Risk for nicotine dependence and lung cancer
is conferred by mRNA expression levels
and amino acid change in CHRNA5
Jen C. Wang1, Carlos Cruchaga1, Nancy L. Saccone2, Sarah Bertelsen1, Pengyuan Liu3,
John P. Budde1, Weimin Duan2, Louis Fox1, Richard A. Grucza1, Jason Kern1, Kevin Mayo1,
Oliver Reyes1, John Rice1, Scott F. Saccone1, Noah Spiegel1, Joseph H. Steinbach4,
Jerry A. Stitzel5, Marshall W. Anderson6, Ming You3, Victoria L. Stevens7, Laura J. Bierut1,
Alison M. Goate1,2,?and COGEND collaborators and GELCC collaborators
1Department of Psychiatry,2Department of Genetics,3Department of Surgery and4Department of Anesthesiology
Basic Science Research, Washington University, 660 South Euclid, PO Box 8134, St Louis, MO 63110, USA,
5Department of Integrative Physiology, University of Colorado, Boulder, CO, USA,6Department of Cancer and Cell
Biology, University of Cincinnati, Cincinnati, OH, USA and7Department of Epidemiology, American Cancer Society,
Atlanta, GA, USA
Received January 29, 2009; Revised March 25, 2009; Accepted May 11, 2009
Nicotine dependence risk and lung cancer risk are associated with variants in a region of chromosome
15 encompassing genes encoding the nicotinic receptor subunits CHRNA5, CHRNA3 and CHRNB4. To identify
potential biological mechanisms that underlie this risk, we tested for cis-acting eQTLs for CHRNA5, CHRNA3
and CHRNB4 in human brain. Using gene expression and disease association studies, we provide evidence
that both nicotine-dependence risk and lung cancer risk are influenced by functional variation in CHRNA5.
We demonstrated that the risk allele of rs16969968 primarily occurs on the low mRNA expression allele of
CHRNA5. The non-risk allele at rs16969968 occurs on both high and low expression alleles tagged by
rs588765 within CHRNA5. When the non-risk allele occurs on the background of low mRNA expression of
CHRNA5, the risk for nicotine dependence and lung cancer is significantly lower compared to those with
the higher mRNA expression. Together, these variants identify three levels of risk associated with
CHRNA5. We conclude that there are at least two distinct mechanisms conferring risk for nicotine depen-
dence and lung cancer: altered receptor function caused by a D398N amino acid variant in CHRNA5
(rs16969968) and variability in CHRNA5 mRNA expression.
Cigarette smoking is a common addictive disorder. In 2007, an
estimated 20% of Americans aged 18 years or older were
current smokers (defined as those who reported that they
smoked 100 cigarettes or more during their lifetime and
were currently smoking every day or some days) (1).
Among current cigarette smokers, 59% were nicotine-
dependent (2). It is well established that smoking has detri-
mental effects on physical health, increasing risk for cancer,
heart disease, stroke and chronic lung disease. According to
the World Health Organization’s report in 2006, tobacco use
is responsible for about five million deaths annually, making
it the largest cause of preventable mortality in the world (3).
In the USA, tobacco use is the leading cause of morbidity
and mortality; it accounts for 30% of all cancer deaths includ-
ing 87% of all deaths from lung cancer (4,5).
Many aspects of cigarette smoking behavior cluster in
families (6). Evidence from twin studies indicates that
genetic factors contribute to the development of smoking,
smoking persistence and nicotine dependence (7–9). Herit-
ability estimates for nicotine dependence range from 60% to
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Human Molecular Genetics, 2009, Vol. 18, No. 16
Advance Access published on May 14, 2009
72% (10), and the risk for the sibling of a nicotine-dependent
individual of developing nicotine dependence is 2-fold
increased over the general population rate.
Neuronal nicotinic acetylcholine receptors (nAChRs) are a
family of pentameric (mostly hetero-pentameric) ligand-gated
ion channels that can mediate fast signal transmission at
synapses (11) as well as modulate the release of several neu-
rotransmitters (12). Nicotine is an exogenous agonist of these
receptors. Within a few seconds of smoking, nicotine pro-
expressed receptor subtype in the brain is the a4b2 subtype.
Some a4b2 receptors also contain an a5 subunit (13).
Inclusion of an a5 subunit significantly increases the rate of
receptor desensitization and calcium permeability (14).
Recent studies have shown that nicotine can also induce
cell proliferation, tumor invasion and angiogenesis, and
confer resistance to apoptosis, processes that are mediated
through nAChRs (15–17). Thus, variations in nAChRs are
strong candidate risk factors for nicotine-dependence and
Several genetic association studies involving addiction in
humans have focused on genes encoding the major nAChR
subunits expressed in the brain (a4 and b2) (18–20). Recently,
our genome-wide association study (GWAS) and candidate
gene study of nicotine dependence identified several variants
in the gene cluster encoding the a5, a3 and b4 subunits on
chromosome 15 that alter risk for nicotine dependence, includ-
ing an amino acid substitution (a change from aspartic acid to
asparagine at codon 398) in the a5 nicotinic receptor subunit
gene (CHRNA5) and several non-coding variants across this
gene cluster (21–23). These associations have now been repli-
cated in independent smoking data sets (24–28). GWAS using
lung cancer populations from Europe, the USA and Iceland
have also demonstrated association between lung cancer sus-
ceptibility and the same variants or highly correlated variants
in the CHRNA5/A3/B4 gene cluster (27,29–31).
