The genetics of alcohol dependence: advancing towards systems-based approaches.
- Authors
- Palmer, R H C; McGeary, J E; Francazio, S; Raphael, B J; Lander, A D; Heath, A C; Knopik, V S
- Year
- 2012
- Journal
- Drug and alcohol dependence
- PMID
- 22854292
- DOI
- 10.1016/j.drugalcdep.2012.07.005
- PMCID
- PMC3470479
Personalized treatment for psychopathologies, in particular alcoholism, is highly dependent upon our ability to identify patterns of genetic and environmental effects that influence a person's risk. Unfortunately, array-based whole genome investigations into heritable factors that explain why one person becomes dependent upon alcohol and another does not, have indicated that alcohol's genetic architecture is highly complex. That said, uncovering and interpreting the missing heritability in alcohol genetics research has become all the more important, especially since the problem may extend to our inability to model the cumulative and combinatorial relationships between common and rare genetic variants. As numerous studies begin to illustrate the dependency of alcohol pharmacotherapies on an individual's genotype, the field is further challenged to identify new ways to transcend agnostic genomewide association approaches. We discuss insights from genetic studies of alcohol related diseases, as well as issues surrounding alcohol's genetic complexity and etiological heterogeneity. Finally, we describe the need for innovative systems-based approaches (systems genetics) that can provide additional statistical power that can enhance future gene-finding strategies and help to identify heretofore-unrealized mechanisms that may provide new targets for prevention/treatments efforts. Emerging evidence from early studies suggest that systems genetics has the potential to organize our neurological, pharmacological, and genetic understanding of alcohol dependence into a biologically plausible framework that represents how perturbations across evolutionarily robust biological systems determine susceptibility to alcohol dependence.
Example of a Theoretical Network Model for Alcohol DependenceThis adapted figure from Koob and Volkow (2010) is used to illustrate an example of a theoretical systems model showing genes involved in alcohol metabolism and alcohol’s effect on the brain’s reward pathway. Note that for the sake of simplicity, the figure does not represent all of the pathways involved, for example, projections from the ventral tegmental area to the amygdala and hippocampus. The figure depicts each of the three components of addiction (intoxication, withdrawal, and Preoccupation), which are mediated by different neurotransmitters and systems that are compromised by alcohol; solid and dotted lines indicate glutamatergic projections, dashed arrows represent dopaminergic projections. Abbreviations. Acb - nucleus accumbens; BNST - bed nucleus of the stria terminalis; CeA - central nucleus of the amygdala; CRF - corticotropin-releasing factor; DGP - dorsal globus pallidus; NE - norepinephrine; SNc - substantia nigra pars compacta; VGP - ventral globus pallidus; VTA, ventral tegmental area. Based on the segments shown, the presence of alcohol in the system is limited by the genetic profile of the metabolic system, while alcohol’s effect on the reward pathway is limited by variation in GABAergic transmission, glutamate transmission, and dopamine transmission. Gene names shown in italics indicates possible sources of variation in the system. Adapted by permission from Macmillan Publishers Ltd: Neuropsychopharmacology (Koob, G.F., Volkow, N.D., 2010. Neurocircuitry of addiction. Neuropsychopharmacology 35, 217–238.), copyright 2010.
Example of a Generic Network ModelVisualization of the results of a typical network model analysis. Nodes (with the letters A thru H) represent variables. Edges represent pathways though which perturbations within each variable propagate through the system.
