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Association of a variant in the muscarinic acetylcholine receptor 2 gene (CHRM2) with nicotine addiction.

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BRIEF RESEARCH COMMUNICATION
Neuropsychiatric Genetics
Association of a Variant in the Muscarinic
Acetylcholine Receptor 2 Gene (CHRM2) With
Nicotine Addiction
A. Mobascher,1,2 D. Rujescu,3,4 K. Mittelstraß,5 I. Giegling,3,4 C. Lamina,5,6 B. Nitz,5 H. Brenner,7
C. Fehr,8 L.P. Breitling,7 J. Gallinat,9 D. Rothenbacher,7 E. Raum,7 H. M€uller,7 A. Ruppert,10
A.M. Hartmann,3,4 H.J. M€oller,4 A. Gal,11 Ch. Gieger,5 H.E. Wichmann,5 T. Illig,5
N. Dahmen,8 and G. Winterer1,2*
1
Department of Psychiatry, Neuropsychiatric Research Laboratory, Heinrich-Heine University, Duesseldorf, Germany
Institute of Neurosciences and Biophysics, Helmholtz Research Center, Juelich, Germany
2
3
Department of Psychiatry, Division of Molecular and Clinical Neurobiology, Ludwig-Maximilians-University, Munich, Germany
4
Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany
Helmholtz Zentrum M€unchen, German Research Center for Environmental Health (GmbH), Institute of Epidemiology, Neuherberg, Germany
5
6
Department of Medical Genetics, Molecular and Clinical Pharmacology, Division of Genetic Epidemiology,
Innsbruck Medical University, Innsbruck, Austria
7
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
Department of Psychiatry, University of Mainz, Mainz, Germany
8
9
Department of Psychiatry, Charite University Medicine Berlin, Campus Mitte, Berlin, Germany
10
Genetics Research Centre GmbH, Munich, Germany
Institute for Human Genetics, University of Hamburg Medical Center Eppendorf, Hamburg, Germany
11
Received 7 January 2009; Accepted 15 June 2009
Genetic factors contribute to the overall risk of developing
nicotine addiction, which is the major cause of preventable
deaths in western countries. However, knowledge regarding
specific polymorphisms influencing smoking phenotypes remains scarce. In the present study we provide evidence that a
common single nucleotide polymorphism (SNP) in the 50 untranslated region of CHRM2, the gene coding for the muscarinic
acetylcholine receptor 2 is associated with nicotine addiction.
CHRM2 was defined as a candidate gene for nicotine addiction
based on previous evidence that linked variations in CHRM2 to
alcohol and drug dependence. A total of more than 5,500 subjects
representative of the German population were genotyped and
How to Cite this Article:
Mobascher A, Rujescu D, Mittelstraß K,
Giegling I, Lamina C, Nitz B, Brenner H, Fehr
C, Breitling LP, Gallinat J, Rothenbacher D,
Raum E, M€
uller H, Ruppert A, Hartmann
AM, M€
oller HJ, Gal A, Gieger Ch, Wichmann
HE, Illig T, Dahmen N, Winterer G. 2010.
Association of a Variant in the Muscarinic
Acetylcholine Receptor 2 Gene (CHRM2)
With Nicotine Addiction.
Am J Med Genet Part B 153B:684–690.
Additional Supporting Information may be found in the online version of this article.
Grant sponsor: German Federal Ministry of Education and Research (BMBF); Grant sponsor: State of Bavaria and the National Genome Research Network
(NGFN); Grant sponsor: BMBF; Grant number: 01EB0113; Grant sponsor: DFG; Grant number: Wi2997/1-1; Grant sponsor: Project Berlin
Neuroimaging Center; Grant number: 01G00208; Grant sponsor: Baden W€
urttemberg Ministry of Research, Science and Arts; Grant sponsor:
Helmholtz Zentrum M€
unchen (KORA, ESTHER); Grant sponsor: Genetics Research Centre, Munich/Germany (NCOOP).
*Correspondence to:
G. Winterer, M.D., Ph.D., Department of Psychiatry, Laboratory of Neuropsychiatric Research, Heinrich-Heine University, Bergische Landstr. 2, 40629
Duesseldorf, Germany. E-mail: georg.winterer@uni-duesseldorf.de
Published online 30 July 2009 in Wiley InterScience (www.interscience.wiley.com)
DOI 10.1002/ajmg.b.31011
2009 Wiley-Liss, Inc.
684
MOBASCHER ET AL.
assessed regarding their smoking habits. The impact of three
SNPs in CHRM2 on smoking behavior/nicotine addiction was
investigated using logistic regression models or a quasi-Poisson
regression model, respectively. We found the T allele of
SNP rs324650 to be associated with an increased risk of smoking/
nicotine dependence according to three different models,
the recessive models of regular or heavy smokers vs. neversmokers (odds ratio 1.17 in both analyses) and according to the
Fagerstr€
om index of nicotine addiction. In the analysis stratified
by gender this association was only found in females. Our data
provide further evidence that variations in CHRM2 may be
associated with the genetic risk of addiction in general or
with certain personality traits that predispose to the development of addiction. Alternatively, variations in CHRM2 could
modulate presynaptic auto-regulation in cholinergic systems
and may thereby affect an individual’s response to nicotine more
specifically. 2009 Wiley-Liss, Inc.
