Genetic susceptibility to substance dependence
N Hiroi1,2and S Agatsuma1
1Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA;2Department of
Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
Despite what is often believed, the majority of those who experiment with substances with a
dependence potential do not develop dependence. However, there is a subpopulation of users
that easily becomes dependent on substances, and these individuals exhibit pre-existing
comorbid traits, including novelty seeking and antisocial behavior. There appears to be a
genetic basis for the susceptibility to dependence and these comorbid traits. Animal studies
have identified specific genes that can alter susceptibility to dependence and response to
novelty. The mechanisms underlying the genetic susceptibility to dependence and response to
novelty are complex, but genetic susceptibility plays a significant role in the transition from
substance use to dependence and from chronic use to addiction. We discuss two models to
explain how genetic variations alter dependence susceptibility. Identification of the specific
genes involved in these processes would help to identify individuals that are vulnerable to
dependence/addiction and to devise novel treatment strategies.
Molecular Psychiatry (2005) 10, 336–344. doi:10.1038/sj.mp.4001622
Published online 7 December 2004
Keywords: gene; addiction; comorbidity; novelty/sensation seeking
Chronic use of several classes of substances results in
physical, psychological, and behavioral changes in
humans. Distinct sets of symptoms characterize
dependence and addiction. Dependence, which in-
cludes both physical and behavioral dependence, is
the most comprehensive definition of substance-
related disorder.1Physical dependence refers to the
tolerance and withdrawal that appear after chronic
use. Withdrawal also results in psychological depen-
dence, in which a substance user continuously or
intermittently craves the substance to avoid a dys-
phoric state. Behavioral dependence, in contrast,
refers to the pathological pattern of substance seeking.
Behavioral dependence is defined as uncontrollable,
persistent use despite negative physical, psychologi-
cal, societal, or legal consequences. Addiction is
defined as a state in which an individual loses control
over the use of substances despite the adverse
consequences associated with substance use.2Addic-
tion is essentially equivalent to behavioral depen-
dence. The most troubling aspect of dependence is
behavioral dependence or addiction, as an individual
can develop physical dependence without addiction
and compulsive substance users may not exhibit
physical dependence.3In this review, we will use
the terms ‘addiction’ and ‘behavioral dependence’
interchangeably, whereas ‘dependence’ refers to a
more global framework that includes both physical
and behavioral dependence.
Recent animal studies have clearly demonstrated
that there are molecular alterations associated with the
chronic use of substances with dependence poten-
tial.2,4These animal studies assume that chronic use
of a substance causes molecular and synaptic plasti-
city, which manifests itself as dependence. However,
plasticity-based dependence models do not fully
account for the fact that only a subpopulation of
chronic users becomes dependent. Here, we review
evidence that individuals susceptible to dependence
exhibit pre-existing behavioral traits and that specific
genes contribute to susceptibility to dependence and
these comorbid traits. We discuss two hypothetical
models to explain this aspect of dependence.
Individual susceptibility to substance dependence
How often does the use of an addictive substance lead
to dependence? Estimates vary from study to study,
but the consensus is that a majority of those who try
substances with dependence potential do not become
dependent. Among a sample of people in the US
between the ages of 15 and 54 years who tried a
substance at least once in their lifetimes, the prob-
ability of becoming dependent is estimated to be 32%
for tobacco, 23% for heroin, 17% for cocaine, 15% for
alcohol, 11% for stimulants other than cocaine, 9%
for cannabis, 9% for anxiolytic, sedative and hypnotic
drugs, 8% for analgesics, 5% for psychedelics, and
4% for inhalants.5A more recent survey including
67500 persons aged 12 years old or older yielded
similar estimates.6For example, among the 120
Received 07 September 2004; revised 19 October 2004; accepted
26 October 2004
Correspondence: N Hiroi, PhD, Laboratory of Molecular Psycho-
biology, Department of Psychiatry and Behavioral Sciences,
Department of Neuroscience, Albert Einstein College of Medicine,
Bronx, NY 10461, USA. E-mail: email@example.com
Molecular Psychiatry (2005) 10, 336–344
& 2005 Nature Publishing Group All rights reserved 1359-4184/05 $30.00
million current drinkers in the US, 15.9 million aged
12 or older are heavy alcohol drinkers (13%). These
estimates are based on individuals who ‘tried a
substance at least once in their lifetime’5or at least
once in the past 30 days.6
A series of studies on the rate of addiction/
behavioral dependence in chronic users of nicotine,
alcohol, and opioids elegantly demonstrated that only
a subpopulation of chronic substance users become
dependent, as discussed below.
It has been established that nicotine is the critical
ingredient for the development of tobacco addiction.
