Abstract
Tobacco smoking is a leading preventable cause of death in the United States and produces a major health and economic burden. Although the majority of smokers want to quit, few are successful. These data highlight the need for additional research into the neurobiology of tobacco dependence. Addiction to nicotine, the main psychoactive component of tobacco, is influenced by multiple factors that include individual differences in genetic makeup. Twin studies have demonstrated that genetic factors can influence vulnerability to nicotine addiction, and subsequent research has identified genes that may alter sensitivity to nicotine. In humans, genome-wide and candidate gene association studies have demonstrated that genes encoding nicotinic acetylcholine receptor (nAChR) proteins are associated with multiple smoking phenotypes. Similarly, research in mice has provided evidence that naturally occurring variability in nAChR genes is associated with changes in nicotine sensitivity. Furthermore, the use of genetic knockout mice has allowed researchers to determine the nAChR genes that mediate the effects of nicotine, whereas research with knockin mice has demonstrated that changes to nAChR genes can dramatically alter nicotine sensitivity. This review will examine the genetic factors that alter susceptibility to nicotine addiction, with an emphasis on the genes that encode nAChR proteins.
Keywords: Genetics, Nicotine, Addiction, Withdrawal, Acetylcholine, Mice
Introduction
The negative health and economic consequences of tobacco use have been well established [17, 137]; however, tobacco smoking causes more deaths worldwide per year than all other drugs combined [136]. In the United States, the majority of smokers (68%) report that they want to quit smoking, but only 5% are successful [16, 116]. Although pharmacotherapeutics for smoking cessation such as nicotine replacement therapy, bupropion, and varenicline are currently available, these drugs only produce a 1.5 to 3 fold increase in the likelihood of successfully quitting [14, 72, 153]. Given that the rates for successfully quitting smoking are low even with pharmacotherapeutic intervention, there is a clear need for additional research into the neurobiology of tobacco dependence.
Addiction to nicotine, the main psychoactive component of tobacco [4], produces numerous changes to behavioral and neural functioning [76, 131] that can be modulated by environmental, developmental, and genetic factors [3, 18, 67]. Research has demonstrated that having family or peers that smoke will increase the likelihood of ever smoking [62, 63]. Furthermore, epidemiological studies suggest that adolescents are more vulnerable to nicotine addiction: 88% of smokers tried their first cigarette before age 18, and the development of daily cigarette smoking typically occurs before age 25 [10, 41]. There is also considerable evidence that genetics influence several smoking-related behaviors. Twin studies have been used extensively to estimate genetic contributions to smoking-related behaviors, such as persistent or current smoking (i.e. long-term continuous tobacco use), number of cigarettes smoked daily, and diagnosed nicotine dependence. Heritability estimates for these smoking phenotypes range from 39 – 82% for persistent smoking [93, 100, 101, 175], 45 – 86% for number of cigarettes smoked daily [65, 83, 164, 178], and 31 – 75% for nicotine dependence [80, 115, 176, 179]. In addition, genetic factors also influence nicotine withdrawal symptoms and failed smoking cessation: heritability estimates for nicotine withdrawal symptoms range from 29 – 53%, whereas estimates for smoking cessation are 51 – 54% [91, 127, 188, 189]. Overall, these data suggest that genetics play an important role in smoking-related behaviors, and therefore an improved understanding of the genetics of nicotine addiction will aid in the development of effective smoking cessation treatments.
In recent years, research has demonstrated that genes that encode nicotinic acetylcholine receptor (nAChR) proteins may play an important role in susceptibility to nicotine addiction. Genome-wide linkage analyses have identified several loci across the human genome that may contain genes that increase vulnerability to a given smoking-related behavior or symptom, such as nicotine dependence or the number of cigarettes smoked. nAChR subunit genes have been found within or near these loci, suggesting that variability in these genes may alter sensitivity to nicotine addiction. Furthermore, candidate gene association studies have demonstrated that variability in genes that encode nAChR subunits are associated with multiple smoking phenotypes. Animal research has also provided insight into genetics of nicotine addition: numerous studies have evaluated the effects of acute nicotine, chronic nicotine, and nicotine withdrawal in mice with genetically modified nAChR subunits, and several studies have investigated whether naturally occurring variability in nAChR subunit genes can influence sensitivity to the effects of nicotine. Thus, research in both humans and animals suggest that genes involved in cholinergic functioning play an important role in altering risk for nicotine addiction, and a more complete understanding of how these genes influence nicotine sensitivity may lead to development of more effective therapeutics for nicotine addiction.
Genome-wide Linkage Analyses
A genome-wide linkage study is an unbiased search for regions across the entire human genome that are strongly associated with a given phenotype (e.g. the number of cigarettes smoked daily). Such studies are ideally conducted using hundreds of large families that contain both smokers and non-smokers, and loci that are similar in affected relatives and dissimilar with non-affected relatives are thought to contain genes that may increase vulnerability to smoking-related behaviors. Associations between genetic variability and a smoking phenotype are plotted as peaks at specific loci across the genome, and the magnitude of the effect is typically determined by a logarithm of the odds (LOD) score. Given that loci identified in linkage analyses are often not replicated in subsequent investigations, Lander and Kruglyak [87] have developed guidelines to evaluate the strength of a reported linkage. The criterion for “significant linkage” depends upon the design of the genome-wide linkage study, and is defined as LOD scores greater than 3.3 – 3.8 or a p value less than 4.9 × 10−5 – 1.3 × 10−5, whereas the criterion for “suggestive linkage” also depends upon the study design, and is defined as LOD scores greater than 1.9 – 2.4 or a p value less than 1.7 × 10−3 – 4.2 × 10−4 [87]. For example, in a linkage study that examines allele sharing between sibling pairs, the criterion for significant linkage is defined as an LOD score that is greater than 3.6 or a p < 2 × 10−5, whereas “suggestive linkage” is defined as LOD scores that range from 2.2 – 3.6, or a p < 7 × 10−4.
Linkage studies have evaluated several smoking phenotypes, such as smoking initiation [120, 178], the number of cigarettes smoked daily (smoking quantity) [92, 96, 95, 120, 165, 182], nicotine dependence [50, 96, 95, 98, 165], and withdrawal severity [165], and overall, one or more regions in nearly all chromosomes have been implicated in smoking-related behaviors. Furthermore, nAChR subunit genes have been found within some of the loci identified in linkage studies, suggesting that these genes may warrant further investigation. Using the criteria established by Lander and Kruglyak [87], suggestive linkage has been found for smoking initiation on chromosome 6 in a sample of Dutch twins [178]; other research has implicated chromosomes 16 and 20, but p values were below the criteria for suggestive linkage [120]. In addition, significant linkage to smoking quantity has been found in regions located on chromosomes 1 and 10–12, whereas chromosomes 3–5, 7–9, 13, 16, 17, 18, and 20 exhibit suggestive linkage to smoking quantity [92, 96, 95, 120, 165, 182]. Several linkage studies have also evaluated nicotine dependence (defined using the Fagerström Test for Nicotine Dependence; FTND, or defined using the DSM-IV), and suggestive linkage for nicotine dependence has been found in regions of chromosomes 3–11, and 20 [50, 96, 95, 98, 165]. Additionally, the genes that encode the α2 and α10 nAChR subunits (CHRNA2 and CHRNA10, respectively) were found within the loci associated with nicotine dependence, suggesting that these genes may influence susceptibility to nicotine addiction [98, 165]. Finally, Swan and colleagues [165] reported suggestive linkage between a region on chromosome 6 and the severity of nicotine withdrawal, and significant linkage to short term quitting (defined as quitting smoking for > 1 month but < 1 year) was found on chromosome 16.
Overall, the data from genome-wide linkage studies reveal that nicotine addiction is a complex disorder that is modulated by numerous genes distributed throughout the human genome, as well as by the interactions between these genes. However, similar to investigations of other complex disorders, few of the loci implicated by linkage studies have been replicated in subsequent research. Several factors likely contribute to this inconsistency across studies. For example, the loci that are implicated in a given smoking-related behavior may vary as function of ethnicity or gender, and it may be difficult to detect these differences if the subject pool is heterogeneous. In support, research has identified different loci for nicotine dependence in samples with European American or African American ancestry [50, 96], and combining both samples decreased the ability to detect some loci [96], which suggests that genetically heterogeneous samples may mask the detection of regions that are ethnicity-specific. Other factors that may limit the replicability of linkage studies are differences in defining phenotypes, the statistical methods used, and differences in sample size. Despite these limitations, genome-wide linkage studies have provided a useful starting point for the identification of genes that may influence smoking phenotypes. Several genes that encode receptors are located within or near the regions implicated by linkage studies, including the CHRNA2 and CHRNA10 nAChR subunit genes, dopamine receptors 1 and 4 (DRD1 and DRD4, respectively), the μ1 opioid receptor (OPRM1), and the GABAB receptor subunit 2 (GABAB2) [95, 98, 165, 180]. Thus, numerous candidate and genome-wide gene association studies have evaluated whether variations in these genes are related to smoking phenotypes.