There is extensive linkage disequilibrium across the
CHRNA5/A3/B4 gene region. Two distinct LD bins (r2.
0.8) are associated with both nicotine dependence and lung
cancer (Supplementary Material, Fig. S1). One bin (bin 1) is
tagged by rs16969968 and the minor allele is linked to
increased risk for nicotine dependence (24–27,32) and lung
cancer (27,29,30). The second bin (bin 2) is tagged by
rs3743078 (or rs578776) and the minor allele is associated
with a reduced risk for nicotine dependence (24,26,28) and
lung cancer (30,31).
Rs16969968 is a missense variant that results in an amino
acid substitution at codon 398 (D398N) of CHRNA5. Our in
vitro functional study demonstrated that heterologously
expressed nicotinic receptors containing the missense variant
of CHRNA5, a4b2a5N398 exhibit reduced response to the
nicotinic agonist epibatidine when compared with receptors
containing the more common variant, a4b2a5D398 (25). No
other obvious functional variants are in this LD bin. Using
quantitative polymerase chain reaction (qPCR), we have pre-
viously shown that CHRNA5 mRNA levels in frontal cortex
and in lymphocytes are highly variable between individuals
and that some of this variability is explained by cis-acting
polymorphisms (33). The goal of this study was to determine
the influence of two potential biological mechanisms in the
etiology of nicotine dependence and lung cancer: the influence
of a missense mutation in a receptor subunit gene and the
influence of subunit mRNA expression level. We find that
both biological mechanisms play a role.
Postmortem interval, age, and smoking status are weakly
associated with CHRNA5, CHRNA3 and CHRNB4
mRNA levels, respectively
We used linear regression to test for evidence of differential
expression in samples of different genotype. First, we tested
whether drinking status affected gene expression in the
samples obtained from the Australian Brain Bank (ABDP).
CHRNB4 mRNA expression were observed between alcoholic
and non-alcoholic subjects. We then combined brain tissues
from both the Washington University Alzheimer’s Disease
Research Center (ADRC) and ABDP for further analysis.
The site of brain bank, postmortem interval, age, gender and
smoking history (ever smoke or never smoke) were tested
for their influence on mRNA levels of CHRNA5, CHRNA3
and CHRNB4 (Supplementary Material, Table S1). For
CHRNA5, only postmortem interval has a weak effect on
mRNA expression levels (P ¼ 0.02). Brain bank site, age
and gender influence CHRNA3 mRNA expression. However,
when theses variables were added to a linear regression
model, only age remained as a significant covariate. For
CHRNB4, site, gender and smoking history influence mRNA
expression. When these variables were included in the logistic
regression model, only smoking history has a significant effect
on mRNA expression levels.
Variability in CHRNA5 mRNA levels is strongly associated
with variants located upstream of the coding region
Single variant analysis. To examine whether the polymorph-
isms associated with nicotine dependence in the chromosome
15q24-25.1 region are also associated with gene expression,
we used real-time PCR to quantitate mRNA levels of
CHRNA5, CHRNA3 and CHRNB4 in the frontal cortex in indi-
viduals of different genotype. We genotyped 104 brain
samples of European descent with 44 variants spanning the
CHRNA5/A3/B4 gene cluster (Table 1 and Supplementary
Material, Table S2). These SNPs tag 79 of the 100 SNPs
that have a minor allele frequency?5% in the HapMap CEU
reference sample in this gene cluster at an r2of 0.8 or better
(dbSNP build 129 and HapMap public release 23a); 94 are
tagged at an r2? 0.6.
Using linear regression with postmortem interval as a cov-
ariate, 28 of 44 variants showed significant evidence for
association(P , 0.001)with
(Table 1). The variant showing the strongest evidence for
(rs3841324) located upstream of the coding region of
CHRNA5. However, several other variants in the upstream
region show comparable levels of association and are in
high linkage disequilibrium with each other (bin 3, Table 1).
3126Human Molecular Genetics, 2009, Vol. 18, No. 16
Subjects homozygous for the minor allele at rs3841324 (S,
short allele) show a 2.9-fold increase in CHRNA5 mRNA
levels in frontal cortex compared with major allele homozy-
gotes (Supplementary Material, Fig. S2). This confirms our
previous finding reported in a subset of the brain tissues
used in this study (33). The same observation was seen in
brain tissue from alcohol-dependent and non-dependent sub-
jects. Under an additive model, 42% of the variation in
CHRNA5 mRNA expression is explained by rs3841324 or
highly correlated polymorphisms. The variants showing the
strongest association with CHRNA5 mRNA expression are
not associated with either nicotine dependence or lung
cancer in single SNP association tests in European American
Variants in the LD bin previously reported to be associated
with reduced risk for nicotine dependence and tagged by
rs3743078 are also associated with variability in CHRNA5
mRNA expression levels. We observed that 13% of the varia-
bility in CHRNA5 mRNA expression is explained by
rs3743078 or highly correlated variants in an additive
model. However, using stepwise discriminant analysis with
rs3841324 (bin 3) and rs3743078 (bin 2), the association
between rs3743078 and CHRNA5 mRNA expression is no
longer significant. The D398N variant (rs16969968 in bin 1)
is more weakly associated with CHRNA5 mRNA expression
(P ¼ 0.01) (Supplementary Material, Fig. S3), though the
association is no longer significant after inclusion of
rs3841324 in the model.
