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Synergistic insights into human health from aptamer- and antibody-based proteomic profiling
Affinity-based proteomics has enabled scalable quantification of thousands of protein targets in blood enhancing biomarker discovery, understanding of disease mechanisms, and genetic evaluation of drug targets in humans through protein quantitative trait loci (pQTLs). Here, we integrate two partly c...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613205/ https://www.ncbi.nlm.nih.gov/pubmed/34819519 http://dx.doi.org/10.1038/s41467-021-27164-0 |
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author | Pietzner, Maik Wheeler, Eleanor Carrasco-Zanini, Julia Kerrison, Nicola D. Oerton, Erin Koprulu, Mine Luan, Jian’an Hingorani, Aroon D. Williams, Steve A. Wareham, Nicholas J. Langenberg, Claudia |
author_facet | Pietzner, Maik Wheeler, Eleanor Carrasco-Zanini, Julia Kerrison, Nicola D. Oerton, Erin Koprulu, Mine Luan, Jian’an Hingorani, Aroon D. Williams, Steve A. Wareham, Nicholas J. Langenberg, Claudia |
author_sort | Pietzner, Maik |
collection | PubMed |
description | Affinity-based proteomics has enabled scalable quantification of thousands of protein targets in blood enhancing biomarker discovery, understanding of disease mechanisms, and genetic evaluation of drug targets in humans through protein quantitative trait loci (pQTLs). Here, we integrate two partly complementary techniques—the aptamer-based SomaScan(®) v4 assay and the antibody-based Olink assays—to systematically assess phenotypic consequences of hundreds of pQTLs discovered for 871 protein targets across both platforms. We create a genetically anchored cross-platform proteome-phenome network comprising 547 protein–phenotype connections, 36.3% of which were only seen with one of the two platforms suggesting that both techniques capture distinct aspects of protein biology. We further highlight discordance of genetically predicted effect directions between assays, such as for PILRA and Alzheimer’s disease. Our results showcase the synergistic nature of these technologies to better understand and identify disease mechanisms and provide a benchmark for future cross-platform discoveries. |
format | Online Article Text |
id | pubmed-8613205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86132052021-12-01 Synergistic insights into human health from aptamer- and antibody-based proteomic profiling Pietzner, Maik Wheeler, Eleanor Carrasco-Zanini, Julia Kerrison, Nicola D. Oerton, Erin Koprulu, Mine Luan, Jian’an Hingorani, Aroon D. Williams, Steve A. Wareham, Nicholas J. Langenberg, Claudia Nat Commun Article Affinity-based proteomics has enabled scalable quantification of thousands of protein targets in blood enhancing biomarker discovery, understanding of disease mechanisms, and genetic evaluation of drug targets in humans through protein quantitative trait loci (pQTLs). Here, we integrate two partly complementary techniques—the aptamer-based SomaScan(®) v4 assay and the antibody-based Olink assays—to systematically assess phenotypic consequences of hundreds of pQTLs discovered for 871 protein targets across both platforms. We create a genetically anchored cross-platform proteome-phenome network comprising 547 protein–phenotype connections, 36.3% of which were only seen with one of the two platforms suggesting that both techniques capture distinct aspects of protein biology. We further highlight discordance of genetically predicted effect directions between assays, such as for PILRA and Alzheimer’s disease. Our results showcase the synergistic nature of these technologies to better understand and identify disease mechanisms and provide a benchmark for future cross-platform discoveries. Nature Publishing Group UK 2021-11-24 /pmc/articles/PMC8613205/ /pubmed/34819519 http://dx.doi.org/10.1038/s41467-021-27164-0 Text en © The Author(s) 2021 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pietzner, Maik Wheeler, Eleanor Carrasco-Zanini, Julia Kerrison, Nicola D. Oerton, Erin Koprulu, Mine Luan, Jian’an Hingorani, Aroon D. Williams, Steve A. Wareham, Nicholas J. Langenberg, Claudia Synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
title | Synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
title_full | Synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
title_fullStr | Synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
title_full_unstemmed | Synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
title_short | Synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
title_sort | synergistic insights into human health from aptamer- and antibody-based proteomic profiling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613205/ https://www.ncbi.nlm.nih.gov/pubmed/34819519 http://dx.doi.org/10.1038/s41467-021-27164-0 |
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