Nicotinic Acetylcholine Receptors: Candidate Gene and Genome-Wide Association Studies
The effects of nicotine are primarily mediated by its actions on nicotinic acetylcholine receptors (nAChR); thus, single nucleotide polymorphisms (SNPs) in genes that encode nAChRs are likely to modulate the effects of nicotine. nAChRs are ligand-gated cation channels that are composed of 5 subunits, and can exist either as homopentamers or heteropentamers (i.e. 5 identical subunits or 5 non-identical subunits, respectively) [68, 90]. Currently, 12 neuronal and 5 muscle nAChR subunits have been identified (Neuronal: α2 – α10, β2 – β4; Muscle: α1, β1, γ, δ, and ε), and research has demonstrated that the α4, β2, and α7 nAChR subunits are the most abundantly expressed in the brain [68, 90]. nAChR subtypes, such as the α4β2*1 and α7 receptors, exhibit functional diversity in their rate of desensitization, binding affinity, and cation permeability [25, 46, 125]. For instance, α4β2* nAChR subtypes bind with high affinity to nicotine and desensitize at a slow rate, whereas α7 subtypes have a lower affinity for nicotine and desensitize rapidly [25, 46]. Thus, the various behavioral and neural effects of nicotine are likely to be mediated by different nAChR subtypes.
Several candidate gene association studies have investigated whether polymorphisms in the genes that encode neuronal nAChR subunits (CHRNA2 – CHRNA10, and CHRNB2 – CHRNB4) are associated with increased or decreased vulnerability to smoking-related behaviors. In candidate gene studies, researchers determine whether one or more alleles in a gene of interest appear more frequently in smokers than in non-smokers. There are several advantages to using this approach. Unlike genome-wide linkage studies, association studies can be conducted using a case-control design (comparing unrelated smokers to non-smokers) or with family-based designs (comparing allele sharing between smokers and their parents or between siblings). Additionally, candidate gene studies may be a more effective approach for identifying genes that produce small changes in risk for smoking phenotypes [138]. One limitation of using the candidate gene approach is that the genes selected for investigation typically depend upon what is currently known about nicotine addiction, and other genes that may also play an influential role can be overlooked. An additional limitation to candidate gene association studies is that false positive results can occur in case-control studies because smoker and non-smoker groups may consist of individuals from diverse genetic backgrounds (i.e. population stratification), and therefore researchers must evaluate the genetic similarity of both groups to control for this issue [161].
Recent advances in genotyping, along with development of databases of genetic variability in the human genome (e.g. the dbSNP database), have led to the development of the genome-wide association studies, which can evaluate thousands of SNPs distributed across the human genome [66, 184]. Similar to a candidate gene association study, allele frequencies in unrelated smokers are compared to controls in a genome-wide association study. However, the focus in a genome-wide association study is not alleles in a particular gene but instead is an unbiased assessment of allele frequencies that are distributed throughout the entire human genome [66, 184]. The unbiased selection of alleles across the human genome is one major advantage to this approach: genes that have been overlooked by candidate gene studies may be identified as playing a role in altering risk for nicotine addiction. However, several issues must be taken into consideration when implementing a genome-wide association study. For instance, it has been recommended that a p-value of 1 × 10−6 be used because of the numerous statistical tests used in genome-wide association studies [184]. Furthermore, a large subject pool is needed so that there is sufficient statistical power to detect gene variants that are associated with a phenotype, and the potential for population stratification between cases and controls must also be assessed [66]. Finally, the independent replication of findings in subsequent genome-wide association studies can verify that the genes identified are not false positives [66, 184].
The α4 nAChR subunit (CHRNA4)
Candidate gene association studies have yielded evidence that several variants of CHNRA4 are protective against smoking-related behaviors (see Table 1 for a summary of candidate gene association studies). A study using a sample of Chinese men identified 2 SNPs (rs1044396 and rs1044397) in exon 5 of CHRNA4 that were associated with reduced risk for nicotine dependence [45]. Both SNPs were synonymous2 and a haplotype of 6 SNPs that included both of the protective variants also was associated with reduced risk for nicotine dependence. Additionally, four SNPs and a haplotype in CHRNA4 have been identified in European Americans and African Americans that were associated with smoking-related behaviors, but the effects varied as a function of ethnicity or gender [94]. Specifically, one synonymous SNP (rs1044396) located in exon 5 was associated with smoking quantity in European Americans, whereas an additional SNP (rs3787137) located in intron 5 was associated with smoking quantity in European American men only. Furthermore, a SNP (rs2236196) located in the 3’ untranslated region (UTR) was associated with nicotine dependence in African American women, and a fourth SNP (rs2273504) was associated with nicotine dependence in African and European American women. A haplotype that consisted of 3 SNPs (including both protective variants of rs2273504 and rs2236196) was found to reduce risk for nicotine dependence in African American women [94].
Table 1.
Summary of Candidate Gene Association Studies
| Gene/SNP ID | Sample | Alleles | Location | Phenotypes | References |
|---|---|---|---|---|---|
| CHRNA3 | |||||
| rs578776 | Austrialians/Americans (European Ancestry) | G/A | 3′UTR | FTND | Saccone et al., 2007 |
| rs1051730 | Austrialians/Americans (European Ancestry) | G/A | Exon (Syn) | FTND | Saccone et al., 2007 |
| rs3743078 | Austrialians/Americans (European Ancestry) | G/C | Intron | FTND | Saccone et al., 2007 |
| rs6495308 | European Ancestry | C/T | Intron | SQ | Berrettini et al., 2008 |
| rs1317286 | European Ancestry | G/A | Intron | SQ | Berrettini et al., 2008 |
| rs1051730 | European Ancestry | G/A | Exon (Syn) | Lung Cancer | Amos et al., 2008 |
| rs1051730 | European Ancestry | G/A | Exon (Syn) | SQ | Thorgeirsson et al., 2008 |
| rs1051730 | European Ancestry | G/A | Exon (Syn) | FTND, DSM-IV Nicotine Dependence | Thorgeirsson et al., 2008 |
| rs1051730 | European Ancestry | G/A | Exon (Syn) | Lung Cancer | Thorgeirsson et al., 2008 |
| rs1051730 | European Ancestry | G/A | Exon (Syn) | Peripheral Arterial Disease | Thorgeirsson et al., 2008 |
| rs1051730 | Diverse | G/A | Exon (Syn) | Lung Cancer | Hung et al., 2008 |
| CHRNA4 | |||||
| rs1044396 | Chinese Men | C/T | Exon (Syn) | FTND, RTQ, Nicotine Addiction | Feng et al., 2004 |
| rs1044397 | Chinese Men | G/A | Exon (Syn) | FTND, RTQ, Nicotine Addiction | Feng et al., 2004 |
| rs1044396 | European Americans | C/T | Exon (Syn) | SQ | Li et al., 2005 |
| rs3787137 | European American Men | G/A | Intron | SQ | Li et al., 2005 |
| rs2236196 | African American Women | G/A | 3′ UTR | SQ, HSI, FTND | Li et al., 2005 |
| rs2273504 | African and European American Women | G/A | Intron | FTND | Li et al., 2005 |
| rs2236196 | Diverse (80% Caucasian) | C/T | 3′ UTR | Subjective Responses, Smoking Cessation | Hutchison et al., 2007 |
| rs6122429 | Diverse (80% Caucasian) | G/A | Promotor Region | Subjective Responses | Hutchison et al., 2007 |
| CHRNA5 | |||||
| rs16969968 | Austrialians/Americans (European Ancestry) | G/A | Exon (NSyn) | FTND | Saccone et al., 2007 |
| rs637137 | Austrialians/Americans (European Ancestry) | A/T | Intron | FTND | Saccone et al., 2007 |
| rs684513 | Austrialians/Americans (European Ancestry) | G/C | Intron | FTND | Saccone et al., 2007 |
| rs514743 | Diverse (72% Caucasian) | A/T | Intron | Smoking Initiation | Schlaepfer et al., 2007 |
| rs16969968 | Diverse | G/A | Exon (NSyn) | Lung Cancer | Hung et al., 2008 |
| CHRNA6 | |||||
| rs2304297 | Austrialians/Americans (European Ancestry) | G/C | 3′UTR | FTND | Saccone et al., 2007 |
| rs2304297 | Diverse (74% Caucasian) | G/C | 3′UTR | Subjective Responses | Zeiger et al., 2007 |
| CHRNB2 | |||||
| rs2072660 | Israeli Women | C/T | 3′UTR | Smoking Initiation | Greenbaum et al., 2006 |
| rs2072658 | Diverse (72% Caucasian) | G/A | Near Gene | Subjective Responses | Ehringer et al., 2007 |
| rs2072660 | Diverse (72% Caucasian) | C/T | 3′UTR | Subjective Responses | Ehringer et al., 2007 |
| CHRNB3 | |||||
| rs13277254 | Austrialians/Americans (European Ancestry) | G/A | Intron | FTND | Bierut et al., 2007 |
| rs6474413 | Austrialians/Americans (European Ancestry) | C/T | Promotor Region | FTND | Bierut et al., 2007 |
| rs10958726 | Austrialians/Americans (European Ancestry) | G/T | Promotor Region | FTND | Saccone et al., 2007 |
| rs6474413 | Austrialians/Americans (European Ancestry) | C/T | Promotor Region | FTND | Saccone et al., 2007 |
| rs4953 | Austrialians/Americans (European Ancestry) | G/C | Exon (Syn) | FTND | Saccone et al., 2007 |
| rs4952 | Austrialians/Americans (European Ancestry) | C/T | Exon (Syn) | FTND | Saccone et al., 2007 |
| rs4950 | Diverse (74% Caucasian) | G/A | Exon (Syn) | Subjective Responses | Zeiger et al., 2007 |
| rs13280604 | Diverse (74% Caucasian) | G/A | Intron | Subjective Responses | Zeiger et al., 2007 |
| hCV25772398 | Diverse (74% Caucasian) | C/T | Intron | Subjective Responses | Zeiger et al., 2007 |
| rs4953 | Diverse (74% Caucasian) | G/C | Exon (Syn) | Subjective Responses | Zeiger et al., 2007 |
| CHRNB4 | |||||
| rs3813567 | Austrialians/Americans (European Ancestry) | G/A | Near Gene | FTND | Saccone et al., 2007 |
| rs1948 | Diverse (72% Caucasian) | C/T | 3′ UTR | Smoking Initiation | Schlaepfer et al., 2007 |
| rs8023462 | Diverse (72% Caucasian) | C/T | Intergenic | Smoking Initiation | Schlaepfer et al., 2007 |
Legend: A = Adenine; C = Cytosine; G = Guanine; T = Thymine; Syn = Synonymous SNP; NSyn = Non-synonymous SNP; UTR = Untranslated Region FTND = Fagerström test for nicotine dependence; RTQ = Revised Tolerance Questionnaire; SQ = Smoking Quantity; HSI = Heaviness of Smoking Index
Hutchison and colleagues [75] have identified SNPs in CHRNA4 in smokers that were associated with subjective responses to smoking. Following an 8 hour abstinence period, participants smoked a cigarette and rated the effects of smoking on 4 dimensions (physical effects, cognitive effects, rush or high, and reward); participants with a heterozygous genotype at SNP rs2236196 (i.e. possessed both variants of this SNP) exhibited an increased sensitivity to all 4 subjective measures of smoking. Additional analyses of this SNP revealed that nicotine nasal spray was a more effective smoking cessation aid than a transdermal nicotine patch in individuals that were heterozygous. Furthermore, an additional SNP (rs6122429) was identified that was associated with increased sensitivity to the rewarding effects of smoking [75]. Together, the results of these studies suggest that variation in CHRNA4 can influence several smoking phenotypes, including the physical, cognitive, and rewarding properties of smoking. However, it is also evident that the effects of some SNPs or haplotypes may depend upon ethnicity or gender, whereas other SNPs may have similar effects across all groups. For instance, Li and colleagues [94] identified different SNPs in African vs. European Americans that were associated with nicotine dependence, but other SNPs such as rs2236196 have been associated with smoking phenotypes in several ethnic groups [75].
