Reported gender differences in smoking behavior and cessation motivated this gender-stratified analysis in two pharmacogenetic smoking cessation trials. Previous research identified SNPs and genes within the two separate clinical trials comprising this study.24–28, 30–32, 50
This analysis builds upon those study results by pooling both studies to look within genders across all four treatments across 53 candidate gene regions. Instead of focusing on estimated heterogeneity between genders, our aim was to identify SNPs with effects specific to males and/or females.
Gender-stratified SNP marginal effects revealed a male-specific association between a region of high LD within EPB41 and smoking abstinence at EOT and 6-month follow-up. Within males, we identified four non-coding SNPs in EPB41 (rs6702335, rs12021667, rs12027267, rs12039988) in strong LD (r2>0.98). rs12021667 lies in the 5′-UTR, rs12039988 in the 3′-UTR, and rs12027267 and rs6702335 both in intronic regions. These SNPs achieved system-level significance in association with smoking abstinence at EOT (adjusted P<6×10−5). At 6-month follow-up, rs6702335 and rs12027267 approached system-level significance (P≤8.0×10−4) while rs12021667 and rs12039988 achieved region-level significance (adjusted Ps=0.002 and 0.005, respectively). In males, these SNPs were associated with a more than two-fold decrease in odds of abstinence at both cessation endpoints.
Erythrocyte membrane protein band 4.1 (EPB41
), known as protein 4.1R, is critical for red blood cell morphology and membrane function.51–54
This protein and its homologues have not been associated with nicotine dependence and smoking, but they were shown to stabilize the localization of dopamine receptors to the plasma membrane,55
and protein 4.1R had a specific organizational role in the arrangement of postsynaptic molecules.54
Our data suggests that genetic variation in EPB41
has gender-specific effects on smoking abstinence, potentially mediated through differential effects on the localization or function of dopamine receptors and further downstream effects on the brain reward pathway.
is adjacent to delta opioid receptor 1 (OPRD1
), which is part of the family of opioid receptor genes associated with substance abuse.56
Using HapMap SNP genotypes from the CEPH population (Release #28, NCBI Build 36)36
none of the SNPs in EPB41
that achieved system-wide significance are in LD with any SNPs in OPRD1
<0.35). However, a SNP in EPB41
achieving region-wide significance (rs16837840) is in moderate LD (r2
=0.6) with a SNP in OPRD1
(rs12404612). After imputation of EPB41
, rs12404612 (certainty score > 0.9) had male-specific marginal associations with abstinence at EOT and 6-month follow-up (0.01 < P
= 0.02 and 0.03, respectively). Interestingly, other imputed SNPs in OPRD1
with imputation certainty scores < 0.9 showed strong associations with smoking abstinence.
Gender-stratified SNP × treatment interaction analyses revealed a male-specific association between smoking abstinence and two SNPs in CNR1
in weak LD (rs806365, rs806369, r2
=0.5). rs806365 lies in the 3′ flanking region of CNR1
, while due to multiple CNR1
rs806369 lies either in an intron or the 5′ flanking region. For abstinence at 6-month follow-up, the male-specific interaction between rs806365 and treatment achieved system-level significance (adjusted interaction LRT P
). The effect of this SNP was most prominent in males within the spray arm, where it was associated with a 25-fold decrease in odds of abstinence. Effects at EOT were similar, where rs806365 was associated with a nearly 6-fold decrease in abstinence odds for males in the spray arm (adjusted interaction LRT P
=0.001). Males with two major alleles in the spray arm had the highest abstinence rates, and this remained relatively unchanged from EOT to 6-month follow-up; males with at least one minor allele had the lowest abstinence rates across all males.
