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  5. Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods

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Article
English
2022

Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods

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English
2022
Science Advances
Vol 8 (33)
DOI: 10.1126/sciadv.abm5164

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Claude Bouchard
Claude Bouchard

Pennington Biomedical Research Center

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Daniel H. Katz
Jeremy Robbins
Shuliang Deng
+16 more

Abstract

High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K ( N = 1301 reagents), the SomaScan5K platform ( N = 4979 reagents), and the Olink Explore ( N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.

How to cite this publication

Daniel H. Katz, Jeremy Robbins, Shuliang Deng, Usman A. Tahir, Alexander G. Bick, Akhil Pampana, Zhi Yu, Debby Ngo, Mark D. Benson, Zsu‐Zsu Chen, Daniel E. Cruz, Dongxiao Shen, Yan Gao, Claude Bouchard, Mark A. Sarzynski, Adolfo Correa, Pradeep Natarajan, James G. Wilson, Robert E. Gerszten (2022). Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. Science Advances, 8(33), DOI: 10.1126/sciadv.abm5164.

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Publication Details

Type

Article

Year

2022

Authors

19

Datasets

0

Total Files

0

Language

English

Journal

Science Advances

DOI

10.1126/sciadv.abm5164

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