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Integrative omics approach to identify the molecular architecture of inflammatory protein levels in healthy older adults

Robert F. Hillary, Daniel Trejo-Banos, Athanasios Kousathanas, Daniel L. McCartney, Sarah E. Harris, Anna J. Stevenson, Marion Patxot, Sven Erik Ojavee, Qian Zhang, David C. Liewald, Craig W. Ritchie, Kathryn L. Evans, Elliot M. Tucker-Drob, Naomi R. Wray, Allan F. McRae, Peter M. Visscher, Ian J. Deary, Matthew R. Robinson, Riccardo E. Marioni
doi: https://doi.org/10.1101/2020.02.17.952135
Robert F. Hillary
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
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Daniel Trejo-Banos
2Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
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Athanasios Kousathanas
2Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
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Daniel L. McCartney
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
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Sarah E. Harris
3Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
8Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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Anna J. Stevenson
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
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Marion Patxot
2Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
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Sven Erik Ojavee
2Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
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Qian Zhang
4Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
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David C. Liewald
3Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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Craig W. Ritchie
5Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK
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Kathryn L. Evans
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
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Elliot M. Tucker-Drob
6Department of Psychology, The University of Texas at Austin, Austin, TX, 78712, USA
7Population Research Center, The University of Texas at Austin, Austin, TX, 78712, USA
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Naomi R. Wray
4Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
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Allan F. McRae
4Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
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Peter M. Visscher
4Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
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Ian J. Deary
3Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
8Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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Matthew R. Robinson
2Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
9Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, 1015, Switzerland
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  • For correspondence: riccardo.marioni@ed.ac.uk matthew.robinson@unil.ch
Riccardo E. Marioni
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
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  • For correspondence: riccardo.marioni@ed.ac.uk matthew.robinson@unil.ch
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Abstract

The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets. Therefore, in this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified three CpG sites spread across three proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to one polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease, and between IL12B and Crohn’s disease. Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.

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Posted February 19, 2020.
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Integrative omics approach to identify the molecular architecture of inflammatory protein levels in healthy older adults
Robert F. Hillary, Daniel Trejo-Banos, Athanasios Kousathanas, Daniel L. McCartney, Sarah E. Harris, Anna J. Stevenson, Marion Patxot, Sven Erik Ojavee, Qian Zhang, David C. Liewald, Craig W. Ritchie, Kathryn L. Evans, Elliot M. Tucker-Drob, Naomi R. Wray, Allan F. McRae, Peter M. Visscher, Ian J. Deary, Matthew R. Robinson, Riccardo E. Marioni
bioRxiv 2020.02.17.952135; doi: https://doi.org/10.1101/2020.02.17.952135
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Integrative omics approach to identify the molecular architecture of inflammatory protein levels in healthy older adults
Robert F. Hillary, Daniel Trejo-Banos, Athanasios Kousathanas, Daniel L. McCartney, Sarah E. Harris, Anna J. Stevenson, Marion Patxot, Sven Erik Ojavee, Qian Zhang, David C. Liewald, Craig W. Ritchie, Kathryn L. Evans, Elliot M. Tucker-Drob, Naomi R. Wray, Allan F. McRae, Peter M. Visscher, Ian J. Deary, Matthew R. Robinson, Riccardo E. Marioni
bioRxiv 2020.02.17.952135; doi: https://doi.org/10.1101/2020.02.17.952135

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