The β2 nAChR subunit (CHRNB2)
Given that α4β2* nAChRs are the predominant high-affinity binding sites for nicotine in the brain [47], and that research using genetic knockout (KO) mice has revealed that mice lacking the β2 nAChR subunit have almost no high-affinity binding for nicotine [129], several studies have investigated whether polymorphisms in CHRNB2 are related to smoking phenotypes. In contrast to research on CHRNA4, evidence for the role of CHRNB2 in smoking phenotypes has been less robust; several studies have found no relation between CHRNB2 polymorphisms and nicotine dependence [45, 94, 99, 154]. However, Greenbaum and colleagues [61] identified one SNP (rs2072660) located in the 3’ UTR, along with a 5 SNP haplotype, that was associated with reduced risk for smoking initiation in Israeli females. Furthermore, a recent study investigated the relation between CHRNB2 and initial subjective responses to smoking (e.g. feeling dizzy or nauseous after smoking) and identified one SNP (rs2072658) located upstream of the CHRNB2 gene that was associated with an increased response to the negative effects of smoking, whereas another SNP (rs2072660) located in the 3’ UTR was associated with a reduced subjective response to the negative effects of smoking [40]. Thus, the results from these studies suggest that polymorphisms in CHRNB2 may also modulate smoking-related behaviors. Given that several studies were unable to find any relation between CHRNB2 and smoking phenotypes, it is possible that its effect on smoking-related behaviors is small or may depend upon the expression of other genes. For example, CHRNB2 may interact with other genes such as CHRNA4 to influence nicotine dependence. Therefore, future research should investigate possible epistatic effects between CHRNB2 and other genes.
The CHRNB3-CHRNA6 and CHRNA5-CHRNA3-CHRNB4 Gene Clusters
Research using genome-wide association and candidate gene approaches has demonstrated that polymorphisms in the CHRNB3-CHRNA6 gene cluster on chromosome 8 are strongly associated with nicotine dependence. Bierut and colleagues [8] evaluated 31,960 SNPs for associations with nicotine dependence (measured using the FTND); 2 SNPs in the CHRNB3 gene (rs13277254 and rs6474413) were associated with risk for nicotine dependence. This finding was supported by a candidate gene association study of 348 genes that was conducted simultaneously by the same group: 2 SNPs located in the 5’ promoter region of CHRNB3 (rs10958726 and rs6474413), 2 synonymous SNPs located in exon 5 of CHRNB3 (rs4953 and rs4952) and 1 SNP in CHRNA6 (rs2304297) were strongly associated with risk for nicotine dependence [142]. Furthermore, an additional candidate gene association study identified four SNPs in CHRNB3 (rs4950, rs13280604, hCV25772398, rs4953) that were associated with adverse (e.g. feeling depressed or paranoid after smoking) and positive (e.g. feeling energetic or sociable after smoking) subjective responses to smoking, and these effects were replicated for 2 SNPs (rs4950 and rs13280604) in a separate sample [192]. Additionally, one SNP in CHRNA6 (rs2304297) was associated with positive subjective responses to smoking in one sample. Overall, these data provide strong evidence that SNPs in CHRNB3 and possibly CHRNA6 are related to multiple smoking phenotypes. Given that the α6 and β3 subunits are highly expressed in the ventral tegmental area (VTA) and the nucleus accumbens (NAC), which are brain areas implicated in the rewarding effects of nicotine [82, 89], additional research should evaluate whether polymorphisms in CHRNB3 and CHRNA6 are related to the rewarding effects of smoking.
Candidate gene association studies investigating the CHRNA5-CHRNA3-CHRNB4 gene cluster located on chromosome 15 have found evidence that variability in this gene cluster is associated with risk for several smoking phenotypes. Saccone and colleagues [142] have reported strong associations between nicotine dependence and the CHRNA5-CHRNA3-CHRNB4 gene cluster. Specifically, 3 SNPs in CHRNA5 (rs16969968, rs637137, and rs684513), 3 SNPs in CHRNA3 (rs578776, rs1051730, and rs3743078) and 1 SNP in CHRNB4 (rs3813567) were related to risk for nicotine dependence. Additional research has demonstrated associations between the CHRNA5-CHRNA3-CHRNB4 gene cluster and smoking initiation (e.g. smoking at least once a month); 1 SNPs in CHRNA5 (rs514743), 1 SNP in CHRNB4 (rs1948), and an intergenic SNP located between CHRNA3 and CHRNB4 (rs8023462) were associated with an earlier age of smoking initiation and were replicated in an independent sample [150].
Finally, several genome-wide association studies have demonstrated that polymorphisms in the CHRNA5-CHRNA3-CHRNB4 gene cluster may influence smoking-related behaviors and alter risk for lung cancer. Berrettini and colleagues [6] evaluated smoking quantity in two independent samples of European ancestry, and identified a SNP in CHRNA3 (rs6495308) that was associated with increased smoking quantity in both samples. An additional SNP in CHRNA3 (rs1317286) was related to increased smoking quantity in a third sample. These SNPs, along with those identified by Saccone and colleagues [142], belong to a common CHRNA5-CHRNA3 haplotype that is associated with risk for smoking quantity. Three independent genome-wide association studies have also linked the CHRNA5-CHRNA3-CHRNB4 gene cluster to risk for lung cancer, smoking quantity, and nicotine dependence [1, 74, 171]. A SNP in CHRNA3 (rs1051730) that is in linkage disequilibrium with other SNPs in the CHRNA5-CHRNA3-CHRNB4 gene cluster [142] was associated with smoking quantity, nicotine dependence, risk for peripheral arterial disease [171], and risk for lung cancer [1, 74, 171]. Furthermore, Hung and colleagues [74] identified a non-synonymous SNP in CHRNA5 (rs16969968) that was associated with risk for lung cancer, and this finding was replicated in five independent studies. Although these data suggest that the CHRNA5-CHRNA3-CHRNB4 gene cluster is directly associated with risk for lung cancer, it is possible that this gene cluster alters risk for nicotine dependence, and subsequent tobacco smoking increases risk for lung cancer. Some evidence suggests that the link between the CHRNA5-CHRNA3-CHRNB4 gene cluster and lung cancer is independent from any association between the gene cluster and nicotine dependence [1, 74], whereas other research indicates that risk for lung cancer may be indirectly modulated by an association between the CHRNA5-CHRNA3-CHRNB4 gene cluster and nicotine dependence [171]. Together, these data suggest that polymorphisms in the CHRNA5-CHRNA3-CHRNB4 gene cluster may influence several smoking phenotypes and alter risk for lung cancer, but it is unclear whether these effects are mediated by SNPs in one or more of the genes in this cluster.