The relationship between cannabinoid receptor 1 (CNR1
) and addictive behaviors has been well-characterized.58–61
Along with its primary role in mediating the effects of marijuana,58
it modulates dopamine release in response to other substances.62
antagonist, rimonabant, was effective in suppressing smoking relapse and attenuating reward seeking behaviors during abstinence.59, 60
There was also a female-specific association between SNPs and haplotypes in CNR1
and both nicotine dependence and smoking initiation.63
Although there is no overlap of SNPs investigated in that study with our current investigation, both point to gender-specific associations of smoking behaviors with CNR1
. Our analysis suggests that gene associations are not only gender-specific but treatment- and gender-specific. Of the treatments administered, the nasal spray most closely mimics the effects of smoking, introducing a sharp, rapid increase in nicotine levels.64
Since males are more responsive to nicotine dosage and pharmacological reinforcement by nicotine, they may be more sensitive to the effects of the spray. Within the spray arm, males with two major alleles for rs806365 and rs806369 had higher abstinence rates than those with at least one minor allele. Opposite and variable effects of these SNPs in females may be attributed to gender differences in the pharmacological effects of nicotine.12, 65
It is worth highlighting that for both marginal and interaction effects, no SNPs achieving region-or system-wide significance within one gender stratum achieved significance within the other gender stratum. For marginal effects, there was no overlap in gene regions between genders, with male-specific significant SNPs in EPB41
, and female-specific SNPs in ANKK1
and α4 and β2 nAChR gene subunits. Across both abstinence outcomes, gene × treatment interactions identified associations across women and men in the nAChR subunit regions and MAPK1
. This consistency in gene regions adds evidence of their putative roles in nicotine dependence and smoking behavior.47, 49, 66–71
These regions, along with the others without overlap, have shown prior evidence of association with nicotine dependence and smoking cessation, and require further study to validate gender-specific effects.
The use of 1000 Genomes Project data for imputation helped to broaden the areas for potential follow-up for the specific putatively causal variant within our top gene regions. Additionally, we imputed within the previously reported region of chromosome 15, a region linked to smoking dependence72
and other smoking related diseases.49, 73–75
For this region, imputation identified two gene regions proximal of the chromosome 15 α5-α3-β4 nAChR complex associated with smoking abstinence (Supplemental Figure 2
have imputed SNPs in LD (r2
>0.6) with our strongest signal in the nAChR gene region (rs684513) that had comparable or more significant SNP × treatment interactions on smoking abstinence at 6-month follow-up within males (1×10−5
). An intronic SNP in AGPHD1
, rs12441354, had the strongest association (P
Strengths and limitations of this study have been described previously,24, 25
but we highlight a few here. We did not have to address potential biases in determining smoking abstinence since information was collected from individuals in a prospective manner, and those claiming to be abstinent were subjected to biochemical verification. Similar study designs between studies suggest that subjects are comparable. However, differential responses in abstinence rates across genders and treatments could have arisen from a key difference in exclusion criteria.25
Only participants in the NRT study were excluded for drug or alcohol dependence or any subsequent treatment. Subjects in the Bupropion study may have used other substances to compensate for any adverse effects from smoking cessation.
In our analysis, we performed an adjustment of P-values that accounted for multiple correlated tests within respective gene regions. A Bonferroni-corrected P-value was then applied across the 53 gene regions and two genders. This correction was less stringent than a uniform Bonferroni-correction across all SNPs, while still accounting for independent gene regions and both genders. Thus, a SNP was significant within a respective region and gender at a P-value < 0.05, while system-wide significance was set at an α-level of 0.05/(53*2)=5×10−4.
While our determination of significance was conservative, the results require independent replication. Identified SNPs with the strongest evidence of association have not been replicated in other studies, and the region with strongest marginal SNP effects, EPB41, has not been associated with nicotine dependence or smoking previously. Confirmation from other studies, especially gender-specific results, would lend support to our findings. However, our study has identified a novel gene region, EPB41, which may be associated with smoking cessation, along with gene regions in CNR1 that may be targeted to further elucidate the etiology of gender differences in smoking behaviors.