Alcohol Dehydrogenases, Aldehyde Dehydrogenases, and Alcohol Use Disorders: A Critical Review

Alcohol use disorders (AUD) are complex traits, meaning that variations in many genes contribute to the risk, as does the environment. Although the total genetic contribution to risk is substantial, most individual variations make only very small contributions. By far the strongest contributors are functional variations in two genes involved in alcohol (ethanol) metabolism. A functional variant in alcohol dehydrogenase 1B (ADH1B) is protective in people of European and Asian descent, and a different functional variant in the same gene is protective in those of African descent. A strongly protective variant in aldehyde dehydrogenase 2 (ALDH2) is essentially only found in Asians. This highlights the need to study a wide range of populations. The likely mechanism of protection against heavy drinking and AUD in both cases is alteration in the rate of metabolism of ethanol that at least transiently elevates acetaldehyde. Other ADH and ALDH variants, including functional variations in ADH1C, have also been implicated in affecting drinking behavior and risk for alcoholism. The pattern of linkage disequilibrium in the ADH region, and the differences among populations, complicate analyses, particularly of regulatory variants. This critical review focuses upon the ADH and ALDH genes as they affect AUDs

Effects of filtering by Present call on analysis of microarray experiments

BACKGROUND: Affymetrix GeneChips(® )are widely used for expression profiling of tens of thousands of genes. The large number of comparisons can lead to false positives. Various methods have been used to reduce false positives, but they have rarely been compared or quantitatively evaluated. Here we describe and evaluate a simple method that uses the detection (Present/Absent) call generated by the Affymetrix microarray suite version 5 software (MAS5) to remove data that is not reliably detected before further analysis, and compare this with filtering by expression level. We explore the effects of various thresholds for removing data in experiments of different size (from 3 to 10 arrays per treatment), as well as their relative power to detect significant differences in expression. RESULTS: Our approach sets a threshold for the fraction of arrays called Present in at least one treatment group. This method removes a large percentage of probe sets called Absent before carrying out the comparisons, while retaining most of the probe sets called Present. It preferentially retains the more significant probe sets (p ≤ 0.001) and those probe sets that are turned on or off, and improves the false discovery rate. Permutations to estimate false positives indicate that probe sets removed by the filter contribute a disproportionate number of false positives. Filtering by fraction Present is effective when applied to data generated either by the MAS5 algorithm or by other probe-level algorithms, for example RMA (robust multichip average). Experiment size greatly affects the ability to reproducibly detect significant differences, and also impacts the effect of filtering; smaller experiments (3–5 samples per treatment group) benefit from more restrictive filtering (≥50% Present). CONCLUSION: Use of a threshold fraction of Present detection calls (derived by MAS5) provided a simple method that effectively eliminated from analysis probe sets that are unlikely to be reliable while preserving the most significant probe sets and those turned on or off; it thereby increased the ratio of true positives to false positives

Mapping of trans-acting regulatory factors from microarray data

To explore the mapping of factors regulating gene expression, we have carried out linkage studies using expression data from individual transcripts (from Affymetrix microarrays; Genetic Analysis Workshop 15 Problem 1) and composite data on correlated groups of transcripts. Quality measures for the arrays were used to remove outliers, and arrays with sex mismatches were also removed. Data likely to represent noise were removed by setting a minimum threshold of present calls among the non-redundant set of 190 arrays. SOLAR was used for genetic analysis, with MAS5 signal as the measure of expression. Probe sets with larger CVs generated more linkages (LOD > 2.0). While trans linkages predominated, linkages with the largest LOD scores (>4) were mostly cis. Hierarchical clustering was used to generate correlated groups of genes. We tested four composite measures of expression for the clusters. The average signal, average normalized signal, and the first principal component of the data behaved similarly; in 8/19 clusters tested, the composite measures linked to a region to which some individual probe sets within the cluster also linked. The second principal component only produced one linkage with LOD > 2. One cluster based upon chromosomal location, containing histone genes, linked to two trans regions. This work demonstrates that composite measures for genes with correlated expression can be used to identify loci that affect multiple co-expressed genes

Estrogen receptor-dependent attenuation of hypoxia-induced changes in the lung genome of pulmonary hypertension rats