Key words: smoking; nicotine addiction; CHRM2
Smoking due to nicotine addiction is the major cause of early,
preventable deaths in western societies [Frieden and Bloomberg,
2007; WHO Report on the global tobacco epidemic, 2008].
Environmental as well as genetic factors play a role in the etiology
of nicotine dependence and twin studies suggest a heritability of at
least 50% [Li, 2006]. A number of studies have found an association
between the CHRNA3-CHRNA5-CHRNB4 nicotinic acetylcholine
receptor subunit gene cluster on chromosome 15q24/25 and
smoking [Bierut et al., 2007, 2008; Saccone et al., 2007; Berrettini
et al., 2008; Chanock and Hunter, 2008; Hung et al., 2008;
Thorgeirsson et al., 2008]. Furthermore, CHRNA4, the gene coding
for the a4-subunit of nicotinic acetylcholine receptors, has been
linked to nicotine addiction and smoking [Feng et al., 2004;
Li et al., 2005; Hutchison et al., 2007; Breitling et al., in press].
However, other genes involved in dopaminergic or GABAergic
neurotransmission as well as genes involved in nicotine metabolism
have also been associated with smoking [for recent reviews see Ho
and Tyndale, 2007; Benowitz, 2008; Ray et al., 2008].
CHRM2, the gene coding for the muscarinic acetylcholine
receptor 2 has previously been identified as a risk gene for alcoholism in the collaborative study on the genetics of alcoholism
[COGA; Wang et al., 2004]. This finding was later replicated
and subsequent research suggested that genetic variations in
CHRM2 may also be associated with the abuse of illicit drugs
[Luo et al., 2005; Dick et al., 2007b]. In fact, the latter study
suggested that the association between CHRM2 and alcoholism in
the COGA sample was driven by a subsample with comorbid drug
abuse.
The comorbidity of alcoholism, drug addiction and nicotine
abuse is high [e.g. Bien and Burge, 1990], a phenomenon that may
be mediated by an overlapping set of risk genes [Grucza and Bierut,
2006]. Therefore and in view of the notion of a common molecular/
neurobiological pathway for addiction that is shared by different
addictive substances [Nestler, 2005], we sought to address the
question whether polymorphisms in CHRM2 may also be associated with smoking and nicotine dependence.
685
Thus, we investigated CHRM2 genotype, extent of nicotine
dependence and smoking habits in 5,561 subjects (derived from
three subsamples R1–R3) recruited from the general population in
Germany.
In the present study, ‘‘smoking status’’ was defined as follows:
people smoking at least one cigarette per day were defined as
regular smokers. People smoking 20 or more cigarettes per
day were defined as heavy smokers. Never-smoking controls had
a life-time history of no more than 100 cigarettes. In the MONICA/
KORA study (R1 sample) and NCOOP study (R2 sample) only
current smokers were considered. However, in the ESTHER
study (R3 sample) former smokers were also considered, if they
had been regular heavy smokers in the past (see also below).
In a subset of participants of the R1 and R2 subsamples, the
Fagerstr€
om test for nicotine dependence (FTND) was also performed. Detailed characteristics of the three study populations
are shown in Table I.
The three population-representative subsamples have been
described in more detail elsewhere [Low et al., 2004; Holle et al.,
2005; Wichmann et al., 2005; Twardella et al., 2006].
In brief, the first sample (R1) was derived from the S3/F3 (1994/
1995 and 10 years later) and S4 (1999/2001) surveys of the
MONICA/KORA study (Cooperative Health Research in the
Augsburg Region) which is a research platform for population
based health research. Out of 9,117 participants of the S3 and
S4 surveys drawn from the southern German population aged
25–84 years, N ¼ 1,412 subjects were randomly selected for
the present study. See Keil et al. [1998], Holle et al. [2005], or
Wichmann et al. [2005] for a further description of the MONICA/
KORA study procedures and characteristics.
The second sample (R2) was recruited within the framework of
the cooperation study on nicotine addiction (NCOOP) that was
performed in five German cities. Study centers were the LudwigMaximilians-University of Munich, the German Cancer Research
Center Heidelberg, the University of Mainz, the Heinrich-Heine
University Duesseldorf and the University of Berlin. The NCOOP
sample consisted of a total of N ¼ 1,855 subjects aged 18–79 years in
which the smoking phenotype was characterized. Due to missing
values, N ¼ 28 subjects of the R2 sample were dropped from the
present analysis.
