bioRxivBioinformaticsPreprint
High-throughput plasma proteomic platforms: Insights from a multi-ethnic Asian cohort
Akash BahaiiD, He WangiD, Pritesh JainiD, Lucas D. WardiD, Oleksandr BoychenkoiD, Zhihao DingiD, Jun Frederiksen, Joanne Yuen Yie NgeowiD, Jimmy LeeiD, Elio RíboliiD, Jianjun LiuiD, Sebastian Maurer‐StrohiD, Enrico G. PetrettoiD, Ching‐Yu ChengiD, Bernett Teck Kwong LeeiD, Saumya Shekhar JamuariD, Nicolas BertiniD, Claire BellisiD, Max LamiD, Weiling ZhengiD, Xueling SimiD, Patrick TaniD, John Campbell ChambersiD, Nilanjana SadhuiD
Abstract
We compared three leading affinity-based and mass-spectrometry-based proteomic platforms (SomaScan11K, Olink Explore HT, Orbitrap Astral with Seer Proteograph [MS-Seer]) in a multi-ethnic Asian cohort, to inform biomarker discovery and functional genomic studies of global populations. We found limited overlap (1,740 proteins) across the three platforms, with modest correlations (0.34-0.10). SomaScan had lower missingness (<1%) and CV (<10%), compared to Olink (51%, 23%) and MS-Seer (12%, 19%). The new assays in Olink Explore HT (absent in Explore3072) primarily drove its higher missingness and CV. The number of phenotypic associations varied by trait, while the number of genetic associations (cis-pQTLs at P<5e-08) were similar for Olink and SomaScan. Protein levels differed between ethnicities, with SomaScan identifying more ethnicity-differentiated proteins than Olink (FDR<0.05). Finally, SomaScan ANML normalization attenuated biologically relevant associations in our study. These findings underscore the importance of platform evaluation and data normalization strategies for application in large-scale, diverse population cohorts.
- organism: human
- assay: proteomics
- research focus: benchmarking
- research focus: differential expression
- research focus: variant effect prediction
- approach: statistical model
- approach: benchmark study
- Citations
- 2
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