Elsevier

Alcohol

Volume 79, September 2019, Pages 81-91
Alcohol

Ethanol activates immune response in lymphoblastoid cells

https://doi.org/10.1016/j.alcohol.2019.01.001Get rights and content

Highlights

  • 48-h treatment of LCLs with ethanol activates immune signaling.

  • Immune signaling increased without exposure to LPS.

  • Interferon signaling is decreased in 48-h treatment compared to 24-h treatment with ethanol.

  • At baseline, cholesterol synthesis genes are lower in alcoholic subjects than in control subjects.

  • At baseline, cytokines are more highly expressed in alcoholic subjects than control subjects.

Abstract

The short-term effects of alcohol on gene expression in brain tissue cannot directly be studied in humans. Because neuroimmune signaling is altered by alcohol, immune cells are a logical, accessible choice to study and may provide biomarkers. RNAseq was used to study the effects of 48-h exposure to ethanol on lymphoblastoid cell lines (LCLs) from 20 alcoholic subjects and 20 control subjects.

Ethanol exposure resulted in differential expression of 4456 of the 12,503 genes detectably expressed in the LCLs (FDR [false discovery rate] ≤ 0.05); 52% of these showed increased expression. Cells from alcoholic subjects and control subjects responded similarly. The genes whose expression changed fell into many pathways: NFκB, neuroinflammation, IL6, IL2, IL8, and dendritic cell maturation pathways were activated, consistent with increased signaling by NFκB, TNF, IL1, IL4, IL18, TLR4, and LPS. Signaling by Interferons A and B decreased, as did EIF2 signaling, phospholipase C signaling, and glycolysis.

Baseline gene expression patterns were similar in LCLs from alcoholic subjects and control subjects. At relaxed stringency (p < 0.05), 465 genes differed, 230 of which were also affected by ethanol. There was a suggestion of compensation because baseline differences (no ethanol) were in the opposite direction of differences due to ethanol exposure in 78% of these genes. Pathways with IL8, phospholipase C, and α-adrenergic signaling were significant. The pattern of expression was consistent with increased signaling by several cytokines, including interferons, TLR2, and TLR3 in alcoholics. Expression of genes in the cholesterol biosynthesis pathway, including the rate-limiting enzyme HMGCR, was lower in alcoholic subjects.

LCLs show many effects of ethanol exposure, some of which might provide biomarkers for alcohol use disorders. Identifying genes and pathways altered by ethanol can aid in interpreting which genes within loci identified by GWAS might play functional roles.

Introduction

Alcohol dependence (AD) is a chronic relapsing brain disorder with both environmental and genetic contributions to risk. It is estimated that 40–60% of the difference in risk among individuals is due to genetic variations (Edenberg and Foroud, 2013, Edenberg and Foroud, 2014, Rietschel and Treutlein, 2013). However, few individual genes have been robustly associated with risk for AD. The largest meta-analysis to date of alcohol dependence in those of European and African ancestry found only one gene associated with the disorder at genome-wide significance, ADH1B (Walters et al., 2018). Another metabolic gene, ALDH2, is associated with alcohol dependence in Asians (Edenberg & McClintick, 2018). Many of the variants for alcohol-related traits identified by GWAS are not in coding regions, and might be eQTLs or be in linkage disequilibrium (LD) with them (Gamazon et al., 2018). Transcriptome analyses may help prioritize genes within GWAS loci, identify the eQTLs and pathways affected by ethanol, and help understand mechanisms by which they act.