Table 1. Association of CHRNA5 mRNA expression in human brain with variants in the CHRNA5–CHRNA3–CHRNB4 gene cluster
The data shown here are from a linear regression including source of brain tissue as a covariate. Bold, italic and bold-italic representations denote highly
correlated (r2? 0.6) variants in bins 1, 2 and 3, respectively. MAF, minor allele frequency. Asterisk (?) indicates a synonymous coding SNP; double
asterisk (??) indicates a non-synonymous coding SNP.
Human Molecular Genetics, 2009, Vol. 18, No. 163127
Among the 44 polymorphisms genotyped, 10 SNPs were
not highly correlated with any variants in bins 1, 2 or
3. Using the same linear regression analysis, we observed
that six of these SNPs, including two rare missense variants
in CHRNA3 and CHRNB4, respectively (rs8192475 and
rs12914008) are associated with CHRNA5 gene expression
(Table 1). Using stepwise discriminant analysis conditioning
on rs3841324, SNPs rs11636605 and rs3813567 (highly corre-
lated with rs11636605) remain weakly associated with mRNA
expression (P ¼ 0.02 and 0.04, respectively). The other SNPs
are no longer significantly associated.
Lower variability in mRNA expression was observed for
CHRNA3 and CHRNB4. Using linear regression with age as
a covariate, variants in bin 2 and bin 3 are weakly associated
with CHRNA3 mRNA expression levels (0.02 ? P ? 0.05)
(Supplementary Material, Table S2). Polymorphisms in bin 3
are also weakly associated with CHRNB4 mRNA expression
(0.01 ? P ? 0.05) in human brains using smoking history as
a covariate and dropping individuals with unknown smoking
history (Supplementary Material, Table S2). The D398N
variant (bin 1) is not associated with differences in mRNA
expression of either CHRNA3 or CHRNB4 (Supplementary
Material, Table S2).
Diplotype analysis. To determine which of the alleles of the
D398N polymorphism exist as high- and low-expressing
alleles, we performed haplotype and diplotype analyses
using a variant associated with CHRNA5 expression levels.
While the insertion/deletion variant, rs3841324, shows the
strongest association with CHRNA5 mRNA expression, this
variant has a lower genotyping success rate when compared
with other variants in bin 3 and was not genotyped in all of
the case–control series. Accordingly, we selected rs588765
for these analyses because it has a high genotyping call rate
(.99%) and is genotyped in two of three case–control
series. Haplotype and diplotype analysis with rs16969968
and rs588765 revealed three major haplotypes and six major
diplotypes. The risk genotype (AA) at rs16969968 usually
occurs with the low expression genotype (CC) at rs588765.
However, the non-risk genotype (GG) at rs16969968 occurs
with both the high expression genotype (TT at rs588765)
and the low expression genotype (CC at rs588765) for
CHRNA5 (Fig. 1, Supplementary Material, Table S3). By
looking at diplotypes, we can examine the effect of each
variant on a constant genotypic background for the other
variant. For instance, among subjects with non-risk genotype
at rs16969968, CHRNA5 mRNA expression levels are signifi-
cantly associated with genotypic variants at rs588765
(GG_CC diplotype shows lower expression than diplotype
P ¼ 3.66 ? 1025)
rs16969968 ona constant
rs588765 (see Fig. 1 and columns in Supplementary Material,
Table S3), there are no differences in expression.
Low levels of CHRNA5 mRNA are associated with lower
risk for nicotine dependence
Based upon our biological evidence that the D398N variant in
CHRNA5 alters receptor activity and that non-coding variation
alters CHRNA5 mRNA expression, we performed a diplotype
analysis in a large case–control series (ACS study) for nic-
otine dependence to test whether both the D398N variant
and CHRNA5 mRNA expression levels influence risk. This
analysis illustrates that both variants independently influence
risk for nicotine dependence (Table 2). The non-risk genotype
at rs16969968 occurs on both the high expression and low
expression alleles of CHRNA5. When the non-risk genotype
at rs16969968 occurs on the high-expression genotype of
CHRNA5 (GG_TT diplotype), the risk for developing nicotine
dependence is increased (OR ¼ 1.72, CI 1.19–2.47) relative to
GG_CC diplotype (Table 2, Fig. 1). Among the subjects
heterozygous at rs16969968, subjects with higher expression
(AG_CC versus AG_CT in Fig. 1) have higher risk for nic-
otine dependence (P ¼ 3.59 ? 1026). The risk genotype of
rs16969968 (AA) almost always occurs on the background
of low expression. On this constant background, this SNP
shows a dose-dependent increase in risk for nicotine depen-
dence (Table 2), and subjects with the AA_CC diplotype
have the highest risk for nicotine dependence (OR ¼ 2.32,
CI 1.58–3.43). Similar findings are seen in the COGEND
data set (data not shown). While these findings indicate that
the risk associated with the amino acid change outweighs
the protective effect of low expression, risk for nicotine depen-
dence is affected by both the D398N variant and variants that
alter CHRNA5 mRNA expression.
