Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial

Autor: 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
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Genome Biology, Vol 19, Iss 1, Pp 1-15 (2018)
Druh dokumentu: article
ISSN: 1474-760X
DOI: 10.1186/s13059-018-1560-8
Popis: 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 measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point 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. Conclusions This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.
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