Smoking contributes to the morbidity and mortality of a large component of the population, and twin studies provide strong evidence that genetic factors contribute substantially to the risk of developing nicotine dependence. This is the first high density, genome wide association study with the goal to identify common susceptibility or resistance gene variants for nicotine dependence.
Several novel genes were identified in this study as potential contributors to the development of nicotine dependence, such as Neurexin 1 (NRXN1
). There were at least two signals in NRXN1
. See . The SNP rs10490162
is weakly correlated with the other two SNPs that were genotyped in the gene (maximum pair wise correlation is r2
= 0.45 with the other two SNPs, which were found to be in strong disequilibrium with each other). Interestingly, another neurexin gene, Neurexin 3 (NRXN3
), was reported as a susceptibility gene for polysubstance addiction in a pooled genome wide association study by Uhl and colleagues (18
). In addition, the most significant SNP in NRXN3
in our study, rs2221299
, had a p-value of 0.0034. While there was substantially less evidence for association with NRXN3
in our study, the fact that two independent studies of substance dependence found evidence of association with neurexin genes merits further investigation.
All SNPs individually genotyped in the genes NRNX1 and VPS13A
The neurexin gene family is a group of polymorphic cell surface proteins expressed primarily in neurons that function in cell-cell interactions and are required for normal neurotransmitter release (19
). Neurexins are important factors in GABAergic and glutamatergic synapse genesis and are the only known factors reported to induce GABAergic postsynaptic differentiation. NRXN1
are among the largest known human genes, and they utilize at least two promoters and alternatively spliced exons to produce thousands of distinct mRNA transcripts and protein isoforms. It is hypothesized that differential expression of neurexin isoforms by GABAergic and glutamatergic neurons contribute to the local induction of postsynaptic specialization. Because substance dependence is modeled as a relative imbalance of excitatory and inhibitory neurotransmission (or related to “disinhibition”)(20
), the neurexin genes are plausible new candidate genes that contribute to the neurobiology of dependence through the regulated choice between excitatory or inhibitory pathways. Biological characterization of these genes may define a role of neural development or neurotransmitter release and dependence.
This study also identified a vacuolar sorting protein, VPS13A
, as a potential contributor to nicotine dependence. Interestingly, three independent genetic linkage studies of smoking (11
) identified a region on chromosome 9 near this gene. This gene appears to control the cycling of proteins through the cell membrane, and there are numerous alternative transcripts. Variants in the VPS13A
gene cause progressive neurodegeneration and red cell acanthocytosis (21
). Another novel gene for further study is TRPC7
(transient receptor potential canonical) channel which encodes a subunit of multimeric calcium channels (22
). A recent study using animal model indicated that TRPC channels can functionally regulate nicotine-induced neuronal activity in the locomotion circuitry (23
There are several other genes tagged by the top SNPs. An alpha catenin gene, CTNNA3
, inhibits Wnt signaling and has variants that affect the levels of plasma amyloid beta protein (Abeta42) in Alzheimer’s disease families (24
), though other reports fail to find an association with Alzheimer’s disease (25
). The CLCA1
gene encodes a calcium-activated chloride channel that may contribute to the pathogenesis of asthma (26
) and chronic obstructive pulmonary disease (27
). While none of these genes has a known relationship to nicotine metabolism or mechanism of action, they are involved in brain and lung function and therefore have plausible biological relationships to smoking behavior and dependence. Replication of these findings and additional biological characterization of these variants and genes may solidify these proposed links.
In addition to the novel genes implicated in the genome wide association study, a classic candidate gene, the β3 nicotinic receptor (CHRNB3) is among the top group. The nicotinic receptors are a family of ligand-gated ion channels that mediate fast signal transmission at synapses. Nicotine is an agonist of these receptors that produce physiological responses.
The SNPs were tested for varying gender effects as part of the primary analytic model. Several of the top SNPs had significantly different odds ratios for men and women (). It is clear from epidemiological data that there are significant gender differences in the risk for the development of dependence, and this study provides evidence that separate genes may contribute to the development of nicotine dependence in men and women. Following the primary analyses, we further analyzed the top ranked SNPs to determine if there was evidence for other modes of transmission, such as recessive or dominant models. There was no evidence for improvement in the fit for either of these models for any of the SNPs in the top group.
The maximum effect size for these top associated SNPs is an odds ratio of 2.53. These estimates are likely to be overestimates of the true population values due to the “jackpot effect” of many multiple comparisons. Several alternatives exist for correction of these estimates, but have not been applied to these data. The effect size estimates are consistent with multiple genes of modest effect contributing to the development of dependence.
This genome wide association study is a first step in a large-scale genetic examination of nicotine dependence. Our analytic plan was determined a priori so that we would be able to interpret the results most clearly. We purposefully chose to examine the entire sample as the primary analysis, rather than use a split sample design because we felt that this had the greatest power to detect true findings (28
). Though we have evidence of true results in this study, confirmation in an independent sample is crucial.
Many other issues will need to be addressed in the future examination of these data. For example, smoking and nicotine dependence are correlated with many other disorders, such as alcohol dependence and major depressive disorder (29
). Preliminary analyses of our sample have confirmed that this clustering of other disorders with nicotine dependence is present in our sample. In addition, nicotine dependence can be defined by other measures, such as the American Psychiatric Association criteria in the Diagnostic and Statistical Manual, Version IV (DSM-IV) (33
). Previous work has shown that though different measures of nicotine dependence are correlated, there is not perfect overlap because the FTND and DSM-IV definitions focus on different features of dependence (34
). The FTND is a measure that focuses on physiological dependence, whereas the DSM-IV dependence includes cognitive and behavioral aspects of dependence. Different classification by FTND and DSM-IV nicotine dependence is also seen in our sample with 75% of our cases (FTND ≥ 4) and 24% of our controls (FTND=0) affected with DSM-IV nicotine dependence. As we move forward with additional analyses, which will include comorbid disorders and varying definitions of nicotine dependence, we hope to explicate some of the individual features that contribute to these findings of association.
In summary, efforts to understand nicotine dependence are important so that new approaches can be developed to reduce tobacco use, especially cigarette smoking. This systematic survey of the genome nominates novel genes, such as NRXN1, that increase an individual’s risk of transitioning from smoking to nicotine dependence. The continued genetic and biological characterization of these genes will help in understanding the underlining causality of nicotine dependence and may provide novel drug development targets for smoking cessation. These variants also may be involved in addictive behavior in general. The current pharmacological treatments for nicotine dependence continue to produce only limited abstinence success, and the tailoring of medications to promote smoking cessation to an individual’s genetic background may significantly increase the efficacy of treatment. Our work is part of an emerging body of knowledge that may facilitate personalized approaches in the practice of medicine through large-scale study of genetic variants. Novel targets can now be studied and hopefully will facilitate the development of improved treatment options to alleviate this major health burden and reduce smoking related deaths.