Figure 1. Association of different rs16969968-rs588765 diplotypes with
CHRNA5 mRNA expression (global test P , 0.0001). Diplotype analysis con-
firms that rs588765 alters CHRNA5 mRNA expression (GG_CC versus
GG_TT; P ¼ 3.66 ? 1025). It also demonstrates that rs16969968 does not
influence CHRNA5 mRNA expression. The bars represent mean+SD of
CHRNA5 mRNA expression. We used SAS software to run t-test for pair-wise
comparison of CHRNA5 mRNA expression with the specific genotype combi-
nation. The comparison of three diplotype groups (GGCC, AGCC and AACC)
was analyzed with F-test.
3128Human Molecular Genetics, 2009, Vol. 18, No. 16
Minor allele of rs3743078 tags the protective haplotype
associated with lower CHRNA5 expression
Previous association studies have shown that rs3743078 and
correlated SNPs in bin 2 (Table 1, Supplementary Material,
Fig. S1) are associated with lower risk for nicotine dependence
(22–24,26). In this study, we observe that these SNPs show
moderate association with CHRNA5 mRNA levels, but are
not strongly correlated with mRNA levels of CHRNA3 or
CHRNB4 (Table 1, Supplementary Material, Table S1). This
association is explained by LD between rs3743078 and
rs588765 and correlated SNPs. To test whether the previously
reported association with nicotine dependence also reflected
differences in CHRNA5 mRNA expression levels, we per-
formed a 2-SNP and 3-SNP haplotype analysis using
rs16969968, rs588765 and rs3743078. Both analyses revealed
only three major haplotypes (Tables 3 and 4). The risk variant
(A allele) of rs16969968 primarily occurs with the major allele
for rs588765 (C) and rs3743078 (C), which are correlated with
low CHRNA5 mRNA expression. The major allele (G) of
rs16969968 can pair with either major (C) (low expression)
or minor (T) (high expression) alleles of rs588765. The GC
haplotype (low expression) is associated with reduced risk
for nicotine dependence (P ¼ 5.27 ? 1029in ACS data set;
P ¼ 1.82 ? 1023
rs3743078 to the haplotype analysis does not change the
result indicating that the minor allele at rs3743078 is
taggingthe GC protective
rs16969968-rs588765 (Tables 3 and 4).
in COGEND data set). Adding SNP
Low levels of CHRNA5 mRNA reduce risk factor
for lung cancer
To examine whether the same haplotypes are associated with
lung cancer risk, we performed haplotype analysis with
rs16969968 and rs6495306 in a case–control series for lung
cancer (GELCC data set). We used rs6495306, which is
highly correlated with rs588765 (r2¼ 1 in COGEND data
set) for haplotype analysis because rs588765 was not included
in our lung cancer study. We observed the same three haplo-
types that were seen in the case–control series for nicotine
dependence. These haplotypes have similar effects on risk
for lung cancer (Table 5). The risk allele of rs16969968 (A,
coding for N398) for lung cancer is always associated with
the major allele of rs6495306 (T), which is associated with
lower mRNA expression of CHRNA5. The non-risk allele of
rs16969968 (G, coding for D398) can be paired with either
the major allele or the minor allele of rs6495306 (C). When
D398 of rs16969968 occurs on the background of low
mRNA expression of CHRNA5 (major allele of rs6495306,
T), the haplotype is associated with lower risk for lung cancer
(Table 5). Inour data set over 86% of cases and 93% ofcontrols
used tobacco. Using pack years as a covariate, we observed
similar association (global haplotype test P ¼ 1.01 ? 1023).
Because of the small size of this data set we were unable to sep-
arately analyze lung cancer individuals who have never
smoked. Nonetheless, these data are consistent with part of
as for nicotine dependence.