The reviewed research from candidate gene and genome-wide association studies has demonstrated that genetic variability in several nAChR subunit genes (CHRNA3–CHRNA6, CHRNB2-CHRNB4) can influence nicotine dependence, as measured by a variety of smoking phenotypes. It is also clear that some nAChR subunit genes may have a greater effect on nicotine dependence than others, and that the effects of a given nAChR subunit gene may depend upon factors such as ethnicity and gender. However, there is much that remains unknown about the role of nAChR subunit genes in nicotine addiction. To date, there are several nAChR subunit genes that have not been directly investigated, including the CHRNA2 and CHRNA10 genes which have been identified as possible candidate genes in genome-wide linkage scans [98, 165]. Additionally, future research should assess the relationship between nAChR subunit genes and nicotine dependence with a more comprehensive selection of smoking phenotypes, including measures of nicotine withdrawal (e.g. number of withdrawal symptoms, withdrawal severity) and the efficacy of pharmacotherapeutic treatments for smoking cessation. In support, it has been shown that variations in CHRNA4 are associated with smoking cessation outcomes [75], and it is possible that polymorphisms in nAChR subunit genes may modulate the effects of nicotine replacement therapy and varenicline (a α4β2* partial agonist and α7 nAChR full agonist) [21, 118] on smoking cessation. Furthermore, given that the protein products of these genes are known to interact with each other to form receptors, it is possible that interactions between nAChR subunit genes may have a greater influence on smoking phenotypes than an individual nAChR subunit gene; thus, additional research should investigate possible gene-gene interactions between nAChR subunit genes.
Nicotinic Acetylcholine Receptors: Animal Research
Nicotine addiction is a complex disorder that is composed of numerous changes to behavior and physiology and can be characterized by several stages such as experimentation, regular use, nicotine dependence, attempts to quit/smoking cessation, and relapse [112]. Several differences exist between humans and other animals, such as the physiologically relevant range of nicotine doses used and the rate of nicotine metabolism [111], and some aspects of nicotine addiction in humans cannot be easily assessed by animal research (e.g. relapse). Despite these limitations, animal research has modeled several effects of acute and chronic nicotine that relate to the effects of nicotine in humans. Similar to other drugs of abuse, nicotine increases dopamine (DA) release in the nucleus accumbens, and the effects of nicotine on the mesolimbic dopaminergic pathway is thought to mediate the rewarding properties of nicotine [42]. Several behavioral paradigms, such as nicotine self-administration and nicotine conditioned place preference (CPP) have been used to model the rewarding effects of nicotine in animals [139, 155]. In nicotine self-administration studies, rodents learn to respond on a lever for nicotine infusions, or receive oral nicotine in a two bottle choice procedure (nicotine-treated water vs. untreated water), whereas subjects in a nicotine CPP procedure learn to prefer a chamber paired with nicotine administration over another chamber that was paired with saline.
In addition to changes in reward, evidence from both human and animal research has demonstrated that nicotine alters cognitive processes, including associative learning [35, 37, 48, 58, 88]. For example, cravings for nicotine were increased following the presentation of previously neutral environmental cues that were associated with smoking [88]. Similarly, withdrawn smokers and non-withdrawn smokers that were exposed to smoking-related stimuli reported increases in cravings [39, 48, 49]. Research has also demonstrated that contextual cues (i.e. cues that indicate smoking availability) can increase cravings for smoking [38, 37, 170, 169]. Consistent with these data, research in mice has demonstrated that nicotine alters contextual learning. In mice trained to form an association between an auditory conditioned stimulus (CS) and a footshock unconditioned stimulus (US; cued conditioning), and an association between the training context CS and the US (contextual conditioning), acute nicotine enhances contextual conditioning, but has no effect on cued conditioning [30, 32, 31, 56, 55, 186]. However, contextual conditioning is not altered by a dose of chronic nicotine that produces the same plasma nicotine levels as the acute dose that produces enhancement, suggesting the development of tolerance [30]. It is important to note that these plasma nicotine levels were within the range observed in smokers [5, 64]. Additionally, withdrawal from chronic nicotine disrupts contextual but not cued conditioning [2, 33, 30, 132, 133], and this impairment in contextual learning can be ameliorated by nicotine replacement and by the smoking cessation drugs bupropion and varenicline [30, 132, 135]. Together, these data suggest that associations between stimuli and the effects of nicotine in humans may contribute to nicotine addiction, and these effects can be modeled in mice by studying the effects of nicotine on contextual learning.
Nicotine withdrawal in humans consists of multiple symptoms, such as insomnia, anxiety, increased appetite, and cravings [73, 71]. Furthermore, nicotine withdrawal produces changes in cognition, including the disruption of attention [78, 141], difficulty in concentration [70, 71], and learning and memory deficits [78, 79, 117]. Many of these nicotine withdrawal phenotypes have been studied in animals. For instance, some research has evaluated somatic symptoms (e.g. increased grooming, scratching, or shaking) in rats or mice that occur following spontaneous withdrawal or nAChR antagonist-precipitated withdrawal [28, 77, 103, 102]. Additionally, mice withdrawn from chronic nicotine have been evaluated using the elevated plus maze, in which the percentage of time spent on the open arms of the maze serves as a measure of anxiety [28, 77]. Mice withdrawn from nicotine spend less time on the open arms relative to saline controls, indicating increased anxiety [28, 77]. Furthermore, nicotine withdrawal-related deficits in contextual learning have been evaluated in mice [33, 30, 132, 133]. Withdrawal-related decreases in the brain reward system in humans has been modeled using the intracranial self stimulation (ICSS) procedure, in which rats press a lever to deliver electrical stimulation to reward-related brain areas. Nicotine withdrawal increases ICSS threshold [26, 81, 156]. Thus, several nicotine withdrawal symptoms reported in humans have been modeled and studied in rodents.
Although the development of a perfect model of nicotine addiction is not possible, multiple animal models of nicotine addiction have been designed that correspond to some of the endophenotypes observed in humans. Furthermore, several, but not all, of the behavioral procedures that model nicotine addiction have been used to investigate the genetic factors that influence sensitivity to nicotine. In the sections that follow, we will discuss research that has utilized these behavioral procedures to demonstrate that nAChR subunit genes play an important role in regulating the effects of nicotine.
The Effects of Nicotine in Inbred Rodent Strains
The genetic factors that influence the effects of nicotine have been investigated in rodents using two different approaches. In order to determine whether naturally occurring genetic variability can modulate nicotine sensitivity, researchers have characterized the effects of nicotine in two or more inbred strains of rodents. By definition, inbred strains are genetically identical after 20 consecutive generations of brother/sister mating [24]; thus, differences between strains reveal genetic influences on sensitivity to nicotine. However, some genetic differences between members of an inbred strain have been reported. For example, copy number variations have been identified in C57BL/6J mice that can alter gene expression [185]. In addition, genetic drift can produce differences in behavior between substrains of an inbred mouse strain that are bred by separate sources (e.g. C57BL/6J vs. C57BL/6Ibg) [158].
The use of genetically modified mice is an additional approach that can be utilized to study the genes that are required for the effects of nicotine. One advantage to this approach is that the use of KO mice can pinpoint the genes that mediate the effects of nicotine. However, the deletion of a gene does not reveal whether variability in this gene can alter sensitivity to nicotine. The generation of knockin (KI) mice that have had a hypersensitive or hyposensitive nAChR subunit inserted into the mouse genome can be used to investigate whether variability in nAChR subunit genes can modulate nicotine sensitivity, but this artificial change in the functional properties of the subunit may not reflect what occurs naturally. Furthermore, it can be difficult to establish whether the effects observed in genetically modified mice are due to the alteration of a gene, or if they result from compensatory changes that occur during development. Despite the limitations of these two approaches, animal research has yielded evidence that genetic variability in nAChR subunits can alter sensitivity to nicotine.
A growing body of research has characterized the effects of nicotine in several strains of inbred rats and has revealed differences in sensitivity to nicotine across multiple strains. For instance, several differences in the rewarding properties of nicotine have been characterized in the Lewis and Fischer 344 inbred rat strains. Lewis rats can learn to self-administer nicotine in an unlimited access procedure but not when there is limited access to nicotine, whereas Fischer 344 rats do not self-administer nicotine in either procedure [12, 151]. Furthermore, Lewis rats can rapidly learn nicotine CPP when lower doses of nicotine are used, whereas Fischer 344 rats require more trials to acquire nicotine CPP at lower doses and can only learn the procedure rapidly when a high dose of nicotine is used [69, 128]. In addition to these differences in the behavioral effects of nicotine, Sziraki and colleagues [166] have demonstrated that nicotine-induced increases in DA release in the nucleus accumbens is greater in Lewis rats than in Fischer 344 rats, and plasma nicotine was cleared faster in Lewis rats. Together, these data suggest that Lewis rats are more sensitive to the rewarding properties of nicotine, and may have increased vulnerability for nicotine dependence. Given that research with other drugs of abuse have demonstrated that Lewis rats acquire cocaine and morphine self-administration more rapidly than Fischer 344 rats [84, 107], it is possible that Lewis rats have a greater generalized sensitivity for drug reinforcement. Variations in the genes encoding nAChR subunits, DA receptors, or enzymes involved in nicotine metabolism may be responsible for the reported differences between Lewis and Fischer 344 rats, but additional research is needed to test this hypothesis.
