This study reports one of the first few GWAS of smoking behavior in Caucasians. Through this study, we identified a cluster of nine SNPs upstream from the IL15
gene, which ranked among the most significant 30 SNPs associated with smoking status in our GWAS (Appendix I
). Gender-specific analyses indicated that these nine SNPs were associated with smoking status in a male-specific manner (). In particular, the SNP rs4956302
achieved a genome-wide significant p
value of 8.80×10−8
in male subjects. Another SNP, rs17354547
, is highly conserved across multiple species (), suggesting its functional importance. Of note, these nine SNPs were also associated with another important phenotype for smoking behavior, cigarette consumption (SQ), and this association was also male specific ().
From these nine SNPs, we choose four SNPs (rs4956302, rs17354547, rs1402812 and rs4956396) to replicate our association findings in an AA family-based cohort containing 1,251 subjects, including 412 males and 839 females. We selected rs4956302 due to the fact that it achieved the highest significance among all the SNPs tested genome-wide in our GWAS cohort. We also selected rs17354547 because it is highly conserved across multiple species. Another two SNPs (rs1402812 and rs4956396) were randomly chosen since all seven of the remaining significant SNPs are in high LD and had similar p values. Interestingly, a male-specific association with multiple ND phenotypes was observed for the SNP rs17354547; in male subjects of our AA replication cohort SNP rs17354547 achieved p values of 0.031, 0.0046 and 0.019 for association with SQ, HSI and FTND, respectively (). Furthermore, in male subjects from our replication sample, a haplotype formed by the SNPs rs17354547, rs1402812 and rs4956396 was also associated with SQ, HSI and FTND, with p values of 0.039, 0.0093 and 0.0093, respectively. The replication results support our GWAS findings for an association between smoking behavior and these SNPs located upstream from the IL15 gene.
To further confirm our GWAS findings, we performed an in silico replication study of the nine interesting SNPs upstream of the IL15 gene using a large FHS sample containing 7,623 Caucasians from 1,731 families. Again, a clear pattern of male-specific association of these SNPs with smoking status was observed; although none of the SNPs achieved p values less than 0.44 in the female subgroup, seven of the SNPs achieved p values less than 0.05 and two achieved p values less than 0.10 in the male subgroup (). The results provide additional support to our GWAS findings and replication findings achieved in the AA cohort.
It was not until very recently that intergenic transcription has been recognized as an active and common cellular process. Evidence has shown that a significant portion of the transcriptome arises from outside annotated genes (31
). As an important function, intergenic transcription can regulate expression at nearby genes (33
). In particular, intergenic transcription was found to be an important mechanism underlying expression of cytokine genes, such as GM-CSF, IL3, IL4, IL5, IL 10,
). Given their location at potential TF binding sites, those SNPs identified in our GWAS that are upstream from the cytokine gene IL15
, might potentially regulate IL15
gene expression through intergenic transcription. Importantly, the SNP, rs17354547
, replicated in both the AA and FHS cohorts, as well as the TF binding site that can be potentially modulated by this SNP, are highly conserved across multiple species (), further supporting the functional importance of this SNP in transcription regulation. Overall, our findings suggest that the observed association of the SNPs upstream of the IL15
gene with smoking status and multiple ND phenotypes may be mediated through regulation of IL15
gene expression, and that this appears to represent a novel mechanism underlying smoking behavior.
Multiple lines of evidence demonstrate that the immune system, in particular, lymphoid cells, play an important role in drug addiction. Destruction of the immune system with irradiation or immunosuppressive drugs has been shown to significantly alleviate the opiate-withdrawal syndrome (39
). In contrast, transfer of lymphoid cells to irradiated rats before morphine administration restores drug-withdrawal signs (41
). These findings suggest a mechanism for neuro-immunological interactions, where factors derived from the immune system may regulate functions of the central nervous system, influencing addictive behaviors. This mechanism is supported by the discovery of functional synapses between neurons and lymphocytes (42
). Given that IL15
is an important immunoregulatory cytokine influencing activation and proliferation of T lymphocytes and natural killer cells, it appears reasonable to speculate that IL15
influences smoking addiction through its immunoregulatory effects.
