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Proteomic Profiling With Two Platforms Provides Complementary Gene, Protein, Phenotype Links

NEW YORK — A team led by researchers at the University of Cambridge's MRC Epidemiology Unit and the Berlin Institute of Health at Charité has combined SomaLogic's SomaScan assay and Olink's antibody-based proteomic platform to investigate the impact of protein quantitative trait loci (pQTLs) linked to 871 different proteins to phenotypes.

In the study, published this week in Nature Communications, the researchers developed a proteome-phenome network consisting of 547 gene-protein-phenotype connections. Of those 547 connections, just over 36 percent were identified with both the Olink and SomaLogic platforms, indicating that the two companies' products "capture distinct aspects of protein biology," the authors wrote.

Boulder, Colorado-based SomaLogic currently measures 7,000 proteins on its SomaScan platform, which uses proprietary aptamer reagents called Somamers. Uppsala, Sweden-based Olink measures up to 3,000 proteins using its proximity extension assay technology (PEA), which uses pairs of antibodies linked to DNA strands that are brought into proximity when the antibodies bind and are then extended by a DNA polymerase, creating a new sequence that can be used as a surrogate marker for the target protein.

Protein quantitative trait loci link changes in protein expression back to genetic variation and have seen uptake within pharma for identifying potential drug targets and drug repurposing. Key to such efforts is the ability to collect genomic and proteomic data from large sets of subjects, an area where proteomic tools have traditionally lagged behind their genomic counterparts. In recent years, SomaLogic and Olink's platforms have emerged as potential tools for such work due to their high throughput and ability to measure large numbers of proteins in plasma.

However, researchers are still working to understand how measurements by these and other proteomic platforms compare to one another; where, for instance, they diverge, and how they might be usefully combined. As the Nature Communications authors note, "information about the consistency of protein measures and the pQTLs identified using different proteomics platforms is needed to inform the generalizability of genetic findings and strategies for future data integration or meta-analytical approaches."

To get at this question, the researchers, which included SomaLogic's chief medical officer Stephen Williams, measured 4,775 unique proteins with the SomaScan platform and 1,069 with the Olink platform, with 871 of those proteins measured by both platforms. The SomaScan measurements were made in 10,708 subjects, while the Olink measurements were made in 485 subjects. Using that data, they identified the 547 gene-protein-phenotype linkages, roughly one-third of which were unique to one of the two platforms (108 unique to Olink and 91 unique to Somalogic).

The researchers also looked at eight gene-protein-phenotype linkages identified by both assays but where the two assays indicated opposite effect directions. For instance, a missense variant in the gene PILRA was inversely associated with PILRA protein expression as measured by the Olink platform, whereas the same genetic signal was positively correlated with two isoforms of the same protein measured by the SomaScan platform and was not associated with SomaScan measurements of the canonical version of PILRA. The authors suggested that this discrepancy stemmed from differences in the binding of the two platforms' reagents to the different PILRA isoforms. More generally, they noted that their findings indicate the importance of protein structural changes and modifications to phenotype, as opposed to just protein expression levels.

The researchers also observed that a number of non-biological factors, such as aspects of the reagent and production process, could underlie the differences between the two platforms, though they noted that they were not able to thoroughly assess this question because much of the required technical information is not in the public domain.

They added that approaches like mass spectrometry could better characterize the specific protein species bound by the SomaLogic and Olink assays or link specific peptide sequences to a given pQTL. This could help further tease out the underlying causes of variation across different proteomic platforms.