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| 20 | 3. Insights and Limitations from GWAS of AD — 3.2 Gene-Gene Interactions (Epistasis) | modest evidence of statistical epistatic effects on AD in the human literature, possibly because of… |
| 21 | 3. Insights and Limitations from GWAS of AD — 3.2 Gene-Gene Interactions (Epistasis) | SNPs, each with three genotypes (i.e., AA, Aa, and aa), would have nine possible genotypes, while a… |
| 22 | 3. Insights and Limitations from GWAS of AD — 3.2 Gene-Gene Interactions (Epistasis) | Non-parametric methods (e.g., data mining, machine learning, and neural network modeling) have been… |
| 23 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD | Missing heritability in AD GWAS is also attributable to the fact that AD’s liability is… |
| 24 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD | every GWAS of AD has had to average the score across individuals with different aspects of an… |
| 25 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD — 3.3.1 Using Comorbidity to Understand Heterogeneity | One approach to understanding the phenotypic/etiological complexity of alcohol is to understand the… |
| 26 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD — 3.3.1 Using Comorbidity to Understand Heterogeneity | symptoms and novelty seeking tendencies were more likely to exhibit high levels of alcohol, tobacco,… |
| 27 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD — 3.3.2 The Endophenotype Approach | The primary approach to overcoming etiological heterogeneity has been the use of endophenotypes… |
| 28 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD — 3.3.2 The Endophenotype Approach | 1994; Schuckit et al., 2004)), alcohol metabolism (Lind et al., 2008b; Martin et al., 1985a; Martin… |
| 29 | 3. Insights and Limitations from GWAS of AD — 3.3 The Phenotypic and Genetic Complexity of AD — 3.3.2 The Endophenotype Approach | inherently destined to consume low/high amounts of alcohol. Likewise, there are many genes located… |
| 30 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.1 The Need for Genomewide Systems-based Studies of AD | Alcohol’s genetic complexity highlights the need for comprehensive models that account for the… |
| 31 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.1 The Need for Genomewide Systems-based Studies of AD | Association Studies) over individual pathway or gene-set enrichment approaches because it… |
| 32 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.1 The Need for Genomewide Systems-based Studies of AD | In addition to GWAS data network-based models can be made to incorporate micro-array/RNA-Seq (i.e.,… |
| 33 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.1 The Need for Genomewide Systems-based Studies of AD | and the transcriptome of select tissue as a whole, we would obtain effects that are more robust. For… |
| 34 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.1 The Need for Genomewide Systems-based Studies of AD | trimethylation (H3K4me3) data to identify expression differences in post-mortem hippocampus tissue… |
| 35 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.2 Including the Environment as a Part of the System | Although not the focus of this paper, it is important that we mention the environment as a key… |
| 36 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.2 Including the Environment as a Part of the System | development of AD. For instance, genetic effects on drinking has been shown to be greater in urban… |
| 37 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.2 Including the Environment as a Part of the System | shown that a person’s genes influence their exposure to 1) alcohol, and 2) their exposure to peers… |
| 38 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.2 Including the Environment as a Part of the System | AD with other psychiatric disorders (Heath and Nelson, 2002). While there have been several advances… |
| 39 | 4. ACHIEVING A SYSTEMS-BASED APPROACH TO STUDYING AD — 4.3 The Integration of Biology into Novel Statistical and Computational Approaches | Current approaches to capturing the missing heritability of complex diseases involve the application… |
| Name | Type |
|---|---|
| acetic acid | drug |
| acetylcholine | drug |
| addiction | phenotype |
| addiction phenotypes | phenotype |
| AD GWAS | cohort |
| ADH | gene |
| ADH1B | gene |
| ADH1C | gene |
| adult antisocial behavior | phenotype |
| African American | cohort |
| alcohol | phenotype |
| alcohol dehydrogenase | gene |
| alcohol dependence | phenotype |
| Alcohol habit local | phenotype |
| alcoholism | phenotype |
| alcohol metabolism | phenotype |
| Alcohol Problems | phenotype |
| alcohol-related diseases | phenotype |
| alcohol-related phenotypes | phenotype |
| Alcohol reward | phenotype |
| alcohol sensitivity | phenotype |
| Alcohol susceptibility genes local | gene |
| Alcohol Use | phenotype |
| Alcohol Use Disorder | phenotype |
| ALDH2 | gene |
| alpha power | phenotype |
| Alpha wave local | phenotype |
| Alzheimer's disease | phenotype |
