Published in

American Association of Immunologists, The Journal of Immunology, 1(196), p. 182-195, 2016

DOI: 10.4049/jimmunol.1501527

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Alcohol Consumption Modulates Host Defense in Rhesus Macaques by Altering Gene Expression in Circulating Leukocytes

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Several lines of evidence indicate that chronic alcohol use disorder leads to increased susceptibility to several viral and bacterial infections, whereas moderate alcohol consumption decreases the incidence of colds and improves immune responses to some pathogens. In line with these observations, we recently showed that heavy ethanol intake (average blood ethanol concentrations > 80 mg/dl) suppressed, whereas moderate alcohol consumption (blood ethanol concentrations < 50 mg/dl) enhanced, T and B cell responses to modified vaccinia Ankara vaccination in a nonhuman primate model of voluntary ethanol consumption. To uncover the molecular basis for impaired immunity with heavy alcohol consumption and enhanced immune response with moderate alcohol consumption, we performed a transcriptome analysis using PBMCs isolated on day 7 post–modified vaccinia Ankara vaccination, the earliest time point at which we detected differences in T cell and Ab responses. Overall, chronic heavy alcohol consumption reduced the expression of immune genes involved in response to infection and wound healing and increased the expression of genes associated with the development of lung inflammatory disease and cancer. In contrast, chronic moderate alcohol consumption upregulated the expression of genes involved in immune response and reduced the expression of genes involved in cancer. To uncover mechanisms underlying the alterations in PBMC transcriptomes, we profiled the expression of microRNAs within the same samples. Chronic heavy ethanol consumption altered the levels of several microRNAs involved in cancer and immunity and known to regulate the expression of mRNAs differentially expressed in our data set.