The third sample (R3) was derived from the ESTHER cohort
study (epidemiological investigations of the chances of preventing,
recognizing early and optimally treating chronic diseases in an
elderly population), a research platform for studies of risk factors
and risk indicators for common diseases. The total ESTHER study
population comprised 9,953 participants aged 50–74 who were
recruited during health screening examinations by their general
practitioner. See Low et al. [2004] and Twardella et al. [2006] for
further details on that study. For the present analysis, only subjects
who reported a daily consumption of more than 20 cigarettes at
some point in their lives and never-smoking controls were considered. We reckoned that ever having reached regular, heavy smoking
status indicated the development of nicotine dependence. Therefore R3 subjects falling into this category were treated as regular and
heavy smokers, although many had already quit smoking at
study enrollment. Eventually, N ¼ 1,525 ever-smokers and N ¼ 769
686
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
TABLE I. Characteristics of the Three Study Populations
Total (N)
Males (N)
Females (N)
Age in years, mean (range)
FTNDa score (N)
Total, mean (range)
Males, mean (range)
Females, mean (range)
Regular smokers
Total, N (%)
Males, N (%)
Females, N (%)
Heavy smokers
Total, N (%)
Males, N (%)
Females, N (%)
Never-smoking controls
Total, N (%)
Males, N (%)
Females, N (%)
KORA
1,412
936
476
46.0 (25–84)
308
3.18 (0–10)
3.34 (0–10)
3.04 (0–10)
NCOOP
1,855
875
980
45.7 (18–79)
751
4.75 (0–10)
4.82 (0–10)
4.67 (0–10)
ESTHER
2,294
1,794
500
60.4 (48–75)
0
—
—
—
786 (55.7)
502 (53.6)
284 (59.7)
823 (44.4)
425 (48.6)
398 (40.6)
1,525 (66.5)
1,194 (66.6)
331 (66.2)
627 (44.4)
425 (45.4)
202 (42.4)
555 (29.9)
319 (36.5)
236 (24.1)
1,525 (66.5)
1,194 (66.6)
331 (66.2)
626 (44.3)
434 (46.4)
192 (40.3)
1004 (54.1)
432 (49.4)
572 (58.4)
769 (33.5)
600 (33.4)
169 (33.8)
a
FTND, Fagerstr€om test for nicotine dependence.
769 controls who were randomly selected (matched for sex and
age-group) from the over-all sample contributed to this study.
Ethical approval from the appropriate institutions was obtained
in the context of the individual studies that contributed to the
present study. The analyses presented in this report were covered by
the ethical approvals and written informed consent that was given
for study participation throughout.
The three single nucleotide polymorphisms (SNPs) rs1824024,
rs2061174, and rs324650 in the 5’ untranslated region of the
CHRM2 gene, which have been associated with alcoholism in the
original COGA report by Wang et al. [2004] were genotyped. DNA
was extracted from peripheral blood in all studies following standard procedures. Genotyping platforms employed were the Illumina BeadStation 500G Sentrix Array Matrices (Illumina, San
Diego, CA) for the MONICA/KORA study and the iPLEX
MALDI-TOF mass spectrometry (Sequenom, San Diego, CA) for
the NCOOP and ESTHER studies. Genotyping was performed
blind for smoking status. Logistic regression models were employed
to examine associations of individual SNPs with smoking status. A
quasi-Poisson regression model was used for association analysis
with FTND. Using R 2.6.0 (R Foundation of Statistical Computing,
2007), additive and recessive genotype models were calculated, all
adjusted for age and sex. Combined effect estimates were obtained
using a fixed effects model with inverse variance weights. A Q-test of
heterogeneity was performed for each SNP to evaluate the appropriateness of the fixed effects assumption [using SAS 9.1 (SAS
Institute, 2003)]. Bonferroni correction was applied on independent number of tests [P(corr)] for the main analyses. This number
was calculated using the effective number of loci [Li and Ji, 2005],
which accounts for the correlation structure between the SNPs.
Multiple testing correction did not include the multiple phenotype
models as well as the two different transmission models (additive
and recessive), as these are highly correlated. A haplotype analysis of
the three SNPs under investigation was performed using package
haplo.stats in R [Schaid et al., 2002].
Genotype information and quality criteria in the three cohorts
are provided in Supplementary Table S1. No deviation from
Hardy–Weinberg–Equilibrium (HWE) was seen in any of the
three sub-samples (P > 0.05). SNPs were moderately to highly
correlated in each sample (D’ ¼ 0.82–0.87 and r2 ¼ 0.66–0.68
between rs1824024 and rs2061174, D’ ¼ 0.52–0.56 and r2 ¼
0.15–0.18 between rs324650 and rs1824024/ rs2061174).