Population stratification and/or ethnic admixture can be an important source of spurious association in genetic association studies. However, these factors did not affect our GWAS sample and are therefore unlikely to have interfered with our association results. Our study cohort came from an apparently homogenous US mid-west white population, living in Omaha, Nebraska and its surrounding areas. We found that the allele frequencies for the interesting SNPs in our sample are very similar to those reported in the typical and representative Caucasian samples used in the HapMap CEU (). Furthermore, using the program Structure 2.2 (24
), we analyzed our study subjects thoroughly in order to detect potential sub-populations in our sample. In these analyses, all subjects tightly clustered together as a single group, suggesting no significant population substructure in our sample (Appendix III
). Furthermore, the measure for population stratification (λ) for our GWAS sample, calculated through the genomic control method (25
), was 1.009 for smoking status and 1.012 for cigarette consumption, suggesting essentially no stratification. For the above reasons, the association results, as detected in our GWAS, are not likely to be plagued by spurious associations due to population admixture/stratification.
In our GWAS discovery cohort, control subjects were defined as never-smokers. This criterion for selecting controls is different from the conventional one, where current non-smoking subjects with a certain degree of previous exposure (e.g., having smoked more than 1 but less than 100 cigarettes in their lifetime) are normally selected as controls. Therefore, a potential problem of our study design is that some “control” subjects in our GWAS sample may in future become smokers if exposed to cigarettes. Depending on the number of such subjects, this potential misclassification problem may undercut the statistical power of our study, leading to false negative results. In our study, we tried to minimize the effects caused by this potential problem by excluding those control (non-smoking) subjects under the age of 25 from our study. Since most smokers initiate smoking behavior in adolescence, non-smoking subjects under the age of 25 may have a much higher chance than older people to develop smoking behavior if exposed to cigarettes. Therefore, after excluding these younger subjects from our control group, the subjects in the group that may later develop smoking behavior due to exposure to cigarettes, if existing, may not be in large numbers. Hence, the potential misclassification problem caused by our control subject selection strategy may have only moderate effects to the overall results of our study. The robustness of our GWAS findings is supported by their replication in both the AA and FHS cohorts.
As another limitation of our study, we did not adjust for multiple testing (for testing multiple smoking behavior-related phenotypes in our GWAS and the AA replication cohorts). However, due to the limited number of different phenotypes (i.e., 2 phenotypes in the GWAS cohort and 3 phenotypes in the AA cohort) and the fact that these phenotypes are correlated smoking behavior traits, adjusting for multiple testing may only have minor effects on the current results. Even with the most stringent correction, Bonferroni correction that does not consider correlation of the multiple traits, the most significant SNP in our GWAS, rs4956302, is still significant at the corrected genome-wide significance level of 2.1×10−7 (= 4.2×10−7/2) for association with smoking status, and the most significant SNP in our AA replication study, rs17354547, is also significant at the corrected significance level of 0.017 (=0.05/3) for association with HSI. Again, replication of our GWAS findings in two different cohorts attests to the findings' robustness and may have attenuated the potential problem due to multiple testing of several phenotypes.
In summary, we identified a group of SNPs, upstream from the IL15
gene, that were associated with both smoking status and quantity of cigarette consumption. Interestingly, a key SNP, rs17354547
, which is highly conserved across multiple species, was replicated in an independent AA cohort for association with multiple ND phenotypes. Moreover, all of the nine SNPs were replicated in silico
in a FHS cohort for association with smoking status. Remarkably, the association of the SNPs with smoking behavior-related phenotypes in both our GWAS and the two replication samples appeared to be male-specific. Higher prevalence of smoking in males than in females in the US (3
) attaches additional importance to our findings. Some of the SNPs, located at potential TF binding sites, may regulate IL15
gene expression and consequently, could have an important regulatory effect on the immune system. The above findings, together with previous data from studies of drug addiction, compel us to propose a novel mechanism for smoking addiction modulated by the immune system, where the IL15
pathway may play a key role. The confirmation and elaboration of this hypothetical mechanism needs further detailed functional studies directed at IL15.