Persistent smoking of tobacco products is not simply
a habit, but represents addiction or behavioral
dependence, as smokers prefer regular cigarettes to
denicotinized cigarettes when given a choice.7,8
There is considerable individual variation in
susceptibility to nicotine dependence. A third of
those who try tobacco products on at least one
occasion in their lifetime become regular smokers
and develop dependence.5
smokers find it hard to quit even after consuming 20
or fewer cigarettes.9Moreover, in a subpopulation of
youths, the first symptoms of nicotine dependence
appear within days to weeks of occasional tobacco
use, prior to the onset of daily smoking.10Smoking
also targets individuals dependent on other sub-
stances; 43% of individuals with substance use
disorders are regular smokers.11
It is not only the transition from initial use to
nicotine dependence that shows individual variation.
Even after regular smoking sets in, there are those
who do not meet the criteria of dependence. A
subgroup (5–10%) of smokers, termed ‘chippers’,
smoke fewer than five cigarettes per day. Chippers
find it easy not to smoke, and exhibit little craving,
withdrawal, or mood/sleep disturbances during ab-
stinence. In contrast, regular smokers show both
physical and behavioral dependence. These indivi-
duals smoke 20–40 cigarettes per day; they find it
extremely difficult to quit and experience withdrawal
symptoms upon abstinence.12–15
There are several possible explanations as to why
chippers do not become regular smokers. One is that
chippers consume far fewer cigarettes than regular
smokers. They may not develop dependence because
the initial load of nicotine does not reach a threshold
necessary for the transition to dependence. However,
before becoming fully dependent, regular smokers
normally go through a phase of being ‘chippers’ for
only 22 days; after this time, they gradually increase
the amount of smoking to the point of becoming
regular smokers. In contrast, chippers remain chip-
pers and show few signs of dependence even after
smoking an average of 46000 cigarettes in 19 years.16
The difference between chippers and regular smokers
does not appear to be due to different rates of
elimination of nicotine, as regular smokers and
chippers inhale the same amount of cigarette smoke,
A small fraction of
absorb equal amounts of nicotine, and eliminate
nicotine at equal rates.14,17,18The difference is also
not attributable to the age at which individuals began
smoking, because there was no difference in the age at
which chippers and regular smokers started to
smoke.13,17Finally, it has been hypothesized that
chippers might find the initial effects of smoking
highly aversive and therefore do not progress to
become regular smokers. However, chippers retro-
spectively report that their experience of initial
cigarettes was actually not as aversive as that felt by
One recent survey shows that 51% of Americans aged
12 years and older reported using alcohol, but only
6.7% of this age group were found to be heavy
drinkers, who consumed five or more drinks on the
same occasion on at least 5 different days in the past
30 days.6Approximately 12–15% of alcohol users are
estimated to be dependent.5,6What distinguishes
heavy drinkers from nondependent users is their
high rates of use of other illicit substances. Among
heavy drinkers, 32.6% had used illicit substances at
least once during the 30 days prior to the survey. The
rates of illicit substance use were 16.6% among binge
drinkers, who consumed five or more drinks on the
same occasion at least once during 30 days prior to
the survey, 5.8% among nonbinge drinkers, and 3.6%
personnel in Southeast Asia during the Vietnam War
and after their return to the US suggested that narcotic
addiction develops only in a subpopulation of
chronic users. In a series of studies, Robins et al19,20
published a surprising group of statistics after
interviewing a sample of 451 Vietnam returnees to
assess the rate of narcotics use and dependence.
During the period of 1970–1971, 43% of the sample
had tried narcotics at least once and 20% had used
narcotics more frequently than once a week for longer
than 6 months. However, by 8–12 months after
returningto the US,only
population was using narcotics and 1% showed
symptoms of dependence. Only 14% of those who
were addictedat thetime
dependent after return.
Treatment for opioid addiction does not seem to
account for the surprisingly low addiction rate of
soldiers returning to the US.21Only a third of those
dependent on narcotics in Vietnam received detox-
ification while in the service, and treatment rates
were less than 2% for those who used narcotics in
Vietnam and 14% for those who were positive for
narcotics at the time of departure and continued to
use narcotics after return. The relatively limited
availability and environmental and societal con-
straints, combined with the lower levels of stress in
the US, are likely to have contributed to the low rate
Studies involvingUS military
10% of thesame
Genes and addiction
N Hiroi and S Agatsuma
of addiction in these soldiers. However, it remains
unknown why a subpopulation of individuals re-
mained dependent on narcotics upon their return.
analgesics should be more frequently prescribed to
patients with chronic pain. The underlying debate
concerns whether those patients would become
addicted to analgesics. Although most patients who
are prescribed opioid analgesics develop physical
dependence, addiction typically does not develop.22
Studies have included patients who received opioid
medication for chronic pain associated with various
illnesses. Most studies show that medical use of
patients.23The stress associated with the chronic
pain of terminal illnesses (eg, cancer) is likely to be
high, but the rate of addiction is low.
One trait that characterizes individual patients in
pain clinics who are likely to become dependent on
opiates is the use of multiple substances. Among
users of codeine for chronic pain management, those
found to become dependent on codeine also more
frequently used alcohol and stimulants, compared
with nondependent users.24
There is a controversy as to whether
in only 3.2–16%of
These examples consistently illustrate three points.