Figure 1 shows a linkage disequilibrium (LD) plot of the three
SNPs in the NCOOP sample (similar results were obtained in the
other two samples, data not shown). Due to this correlation
structure, the effective number of loci was estimated to be two out
of the three tested loci.
While rs1824024 and rs2061174 were not associated with nicotine
addiction in our study, we found rs324650 (an A/T single nucleotide polymorphism [with a minor (T-) allele frequency between
46% and 49% in the three samples]) to be associated with smoking
status in the NCOOP sample alone as well as in the pooled analysis
according to three different models: the recessive model of regular
smokers vs. nonsmokers, the recessive model of heavy smokers
versus nonsmokers and according to the additive model of nicotine
addiction as quantified by the Fagerstr€
om index. See Table II for
further details. There was no evidence for heterogeneity between
studies. A haplotype analysis of the three SNPs did not provide
additional information, that is, within these SNPs the genetic
liability for nicotine addiction was completely driven by rs324650.
FIG. 1. Linkage disequilibrium (LD plot) plot of CHRNA4 single
nucleotide polymorphisms (SNPs) in the NCOOP sample. [Color
figure can be viewed in the online issue, which is available at
www.interscience.wiley.com.]
In a post-hoc analysis stratified by gender the association of
rs324650 with smoking was only found in females (Table II).
We found rs324650, a variant in the 5’ untranslated region
of CHRM2, to be associated with smoking in a large sample
representative of the German population. Smoking behavior
has several—partially associated dimensions—such as smoking
initiation, smoking persistence, cigarettes smoked per day, and
nicotine dependence. Heritability estimates suggest that the genetic
architecture of the different aspects of smoking like smoking
initiation and nicotine dependence only partially overlaps [Maes
et al., 2004; Vink et al., 2005; Ho and Tyndale, 2007]. This means
that some risk genes are most likely specific to certain smoking
phenotypes [Sullivan et al., 2001] while others may have pleiotropic
effects [Caporaso et al., 2009]. Our data on rs324650 suggest that
CHRM2 may be associated with at least two different aspects of
smoking behavior, namely smoking initiation (being a regular or
heavy smoker) and severity of nicotine dependence as assessed by
the FTND.
However, the association between rs324650 and smoking
was restricted to females, a finding that is consistent with
gender-specific aspects in the genetic liability of smoking and
nicotine addiction.
Our Results allow at least three Different Interpretations.
KORA
0.40/0.80
0.57/1
0.97/1
P/Pcorr
OR# (95% CI)/
b (95% CI)*
NCOOP
P/Pcorr
0.02/0.04
0.015/0.03
0.019/0.038
0.167/0.334
0.019*/0.038*
0.242/0.484
0.017*/0.034*
0.80 (0.57, 1.10)
1.44 (1.06, 1.96)
0.81 (0.57, 1.15)
1.55 (1.08, 2.22)
P/Pcorr
0.43/0.86
0.43/0.86
P/Pcorr
0.021/0.042
0.029/0.058
0.028/0.056
P/Pcorr
OR# (95% CI)
P/Pcorr
Combined analysis
1.17 (1.02, 1.34)
1.17 (1.01, 1.35)
0.05 (0.01, 0.10)
OR# (95% CI)/
b (95% CI)*
Combined analysis
1.14 (0.89, 1.46) 0.313/0.626 1.00 (0.91–1.10)
0.995/1
0.95 (0.60, 1.49) 0.822/1
1.27 (1.02–1.59) 0.034*/0.068
1.14 (0.89, 1.46) 0.313/0.626 0.993 (0.895–1.10)
0.896/1
0.95 (0.60, 1.49) 0.822/1
1.26 (1.00–1.59) 0.048*/0.096
OR# (95% CI)
ESTHER
1.09 (0.88, 1.36)
1.09 (0.88, 1.36)
OR# (95% CI)/
b (95% CI)*
ESTHER
OR, odds ratio; CI, confidence interval; Pcorr, P-value corrected for number of effective loci (see LD plot); #OR are given for the minor (T) allele; Asterisk (*) for case–control analyses (model (a)) and (b); the OR and its CI is given; for Fagerstr€om analyses (model
(c)); the b-estimator and its CI is given; RS, regular smokers; HS, heavy smokers; NS, never-smokers.
P/Pcorr
OR# (95% CI)
NCOOP
1.23 (1.04, 1.61)
1.36 (1.06, 1.74)
0.06 (0.01, 0.10)
OR# (95% CI) P/Pcorr
b: Models adjusted for age, stratified by sex
Males: recessive model RS vs. NS 1.03 (0.75, 1.42) 0.842/1
Females: recessive model RS vs. NS 1.30 (0.81, 2.10) 0.275/0.55
Males: recessive model HS vs. NS 0.96 (0.66, 1.41) 0.842/1
Females: recessive model HS vs. NS 1.22 (0.81, 1.85) 0.336/0.672
a: Models adjusted for age and sex
Recessive model RS vs. NS 1.12 (0.86, 1.46)
Recessive model HS vs. NS 1.08 (0.82, 1.43)
Additive model FTND
0.00 (0.12, 0.13)
OR# (95% CI)/
b (95% CI)*
KORA
TABLE II. Association of CHRM2 SNP rs324650 With Smoking-Related Phenotypes
MOBASCHER ET AL.
