Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data.
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ABSTRACT:
SUBMITTER: Mignogna KM
PROVIDER: S-EPMC6481773 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Chronic alcohol abuse alters the molecular structure and function of brain cells. Recent work suggests adaptations made by glial cells, such as astrocytes and microglia, regulate physiological and behavioral changes associated with addiction. Defining how alcohol dependence alters the transcriptome of different cell types is critical for developing the mechanistic hypotheses necessary for a nuanced understanding of cellular signaling in the alcohol-dependent brain. We performed RNA-sequencing on total homogenate and glial cell populations isolated from mouse prefrontal cortex (PFC) following chronic intermittent ethanol vapor exposure (CIE). Compared with total homogenate, we observed unique and robust gene expression changes in astrocytes and microglia in response to CIE. Gene co-expression network analysis revealed biological pathways and hub genes associated with CIE in astrocytes and microglia that may regulate alcohol-dependent phenotypes. Astrocyte identity and synaptic calcium signaling genes were enriched in alcohol-associated astrocyte networks, while TGF-? signaling and inflammatory response genes were disrupted by CIE treatment in microglia gene networks. Genes related to innate immune signaling, specifically interferon pathways, were consistently up-regulated across CIE-exposed astrocytes, microglia, and total homogenate PFC tissue. This study illuminates the cell-specific effects of chronic alcohol exposure and provides novel molecular targets for studying alcohol dependence.
| S-EPMC6662804 | biostudies-literature
Project description:The present study searched for replicable risk genomic regions for alcohol and nicotine co-dependence using a genome-wide association strategy. The data contained a total of 3,143 subjects including 818 European-American (EA) cases with alcohol and nicotine co-dependence, 1,396 EA controls, 449 African-American (AA) cases, and 480 AA controls. We performed separate genome-wide association analyses in EAs and AAs and a meta-analysis to derive combined P-values, and calculated the genome-wide false discovery rate (FDR) for each SNP. Regions with P < 5 × 10(-7) together with FDR < 0.05 in the meta-analysis were examined to detect all replicable risk SNPs across EAs, AAs, and meta-analysis. These SNPs were followed with a series of functional expression quantitative trait locus (eQTL) analyses. We found a unique genome-wide significant gene region--SH3BP5-NR2C2--that was enriched with 11 replicable risk SNPs for alcohol and nicotine co-dependence. The distributions of -log(P) values for all SNP-disease associations within this region were consistent across EAs, AAs, and meta-analysis (0.315 ≤ r ≤ 0.868; 8.1 × 10(-52) ≤ P ≤ 3.6 × 10(-5)). In the meta-analysis, this region was the only association peak throughout chromosome 3 at P < 0.0001. All replicable risk markers available for eQTL analysis had nominal cis- and trans-acting regulatory effects on gene expression. The transcript expression of the genes in this region was regulated partly by several nicotine dependence (ND)-related genes and significantly correlated with transcript expression of many alcohol dependence- and ND-related genes. We concluded that the SH3BP5-NR2C2 region on Chromosome 3 might harbor causal loci for alcohol and nicotine co-dependence.
| S-EPMC3405545 | biostudies-literature
Project description:Alcohol dependence is associated with heightened risk tolerance and altered decision-making. This raises the question as to whether alcohol dependent patients (ADP) are incapable of proper risk assessment. We investigated how healthy controls (HC) and ADP engage neural networks to cope with the increased cognitive demands of risky decisions. We collected fMRI data while 34 HC and 16 ADP played a game that included "safe" and "risky" trials. In safe trials, participants accrued money at no risk of a penalty. In risky trials, reward and risk simultaneously increased as participants were instructed to decide when to stop a reward accrual period. If the participant failed to stop before an undisclosed time, the trial would "bust" and participants would not earn the money from that trial. Independent Component Analysis was used to identify networks engaged during the anticipation and the decision execution of risky compared with safe trials. Like HC, ADP demonstrated distinct network engagement for safe and risky trials at anticipation. However, at decision execution, ADP exhibited severely reduced discrimination in network engagement between safe and risky trials. Although ADP behaviorally responded to risk they failed to appropriately modify network engagement as the decision continued, leading ADP to assume similar network engagement regardless of risk prospects. This may reflect disorganized network switching and a facile response strategy uniformly adopted by ADP across risk conditions. We propose that aberrant salience network (SN) engagement in ADP might contribute to ineffective network switching and that the role of the SN in risky decisions warrants further investigation.
| S-EPMC4814760 | biostudies-literature
Project description:A novel systems approach was applied to transcriptome profiling that included the traditional analysis of differentially expressed genes, gene co-expression networks, cell type - specific transcriptomes and a wide range of gene annotations. By integrating our data with previous findings, we generated the first systems hypothesis of human alcoholism that integrates epigenetic regulation of gene expression with structural and functional alterations in alcoholic brain. Total RNA was extracted from human post-mortem brain and gene expression profiles were compared between alcoholics and matched controls.
2011-07-12 | E-GEOD-29555 | biostudies-arrayexpress
Project description:A novel systems approach was applied to transcriptome profiling that included the traditional analysis of differentially expressed genes, gene co-expression networks, cell type - specific transcriptomes and a wide range of gene annotations. By integrating our data with previous findings, we generated the first systems hypothesis of human alcoholism that integrates epigenetic regulation of gene expression with structural and functional alterations in alcoholic brain.