Further insights into the genetic basis of nicotine dependence
and smoking have strong potential to inform ongoing lung
cancer prevention and control efforts. The demonstration
that variants in nAChRs are associated with nicotine depen-
dence and lung cancer is an important step in understanding
the pathogenesis of nicotine dependence and correlated
In this study, we provide compelling evidence for at least
two different mechanisms of action: both a coding variant
that changes amino acid sequence in CHRNA5 (D398N) and
non-coding variants that regulate CHRNA5 gene expression
show association with risk for both nicotine dependence and
Surprisingly, the variants showing the strongest association
with CHRNA5 expression are not associated with either nic-
otine dependence or lung cancer in single SNP association
tests in European Americans. Only after diplotype analysis
do we see that when subjects with the non-risk genotype for
the D398N variant are associated with the low expression
(GG_CC diplotype of rs16969968-rs588765 in ACS data
set), the risk for developing nicotine dependence and lung
cancer is significantly lower compared to those with the
higher expression genotype
CHRNA5 (D398N), which greatly increases the risk for both
disorders, primarily occurs on the background of low mRNA
expression of CHRNA5. A small number of individuals carry
this risk allele on a high-expressing CHRNA5 allele. We
speculate that the risk for developing nicotine dependence
and lung cancer is further increased among these individuals,
although the number of individuals with this haplotype was
too small to formally test this hypothesis. The observation
that lower mRNA expression of CHRNA5 with the non-risk
genotype of rs16969968 is protective for nicotine dependence
and lung cancer suggests that altered function of the N398
variant of a5 subunit likely does not fully explain the associ-
ation between CHRNA5 and nicotine dependence and lung
cancer. Genetic variants tagged by rs3740378 are associated
with reduced risk for nicotine dependence and lung cancer
in single SNP association tests. Our data show that this associ-
ation reflects tagging of the protective haplotype associated
with low mRNA expression of the normal CHRNA5 allele.
Although we believe, based on our single SNP, haplotype
and functional studies, that there are two distinct mechanisms
associated with risk for nicotine dependence, we cannot
Table 2. Association of nicotine dependence with rs16969968-rs588765
diplotype in ACS study
CC (case/control) CT (case/control)TT (case/control)
OR (95% CI)
OR (95% CI)
OR (95% CI)
1.61 (1.12 2.33)
2.32 (1.58 3.43)
1.17 (0.82 1.69)
2.07 (1.47 2.94)
1.72 (1.19 2.47)
Human Molecular Genetics, 2009, Vol. 18, No. 16 3129
completely rule out the possibility that there is a third untyped
variant that could explain both the protective and risk effects
Neuronal nicotinic acetylcholine receptors form pentameric
ligand-gated ion channels. In the brain, CHRNA5 is most com-
monly found in heteromeric receptors composed of a4b2a5
sub-units. In addition, the a5 subunit is expressed outside
the brain, most prominently in postsynaptic receptors on
ganglionic neurons (34). However, a number of studies have
found that mRNA for the a5 subunit can be found in a
number of non-neuronal cells (35). These observations indi-
cate that genetic variation of a5 could have physiological
effects at a number of sites of significance in terms of
studies of behavior and addiction or carcinogenesis. Unfortu-
nately, studies of the variants of the a5 subunit are at an
early state, and only one previous functional study has been
In speculating about possible connections, three aspects
must be considered. The first is functional differences
between receptors containing different variants. The second
is the role of altered levels of protein expression of (either)
a5 variant. Finally, there may be alterations in expression of
other subunits in response to changes in a5 function or
expression. Regarding the first point, our previous work has
shown that a4b2?receptors containing the N398 CHRNA5
have a lower maximal response to acetylcholine than receptors
containing a5 D398 (25). In addition, sorting and trafficking
of nAChRs also depends strongly on the subunit composition
nAChRs in neurons will strongly affect neuronal responses
to nicotine (36). Cellular trafficking (37) as well as interaction
of a4b2?nAChRs with synaptic scaffolding proteins (13) is
altered by the presence of the a5 subunit. The variant is
located in the major cytoplasmic loop of the subunit, and
might influence localization of receptors. Hence, there is
reason to suggest that there will be differences in function
and possibly in the location of receptors containing the two
variants. Taking the second point, the specific subunit compo-
sition of nAChRs governs the acute responses to agonists, such
as endogenous acetylcholine and exogenous nicotine. The
presence of the a5 subunit affects the potency of agonists at
a4b2?receptors, shifting the activation curve to lower concen-
trations of acetylcholine by 10-fold or more (37–39). Desen-
sitization, which occurs at all nAChRs, describes the
phenomenon that even in the maintained presence of
agonist, the receptor has a closed channel. Kuryatov et al.
Table 5. Association of lung cancer with haplotype of rs16969968-rs6495306-rs3743078
Data set Haplotype Frequency of
P-value Effect on lung
GELCC (194 cases,
Global haplotype test: P ¼ 7.9E204.
Table 3. Association of nicotine dependence with 2-SNP haplotype of rs16969968-rs588765
Data set HaplotypeFrequency of
P-value Effect on nicotine
aGlobal test: P ¼ 5.69E210.
bGlobal test: P ¼ 2.36E204.
Table 4. Association of nicotine dependence with 3-SNP haplotype of rs16969968-rs588765-rs3743078 in ACS data set
HaplotypeFrequency of affected
Frequency of unaffected
P-value Effect on nicotine
Global haplotype test: P ¼ 4.68E210.
3130 Human Molecular Genetics, 2009, Vol. 18, No. 16
(37) have shown that inclusion of the a5 subunit significantly
increases the rate of desensitization of a4b2?nAChRs.