687
688
Firstly, the association found may be driven by undetected
comorbid alcohol abuse/alcoholism or drug abuse. This possibility
seems least likely because of the structure of the three populationrepresentative samples.
Secondly, rs324650 may be associated with addiction in the
broader sense of an unspecific ‘‘addiction gene.’’ This notion would
not only be in line with previous findings regarding its association
with alcoholism and drug addiction [Wang et al., 2004; Luo et al.,
2005; Dick et al., 2007b], but also with evidence that CHRM2 may
be associated with certain personality traits such as externalizing
behavior which itself is associated with alcohol and drug
dependence/abuse [Dick et al., 2008]. However, in this context it
is interesting to note that in our study the T-allele of rs324650 was
the risk variant while in the original report on the COGA sample
[Wang et al., 2004] the T-allele was part of the T-T-T (rs1824024rs2061174-rs324650) haplotype that was under-transmitted to
subjects with alcoholism.
Thirdly, though not immediately apparent, genetic variations in
CHRM2 could be associated with nicotine addiction in a more
specific way. A direct modulation of the CHRM2 receptor by
nicotine seems unlikely based on the fundamental pharmacological
differences between nicotinic and muscarinic acetylcholine receptors. This is a striking difference between the association of the
variation in CHRM2 and smoking behavior/nicotine addiction
found in our study and numerous previous reports of the contribution of variations in genes coding for nicotinic acetylcholine
receptor subunits to the genetic liability of smoking. However,
CHRM2 is a G-protein coupled receptor that is most abundant in
the brain on presynaptic terminals of cholinergic neurons where it
regulates acetylcholine release [Mash et al., 1985; Zhou et al., 2001].
SNPs in the 50 UTR of CHRM2—like rs324650 which is located in
intron 5 of the 50 UTR—may alter gene expression and receptor
protein levels. It seems therefore plausible that a risk allele in
CHRM2 may shift the cholinergic tone in neuronal networks
involved in cognition or reward—networks that play a role in the
development of nicotine addiction—away from its optimum. This
situation could make an individual more susceptible to the addictive effects of nicotine and may therefore increase the risk for
nicotine dependence. For instance, there is increasing evidence
that subjects with impaired cognitive performance (like patients
suffering from schizophrenia or attention deficit hyperactivity
disorder) are more likely to be smokers than the general population
and that beneficial effects of nicotine on cognition are more
pronounced in these groups [Mobascher and Winterer, 2008].
In this context it is interesting to note, that variations in CHRM2
have also been implicated in the genetics of intelligence [Comings
et al., 2003; Gosso et al., 2006; Dick et al., 2007a]. Moreover it has
been reported that this gene is associated with event-related
electrophysiological brain responses to infrequent target stimuli
(EEG P300 oscillations), a cognitive endophenotype [Jones et al.,
2004].
The main purpose of this study was to investigate the role of
CHRM2, a gene that has previously been shown to be associated
with alcoholism and drug addiction, in the genetics of smoking
behavior and nicotine addiction. The significant association between rs324650 and smoking found in the pooled analysis was
mainly driven by one out of three subsamples with a higher
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
proportion of female participants than the other two samples.
Clearly, these results should be replicated in other, ideally still
larger studies which provide not only the adequate power to assess
potential variation of associations according to sex and possibly
other modifying factors but also feature improved gene coverage.
In summary, we found a common genetic variation (SNP
rs324650) in CHRM2, to be associated with smoking in a large
sample representative of the German population. This finding
provides further evidence that CHRM2 may be associated with
addiction in a broader sense, for instance by affecting certain
personality traits. However, more specific mechanisms that could
be related to the regulation of cholinergic neurotransmission may
also play a role.
Further research is needed to clarify how this and other SNPs in
CHRM2 affect gene function and gene expression and how these
genetic variants ultimately impact on the genetic liability for
nicotine dependence and other addictions.
ACKNOWLEDGMENTS
We are indebted to the study participants and personnel contributing to all aspects of the studies involved. The present work was
funded by grants within the German Research Foundation (DFG)
national priority programme SPP1226 ‘‘Nicotine: Physiological
and Molecular Effect in the CNS’’ (Br1704/11-1, Da370/5-1,
Ga804/1-1, Ru744/4-1, Wi1316/6-1, Wi1316/7-1). KORA was
supported by the German Federal Ministry of Education and
Research (BMBF), the State of Bavaria and the National Genome
Research Network (NGFN). NCOOP was supported in parts by
BMBF (#01EB0113), DFG (Wi2997/1-1), and further BMBF
funding is gratefully acknowledged (Project Berlin Neuroimaging
Center, #01G00208). ESTHER was supported by the Baden
W€
urttemberg Ministry of Research, Science and Arts. Genotyping
was carried out at the Genome Analysis Center (GAC) of the
Helmholtz Zentrum M€
unchen (KORA, ESTHER) and the Genetics
Research Centre, Munich/Germany (NCOOP) a joint venture
between LMU and GlaxoSmithKline Germany.