17β-estradiol (E2) exerts complex and context-dependent effects in pulmonary hypertension. In hypoxia-induced pulmonary hypertension (HPH), E2 attenuates lung vascular remodeling through estrogen receptor (ER)-dependent effects; however, ER target genes in the hypoxic lung remain unknown. In order to identify the genome regulated by the E2-ER axis in the hypoxic lung, we performed a microarray analysis in lungs from HPH rats treated with E2 (75 mcg/kg/day) ± ER-antagonist ICI182,780 (3 mg/kg/day). Untreated HPH rats and normoxic rats served as controls. Using a false discovery rate of 10%, we identified a significantly differentially regulated genome in E2-treated versus untreated hypoxia rats. Genes most upregulated by E2 encoded matrix metalloproteinase 8, S100 calcium binding protein A8, and IgA Fc receptor; genes most downregulated by E2 encoded olfactory receptor 63, secreted frizzled-related protein 2, and thrombospondin 2. Several genes affected by E2 changed in the opposite direction after ICI182,780 co-treatment, indicating an ER-regulated genome in HPH lungs. The bone morphogenetic protein antagonist Grem1 (gremlin 1) was upregulated by hypoxia, but found to be among the most downregulated genes after E2 treatment. Gremlin 1 protein was reduced in E2-treated versus untreated hypoxic animals, and ER-blockade abolished the inhibitory effect of E2 on Grem1 mRNA and protein. In conclusion, E2 ER-dependently regulates several genes involved in proliferative and inflammatory processes during hypoxia. Gremlin 1 is a novel target of the E2-ER axis in HPH. Understanding the mechanisms of E2 gene regulation in HPH may allow for selectively harnessing beneficial transcriptional activities of E2 for therapeutic purposes

Reproducibility of oligonucleotide arrays using small samples

BACKGROUND: Low RNA yields from small tissue samples can limit the use of oligonucleotide microarrays (Affymetrix GeneChips(®)). Methods using less cRNA for hybridization or amplifying the cRNA have been reported to reduce the number of transcripts detected, but the effect on realistic experiments designed to detect biological differences has not been analyzed. We systematically explore the effects of using different starting amounts of RNA on the ability to detect differential gene expression. RESULTS: The standard Affymetrix protocol can be used starting with only 2 micrograms of total RNA, with results equivalent to the recommended 10 micrograms. Biological variability is much greater than the technical variability introduced by this change. A simple amplification protocol described here can be used for samples as small as 0.1 micrograms of total RNA. This amplification protocol allows detection of a substantial fraction of the significant differences found using the standard protocol, despite an increase in variability and the 5' truncation of the transcripts, which prevents detection of a subset of genes. CONCLUSIONS: Biological differences in a typical experiment are much greater than differences resulting from technical manipulations in labeling and hybridization. The standard protocol works well with 2 micrograms of RNA, and with minor modifications could allow the use of samples as small as 1 micrograms. For smaller amounts of starting material, down to 0.1 micrograms RNA, differential gene expression can still be detected using the single cycle amplification protocol. Comparisons of groups of four arrays detect many more significant differences than comparisons of three arrays

Embryonic ethanol exposure alters expression of sox2 and other early transcripts in zebrafish, producing gastrulation defects

Ethanol exposure during prenatal development causes fetal alcohol spectrum disorder (FASD), the most frequent preventable birth defect and neurodevelopmental disability syndrome. The molecular targets of ethanol toxicity during development are poorly understood. Developmental stages surrounding gastrulation are very sensitive to ethanol exposure. To understand the effects of ethanol on early transcripts during embryogenesis, we treated zebrafish embryos with ethanol during pre-gastrulation period and examined the transcripts by Affymetrix GeneChip microarray before gastrulation. We identified 521 significantly dysregulated genes, including 61 transcription factors in ethanol-exposed embryos. Sox2, the key regulator of pluripotency and early development was significantly reduced. Functional annotation analysis showed enrichment in transcription regulation, embryonic axes patterning, and signaling pathways, including Wnt, Notch and retinoic acid. We identified all potential genomic targets of 25 dysregulated transcription factors and compared their interactions with the ethanol-dysregulated genes. This analysis predicted that Sox2 targeted a large number of ethanol-dysregulated genes. A gene regulatory network analysis showed that many of the dysregulated genes are targeted by multiple transcription factors. Injection of sox2 mRNA partially rescued ethanol-induced gene expression, epiboly and gastrulation defects. Additional studies of this ethanol dysregulated network may identify therapeutic targets that coordinately regulate early development

Ethanol Activates Immune Response In Lymphoblastoid Cells

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 might provide biomarkers. RNAseq was used to study the effects of 48 h exposure to ethanol on lymphoblastoid cell lines (LCLs) from 21 alcoholics and 21 controls. Ethanol exposure resulted in differential expression of 4,577 of the 12,526 genes detectably expressed in the LCLs (FDR ≤ 0.05); 55% of these showed increased expression. Cells from alcoholics and controls responded similarly. The genes whose expression changed fell into many pathways. NFκB, neuroinflammation, IL-6, and dendritic cell maturation pathways were activated, consistent with increased signaling by NFκB, TNF, TGFβ, IL1, IL4, IL18, TLR4, and LPS. Signaling by Interferons A and B decreased, which may be responsible for a slightly blunted immune response compared to 24 h ethanol treatment. EIF2, phospholipase C and VEGF signaling were decreased. Baseline gene expression patterns were similar in LCLs from alcoholics and controls. At relaxed stringency (p<0.05), 1164 genes differed, 340 of which were also affected by ethanol. There was a suggestion of compensation, with 77% showing opposing fold changes. Aldosterone signaling and phospholipase C signaling differed. The pattern of expression was consistent with increased signaling by several cytokines and TLR2 in alcoholics. The cholesterol biosynthesis pathway was lower in alcoholics, including a decrease in the rate-limiting enzyme HMGCR. LCLs show many effects of ethanol exposure, some of which might provide biomarkers for AUD and aid in interpreting the effects of genes identified by GWAS

