately, 24-h or 48-h after blood collection from 14 participants; and (2) 80 plasma samples from 40 participants collected 1-year apart. When comparing samples processed immediately, 24-h, and 48-h later, 55% of assays had an ICC/r ≥ 0.75 and 87% had an ICC/r ≥ 0.40 in Olink compared to 44% with an ICC/r ≥ 0.75 and 72% with an ICC/r ≥ 0.40 in SOMAscan7K. For both platforms, >90% of the assays were stable (ICC/r ≥ 0.40) in samples collected 1-year apart. Among 817 proteins measured with both platforms, Spearman's correlations were high (r > 0.75) for 14.7% and poor (r < 0.40) for 44.8% of proteins. High-throughput proteomics profiling demonstrated reproducibility in archived plasma samples and stability after delayed processing in epidemiological studies, yet correlations between proteins measured with the Olink and SOMAscan7K platforms were highly variable.

Original languageEnglish
Article number2100170
JournalProteomics
Volume22
Issue number13-14
DOIs
StatePublished - Jul 2022

Keywords

  • Aptamers
  • biomarkers
  • epidemiology studies
  • laboratory methods and tools
  • multiplexing
  • systems biology

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