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Large-scale plasma proteomics comparisons through genetics and disease associations
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 Proteo...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567571/ https://www.ncbi.nlm.nih.gov/pubmed/37794188 http://dx.doi.org/10.1038/s41586-023-06563-x |
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author | Eldjarn, Grimur Hjorleifsson Ferkingstad, Egil Lund, Sigrun H. Helgason, Hannes Magnusson, Olafur Th. Gunnarsdottir, Kristbjorg Olafsdottir, Thorunn A. Halldorsson, Bjarni V. Olason, Pall I. Zink, Florian Gudjonsson, Sigurjon A. Sveinbjornsson, Gardar Magnusson, Magnus I. Helgason, Agnar Oddsson, Asmundur Halldorsson, Gisli H. Magnusson, Magnus K. Saevarsdottir, Saedis Eiriksdottir, Thjodbjorg Masson, Gisli Stefansson, Hreinn Jonsdottir, Ingileif Holm, Hilma Rafnar, Thorunn Melsted, Pall Saemundsdottir, Jona Norddahl, Gudmundur L. Thorleifsson, Gudmar Ulfarsson, Magnus O. Gudbjartsson, Daniel F. Thorsteinsdottir, Unnur Sulem, Patrick Stefansson, Kari |
author_facet | Eldjarn, Grimur Hjorleifsson Ferkingstad, Egil Lund, Sigrun H. Helgason, Hannes Magnusson, Olafur Th. Gunnarsdottir, Kristbjorg Olafsdottir, Thorunn A. Halldorsson, Bjarni V. Olason, Pall I. Zink, Florian Gudjonsson, Sigurjon A. Sveinbjornsson, Gardar Magnusson, Magnus I. Helgason, Agnar Oddsson, Asmundur Halldorsson, Gisli H. Magnusson, Magnus K. Saevarsdottir, Saedis Eiriksdottir, Thjodbjorg Masson, Gisli Stefansson, Hreinn Jonsdottir, Ingileif Holm, Hilma Rafnar, Thorunn Melsted, Pall Saemundsdottir, Jona Norddahl, Gudmundur L. Thorleifsson, Gudmar Ulfarsson, Magnus O. Gudbjartsson, Daniel F. Thorsteinsdottir, Unnur Sulem, Patrick Stefansson, Kari |
author_sort | Eldjarn, Grimur Hjorleifsson |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10567571 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105675712023-10-13 Large-scale plasma proteomics comparisons through genetics and disease associations Eldjarn, Grimur Hjorleifsson Ferkingstad, Egil Lund, Sigrun H. Helgason, Hannes Magnusson, Olafur Th. Gunnarsdottir, Kristbjorg Olafsdottir, Thorunn A. Halldorsson, Bjarni V. Olason, Pall I. Zink, Florian Gudjonsson, Sigurjon A. Sveinbjornsson, Gardar Magnusson, Magnus I. Helgason, Agnar Oddsson, Asmundur Halldorsson, Gisli H. Magnusson, Magnus K. Saevarsdottir, Saedis Eiriksdottir, Thjodbjorg Masson, Gisli Stefansson, Hreinn Jonsdottir, Ingileif Holm, Hilma Rafnar, Thorunn Melsted, Pall Saemundsdottir, Jona Norddahl, Gudmundur L. Thorleifsson, Gudmar Ulfarsson, Magnus O. Gudbjartsson, Daniel F. Thorsteinsdottir, Unnur Sulem, Patrick Stefansson, Kari Nature Article 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. Nature Publishing Group UK 2023-10-04 2023 /pmc/articles/PMC10567571/ /pubmed/37794188 http://dx.doi.org/10.1038/s41586-023-06563-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Eldjarn, Grimur Hjorleifsson Ferkingstad, Egil Lund, Sigrun H. Helgason, Hannes Magnusson, Olafur Th. Gunnarsdottir, Kristbjorg Olafsdottir, Thorunn A. Halldorsson, Bjarni V. Olason, Pall I. Zink, Florian Gudjonsson, Sigurjon A. Sveinbjornsson, Gardar Magnusson, Magnus I. Helgason, Agnar Oddsson, Asmundur Halldorsson, Gisli H. Magnusson, Magnus K. Saevarsdottir, Saedis Eiriksdottir, Thjodbjorg Masson, Gisli Stefansson, Hreinn Jonsdottir, Ingileif Holm, Hilma Rafnar, Thorunn Melsted, Pall Saemundsdottir, Jona Norddahl, Gudmundur L. Thorleifsson, Gudmar Ulfarsson, Magnus O. Gudbjartsson, Daniel F. Thorsteinsdottir, Unnur Sulem, Patrick Stefansson, Kari Large-scale plasma proteomics comparisons through genetics and disease associations |
title | Large-scale plasma proteomics comparisons through genetics and disease associations |
title_full | Large-scale plasma proteomics comparisons through genetics and disease associations |
title_fullStr | Large-scale plasma proteomics comparisons through genetics and disease associations |
title_full_unstemmed | Large-scale plasma proteomics comparisons through genetics and disease associations |
title_short | Large-scale plasma proteomics comparisons through genetics and disease associations |
title_sort | large-scale plasma proteomics comparisons through genetics and disease associations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567571/ https://www.ncbi.nlm.nih.gov/pubmed/37794188 http://dx.doi.org/10.1038/s41586-023-06563-x |
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