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Discovering in vivo cytokine eQTL interactions from a lupus clinical trial

View ORCID ProfileEmma E. Davenport, Tiffany Amariuta, Maria Gutierrez-Arcelus, Kamil Slowikowski, Harm-Jan Westra, Yang Luo, Ciyue Shen, Deepak A. Rao, Ying Zhang, Stephen Pearson, David von Schack, Jean S. Beebe, Nan Bing, Sally John, Michael S. Vincent, Baohong Zhang, Soumya Raychaudhuri
doi: https://doi.org/10.1101/118703
Emma E. Davenport
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
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  • ORCID record for Emma E. Davenport
Tiffany Amariuta
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
5Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
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Maria Gutierrez-Arcelus
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
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Kamil Slowikowski
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
5Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
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Harm-Jan Westra
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
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Yang Luo
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
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Ciyue Shen
6Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
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Deepak A. Rao
7Division of Rheumatology, Allergy, Immunology, Brigham and Women’s Hospital, Harvard Medical School, MA 02115, USA.
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Ying Zhang
8Pfizer Inc., Cambridge, MA, 02139, USA.
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Stephen Pearson
9Pfizer New Haven Clinical Research Unit, New Haven, CT, 06511, USA.
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David von Schack
8Pfizer Inc., Cambridge, MA, 02139, USA.
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Jean S. Beebe
8Pfizer Inc., Cambridge, MA, 02139, USA.
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Nan Bing
8Pfizer Inc., Cambridge, MA, 02139, USA.
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Sally John
10Biogen, Cambridge, MA, 02142, USA.
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Michael S. Vincent
8Pfizer Inc., Cambridge, MA, 02139, USA.
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Baohong Zhang
8Pfizer Inc., Cambridge, MA, 02139, USA.
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Soumya Raychaudhuri
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, 02115, USA.
2Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA.
3Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA.
4Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
5Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
11Faculty of Medical and Human Sciences, University of Manchester, Manchester, M13 9PL, UK.
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  • For correspondence: soumya@broadinstitute.org
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Abstract

Background Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.

Results In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus we measured interferon (IFN) status, anti-IL-6 drug exposure and genome-wide gene expression at three time points (379 samples from 157 individuals). First, we show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point by 64%. Then, after identifying 4,818 cis-eQTLs, we observed a statistically significant enrichment of in vivo eQTL interactions with IFN status (p<0.001 by permutation) and anti-IL-6 drug exposure (p<0.001). We observed 210 and 72 interactions for IFN and anti-IL-6 respectively (FDR<20%). Anti-IL-6 interactions have not yet been described while 99 of the IFN interactions are novel. Finally, we found transcription factor binding motifs interrupted by eQTL interaction SNPs, pointing to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.

Conclusion This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted February 20, 2018.
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Discovering in vivo cytokine eQTL interactions from a lupus clinical trial
Emma E. Davenport, Tiffany Amariuta, Maria Gutierrez-Arcelus, Kamil Slowikowski, Harm-Jan Westra, Yang Luo, Ciyue Shen, Deepak A. Rao, Ying Zhang, Stephen Pearson, David von Schack, Jean S. Beebe, Nan Bing, Sally John, Michael S. Vincent, Baohong Zhang, Soumya Raychaudhuri
bioRxiv 118703; doi: https://doi.org/10.1101/118703
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Discovering in vivo cytokine eQTL interactions from a lupus clinical trial
Emma E. Davenport, Tiffany Amariuta, Maria Gutierrez-Arcelus, Kamil Slowikowski, Harm-Jan Westra, Yang Luo, Ciyue Shen, Deepak A. Rao, Ying Zhang, Stephen Pearson, David von Schack, Jean S. Beebe, Nan Bing, Sally John, Michael S. Vincent, Baohong Zhang, Soumya Raychaudhuri
bioRxiv 118703; doi: https://doi.org/10.1101/118703

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