2011-07-12 | GSE29555 | GEO
Project description:Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD.
| S-EPMC4575063 | biostudies-literature
Project description:BackgroundThe organization of risk genes within signaling pathways may provide clues about the converging neurobiological effects of risk genes for alcohol dependence.AimIdentify risk genes and risk gene pathways for alcohol dependence.MethodsWe conducted a pathway-based genome-wide association study (GWAS) of alcohol dependence using a gene-set-rich analytic approach. Approximately one million genetic markers were tested in the discovery sample which included 1409 European-American (EA) alcohol dependent individuals and 1518 EA healthy comparison subjects. An additional 681 African-American (AA) cases and 508 AA healthy subjects served as the replication sample.ResultsWe identified several genome-wide replicable risk genes and risk pathways that were significantly associated with alcohol dependence. After applying the Bonferroni correction for multiple testing, the 'cellextracellular matrix interactions' pathway (p<2.0E-4 in EAs) and the PXN gene (which encodes paxillin) (p=3.9E-7 in EAs) within this pathway were the most promising risk factors for alcohol dependence. There were also two nominally replicable pathways enriched in alcohol dependence-related genes in both EAs (0.015≤p≤0.035) and AAs (0.025≤p≤0.050): the 'Na+/Cl- dependent neurotransmitter transporters' pathway and the 'other glycan degradation' pathway.ConclusionThese findings provide new evidence highlighting several genes and biological signaling processes that may be related to the risk for alcohol dependence.
| S-EPMC4466852 | biostudies-literature
Project description:OBJECTIVE:To report the genome-wide significant and/or replicable risk variants for alcohol dependence and explore their potential biological functions. METHODS:We searched in PubMed for all genome-wide association studies (GWASs) of alcohol dependence. The following three types of the results were extracted: genome-wide significant associations in an individual sample, the combined samples, or the meta-analysis (p?<?5?×?10(-8) ); top-ranked associations in an individual sample (p?<?10(-5) ) that were nominally replicated in other samples (p?<?.05); and nominally replicable associations across at least three independent GWAS samples (p?<?.05). These results were meta-analyzed. cis-eQTLs in human, RNA expression in rat and mouse brains and bioinformatics properties of all of these risk variants were analyzed. RESULTS:The variants located within the alcohol dehydrogenase (ADH) cluster were significantly associated with alcohol dependence at the genome-wide level (p?<?5?×?10(-8) ) in at least one sample. Some associations with the ADH cluster were replicable across six independent GWAS samples. The variants located within or near SERINC2, KIAA0040, MREG-PECR or PKNOX2 were significantly associated with alcohol dependence at the genome-wide level (p?<?5?×?10(-8) ) in meta-analysis or combined samples, and these associations were replicable across at least one sample. The associations with the variants within NRD1, GPD1L-CMTM8 or MAP3K9-PCNX were suggestive (5?×?10(-8) ?<?p?<?10(-5) ) in some samples, and nominally replicable in other samples. The associations with the variants at HTR7 and OPA3 were nominally replicable across at least three independent GWAS samples (10(-5) ?<?p?<?.05). Some risk variants at the ADH cluster, SERINC2, KIAA0040, NRD1, and HTR7 had potential biological functions. CONCLUSION:The most robust risk locus was the ADH cluster. SERINC2, KIAA0040, NRD1, and HTR7 were also likely to play important roles in alcohol dependence. PKNOX2, MREG, PECR, GPD1L, CMTM8, MAP3K9, PCNX, and OPA3 might play less important roles in risk for alcohol dependence based on the function analysis. This conclusion will significantly contribute to the post-GWAS follow-up studies on alcohol dependence.
| S-EPMC4187224 | biostudies-literature
Project description:Alcohol dependence is a serious and common public health problem. It is well established that genetic factors play a major role in the development of this disorder. Identification of genes that contribute to alcohol dependence will improve our understanding of the mechanisms that underlie this disorder.To identify susceptibility genes for alcohol dependence through a genome-wide association study (GWAS) and a follow-up study in a population of German male inpatients with an early age at onset.The GWAS tested 524,396 single-nucleotide polymorphisms (SNPs). All SNPs with P < 10(-4) were subjected to the follow-up study. In addition, nominally significant SNPs from genes that had also shown expression changes in rat brains after long-term alcohol consumption were selected for the follow-up step.Five university hospitals in southern and central Germany.The GWAS included 487 male inpatients with alcohol dependence as defined by the DSM-IV and an age at onset younger than 28 years and 1358 population-based control individuals. The follow-up study included 1024 male inpatients and 996 age-matched male controls. All the participants were of German descent.Significant association findings in the GWAS and follow-up study with the same alleles.The GWAS produced 121 SNPs with nominal P < 10(-4). These, together with 19 additional SNPs from homologues of rat genes showing differential expression, were genotyped in the follow-up sample. Fifteen SNPs showed significant association with the same allele as in the GWAS. In the combined analysis, 2 closely linked intergenic SNPs met genome-wide significance (rs7590720, P = 9.72 x 10(-9); rs1344694, P = 1.69 x 10(-8)). They are located on chromosome region 2q35, which has been implicated in linkage studies for alcohol phenotypes. Nine SNPs were located in genes, including the CDH13 and ADH1C genes, that have been reported to be associated with alcohol dependence.This is the first GWAS and follow-up study to identify a genome-wide significant association in alcohol dependence. Further independent studies are required to confirm these findings.
| S-EPMC4229246 | biostudies-literature
Project description:It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene-set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol-dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the 'synthesis and degradation of ketone bodies' pathway. Our results also support the potential involvement of the 'neuroactive ligand-receptor interaction' pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence.
| S-EPMC3854955 | biostudies-literature