Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells
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Regev_Common genetic.pdf
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Author(s)
Lee, M. N.
Ye, C.
Villani, A.-C.
Raj, T.
Li, W.
Eisenhaure, Thomas
Imboywa, S. H.
Chipendo, P. I.
Slowikowski, K.
Raddassi, K.
Date Issued
March 2014
Journal
Science
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Lee, M. N., C. Ye, A.-C. Villani, T. Raj, W. Li, T. M. Eisenhaure, S. H. Imboywa, et al. “Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells.” Science 343, no. 6175 (March 6, 2014): 1246980–1246980.
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Author's final manuscript
Abstract
Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
McGovern Institute for Brain Research at MIT
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DOI of Published Version
https://doi.org/10.1126/science.1246980
