The latest breakthrough in biomarker discovery is the proximity extension assay (PEA) technology developed by Olink (Sweden). This antibody-based technology allows for relative quantification of 1165 human protein biomarkers in plasma and other biological samples. Helmholtz Center Munich hosts the first platform certified for Olink technology in Germany. Upon integration of this platform in our proteomics facility, we aim to correlate PEA-based profiling with mass spectrometry-based measurements (MS) in human plasma.
We used 370 plasma samples from the Cooperative Health Research in the Region of Augsburg (KORA) study, a population-based longitudinal study. These samples are analyzed by PEA (10 different Olink panels), data-independent acquisition (DIA)-MS, targeted SRM-MS, and SOMAscanAssay V3.2 (SomaLogic).
We have accumulated a DIA-MS dataset from 370 non-depleted human plasma samples quantified by matching to a comprehensive in-house spectral library covering 1924 proteins (based on 16 918 peptides). When comparing the proteins quantified by DIA-MS (direct identification above threshold in >75% of samples, 1% protein FDR filtered) to the complete set of markers measured by PEA (valid data in >95% of samples), we observe an overlap of 30 proteins. As expected, the overlapping proteins are mainly contained in Olink panels enriched for high abundant proteins. We find convincing correlations between PEA and DIA-MS in the overlapping proteins. Further, correlation to overlapping SRM-MS measurements are excellent, exemplified by MBL2, which correlates at 0.87 and 0.82 (Spearman) when comparing PEA to DIA-MS and SRM-MS, respectively. Additional correlations between technologies, including SomaLogic will be presented. Further, correlations between genetics and protein abundances (pWAS) measured by the different technologies will be discussed.
PEA provides a highly complementary technology to mass spectrometry-based proteomics, overcoming the notorious challenge of low identification and quantification rates in plasma samples. The high correlation of proteins detected by both technologies mutually confirms the methods for biomarker discovery.