Large-scale plasma proteomics comparisons through genetics and disease associations

Large-scale plasma proteomics comparisons through genetics and disease associations - Nature
Comparisons of phenotypic and genetic association with protein levels from Icelandic and UK Biobank cohorts show that using multiple analysis platforms and stra...

In this study, we utilized a high-throughput proteomics platform capable of measuring thousands of proteins in plasma. By combining genetic and phenotypic information, we explored the potential to bridge the gap between the genome and diseases. We conducted a related study on the Olink Explore 3072 data from plasma samples obtained from over 50,000 UK Biobank participants by the UK Biobank Pharma Proteomics Project. The focus was on individuals with ancestry from the UK, Ireland, Africa, and South Asia. We also compared the results with the SomaScan v4 study from the plasma of 36,000 Icelanders, with Olink data also available for 1,514 individuals. Moderate correlations were observed between the two platforms, and certain protein genetic associations differed between platforms​1​.

How did they differ specifically?

The study provided instances where different genetic associations were detected on the two platforms (Olink and SomaScan) and how these differences might impact conclusions drawn from integrating protein levels and disease research. These differences were particularly evident in the detection of cis protein quantitative trait loci (cis-pQTLs), with the Olink platform detecting these cis-pQTLs at a higher rate than the SomaScan platform (72% vs. 43%). Furthermore, different genetic associations for proteins were observed between the platforms, indicating potential impacts on study conclusions​1​.

Explain cis protein quantitative trait loci (cis-pQTLs) in simpler terms.

Cis protein quantitative trait loci (cis-pQTLs) refer to gene variants (genetic mutations) that regulate the amount or activity of a specific protein. These variants are named “cis” because they are located near the gene that codes for that protein on the same chromosome. Cis-pQTLs can influence protein expression and, in turn, affect an individual’s phenotype or risk of disease.

How are cis-pQTLs determined?

Cis-pQTLs are identified using statistical methods, comparing genetic information with protein quantity data. Specifically, the association between individual gene variants (like SNPs) and the amount of protein coded nearby is examined. If the association is statistically significant, that gene variant may be identified as a cis-pQTL. This process uses an individual’s genetic data and proteomics (protein measurement) data to understand to what extent the quantity of a specific protein is genetically regulated.

What’s the difference between the Olink platform and the SomaScan platform?

The Olink and SomaScan platforms use different technologies for plasma proteomics analysis. The research indicated that the Olink platform detected cis-pQTLs at a higher rate than the SomaScan platform, and different genetic associations for proteins were observed between platforms​1​.

How do they technically differ?

Olink and SomaScan use distinct technologies for proteomics analysis. Here are their technical differences:

  1. Detection Technology:
    • Olink: The Olink platform employs the Proximity Extension Assay (PEA) technology, which is antibody-based. It uses pairs of antibodies that bind to a specific protein for its detection and quantification​1​.
    • SomaScan: In contrast, the SomaScan platform utilizes aptamer-based technology, which involves short single-stranded DNA or RNA molecules binding to specific proteins​2​.
  2. Measurement Accuracy and Analysis Range:
    • The Olink platform is shown to have high specificity for target proteins and a large number of phenotype-related counts​3​.
    • On the other hand, the SomaScan platform is recognized for its broad measurement accuracy and analysis range across the proteome​3​.
  3. Correlation Range:
    • There is a broad range of correlations observed between Olink and SomaScan in protein expression assessments. This suggests that, due to their different technologies, the same protein might yield different results across platforms​4​.

These differences could be factors in determining which platform to choose based on the design and objective of a study. Additionally, they may influence the interpretation of research results obtained using different platforms.