In addition, calcium permeability varies markedly with
subunit (40–42) composition, and inclusion of the a5
subunit in a4b2?nAChRs significantly increases calcium per-
meability (37,41). Since nicotine is much more slowly metab-
olized than acetylcholine, there may be a sustained Ca2þinflux
which is thought to play a role in activating several signal
transduction pathways that could lead to gene activation (in
addiction) (43,44) or to cell proliferation (in cancer) (45).
Finally, nicotine also acts as a pharmacological chaperone to
assist in the folding and maturation of nAChRs (46–48).
receptor number and stoichiometry is a general mechanism
for the phenomenon first described in 1983 that chronic
exposure to nicotine upregulates nAChRs (49–51). Such cha-
peroning by nicotine varies with detailed receptor stoichi-
ometry, and in particular between a4b2 receptors and
a4b2a5 receptors (although the reports differ in terms of the
effect seen) (37,52). All of these studies indicate that the
level of expression of the a5 subunit, in addition to functional
differences between variants, will have an influence on the
properties of a4b2?receptors. The final point, changes in
the expression of other subunits depending on the level of
expression of a5 protein, is suggested by studies of the
release in striatum from a6 receptors was found to be inver-
sely related to expression of the a5 subunit when wild-type
mice, mice heterozygous for a null mutation in Chrna5 and
mice homozygous for a null mutation in Chrna5 were com-
Taking into account all of these observations, it is possible
that the two biological factors are operating in two fashions.
First, the risk for individuals having the D398 (lower risk)
variant is lowered with low mRNA expression. This might
suggest that a high level of a5 expression is a risk factor,
per se, perhaps because of the functional consequences of
incorporation of the a5 subunit into a4b2?receptors (dis-
cussed above). Second, the higher-risk, N398, variant is very
strongly associated with low mRNA expression. This suggests
that an additional property of this variant subunit confers an
increased risk regardless of the expression level. It is not
known what property this is, nor whether the risks for addic-
tion or carcinogenesis will reflect the same property under-
lying this association.
Further studies are necessary to determine which of these
meability, chaperoning and potentially others) has the most
significant impact on risk for nicotinic addiction.
Although investigators in the lung cancer field have
suggested that the variants influencing risk for lung cancer
may lie outside the nicotinic receptor gene cluster, gene
expression data, functional data and genetic data point to the
nicotinic receptor genes particularly for addiction and specifi-
cally CHRNA5 as the most likely candidate. Furthermore, a
recent paper has reported that CHRNA5 mRNA expression is
elevated in lung adenocarcinoma compared with normal
lung tissue and that expression of CHRNA5 in normal lung
tissue is associated with genotype at rs16969968 suggesting
that CHRNA5 is also the most likely candidate gene for lung
cancer (54). No other SNPs were tested for association with
CHRNA5 mRNA expression in that study. However, based
on our studies in brain and lymphocytes, we would anticipate
that CHRNA5 mRNA expression in lung is more strongly
associated with rs588765 and other highly correlated SNPs
than with rs16969968.
This work provides a potential drug target for the treatment
of nicotine addiction/lung cancer and will lead to a better
understanding of the underlying biology of nicotine addiction
and smoking-related illnesses.
MATERIALS AND METHODS
Quantitative gene expression analysis in human brain
Postmortem brain tissue derived from the frontal cortex of 44
unrelated, non-demented elderly European Americans was
obtained from the Alzheimer’s Disease Research Center
(ADRC) of Washington University in St Louis (http://
alzheimer.wustl.edu/). Smoking status (tobacco use) is avail-
able for these subjects. We have also obtained a second set
of frontal cortex samples from the Australian Brain Donor
Program (ABDP), Sydney, Australia. Thirty-four of these
samples were derived from unrelated, non-alcohol-dependent
subjects and 35 samples were from alcohol-dependent sub-
jects. Fifty-nine samples were of European descent. Though
the smoking history (ever smoke or never smoke) was not
always recorded, 22 subjects who are alcohol-dependent
were smokers, and two were non-smokers. Among the
non-alcohol-dependent subjects 14 were smokers and four
were non-smokers. Others are unknown.
We used Qiagen’s DNeasy Blood and Tissue Kit and
RNeasy Lipid Tissue kit (http://www.qiagen.com) to extract
DNA and total RNA from brain tissues, respectively.
A cDNA library was prepared from total RNA using the
appliedbiosystems.com). Genomic DNA from all subjects
was genotyped for 44 polymorphisms in the CHRNA5/A3/B4
gene cluster. We used the Sequenom MassArray platform
for genotyping. A detailed genotyping protocol using MassAr-
ray technology is described elsewhere (55).
TaqMan assays (Applied Biosystems, CA, USA) were
CHRNB4 (Hs00609520_m1) mRNAs in human frontal
cortex. Gene expression levels were analyzed by real-time
PCR using an ABI-7500 real-time PCR system. The
program, Primer Express 3 (ABI) was used to design
primers and a TaqMan probe for the GAPDH gene. Each real-
time PCR run included within-plate duplicates and each exper-
iment was performed twice for each sample. Correction for
sample-to-sample variation was done by simultaneously
amplifying GAPDH as a reference. Real-time data was ana-
lyzed using the comparative Ct method (56).