REFERENCES
Benowitz NL. 2008. Clinical pharmacology of nicotine: Implications
for understanding, preventing, and treating tobacco addiction. Clin
Pharmacol Ther 83:531–541.
Berrettini W, Yuan X, Tozzi F, Song K, Francks C, Chilcoat H, Waterworth
D, Muglia P, Mooser V. 2008. - a-5/a-3 nicotinic receptor subunit alleles
increase risk for heavy smoking. Mol Psychiatry 13:368–373.
Bien TH, Burge R. 1990. Smoking and drinking: A review of the literature.
Int J Addiction 25:1429–1454.
Bierut LJ, Madden PA, Breslau N, Johnson EO, Hatsukami D, Pomerleau
OF, Swan GE, Rutter J, Bertelsen S, Fox L, Fugman D, Goate AM,
Hinrichs AL, Konvicka K, Martin NG, Montgomery GW, Saccone NL,
Saccone SF, Wang JC, Chase GA, Rice JP, Ballinger DG. 2007. Novel genes
identified in a high-density genome wide association study for nicotine
dependence. Hum Mol Genet 16:24–35.
Bierut LJ, Stitzel JA, Wang JC, Hinrichs AL, Grucza RA, Xuei X, Saccone
NL, Saccone SF, Bertelsen S, Fox L, Horton WJ, Breslau N, Budde J,
MOBASCHER ET AL.
Cloninger CR, Dick DM, Foroud T, Hatsukami D, Hesselbrock V,
Johnson EO, Kramer J, Kuperman S, Madden PA, Mayo K, Nurnberger J
Jr, Pomerleau O, Porjesz B, Reyes O, Schuckit M, Swan G, Tischfield JA,
Edenberg HJ, Rice JP, Goate AM. 2008. Variants in nicotinic receptors
and risk for nicotine dependence. Am J Psychiatry 165:1163–1171.
Breitling LP, Dahmen N, Mittelstraß K, Rujescu D, Gallinat J, Fehr C,
Giegling I, Lamina C, Illig T, M€
uller H, Raum E, Rothenbacher D,
Wichmann HE, Brenner H, Winterer G. In press. Association of
nicotinic acetylcholine receptor subunit alpha-4 polymorphisms with
nicotine dependence in 5500 Germans. Pharmacogenomics J doi:
10.1038/tpj.2009.6.
Caporaso N, Gu F, Chatterjee N, Sheng-Chih J, Yu K, Yeager M, Chen C,
Jacobs K, Wheeler W, Landi MT, Ziegler RG, Hunter DJ, Chanock S,
Hankinson S, Kraft P, Bergen AW. 2009. Genome-wide and candidate
gene association study of cigarette smoking behaviors. PLoS One.
4(2):e4653.
Chanock SJ, Hunter DJ. 2008. When the smoke clears. Nature 452:537–538.
Comings DE, Wu S, Rostamkhani M, McGue M, Iacono WG, Cheng LSC,
MacMurray JP. 2003. Role of the cholinergic muscarinic 2 receptor
(CHRM2) gene in cognition. Mol Psychiatry 8:10–13.
Dick DM, Aliev F, Kramer J, Wang JC, Hinrichs A, Bertelsen S, Kuperman S,
Schuckit M, Nurnberger J Jr, Edenberg HJ, Porjesz B, Begleiter H,
Hesselbrock V, Goate A, Bierut L. 2007a. Association of CHRM2 with
IQ: Converging evidence for a gene influencing intelligence. Behav Genet
37:265–272.
Dick DM, Agrawal A, Wang JC, Hinrichs A, Bertelsen S, Bucholz KK,
Schuckit M, Kramer J, Nurnberger J Jr, Tischfield J, Edenberg HJ, Goate
A, Bierut LJ. 2007b. Alcohol dependence with comorbid drug dependence: Genetic and phenotypic associations suggest a more severe form of
the disorder with stronger genetic contribution to risk. Addiction
102:1131–1139.
Dick DM, Aliev F, Wang JC, Grucza RA, Schuckit M, Kuperman S, Kramer
J, Hinrichs A, Bertelsen S, Budde JP, Hesselbrock V, Porjesz B, Edenberg
HJ, Bierut LJ, Goate A. 2008. Using dimensional models of externalizing
psychopathology to aid in gene identification. Arch Gen Psychiatry
65:310–318.