| Alzheimer's disease susceptibility local | phenotype |
| amygdala | anatomy |
| animal models | cohort |
| ANKK1 | gene |
| antisocial personality disorder | phenotype |
| AUTS2 | gene |
| basal ganglia | anatomy |
| behavioral disinhibition | phenotype |
| behavioral variation local | phenotype |
| Beta wave local | phenotype |
| Binge/Intoxication Stage local | phenotype |
| body mass index | phenotype |
| cancer | phenotype |
| cancer phenotypes | phenotype |
| cannabis dependence | phenotype |
| cannabis use | phenotype |
| Catalase | gene |
| causal variants | cohort |
| cerebellum | anatomy |
| childhood conduct disorder | phenotype |
| CHRM2 | gene |
| cocaine | phenotype |
| Collaborative Studies on the Genetics of Alcoholism | cohort |
| Collaborative Study on the Genetics of Alcoholism (COGA) | cohort |
| common variants | cohort |
| COMT | gene |
| conduct disorder | phenotype |
| controls | cohort |
| control subjects | cohort |
| copy number variants | variant |
| coronary artery disease | phenotype |
| corticotropin-releasing factor | drug |
| Corticotropin-releasing factor system local | drug |
| craving | phenotype |
| CRF | drug |
| cumulative genetic risk scores local | drug |
| CYP2E1 | gene |
| disease state | phenotype |
| dopamine | drug |
| Dopaminergic system | drug |
| dorsolateral prefrontal cortex | anatomy |
| DRD2 | gene |
| DRD4 | gene |
| drinking | phenotype |
| Drinking phenotypes local | phenotype |
| Drosophila insertion mutants local | cohort |
| drug dependence | phenotype |
| drug-seeking behavior | phenotype |
| EEG | phenotype |
| endogenous opioids | drug |
| endophenotype | phenotype |
| epigenetic factor local | drug |
| ethanol consumption | phenotype |
| European ancestry | cohort |
| event-related potential | phenotype |
| Event related potentials local | phenotype |
| Exposure to alcohol local | phenotype |
| Exposure to peers who use alcohol local | phenotype |
| extended amygdala | anatomy |
| externalizing behavior | phenotype |
| Externalizing psychopathologies local | phenotype |
| Extra-hypothalamic corticotrophin releasing factor system local | anatomy |
| Family-based whole-genome studies local | cohort |
| Fatty acid ethyl ester local | drug |
| First-degree relatives of alcohol dependent cases local | cohort |
| forebrain | anatomy |
| Fowler 2007 twin study local | cohort |
| GABA | phenotype |
| GABAA receptor | drug |
| GABRA2 | gene |
| gene | gene |
| generalized anxiety disorder | phenotype |
| genes | gene |
| Genes identified in Mulligan’s study local | gene |
| genetic factor local | drug |
| genetic variants | cohort |
| glutamate | drug |
| GRIN2B | gene |
| height | phenotype |
| High-risk background local | phenotype |
| hippocampus | anatomy |
| human alcoholics | phenotype |
| human brain | anatomy |
| Hypodopaminergic state local | phenotype |
| internalizing disorders | phenotype |
| Kendler2003 local | cohort |
| Kendler 2011 GWAS local | cohort |
| Kendler et al. 2011 GWAS local | cohort |
| light drinkers | phenotype |
| Liver cirrhosis | phenotype |
| major depressive disorder | phenotype |
| MAOA | gene |
| marital status | phenotype |
| maximum drinks | phenotype |
| Mesolimbic dopamine neurons local | anatomy |
| Mesolimbic dopamine-neurons local | anatomy |
| missing heritability | phenotype |
| Molecular Genetics of Schizophrenia Control Sample local | cohort |
| Mulligan’s study (2006) local | cohort |
| multiple sclerosis | phenotype |
| mutations | variant |
| neuropeptide Y | drug |
| next generation sequencing local | drug |
| novelty seeking | phenotype |
| Novelty seeking tendencies local | phenotype |
| nucleus accumbens | anatomy |
| opioid | drug |
| Opioid antagonists local | drug |
| Opioid system | drug |
| OPRK1 | cohort |
| OPRM1 | cohort |
| other drug dependence | phenotype |
| other drugs | drug |
| P300 amplitude | phenotype |
| P300 measures | phenotype |
| Palmer2011 local | cohort |
| phobic anxiety | phenotype |
| Phospholipase D local | gene |
| prefrontal cortex | anatomy |
| problem use | phenotype |
| proteomic factor local | drug |
| psychiatric disorders | phenotype |
| rare variant | cohort |
| reward system | anatomy |
| risk allele | cohort |
| rodent studies | cohort |
| rs279871 | variant |
| serotonin | drug |
| Serotonin system local | drug |
| single nucleotide polymorphism | variant |
| SLC6A4 | gene |
| SNP | cohort |
| SNPs (genotyping platform) local | variant |
| striatum | anatomy |
| structural variant | cohort |
| Substance abusing peers local | phenotype |
| Theta-band oscillations local | phenotype |
| tobacco dependence | phenotype |
| tobacco use | phenotype |
| transcriptomic factor local | drug |
| Twin cohort (862 twin pairs) local | cohort |
| United States of America local | cohort |
| Urge sensitivity profile local | phenotype |
| ventral tegmental area | anatomy |
| voluntary alcohol consumption | phenotype |
| whole brain | anatomy |
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External
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