We used linear regression to test for evidence of differential
expression in samples of different genotypes. To minimize
possible effects of sample heterogeneity, we performed our
association analyses in subjects of European descent only.
The origin of the sample (brain bank site), postmortem inter-
val, age, gender, drinking status and smoking history were
Human Molecular Genetics, 2009, Vol. 18, No. 16 3131
used as covariates. For diplotype analysis, we first log-
transformed relative mRNA expression to obtain a normal
distribution and then used a t-test to run pair-wise comparisons
of CHRNA5 mRNA expression with the specific genotype
combination. A comparison of three diplotype groups
(GGCC, AGCC and AACC) was made using F-test in the
SAS software release 9.1 (SAS Institute, Cary, NC, USA).
The Collaborative Genetic Study of Nicotine Dependence
recruited subjects from three urban areas in the USA: St
telephone-screening interview was used to identify individuals
who had smoked at least 100 cigarettes in their lifetime
(smokers). These individuals then completed the Fagerstorm
Test of Nicotine Dependence (FTND) questionnaire. Case
subjects were current smokers with a score of four or more
on the FTND, which defines nicotine dependence. Control
subjects smoked 100 cigarettes but never exhibited symptoms
of nicotine dependence (FTND ¼ 0), even during the heaviest
period of smoking. Details of this sample and genotyping
process have been reported elsewhere (21,23,57).
The smokers used in this study were participants in the
American Cancer Society CPS-II Cohort, a prospective
study of cancer mortality begun in 1982, and the CPS-II Nutri-
tion Cohort, a prospective study of cancer incidence formed in
1992 using a subset of CPS-II participants. Details regarding
recruitment into these studies are described elsewhere (26).
Information on smoking behavior from questionnaires admi-
nistered in 1982, 1992 and 1997 was used to identify light
and heavy smokers among participants. Individuals who
reported smoking at least 30 cigarettes/day for at least 5
years were defined as heavy smokers. This phenotype is
strongly correlated with nicotine dependence (26). We ran-
domly selected 750 heavy smoking men and 750 heavy
smoking women for this study (total n ¼ 1500). Light
smokers were defined as individuals who reported smoking
for at least 1 year during their lifetime and in 1982 and
1992, reported always smoking fewer than 10 cigarettes/day.
This was a rare phenotype especially among men. Among par-
ticipants with DNA, 461 men and 1482 women met these cri-
teria. We included all men defined as light smokers as well as
a random sample of 1039 light smoking women to give a total
of 1500 light smokers. A detailed description of the genotyp-
ing process was described elsewhere (26).
Lung cancer study subjects
We genotyped 194 cases with familial lung cancer and 219
cancer-free control subjects of European descent from the
(GELCC) using Affymetrix 500K or Affymetrix Genome-
Wide Human SNP Array 6.0 (Santa Clara, CA, USA).
A detailed description of the genotyping process is described
elsewhere (31). A sample of unrelated case individuals was
identified by selecting one case from each high-risk lung
cancer family. Among 194 cases, 186 individuals were
smokers. Non-cancer control subjects were recruited from a
combination of unaffected spouses from GELCC families
(n ¼ 36), unaffected individuals from the Coriell Institute for
Medical Research (Camden, NJ, USA) (n ¼ 11) and the
Fernald Medical Monitoring Program (Fernald, OH, USA)
(n ¼ 172). These control subjects had no blood relationship
with any selected case patients. Among 219 controls, 205 indi-
viduals used tobacco. Basic characteristics of the GELCC sub-
jects are presented elsewhere (31).
Data analysis. To minimize possible effects of sample hetero-
geneity, we performed our association analyses in subjects of
European descent only. We used the program PLINK (http://
pngu.mgh.harvard.edu/purcell/plink/) to generate haplotypes
and used linear regression to test the association of different
haplotypes with nicotine dependence and lung cancer. The
SAS software release 9.1 (SAS Institute, Cary, NC, USA)
was used to test the association of specific genotype combi-
nations with nicotine dependence.
Supplementary Material is available at HMG online.
We are grateful to the families for their participation in the
studies at the Washington University Alzheimer’s Disease
Research Center (ADRC) and at the Australian Brain Donor
Program (ABDP), Sydney, Australia. Funding for the research
at the ADRC was provided by grants from the National Insti-
tute on Aging: P50 AG05681 and P01 AG03991 to J.C.M. We
thank Dr Henry Lester for helpful discussions.