Feng Y, Niu T, Xing H, Xu X, Chen C, Peng S, Wang L, Laird N, Xu X. 2004.
A common haplotype of the nicotine acetylcholine receptor alpha
4 subunit gene is associated with vulnerability to nicotine addiction in
men. Am J Hum Genet 75:112–121.
Frieden TR, Bloomberg MR. 2007. How to prevent 100 million deaths from
tobacco. Lancet 369:1758–1761.
Gosso MF, vam Belzen M, de Geus EJ, Polderman JC, Heutink P, Boomsma
DI, Posthuma D. 2006. Association between the CHRM2 gene and
intelligence in a sample of 304 Dutch families. Genes Brain Behav 5:
577–584.
Grucza RA, Bierut LJ. 2006. Co-occuring risk factors for alcohol dependence and habitual smoking: Update on findings from the Collaborative
Study on the Genetics of Alcoholism. Alcohol Res Health 29:172–178.
689
Lagiou P, Trichopoulos D, Holcatova I, Merletti F, Kjaerheim K, Agudo
A, Macfarlane G, Talamini R, Simonato L, Lowry R, Conway DI, Znaor A,
Healy C, Zelenika D, Boland A, Delepine M, Foglio M, Lechner D,
Matsuda F, Blanche H, Gut I, Heath S, Lathrop M, Brennan P. 2008. A
susceptibility locus for lung cancer maps to nicotinic acetylcholine
receptor subunit genes on 15q25. Nature 452:633–637.
Hutchison KE, Allen DL, Filbey FM, Jepson C, Lerman C, Benowitz NL,
Stitzel J, Bryan A, McGeary J, Haughey HM. 2007. CHRNA4 and tobacco
dependence: From gene regulation to treatment outcome. Arch Gen
Psychiatry 64:1078–1086.
Jones AJ, Porjesz B, Alsmasy L, Bierut L, Goate A, Wang JC, Dick DM,
Hinrichs A, Kwon J, Rice JP. 2004. Linkage and linkage disequilibrium of
evoked EEG oscillations with CHRM2 receptor gene polymorphisms:
Implications for human brain dynamics and cognition. Int J Psychophysiol 53:75–90.
Keil U, Liese AD, Hense HW, Filipiak B, Doring A, Stieber J, Lowel H. 1998.
Classical risk factors and their impact on incident non-fatal and
fatal myocardial infarction and all-cause mortality in southern
Germany. Results from the MONICA Augsburg cohort study
1984–1992. Monitoring trends and determinants in cardiovascular
diseases. Eur Heart J 19:1197–1207.
Li MD. 2006. The genetics of nicotine dependence. Curr Psychiatry Rep
8:158–164.
Li J, Ji L. 2005. Adjusting multiple testing in multilocus analyses using the
eigenvalues of a correlation matrix. Heredity 95:221–227.
Li MD, Beuten J, Ma JZ, Payne TJ, Lou XY, Garcia V, Duenes AS, Crews KM,
Elston RC. 2005. Ethnic- and gender-specific association of the nicotinic
acetylcholine receptor a4 subunit gene (CHRNA4) with nicotine
dependence. Hum Mol Genet 14:1211–1219.
Low M, Stegmaier C, Ziegler H, Rothenbacher D, Brenner H. 2004.
Epidemiological investigations of the chances of preventing, recognizing
early and optimally treating chronic diseases in an elderly population
(ESTHER) study. Dtsch Med Wochenschrift 129:2643–2647.
Luo X, Kranzler HR, Zuo L, Wang S, Blumberg HP, Gelernter J. 2005.
CHRM2 gene predisposes to alcohol dependence, drug dependence and
affective disorders: Results from an extended case-control structured
association study. Hum Mol Genet 14:2421–2434.
Maes HH, Sullivan P, Bulik CM, Neale MC, Prescott CA, Eaves LJ, Kendler
KS. 2004. A twin study of genetic and environmental influences on
tobacco initiation, regular tobacco use and nicotine dependence. Psychol
Med 34:1251–1261.
Mash DC, Flynn DD, Potter LT. 1985. Loss of M2 muscarine receptors in
the cerebral cortex in Alzheimer’s disease and experimental cholinergic
denervation. Science 228:1115–1117.
Mobascher A, Winterer G. 2008. The molecular and cellular neurobiology
of nicotine abuse in schizophrenia. Pharmacopsychiatry 41(Suppl 1):
51–59.
Nestler EJ. 2005. Is there a common molecular pathway for addiction?
Nature Neurosci 11:1445–1449.
Ho MK, Tyndale RF. 2007. Overview of the pharmacogenomics of cigarette
smoking. Pharmacogenomics 7:81–98.
R Foundation of Statistical Computing. 2007. R v2.6.0. Vienna
Holle R, Happich M, L€
owel H, Wichmann HE. 2005. KORA—A research
platform for population based health research. Gesundheitswesen
67(Suppl 1):S19–S25.
