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Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies

View ORCID ProfileJingning Zhang, Diptavo Dutta, View ORCID ProfileAnna Köttgen, View ORCID ProfileAdrienne Tin, View ORCID ProfilePascal Schlosser, View ORCID ProfileMorgan E. Grams, View ORCID ProfileBenjamin Harvey, CKDGen Consortium, Bing Yu, Eric Boerwinkle, View ORCID ProfileJosef Coresh, View ORCID ProfileNilanjan Chatterjee
doi: https://doi.org/10.1101/2021.03.15.435533
Jingning Zhang
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Diptavo Dutta
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Anna Köttgen
2Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
3Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
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Adrienne Tin
2Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
4MIND Center and Division of Nephrology, University of Mississippi Medical Center, Jackson, MS, USA
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Pascal Schlosser
2Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
3Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
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Morgan E. Grams
2Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
5Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
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Benjamin Harvey
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Bing Yu
6Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
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Eric Boerwinkle
6Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
7Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
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Josef Coresh
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
2Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
5Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
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Nilanjan Chatterjee
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
8Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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  • For correspondence: nilanjan@jhu.edu
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Abstract

Improved understanding of genetic regulation of proteome can facilitate the identification of causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American (AA) individuals from the ARIC study, and further replicated findings on 467 AA individuals from the AASK study. Here we identified 2,004 proteins in EA and 1,618 in AA, with majority overlapping, which showed associations with common variants in cis-regions. Availability of AA samples led to smaller credible sets and significant number of population-specific cis-pQTLs. Elastic-net produced powerful models for protein prediction in both populations. An application of proteome-wide association studies (PWAS) to serum urate and gout, implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study for genetic mechanisms of molecular phenotypes and their relationship with complex traits.

Competing Interest Statement

Proteomic assays in ARIC were conducted free of charge as part of a data exchange agreement with Soma Logic. The authors declare no other competing interests.

Footnotes

  • Formatting and cleaning tables and figures.

  • http://nilanjanchatterjeelab.org/pwas/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 27, 2022.
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Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies
Jingning Zhang, Diptavo Dutta, Anna Köttgen, Adrienne Tin, Pascal Schlosser, Morgan E. Grams, Benjamin Harvey, CKDGen Consortium, Bing Yu, Eric Boerwinkle, Josef Coresh, Nilanjan Chatterjee
bioRxiv 2021.03.15.435533; doi: https://doi.org/10.1101/2021.03.15.435533
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Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies
Jingning Zhang, Diptavo Dutta, Anna Köttgen, Adrienne Tin, Pascal Schlosser, Morgan E. Grams, Benjamin Harvey, CKDGen Consortium, Bing Yu, Eric Boerwinkle, Josef Coresh, Nilanjan Chatterjee
bioRxiv 2021.03.15.435533; doi: https://doi.org/10.1101/2021.03.15.435533

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