In memory of Theodore Reich, founding Principal Investigator
of Collaborative Genetic Study of Nicotine Dependence
(COGEND), we are indebted to his leadership in the establish-
ment and nurturing of COGEND and acknowledge with great
admiration his seminal scientific contributions to the field. The
COGEND project is a collaborative research group and part of
the NIDA Genetics Consortium. Subject collection was sup-
ported by NIH grant CA89392 (PI-L Bierut) from the National
Cancer Institute. Lead investigators directing data collection
are Laura Bierut, Naomi Breslau, Dorothy Hatsukami and
Eric Johnson. The authors thank Heidi Kromrei and Tracey
Richmond for their assistance in data collection. Genotyping
work at Perlegen Sciences was performed under NIDA Con-
tract HHSN271200477471C. Phenotypic and genotypic data
are stored in the NIDA Center for Genetic Studies (NCGS)
HHSN271200477451C (PIs J Tischfield and J Rice). Genotyp-
ing services were also provided by the Center for Inherited
Disease Research (CIDR). CIDR is fully funded through a
federal contract from the National Institutes of Health to
TheJohns Hopkins University,
3132 Human Molecular Genetics, 2009, Vol. 18, No. 16
The following authors are included under the COGEND col-
laborators: N. Breslau1, R. Culverhouse2, D. Hatsukami3,
A. Hinrichs2and Eric Johnson4.
1Department of Epidemiology, Michigan State University,
East Lansing, MI 48824, USA.
2Department of Psychiatry, Washington University, St Louis,
3Department of Psychiatry, University of Minnesota, Minnea-
polis, MN 55454, USA.
4Research Triangle Institute International, Research Triangle
Park, NC 27709, USA.
The Genetic Epidemiology of Lung Cancer Consortium
(GELCC) was formed by scientists from several US univer-
sities, plus the National Cancer Institute and the Human
Genome Research Institute to identify lung cancer suscepti-
bility genes in familial lung cancer populations. The Principal
Investigator is Dr Marshall Anderson, and the members of
GELCC are: University of Cincinnati (M Anderson, SM
Pinney, J Lee, E Kupert), Washington University (M You, Y
Wang, P Liu, H Vikis, Y Lu), Mayo Foundation & Clinic
(M de Andrade, P Yang, GM Petersen), Karmanos Cancer
Center (AG Schwartz), University of Colorado Health
Science (PR Fain), University of Toledo College of Medicine
(C Gaba), University of Texas Southwestern Medical Center (J
Minna, A Gazdar), Louisiana State University (Diptasri
Mandal), National Cancer Institute (D Seminara), National
Human Genome Research Institute (JE Bailey-Wilson), MD
Anderson Cancer Center (CI Amos). This work was supported
by the NIH grant U01CA076293 from the National Cancer
The following authors are included under the GELCC collab-
orators: Haris Vikis1, Yan Lu1, Yian Wang1, Ping Yang2,
Susan M. Pinney3, Gloria M. Petersen2, Mariza de Andrade2,
Ann G. Schwartz4, Adi Gazdar5, Colette Gaba6, Diptasri
Mandal7, Elena Kupert3, Juwon Lee3, Daniela Seminara8,
Pamela R. Fain9, John Minna5, Joan E. Bailey-Wilson10,
Yafang Li11, Christopher I. Amos11
1Department of Surgery, Washington University, St Louis,
2Mayo Clinic, Rochester, MN, USA.
3University of Cincinnati, Cincinnati, OH, USA.
4Karmanos Cancer Institute, Detroit, MI, USA.
5University of Texas Southwestern Medical Center, Dallas,
6University of Toledo College of Medicine, Toledo, OH, USA.
7Louisiana State University Health Science Center from
Louisiana State University, New Orleans, LA, USA.
8National Cancer Institute, Bethesda, MD, USA.
9University of Colorado, Denver, CO, USA.
10National Human Genome Research Institute, Bethesda, MD,
11M. D. Anderson Cancer Center, Houston, TX, USA.
This study is partially supported by the COGA project. The
Collaborative Study on the Genetics of Alcoholism (COGA),
Co-Principal Investigators B. Porjesz, V. Hesselbrock, H.
Edenberg, L. Bierut, includes nine different centers where
data collection, analysis and storage take place. The nine
sites and Principal Investigators and Co-investigators are: Uni-
versity of Connecticut (V. Hesselbrock); Indiana University
(H.J. Edenberg, J. Nurnberger Jr, T. Foroud); University of
Washington University in St Louis (L. Bierut, A. Goate, J.
Rice); University of California at San Diego (M. Schuckit);
Howard University (R. Taylor); Rutgers University (J. Tisch-
field); Southwest Foundation (L. Almasy). Q. Max Guo is the
NIAAA Staff Collaborator. This national collaborative study
is supported by the NIH Grant U10AA008401 from the
(NIAAA) and the National Institute on Drug Abuse (NIDA).
In memory of Henri Begleiter and Theodore Reich, Principal
and Co-Principal investigators of COGA since its inception;
we are indebted to their leadership in the establishment and
nurturing of COGA, and acknowledge with great admiration
their seminal scientific contributions to the field.
Downstate (B. Porjesz);
Conflict of Interest statement. L.J.B., A.M.G., A.J. Hinrichs,
J.P.R., S.F.S. and J.C.W. are listed as inventors on a patent
(US 20070258898) held by Perlegen Sciences, Inc., covering
the use of certain SNPs in determining the diagnosis, progno-
sis and treatment of addiction. N.L.S. is the spouse of S.F.S.,
who is listed as an inventor on the above-mentioned patent.
Bierut has acted as a consultant for Pfizer, Inc. in 2008.
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