Effects of chronic intermittent ethanol exposure and withdrawal on neuroblastoma cell transcriptome

Cycles of heavy drinking and abstinence can lead to ethanol abuse disorder. We studied the effects of chronic intermittent ethanol exposure (CIE) over three weeks on neuroblastoma cells, using an ethanol concentration frequently attained in binge drinking (40 mM, 184 mg/dl). There were many changes in gene expression but most were small. CIE affected pathways instrumental in the development or plasticity of neurons, including axonal guidance, reelin signaling and synaptogenesis. Genes involved in dopamine and serotonin signaling were also affected. Changes in transporters and receptors could dampen both NMDA and norepinephrine transmissions. Decreased expression of the GABA transporter SLC6A11 could increase GABA transmission and has been associated with a switch from sweet drinking to ethanol consumption in rats. Ethanol increased stress responses such as unfolded protein response. TGF-β and NFκB signaling were increased. Most of the genes involved in cholesterol biosynthesis were decreased in expression. Withdrawal for 24 h after CIE caused most of the CIE-induced expression changes to move back toward unexposed levels

Gene expression changes in serotonin, GABA-A receptors, neuropeptides and ion channels in the dorsal raphe nucleus of adolescent alcohol-preferring (P) rats following binge-like alcohol drinking

Alcohol binge-drinking during adolescence is a serious public health concern with long-term consequences. We used RNA sequencing to assess the effects of excessive adolescent ethanol binge-drinking on gene expression in the dorsal raphe nucleus (DRN) of alcohol preferring (P) rats. Repeated binges across adolescence (three 1h sessions across the dark-cycle per day, 5 days per week for 3 weeks starting at 28 days of age; ethanol intakes of 2.5-3 g/kg/session) significantly altered the expression of approximately one-third of the detected genes. Multiple neurotransmitter systems were altered, with the largest changes in the serotonin system (21 of 23 serotonin-related genes showed decreased expression) and GABA-A receptors (8 decreased and 2 increased). Multiple neuropeptide systems were also altered, with changes in the neuropeptide Y and corticotropin-releasing hormone systems similar to those associated with increased drinking and decreased resistance to stress. There was increased expression of 21 of 32 genes for potassium channels. Expression of downstream targets of CREB signaling was increased. There were also changes in expression of genes involved in inflammatory processes, axonal guidance, growth factors, transcription factors, and several intracellular signaling pathways. These widespread changes indicate that excessive binge drinking during adolescence alters the functioning of the DRN and likely its modulation of many regions of the central nervous system, including the mesocorticolimbic system

Identification of candidate genes for alcohol preference by expression profiling of congenic rat strains

BACKGROUND: A highly significant quantitative trait locus (QTL) on chromosome 4 that influenced alcohol preference was identified by analyzing crosses between the iP and iNP rats. Congenic strains in which the iP chromosome 4 QTL interval was transferred to the iNP (NP.P) exhibited the expected increase in alcohol consumption compared with the iNP background strain. This study was undertaken to identify genes in the chromosome 4 QTL interval that might contribute to the differences in alcohol consumption between the alcohol-naïve congenic and background strains. METHODS: RNA from 5 brain regions from each of 6 NP.P and 6 iNP rats was labeled and analyzed separately on an Affymetrix Rat Genome 230 2.0 microarray to look for both cis-regulated and trans-regulated genes. Expression levels were normalized using robust multi-chip average (RMA). Differential gene expression was validated using quantitative real-time polymerase chain reaction. Five individual brain regions (nucleus accumbens, frontal cortex, amygdala, hippocampus, and striatum) were analyzed to detect differential expression of genes within the introgressed QTL interval, as well as genes outside that region. To increase the power to detect differentially expressed genes, combined analyses (averaging data from the 5 discrete brain regions of each animal) were also carried out. RESULTS: Analyses within individual brain regions that focused on genes within the QTL interval detected differential expression in all 5 brain regions; a total of 35 genes were detected in at least 1 region, ranging from 6 genes in the nucleus accumbens to 22 in the frontal cortex. Analysis of the whole genome detected very few differentially expressed genes outside the QTL. Combined analysis across brain regions was more powerful. Analysis focused on the genes within the QTL interval confirmed 19 of the genes detected in individual regions and detected 15 additional genes. Whole genome analysis detected 1 differentially expressed gene outside the interval. CONCLUSIONS: Cis-regulated candidate genes for alcohol consumption were identified using microarray profiling of gene expression differences in congenic animals carrying a QTL for alcohol preference