Alcohol-dependent individuals are chronically exposed to large quantities of ethanol. This leads to multiple organ damage, including the liver (Osna, Donohue, & Kharbanda, 2017), brain (Zahr & Pfefferbaum, 2017), and immune system (Szabo & Saha, 2015). Gene expression studies of post mortem human brain tissue can shed light on how the brain is damaged by and adapts to chronic ethanol exposure (Farris et al., 2015, Flatscher-Bader et al., 2006, Hermann et al., 2017, Mayfield et al., 2013, McClintick et al., 2013). Changes to the brain include direct effects of ethanol and also insults caused by circulating cytokines that can cross the blood–brain barrier (Crews & Vetreno, 2016). These studies identified effects on NFκB, TLRs, IL1β, and TNFα, and thereby point toward neuroimmune signaling as an important effect of chronic ethanol exposure and a potential contributor to AD (Crews and Vetreno, 2016, Mayfield et al., 2013, Pascual et al., 2014). Ethanol has been shown to potentiate and prolong the effects of proinflammatory cytokines and microglial activation (Qin et al., 2008). This suggests that immune cells may provide an accessible window into how ethanol affects gene expression. Post mortem brains show the effects of both potentially pre-existing differences between alcoholic individuals and control individuals, and effects of long-term exposure to high levels of alcohol. There are many unrelated variables, however, including cause of death, recency of exposure to ethanol, and post mortem interval. Lymphoblastoid cell lines (LCLs) can be studied under controlled conditions, and have been used for functional studies that cannot be done with post mortem brain tissue, such as identifying lithium-induced gene expression changes in bipolar patients and control individuals (Fries et al., 2017). Recent studies have shown strong correlations between blood and brain for cis expression QTLs (eQTLs) and methylation QTLs (Qi et al., 2018).

Transcriptome-wide analysis of expression in LCLs from AD individuals and control individuals may aid the interpretation of variants identified by genetic association studies. Treatment of LCLs with ethanol can reveal direct, relatively short-term effects on cellular function. In a previous microarray study, we examined the effects of 24-h exposure to 75-mM ethanol, which was not toxic to the cells, in LCLs from 21 individuals who met DSM-IV criteria for alcohol dependence and from 21 control individuals (McClintick et al., 2014). The individuals from whom LCLs were created were carefully diagnosed as part of the Collaborative Study on the Genetics of Alcoholism (COGA) (Begleiter et al., 1995). Nearly half of all the expressed genes were affected by ethanol, but most changes were very small; fewer than 20% had absolute fold changes >1.2. Pathways affected included increased pro-inflammatory pathways, including IL6, dendritic cell maturation, TNF, and NFκB, and a decrease in the anti-inflammatory IL10 pathway. Analysis indicated that NFκB, IL6, TNF, and other cytokines were likely active, along with TLRs and interferons (McClintick et al., 2014). There was limited power to detect differences between untreated AD subjects and control subjects, but decreased IGF1 signaling and increases in protein ubiquitination and hypoxia signaling were identified.

Here, we have analyzed cells from the same individuals exposed to the same concentration of ethanol (75 mM) but for 48 h, to see whether changes detected at 24 h are stable over a longer exposure. We also examined the untreated cells for differences in expression between AD subjects and control subjects using data from both the 48-h and 24-h exposures. Differences between unexposed cells from AD subjects and control subjects could provide insight into the genetics of AD.

Section snippets

Cell culture and ethanol treatment

Lymphoblastoid cell lines (LCLs) were created by transformation with Epstein–Barr virus of peripheral blood mononuclear cells isolated from subjects recruited as part of the Collaborative Study on the Genetics of Alcoholism (Begleiter et al., 1995) and who had been interviewed with the SSAGA instrument (Bucholz et al., 1994). LCLs were from 42 subjects, 21 alcohol-dependent (AD) subjects and 21 control subjects. AD was defined as meeting DSM-IV criteria for alcohol dependence (American

Results and discussion

We examined gene expression in LCLs from alcohol-dependent subjects and control subjects to detect both pre-existing differences and the effects of ethanol. Because many data from brain transcriptome studies suggest that ethanol is associated with changes in neuroimmune genes and pathways (Crews and Vetreno, 2016, Mayfield et al., 2013, McClintick et al., 2013), and because many of the genes expressed in the brain are also expressed in LCLs, LCLs are reasonable candidates to study both

Conclusions

The results of this study provide additional data on genes potentially linked either to the development of alcohol dependence or to the effects of excessive alcohol. There are, however, limitations. Even though most of the genes we found differentially expressed in the LCLs exposed to ethanol are also expressed in brain, the changes we found might not mirror what happens in the brain. Long-term drinking patterns are highly variable and are not replicated in vitro; our goal was to determine

Declarations of interest

None.

Acknowledgments

The Center for Medical Genomics at the Indiana University School of Medicine performed the RNA sequencing and alignment. The Collaborative Study on the Genetics of Alcoholism (COGA), Principal Investigators B. Porjesz, V. Hesselbrock, H. Edenberg, L. Bierut, includes 11 different centers: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman, J. Kramer); SUNY Downstate (B. Porjesz); Washington University in

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