Comparisons between outbred rat strains, such as Sprague-Dawley and Long-Evans rats, have demonstrated that naturally occurring genetic variability can alter sensitivity to nicotine in several behavioral procedures. Both Sprague-Dawley and Long-Evans rats self-administered nicotine in a limited access procedure whereas Lewis and Fischer 344 rats did not, suggesting that the former two strains may be more sensitive to the rewarding properties of nicotine than Lewis and Fischer 344 inbred rats [151]. Additionally, Faraday and colleagues [43] reported that nicotine has differential effects on the acoustic startle response (ASR) and sensory gating, as measured by prepulse inhibition of the acoustic startle response (PPI). Specifically, nicotine enhanced ASR and PPI in Sprague-Dawley rats, but disrupted ASR and PPI in Long-Evans rats. The effects of chronic nicotine have also been characterized in these two strains: Long-Evans rats exhibited greater locomotor activity during chronic nicotine administration than Sprague-Dawley rats [44]. Thus, research comparing Sprague-Dawley and Long-Evans rats has revealed that genetic variability can alter sensitivity to nicotine, but one limitation with using outbred rat strains is that the greater genetic variability within an outbred strain will make it difficult to identify the variants of genes that modulate nicotine sensitivity.
Additional support for genetic influences on the effects of nicotine comes from comparisons of multiple strains of inbred mice, and subsequent research has demonstrated that polymorphisms in nAChR subunits may alter sensitivity to nicotine. A comparison of 19 inbred mouse strains revealed considerable differences in the effects of nicotine on respiration, heart rate, body temperature, acoustic startle response, and locomotor activity on the Y-maze [22, 104], and strain-dependent differences in nicotine and α-bungarotoxin binding sites were also reported [105]. Furthermore, inbred mouse strains developed tolerance to the effects of nicotine on these measures during chronic nicotine infusion, but the nicotine dose that produced tolerance varied between the inbred mouse strains that were tested [22, 106]. For instance, C57BL/6Ibg mice developed tolerance to the physiological effects of nicotine when low doses of chronic nicotine were infused, whereas high doses were required to produce tolerance in C3H/2Ibg mice [106]. Furthermore, inbred mouse strains that were more sensitive to low doses of acute nicotine were more likely to develop tolerance during chronic nicotine infusion [23, 106], suggesting that the gene variants that increase sensitivity to acute nicotine may also regulate the development of tolerance.
The effects of nicotine have been well characterized in the C57BL/6 inbred mouse strain; thus, several studies have compared the behavioral effects of nicotine and nicotine withdrawal in this strain to other inbred strains, such as DBA/2 mice3. C57BL/6Ibg mice exhibited greater oral nicotine self-administration than DBA/2Ibg, ST/bJ, BUB/J, A/Ibg, and C3H/2Ibg mice [140]. Furthermore, C57BL/6J mice developed nicotine CPP, whereas DBA/2J mice did not [60]. These data suggest that C57BL/6 mice have increased sensitivity to the rewarding properties of nicotine relative to other strains. Inbred mouse strains such as A/J and 129/SvEv mice were more sensitive to the antinociceptive effects of acute nicotine than C57BL/6J and DBA/2Ibg mice [29]. However, C57BL/6J mice showed increased sensitivity to pain during nicotine-precipitated withdrawal, but precipitated withdrawal had no effect on pain perception in 129/SvEv mice [28]. Furthermore, nicotine-precipitated withdrawal also increased anxiety (as measured by decreased time in the open arms of the elevated plus maze) and somatic symptoms (e.g. increased head shakes, paw tremors, or scratching) in C57BL/6J mice but not 129/SvEv mice, suggesting that genetic factors mediate the severity of nicotine withdrawal symptoms [28]. Together, these data provide evidence that genetic variability can influence the effects of nicotine on reward and pain perception, as well as the symptoms observed during nicotine withdrawal. The C57BL/6 mouse strain may be more sensitive to many of the effects of nicotine relative to other strains, but it is important to note that this trend was not observed in all of the behavioral procedures tested.
One limitation of inbred strain studies is that it is difficult to determine the genes (and the variations of these genes) that are mediating the effects. However, inbred strains can be used to identify quantitative trait loci (QTL) associated with nicotine-related behaviors. These studies have identified loci containing nAChR subunit genes, and have found some regions associated with nicotine phenotypes that have also been linked to nicotine dependence in humans. Gill and colleagues [52] examined the effects of nicotine on locomotor activity in recombinant congenic strains (RCS) of mice. Briefly, RCS mice were generated by backcrossing F1 hybrid mice (C57BL/6J × A/J) with one of the progenitor strains (C57BL/6J or A/J mice), such that some RCS mice were backcrossed to A/J mice (AcB) whereas others were backcrossed to C57BL/6J mice (BcA). The offspring from the first backcross were also backcrossed to one of the two background strains; thus, the subsequent generation possessed ~12.5% of the genes from the donor strain and ~87.5% of the background strain. Following 20 or more generations of brother/sister inbreeding, the chromosomal maps from AcB/BcA RCS mice can be used to identify loci associated with nicotine-related phenotypes. In AcB mice, a single locus association analysis revealed QTL for the locomotor-enhancing effects of nicotine on chromosomes 11–14 and 17, and a locus on chromosome 11 was linked to the locomotor-suppressant effects of nicotine. Furthermore, seven loci located on chromosomes 2, 7, 8, 13, 14, 16 and 17 were linked to nicotine-induced increases in locomotion in BcA mice [52]. Interestingly, the locus on chromosome 14 associated with the effects of nicotine on locomotion in BcA mice contains the Chrna2 gene, suggesting that nAChR subunit genes may play an important role in sensitivity to the effects of nicotine on locomotion [52]. Additional research with inbred mice has also identified loci associated with oral nicotine consumption. Previous research has demonstrated substantial differences in oral nicotine consumption between C57BL/6J and C3H/HeJ mice [140]; thus, Li and colleagues [97] used a genetic cross between these two strains to identify loci associated with sensitivity to oral nicotine consumption. Four loci associated with oral nicotine consumption (located on chromosomes 1, 4, 7, and 15) were identified in F2 hybrid mice [97]. The locus found on chromosome 1 is syntenic with the human chromosome 1, and this region has also been associated with smoking quantity in humans [182]. Together, these data suggest that nAChR subunit genes play an important role in mediating sensitivity to nicotine, and reveal that some loci associated with nicotine phenotypes may be common across multiple species.
Although research from inbred rodent strains has demonstrated that genetic variability can alter sensitivity to nicotine, many of the specific genes that regulate nicotine sensitivity remain unknown. However, polymorphisms in the Chrna4, Chrna5, and Chrna7 genes have been identified that may influence the effects of nicotine in inbred mouse strains. Stitzel and colleagues [159] identified restriction fragment length polymorphisms (RFLPs) between C3H/2Ibg and DBA/2Ibg mice in both Chrna5 and Chrna7, and used a classic genetic cross between these two strains to determine whether these RFLPs are associated with sensitivity to nicotine-induced seizures. F2 hybrid mice that were homozygous for the C3H/2Ibg variant of the Chrna5 RFLP had greater vulnerability for nicotine-induced seizures than mice that were homozygous for the DBA/2Ibg variant of this RFLP. Furthermore, the C3H/2Ibg variant of the Chrna7 RFLP increased susceptibility for nicotine-induced seizures and mice that possessed C3H/2Ibg alleles for both Chrna5 and Chrna7 had greater sensitivity to nicotine-induced seizures than mice carrying only one of the C3H/2Ibg alleles, suggesting that the two RFLPs function in an additive manner to increase sensitivity [159].
A SNP in Chrna4 that results in an alanine or threonine amino acid substitution (A529T) at position 529 of the α4 nAChR subunit has also been linked to strain-dependent differences in responses to nicotine [160]. This SNP was associated with changes in the functional properties of α4 containing receptors: nicotine-induced 86Rb+ efflux was significantly greater in mice that possess the A529 variant [36]. Additionally, mice carrying the A529 variant of this SNP were less sensitive to the effects of nicotine on locomotor activity (measured on the Y-maze), body temperature, and respiration when compared to mice that have the T529 variant [172, 173]. However, A529 mice were more sensitive to nicotine-induced changes in acoustic startle relative to T529 mice [173]. Furthermore, a comparison of 14 inbred mouse strains revealed that mice carrying the A529 variant of this SNP consumed less nicotine than mice with the T529 variant [13]. Furthermore, Butt and colleagues studied nicotine preference and consumption in F2 mice generated by crossing A/J mice with C57BL/6J mice that lack the β2 nAChR subunit. F2 mice that possessed the A529 variant showed significantly less preference and consumption of nicotine, but only if they were β2 subunit WT mice [13]. The fact that the association between A529T and nicotine preference and consumption was not present in β2 KO mice suggests that variability in either Chrna4 or Chrnb2 is mediating nicotine preference and consumption. Together, these data suggest that variability in Chrna4 can influence sensitivity to nicotine, and demonstrate that the use of both inbred mouse strains and genetic KO mice can provide new insight into the genes that are responsible for individual differences in the response to nicotine.
