TY - JOUR
T1 - Large-scale plasma proteomics comparisons through genetics and disease associations
AU - Eldjarn, Grimur Hjorleifsson
AU - Ferkingstad, Egil
AU - Lund, Sigrun H.
AU - Helgason, Hannes
AU - Magnusson, Olafur Th
AU - Gunnarsdottir, Kristbjorg
AU - Olafsdottir, Thorunn A.
AU - Halldorsson, Bjarni V.
AU - Olason, Pall I.
AU - Zink, Florian
AU - Gudjonsson, Sigurjon A.
AU - Sveinbjornsson, Gardar
AU - Magnusson, Magnus I.
AU - Helgason, Agnar
AU - Oddsson, Asmundur
AU - Halldorsson, Gisli H.
AU - Magnusson, Magnus K.
AU - Sævarsdóttir, Sædís
AU - Eiriksdottir, Thjodbjorg
AU - Masson, Gisli
AU - Stefansson, Hreinn
AU - Jonsdottir, Ingileif
AU - Holm, Hilma
AU - Rafnar, Thorunn
AU - Melsted, Pall
AU - Saemundsdottir, Jona
AU - Norddahl, Gudmundur L.
AU - Thorleifsson, Gudmar
AU - Ulfarsson, Magnus O.
AU - Gudbjartsson, Daniel F.
AU - Thorsteinsdottir, Unnur
AU - Sulem, Patrick
AU - Stefansson, Kari
N1 - Publisher Copyright: © 2023, The Author(s).
PY - 2023/10/4
Y1 - 2023/10/4
N2 - High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project 1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people 2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.
AB - High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project 1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people 2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.
KW - Africa/ethnology
KW - Asia, Southern/ethnology
KW - Biological Specimen Banks
KW - Blood Proteins/analysis
KW - Datasets as Topic
KW - Disease Susceptibility
KW - Genome, Human/genetics
KW - Genomics
KW - Genotype
KW - Humans
KW - Iceland/ethnology
KW - Ireland/ethnology
KW - Phenotype
KW - Plasma/chemistry
KW - Proteome/analysis
KW - Proteomics/methods
KW - Quantitative Trait Loci
KW - United Kingdom
UR - https://doi.org/10.1038/s41586-023-06563-x
UR - https://www.scopus.com/pages/publications/85173272192
U2 - 10.1038/s41586-023-06563-x
DO - 10.1038/s41586-023-06563-x
M3 - Article
C2 - 37794188
SN - 0028-0836
VL - 622
SP - 348
EP - 358
JO - Nature
JF - Nature
IS - 7982
ER -