Ray R, Loughead J, Wang Z, Detre J, Yang E, Gur R, Lerman C. 2008.
Neuroimaging, genetics and the treatment of nicotine addiction. Bev
Brain Res 193:159–169.
Hung RJ, McKay JD, Gaborieau V, Boffetta P, Hashibe M, Zaridze D,
Mukeria A, Szeszenia-Dabrowska N, Lissowska J, Rudnai P, Fabianova E,
Mates D, Bencko V, Foretova L, Janout V, Chen C, Goodman G, Field JK,
Liloglou T, Xinarianos G, Cassidy A, McLaughlin J, Liu G, Narod S,
Krokan HE, Skorpen F, Elvestad MB, Hveem K, Vatten L, Linseisen J,
Clavel-Chapelon F, Vineis P, Bueno-de-Mesquita HB, Lund E, Martinez
C, Bingham S, Rasmuson T, Hainaut P, Riboli E, Ahrens W, Benhamou S,
Saccone SF, Hinrichs AL, Saccone NL, Chase GA, Konvicka K, Madden PA,
Breslau N, Johnson EO, Hatsukami D, Pomerleau O, Swan GE, Goate
AM, Rutter J, Bertelsen S, Fox L, Fugman D, Martin NG, Montgomery
GW, Wang JC, Ballinger DG, Rice JP, Bierut LJ. 2007. Cholinergic
nicotinic receptor genes implicated in a nicotine dependence association
study targeting 348 candiate genes with 3713 SNPs. Hum Mol Genet
16:36–49.
690
SAS Institute. 2003. Statistical analysis software, release 9.1. Cary, NC: SAS
Institute.
Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA. 2002. Score
tests for association between traits and haplotypes when linkage phase is
ambiguous. Am J Hum Genet 70:425–434.
Sullivan PF, Jiang Y, Neale MC, Kendler KS, Straub RE. 2001. Association
oft he tryptophan hydroxylase gene with smoking initiation but
not progression to nicotine dependence. Am J Med Genet 105:479–484.
Thorgeirsson TE, Geller F, Sulem P, Rafnar T, Wiste A, Magnusson KP,
Manolescu A, Thorleifsson G, Stefansson H, Ingason A, Stacey SN,
Bergthorsson JT, Thorlacius S, Gudmundsson J, Jonsson T, Jakobsdottir
M, Saemundsdottir J, Olafsdottir O, Gudmundsson LJ, Bjornsdottir G,
Kristjansson K, Skuladottir H, Isaksson HJ, Gudbjartsson T, Jones GT,
Mueller T, Gotts€ater A, Flex A, Aben KK, de Vegt F, Mulders PF, Isla D,
Vidal MJ, Asin L, Saez B, Murillo L, Blondal T, Kolbeinsson H, Stefansson
JG, Hansdottir I, Runarsdottir V, Pola R, Lindblad B, van Rij AM,
Dieplinger B, Haltmayer M, Mayordomo JI, Kiemeney LA, Matthiasson
SE, Oskarsson H, Tyrfingsson T, Gudbjartsson DF, Gulcher JR, Jonsson S,
Thorsteinsdottir U, Kong A, Stefansson K. 2008. A variant associated with
nicotine dependence, lung cancer and peripheral arterial disease. Nature
452:638–641.
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
Twardella D, Loew M, Rothenbacher D, Stegmaier C, Ziegler H, Brenner H.
2006. The diagnosis of smoking-related disease is a prominent trigger for
smoking cessation in a retrospective cohort study. J Clin Epidemiol
59:82–89.
Vink JM, Willemsen G, Boomsma DI. 2005. Heritability of smoking
initiation and nicotine dependence. Behav Genet 35:397–406.
Wang JC, Hinrichs AL, Stock H, Budde J, Allen R, Bertelsen S, Kwon JM,
Wu W, Dick DM, Rice J, Jones K, Nurnberger JI Jr, Tischfield J, Porjesz B,
Edenberg HJ, Hesselbrock V, Crowe R, Schuckit M, Begleiter H, Reich T,
Goate AM, Bierut LJ. 2004. Evidence of common and specific genetic
effects: Association of the muscarinic acetylcholine receptor M2
(CHRM2) gene with alcohol dependence and major depressive syndrome. Hum Mol Genet 13:1903–1911.
WHO Report on the global tobacco epidemic. 2008. http://www.who.int/
tobacco.
Wichmann HE, Gieger C, Illig T. 2005. KORA-gen—Resource for population genetics, controls and broad spectrum of disease phenotypes.
Gesundheitswesen 67(Suppl 1):S26–S30.
Zhou C, Fryer AD, Jacoby DB. 2001. Structure of the human M2 muscarinic
acetylcholine receptor gene and its promoter. Gene 271:87–92.
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