Overall, research comparing the effects of nicotine in multiple inbred rodent strains has provided strong evidence that naturally occurring genetic variability can modulate the response to nicotine. Furthermore, research by Stitzel and colleagues has demonstrated that variability in nAChR subunit genes is associated with changes in the functional properties of receptors and in some of the behavioral effects of nicotine. These data correspond with research in humans that has linked variability in nAChR subunit genes to smoking phenotypes, suggesting that additional research in mice may lead to a better understanding of how individual differences in genetics can increase or decrease vulnerability to nicotine addiction. Future research should investigate whether variability in other nAChR subunit genes are associated with changes in nicotine sensitivity.
The Effects of Nicotine in Genetic Knockout and Knockin Mice
The use of genetically manipulated animals that have had a gene of interest inserted or deleted (KI and KO mice, respectively) has allowed researchers to uncover details about the possible functions of nAChRs and also has revealed that the genes encoding nAChRs mediate variability in many of the behavioral effects of nicotine. To date, knockout mice have been generated that lack the α3 [191], α4 [108], α5 [183], α6 [19], α7 [123], α9 [177], β2 [129, 190], β3 [27], and β4 [190] nAChR subunits, and subsequent research has demonstrated that the deletion of these genes will alter many of the effects of nicotine in mice. Additionally, KI mice with point mutations that produce hypersensitive nAChRs have been generated for the α4 [86, 167] and α7 subunits [124]. Although genetically modified mice can help to determine the possible functions of a given gene, there are some limitations to using this approach [20, 162]. For instance, developmental compensatory mechanisms that result from the deletion of a gene could alter the function of other nAChRs or other processes. In addition, nAChR subunit KO mice generated using 129/SvEv mice that are backcrossed onto a C57BL/6J background may have genes flanking the targeted nAChR subunit gene that carry 129/SvEv alleles, rather than the alleles found in C57BL/6J mice [187]. Therefore, it is possible that differences in flanking genes may be responsible for the effects of nicotine observed in KO mice. Another potential complication with the phenotypes observed in genetic KO mice is that some sequences within the targeting vector, such as the promoter region of a selectable marker, may alter the expression of genes located near the gene targeted for deletion [121]. Finally, the deletion of some genes can produce a dramatically shortened lifespan (e.g. α3 KO mice) or result in embryonic death. However, the development of conditional KO mice, which have a target gene deleted only in a given brain region, can address this issue.
The β2 nAChR Subunit
The β2 subunit was the first nAChR subunit successfully targeted for deletion [129], and research with KO mice has demonstrated that β2-containing nAChRs are required for many of the effects of nicotine, including alterations of reward, avoidance learning, and hippocampus-dependent learning. In addition, β2-containing nAChRs also mediate several nicotine withdrawal symptoms (see Table 2 for a summary of nAChR subunit KO studies). β2 subunit KO mice do not self-administer nicotine and do not show nicotine-evoked increases in DA release in the ventral striatum, in contrast to WT littermates [7, 130]. Similarly, β2 KO mice do not exhibit nicotine CPP, whereas wild-type (WT) mice can learn to associate a previously neutral context with nicotine administration [181]. Additional research has also demonstrated that intra-VTA nicotine self-administration can be restored in β2 KO mice by administering a lentiviral vector into the VTA that expresses the β2 subunit [110], which suggests that β2-containing nAChRs in the VTA are sufficient for the rewarding effects of nicotine. Together, these studies provide strong evidence that the rewarding properties of nicotine require β2-containing nAChRs, but it remains unknown whether naturally occurring genetic variability in Chrnb2 will alter sensitivity to the rewarding effects of nicotine.
Table 2.
The Effects of Nicotine in nAChR Knockout and KnockIn Mice
| Gene | Effect in KO/KI Mice | References |
|---|---|---|
| CHRNA3 | ||
| KO Mice | +/− mice less sensitive to nicotine-induced seizures | Salas et al., 2004b |
| Effects of nicotine on locomotion are normal | Salas et al., 2004b | |
| CHRNA4 | ||
| KO Mice | No high-affinity binding sites for nicotine | Marubio et al., 1999 |
| Reduced antinociception (Hot-Plate Test) | Marubio et al., 1999 | |
| No nicotine-induced changes in body temperature | Tapper et al., 2007 | |
| No nicotine-induced changes in locomotion | Tapper et al., 2007 | |
| Nicotine-induced increases in DA not present | Marubio et al., 2003 | |
| Reduced DA transport functioning | Parish et al., 2005 | |
| Leu9'Ser KI mice | KI mice have a 30-fold increase in nicotine/acetylcholine sensitivity | Labarca et al., 2001 |
| Nicotine-induced changes in pain perception are enhanced in +/− mice | Damaj et al., 2007b | |
| Leu9'Ala KI mice | KI mice have a 50-fold increase in nicotine sensitivity | Tapper et al., 2004 |
| Develop nicotine CPP at 50-fold lower dose than WT | Tapper et al., 2004 | |
| Tolerance to nicotine can occur with a 50-fold lower dose than WT | Tapper et al., 2004 | |
| Nicotine-induced changes in body temperature are enhanced | Tapper et al., 2007 | |
| Nicotine-induced changes in locomotion are enhanced | Tapper et al., 2007 | |
| CHRNA5 | ||
| KO Mice | Reduced sensitivity to nicotine-induced seizures | Salas et al., 2003b |
| Effects of nicotine on locomotion are reduced | Salas et al., 2003b | |
| Somaic signs of nicotine withdrawal are disrupted | Jackson et al., 2008 | |
| Normal nicotine withdrawal-induced hyperalgesia | Jackson et al., 2008 | |
| Normal nicotine withdrawal-induced increases in anxiety | Jackson et al., 2008 | |
| Normal nicotine CPA | Jackson et al., 2008 | |
| CHRNA6 | ||
| KO Mice | No high affinity αCtxMII-sensitive binding sites | Champtiaux et al., 2002 |
| CHRNA7 | ||
| KO Mice | Normal nicotine CPP | Walters et al., 2006 |
| Normal nicotine enhanced contextual conditioning | Wehner et al., 2004 | |
| Davis and Gould, 2007b | ||
| Normal nicotine withdrawal-induced deficits in contextual conditioning | Portugal et al., 2008 | |
| Normal nicotine enhanced trace cued conditioning | Davis and Gould, 2007b | |
| Normal nicotine CPA | Jackson et al., 2008 | |
| Normal nicotine withdrawal-related increases in anxiety | Jackson et al., 2008 | |
| Normal nicotine-induced changes in locomotion | Naylor et al., 2005 | |
| Normal tolerance to nicotine-induced changes in locomotion | Naylor et al., 2005 | |
| Somaic signs of nicotine withdrawal are disrupted | Salas et al., 2007 | |
| Nicotine withdrawal-related hyperalgesia is reduced | Grabus et al., 2005 | |
| L250T KI Mice | Enhanced sensitivity to nicotine-induced seizures in +/− mice | Gil et al., 2002 |
| CHRNB2 | ||
| KO Mice | No nicotine CPP | Walters et al., 2006 |
| No nicotine self-administration | Picciotto et al., 1998 | |
| Besson et al., 2006 | ||
| Nicotine-induced increases in DA not present | Picciotto et al., 1998 | |
| No nicotine enhanced contextual conditioning | Wehner et al., 2004 | |
| No nicotine withdrawal-induced deficits in contextual conditioning | Portugal et al., 2008 | |
| No nicotine enhanced trace cued conditioning | Davis and Gould, 2007b | |
| Enhanced PA, but nicotine does not alter PA in KO mice | Picciotto et al., 1995 | |
| No nicotine CPA | Jackson et al., 2008 | |
| Reduced nicotine CTA | Shoaib et al., 2002 | |
| No nicotine withdrawal-related increases in anxiety | Jackson et al., 2008 | |
| Somaic signs of nicotine withdrawal are normal | Salas et al., 2004a | |
| Besson et al., 2006 | ||
| Jackson et al., 2008 | ||
| No high-affinity binding sites for nicotine | Picciotto et al., 1995 | |
| Reduced antinociception (Hot-Plate Test) | Marubio et al., 1999 | |
| No nicotine-induced changes in body temperature | Tritto et al., 2004 | |
| McCallum et al., 2006 | ||
| No nicotine-induced changes in locomotion | Tritto et al., 2004 | |
| McCallum et al., 2006 | ||
| Lentiviral re-expression | Re-expression of β2 nAChRs in VTA restores self-administration | Maskos et al., 2005 |
| CHRNB3 | ||
| KO Mice | No inhibition of nicotine-induced DA release by αCtxMII | Cui et al., 2003 |
| Salminen et al., 2004 | ||
| Enhanced open field locomotor activity | Cui et al., 2003 | |
| Reduced PPI | Cui et al., 2003 | |
| Decreased anxiety (elevated plus maze) | Booker et al., 2007 | |
| CHRNB4 | ||
| KO Mice | Reduced sensitivity to nicotine-induced seizures | Salas et al., 2004b |
| Effects of nicotine on locomotion are reduced | Salas et al., 2004b | |
| Somaic signs of nicotine withdrawal are disrupted | Salas et al., 2004a | |
| No nicotine-induced changes in body temperature | Sack et al., 2005 | |
| Decreased anxiety (elevated plus maze) | Salas et al., 2003a | |
Legend: KO = Knockout; KI = Knockin; WT = Wild-type; DA = Dopamine; αCtxMII = α Conotoxin MII; CPP = Conditioned Place Preference; CPA = Conditioned Place Aversion; CTA = Conditioned Taste Aversion; PA = Passive Avoidance; VTA = Ventral Tegmental Area; PPI = Prepulse Inhibition
In addition to mediating nicotine-induced changes in reward, β2-containing nAChRs are also critically involved in the effects of nicotine on avoidance learning. Avoidance learning has been assessed using several behavioral procedures, including passive avoidance, conditioned place aversion (CPA), and conditioned taste aversion (CTA). In the passive avoidance procedure, mice are placed in a well-lit portion of a chamber and receive a footshock when they cross over to the dark portion of the chamber. An association between the dark chamber and the footshock is assessed on testing day by measuring the time to enter the dark chamber [157]. Research with β2 KO mice has demonstrated that saline-treated KO mice exhibit greater passive avoidance relative to WT mice; however, nicotine enhances passive avoidance in WT mice but has no effect in KO mice [129]. In the nicotine CPA procedure, mice treated with chronic nicotine learn to avoid a chamber that is paired with nAChR antagonist-precipitated withdrawal [163]. β2 KO mice do not show nicotine CPA whereas WT mice do [77]. Finally, mice trained in the nicotine CTA procedure learn to avoid flavored water that is paired with nicotine [53]; a study investigating CTA in β2 KO mice has shown that KO mice have reduced CTA relative to WT mice [152]. Overall, research using several behavioral procedures has consistently demonstrated that the effects of nicotine on avoidance learning, which models the effects of nicotine on affect and cognition in humans, are mediated by β2-containing nAChRs.
Acute nicotine enhances hippocampus-dependent forms of learning, such as trace cued conditioning [56, 54] and contextual conditioning [34, 57], whereas withdrawal from chronic nicotine produces deficits in contextual conditioning [33, 30, 132, 135]. Research with KO mice has demonstrated that the effects of nicotine on hippocampus-dependent forms of learning require the β2 nAChR subunit. In trace cued conditioning, an auditory CS is separated by an interval of time before mice receive a footshock US. Mice acquire a context-US and a CS-US association, but the insertion of a time interval between the CS and US requires working memory to be engaged [15]. Therefore, the hippocampus is required for both the context-US and CS-US associations [114, 134]. Research from our lab has demonstrated that β2 KO mice show no enhancement of trace cued conditioning by acute nicotine, whereas WT littermates do [34]. Similarly, acute nicotine enhances contextual conditioning in β2 WT mice but not in KO mice, suggesting that the effects of acute nicotine on hippocampus-dependent learning likely require α4β2* nAChRs [186]. Furthermore, nicotine withdrawal-related deficits in contextual conditioning are present in β2 subunit WT mice but not in KO mice [133]. Taken together, these data reveal that β2-containing nAChRs are required for the enhancing effects of nicotine on hippocampus-dependent learning, as well as for the disruption of learning that occurs during nicotine withdrawal. It remains unknown whether variability in the mouse Chrnb2 gene can influence sensitivity to the effects of acute nicotine and nicotine withdrawal on hippocampus-dependent learning.
Symptoms of nicotine withdrawal have been studied using β2 KO mice, including withdrawal-related changes in anxiety, hippocampus-dependent learning (described in the previous paragraph), and somatic symptoms of withdrawal. β2 subunit KO mice withdrawn from chronic nicotine do not exhibit withdrawal-associated increases in anxiety, as measured by the elevated plus maze [77]. In contrast, the somatic symptoms of nicotine withdrawal are present in both β2 KO and WT mice, suggesting that the somatic symptoms of nicotine withdrawal are mediated by other nAChR subunits [7, 77, 146]. Research with other nAChR subunit KO mice has demonstrated that the β4 [146], α5 [77], and α7 nAChR subunits [148] likely mediate the somatic symptoms of withdrawal. Thus, these studies provide evidence that the various symptoms of nicotine withdrawal are mediated by different nAChR subunits.
Overall, research from genetically modified mice has provided strong evidence that β2-containing nAChRs are required for the effects of nicotine on reward, avoidance learning, hippocampus-dependent learning, and withdrawal-related changes to learning and anxiety. Although these data are consistent with research in humans that have implicated the CHRNB2 gene in some of effects of nicotine, the data collected in humans on the role of CHRNB2 in nicotine addiction has been mixed. One possible explanation for this discrepancy between human and animal research is that all of the phenotypes studied in β2 KO and WT mice have yet to be tested in humans, and therefore it is possible that variability in CHRNB2 in humans may be associated with the effects of nicotine on reward, cognition, and withdrawal-induced alterations of learning and anxiety. Additionally, research in humans has found associations between CHRNB2 and smoking phenotypes [40]; therefore future research could address whether polymorphisms in the mouse Chrnb2 gene may also modulate the effects of nicotine.
The α4 nAChR Subunit
Mice lacking the α4 subunit exhibit several similarities to β2 KO mice, providing further evidence that α4β2* nAChRs likely mediate many of the effects of nicotine. For instance, both α4 and β2 KO mice do not have high affinity binding sites for nicotine [108, 129], exhibited a reduced antinociceptive effect in a hot-plate test [108], and showed reduced sensitivity to the effects of nicotine on locomotor activity and nicotine-induced hypothermia [113, 168, 174]. Furthermore, α4 and β2 KO mice do not show nicotine-induced increases in striatal DA, whereas their respective WT littermates do [109, 130]. However, basal striatal DA levels were significantly greater in α4 KO mice than in WT mice [109]. An additional abnormality in dopaminergic function has been reported: α4 KO mice have reduced DA transporter function when compared to WT mice [126]. Although the similarities between β2 and α4 KO mice in response to nicotine suggest that α4β2* nAChRs are involved in the effects of nicotine on pain perception, locomotor activity, body temperature, and nicotine-induced changes in DA release, many of the phenotypes examined in β2 KO mice have yet to be tested in α4 subunit KO mice. Given that β2 subunits can interact with several subunits other than α4 to form receptors [119], it is possible that some of the effects observed in β2 KO mice are attributable to associations with non-α4 subunits (e.g. α2, α3, α5, or α6). Thus, a more complete assessment of the effects of nicotine in α4 subunit KO mice is necessary.
In addition to α4 subunit KO mice, two lines of α4 KI mice have been generated that have either a leucine to serine (Leu9’Ser) or a leucine to alanine (Leu9’Ala) point mutation in the pore-forming M2 transmembrane domain of the α4 subunit [86, 167]. In Leu9’Ser mice, this point mutation produces α4-containing nAChRs with a ~30-fold increase in sensitivity to acetylcholine and nicotine. The mutation is lethal to homozygous mice but not to heterozygous mice that possess a neomycin resistance cassette [86]. Subsequent research has demonstrated that Leu9’Ser heterozygous mice are more sensitive to the antinociceptive effects of nicotine than WT mice [29]. Although in vivo research using Leu9’Ser mice is limited to heterozygotes, Tapper and colleagues [167] have shown that Leu9’Ala homozygous mice are viable and will exhibit a ~50-fold increase in sensitivity to nicotine, develop nicotine CPP at a ~50-fold lower dose of nicotine than in WT mice, and develop tolerance to nicotine-induced changes in body temperature at a ~50-fold lower dose of nicotine. Furthermore, a recent study that utilized both α4 KO and Leu9’Ala KI mice demonstrated that if the responses to nicotine-induced changes to body temperature and locomotor activity in both mutant lines were summed together, this predicted response would resemble the effects of nicotine in WT mice [168]. These data suggest that α4-containing nAChRs are both necessary and sufficient for the effects of nicotine on body temperature and locomotor activity. Research utilizing α4 KI mice reveals that genetic variability in the α4 subunit can produce dramatic changes to nicotine sensitivity, and suggest that naturally occurring variability in the human CHRNA4 gene may alter sensitivity to nicotine and increase vulnerability to nicotine addiction. Additionally, the existence of both a KO and hypersensitive KI strain can allow future research to better characterize the contributions of α4 and non-α4 containing nAChRs to the effects of nicotine.
The α7 nAChR Subunit
The homomeric α7 nAChR is abundantly expressed throughout the brain [68, 90], and likely plays an important role in the effects of nicotine. However, research using α7 subunit KO mice has found few differences in the effects of nicotine between KO and WT mice. Research examining the rewarding properties of nicotine has found that both α7 KO and WT mice can develop nicotine CPP, suggesting that α7 nAChRs are not critical for the effects of nicotine on reward [181]. The enhancing effects of acute nicotine on contextual conditioning and trace cued conditioning are also normal in α7 KO mice, but only when a lower footshock US intensity is used [34, 186]. At higher footshock intensities, both α7 KO and WT mice do not show enhancement of contextual conditioning by acute nicotine [186]. In addition, Jackson and colleagues [77] have found no difference between α7 KO and WT mice in avoidance learning as measured by nicotine CPA. Finally, the locomotor suppressant effect of acute nicotine and tolerance to the effects of nicotine on locomotion are equivalent between α7 KO and WT mice [122]. Although these data suggest that α7 nAChRs are not critically involved in many of the effects of nicotine, these results do not rule out the possibility that α7 nAChRs play an ancillary role in these phenotypes. Furthermore, it is possible that compensatory mechanisms in α7 KO mice may obscure the role of this subunit in the effects of nicotine. In support, α7 KO mice have enhanced trace cued conditioning at higher footshock intensities, regardless of whether nicotine or saline was administered [34].
Investigations of nicotine withdrawal symptoms have demonstrated that α7 nAChRs play a role in withdrawal-related changes in somatic symptoms and hyperalgesia [59, 77, 148], but do not play a crucial role in other withdrawal symptoms. Salas and colleagues [148] reported that somatic signs during nAChR antagonist-precipitated withdrawal are reduced in α7 KO mice relative to WT littermates. In addition, studies using two different methods of chronic nicotine administration (either chronic oral nicotine or osmotic mini-pumps) have demonstrated that nicotine withdrawal-induced hyperalgesia is present in α7 WT mice, but not in KO mice [59, 77]. Although these data suggest that α7 nAChRs mediate some aspects of nicotine withdrawal, other research has found that withdrawal-associated changes in contextual learning and anxiety are not affected by the deletion of the α7 subunit. Specifically, α7 KO and WT mice both exhibit nicotine withdrawal-related deficits in contextual conditioning [133]. Furthermore, withdrawal-associated increases in anxiety, as measured by decreased time in the open arms of the elevated plus maze, were present in both KO and WT mice [77]. Thus, α7 nAChRs are involved in select nicotine withdrawal symptoms.
Research with α7 KI mice suggest that alterations in the functional properties of α7 nAChRs can lead to significant changes in sensitivity to nicotine. Specifically, homozygous α7 KI mice that have a leucine to threonine (L250T) point mutation in the pore-forming domain of the α7 subunit will die after birth, but heterozygotes remain viable and exhibit increased sensitivity to nicotine induced seizures [11, 51, 124]. These studies reveal that a gain of function in the α7 nAChR can produce substantial alterations of nicotine-related phenotypes; thus, a more complete evaluation of the effects of nicotine in α7 KI mice is necessary. Furthermore, research with α7 KI mice suggest that naturally occurring variants of CHRNA7 in humans may enhance sensitivity to nicotine and increase vulnerability to nicotine addiction; future candidate gene association studies could evaluate associations between CHRNA7 and smoking phenotypes.
Additional nAChR Subunits
Similar to humans, the genes that encode the α6 and β3 nAChR subunits exist in a cluster located on chromosome 8; α6 and β3 KO mice have been generated, but few phenotypes have been evaluated in these mice. Nicotine stimulates DA release in reward-related brain areas such as the striatum, and this effect is partially inhibited by α-conotoxin MII (αCtxMII) [85]. Research with α6 and β3 KO mice has demonstrated αCtxMII inhibits nAChRs that contain both of these subunits. Champtiaux and colleagues [19] reported no gross anatomical abnormalities in α6 KO mice, but α6 KO mice no longer possess high affinity binding sites for [125I]αCtxMII. In β3 KO mice, the inhibition of nicotine-induced DA release by αCtxMII is virtually absent [27, 149]. β3 KO mice also exhibit greater activity in an open field arena, have decreased prepulse inhibition of the acoustic startle response, and show reduced anxiety relative to WT mice [9, 27]. These data suggest that β3-containing nAChRs may play a role in anxiety, but the effects of nicotine on these behavioral procedures remain unknown. Furthermore, given that research in humans has implicated the CHRNA6 and CHRNB3 genes in modulating nicotine dependence, testing of the effects of nicotine in α6 and β3 KO mice may clarify the role of this gene cluster in nicotine dependence-related behaviors.
The genes encoding the α5, α3, and β4 subunits have been successfully targeted for deletion in mice, but many of the effects of nicotine have yet to be studied in these KO mice. α5 KO mice do not appear to have any physical abnormalities and have normal mRNA expression of non-α5 nAChR subunits, but α5 KO mice have substantially reduced sensitivity to nicotine-induced seizures and are resistant to the locomotor suppressant effects of nicotine [144]. Furthermore, α5 KO mice have reduced somatic signs during nAChR antagonist-precipitated withdrawal, but show normal precipitated withdrawal-related changes in pain perception and anxiety relative to WT mice; nicotine CPA in α5 KO mice is also similar to WT mice [77]. α3 KO mice have several physical abnormalities and die within 1–8 weeks after birth, but heterozygous mice do not have any gross physical deformities and can be used to study the behavioral effects of nicotine [191]. Salas and colleagues [147] have demonstrated that α3 heterozygous mice are less sensitive to nicotine-induced seizures but showed normal suppression of locomotor activity in response to acute nicotine. Finally, β4 KO mice have been tested for several phenotypes and show some similarity to α3 and α5 KO mice. For example, β4 KO mice exhibit reduced sensitivity to the hypolocomotor effects of nicotine, have increased resistance to nicotine-induced seizures, and show reduced somatic signs during nAChR antagonist-precipitated withdrawal when compared to WT mice [147, 146]. Furthermore, the core body temperature of β4 KO mice is lower than WT mice, and the effects of nicotine on body temperature are reduced in the KO mice [143]. Additionally, Salas and colleagues [145] evaluated anxiety in β4 KO and WT mice; β4 KO mice exhibited less changes in heart rate in the open arms of the elevated plus maze when compared with WT mice, but no differences were reported in other measures of anxiety. Thus, research with α5, α3, and β4 KO mice has revealed that related genes may mediate similar effects of nicotine: all three lines of genetically modified mice exhibit resistance to nicotine-induced seizures, whereas the α5 and β4 subunits mediate both the locomotor suppressant effects of nicotine and somatic signs of nicotine withdrawal. Given that the genes that encode the α5, α3, and β4 subunits exist as a cluster in both mice (chromosome 9) and humans (chromosome 15), data suggest that this gene cluster may regulate multiple effects of nicotine.
In summary, research using genetically modified mice has demonstrated that nAChR subunits mediate the effects of nicotine on reward, associative learning, locomotor activity, pain perception, and several symptoms of nicotine withdrawal. These data in mice are consistent with research in humans, and suggest that data obtained from genetic KO/KI studies may help to determine the functions of these genes in humans. For instance, the effects of nicotine are similarly altered in α5, α3, and β4 KO mice; thus, multiple genes in the CHRNA5-CHRNA3-CHRNB4 gene cluster in humans may be critically involved in the behavioral effects of nicotine. It is important to note that one major limitation of research with genetically manipulated mice is that the deletion of a given nAChR subunit does not reveal whether variability in this gene can alter the response to nicotine. However, this issue can be addressed by observing the effects of nicotine in both KO and KI mice, as was done recently by Tapper and colleagues [168]. Additionally, Butt and colleagues [13] have demonstrated that stronger links between genetic variability and sensitivity to nicotine can be established by crossing inbred mouse strains with KO mice. Thus, future research examining the genetic factors that influence nicotine addiction should utilize these more powerful research designs.
Conclusion
Nicotine addiction is major worldwide health problem, and a more complete understanding of how genetic variability can influence vulnerability to addiction can explain individual differences in response to nicotine and in response to smoking cessation treatments. Additionally, a better understanding of genetic influences on nicotine addiction can aid in the development of more effective therapeutics. The reviewed research in humans has provided evidence that variability in nAChR subunit genes is associated with multiple smoking phenotypes, and that these effects depend upon other factors such as gender or ethnicity. These findings are consistent with studies in inbred strains of rats and mice, which exhibit significant strain-dependent differences in the response to nicotine. Furthermore, research with genetically manipulated mice has shown that nAChR subunit genes mediate the effects of nicotine, and that artificial changes in the amino acid sequence of these proteins can produce substantial changes in the functional properties of these receptors and will also alter the behavioral effects of nicotine. Naturally occurring variability in nAChR subunit genes in mice has also been linked to changes in receptor function and in the behavioral effects of nicotine. Although much remains unknown regarding the role of nAChR subunit genes in nicotine addiction, an important next step in understanding the genetic factors that modulate nicotine addiction will be the combined use of inbred mouse strains and KO mice to link genetic variability in nAChR subunit genes with background genotype.
Acknowledgements
The authors would like to acknowledge that the studies reviewed from our laboratory were supported by grants from the National Institute on Drug Abuse (DA017949 TG), and the National Cancer Institute/National Institute on Drug Transdisciplinary Tobacco Research Center Grant (P5084718 PI: Caryn Lerman Ph.D).
Footnotes
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An “*” indicates that other nAChR subunits may combine with the α4 and β2 subunits to form receptors.
In a synonymous SNP, the substitution of a nucleotide produces no changes in amino acid sequence, whereas in a non-synonymous SNP, a nucleotide substitution will change the amino acid sequence of the protein.
Substrains of an inbred mouse strain that are bred by separate sources (e.g. C57BL/6J vs. C57BL/6Ibg) can exhibit differences in behavior due to genetic drift [158]. Therefore, the inbred mouse strains described here will make a distinction between breeders.
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