First, not all individuals exposed to an addictive
substance develop dependence or addiction; the rate
of transition from use to dependence/addiction is
low. Second, prolonged exposure is not a sufficient
condition for dependence or addiction. Despite the
long-term use of nicotine, alcohol, and narcotics,
some users do not develop dependence/addiction. On
the other hand, some individuals are easily addicted
to substances after only a few exposures. Third, those
susceptible to dependence/addiction tend to be
multiple substance users.
Comorbid behavioral traits of substance users
The majority of people in the general population will
not exhibit behavioral dependence in response to
chronic exposure to a substance with dependence
potential. This is likely to reflect many factors,
including the effects of genetic variations and
environmental factors (eg, stress, developmental
factors, and social factors). While it remains unclear
how various factors increase addiction susceptibility,
certain pre-existing personality traits distinguish
those who are prone to dependence/addiction from
those who are not.
There is a high degree of correlation among person-
ality traits variably labeled as ‘novelty seeking’ and
‘impulsive sensation seeking’.25Cloninger26defined
‘novelty seeking’ as a heritable tendency toward
intense exhilaration or excitement in response to
novel stimuli or cues for potential rewards or
potential relief of punishment, leading to frequent
exploratory activity in pursuit of potential rewards.
High novelty/sensation seeking scores are correlated
with impulsiveness, exploratory excitability, extra-
vagance, and disorderliness.26,27
Kuhlman28defined ‘impulsive sensation seeking’ as
a trait by which an individual seeks varied, novel,
complex, and intense sensations and experiences and
is willing to take physical, social, legal, and financial
risks for the sake of such experiences, combined with
impulsivity, in which an individual enters into
situations or rapidly responds to cues for potential
reward without much planning or deliberation or
without considering the potential for punishment or
loss of reward. In other words, individuals with high
sensation seeking-impulsivity scores tend to seek
novel and risky situations and show less anxiety
about these situations.
sensation seeking, as compared to nonsmokers, and
this correlation has been confirmed in different age
groups and countries, using various scales.28Even
among nonsmokers, individuals with high sensation
seeking scores tend to show a higher level of
subjective responses to nicotine.29
Novelty seeking is an index that predicts whether
one will start smoking, but not how much one
eventually becomes addicted to or dependent on
cigarettes.30,31Chippers, who do not develop nicotine
dependence and do not escalate smoking after many
years of smoking, do not differ from regular smokers
in sensation seeking.32Nor does sensation seeking
predict whether one is capable of quitting smoking.33
The degree of relapse is correlated with the degree of
dependence, but not with the level of novelty
seeking.30This personality trait is not a consequence
of smoking or dependence, because longitudinal
studies show that this trait is present before indivi-
duals start to smoke.33–35
Smokers exhibit higher levels of novelty/
alcohol dependence, termed Type I and Type II. Type I
is characterized by few premorbid comorbidities, few
antisocial behaviors, low impulsivity and a relatively
late onset. By contrast, Type II alcohol dependence is
defined by multisubstance dependence, antisocial
behaviors, aggression, impulsivity, and early onset of
alcoholism; Type II alcohol dependence is also
thought to have a genetic component.36–39Novelty
seeking is one of the behavioral traits that define Type
II alcohol dependence.40Novelty seeking was found
to precede the onset of alcohol dependence in
longitudinal studies,37suggesting that the higher
level of novelty seeking among alcoholics is not a
consequence of alcohol dependence.
There are at least two distinct types of
been found to be correlated with the degree of use of
marihuana and other addictive substances.35,41–43
Novelty/sensation seeking has also
Genes and addiction
N Hiroi and S Agatsuma
Novelty/sensation seeking is more tightly correlated
with the use of multiple substances than with the use
of a single substance.44
Other comorbid behavioral traits
Conduct disorder in adolescents and antisocial
personality disorder in adults are associated with
progression from experimentation to regular smoking
and difficulty in quitting smoking.45–49
disorder and antisocial personality disorder are
predictors of alcohol dependence.50,51Treatment out-
come for alcohol dependence is also inversely
correlated with the presence of conduct disorder.52
Antisocial behavior precedes the onset of Type II
alcohol dependence, suggesting that this personality
trait is a pre-existing trait for addiction susceptibil-
ity.53–57The most reliable predictor of opiate addic-
tion among Vietnam War returnees was pre-existing
conduct disorders that were present before they were
sent to Vietnam.21Antisocial personality has also
been reported to be associated with multisubstance
Genetics of addiction and comorbid traits
It seems clear that there is a subpopulation of
substance users who become dependent or addicted
more easily than others. While many environmental
factors are likely to contribute to the different degrees
of dependence susceptibility, this is also likely to be
heavily influenced by an individual’s genetic make-
Twin studies have demonstrated that genetic factors
play a significant role in the initiation of smoking
and in nicotine dependence. Estimates indicate
that the genetic contribution to smoking initiation in
twins accounts for 60% of the variance; heritability
can also account for 70% of the variance in persis-
tent smoking and nicotine dependence.60Sibs of
alcohol-dependent probands are three- to eight-fold
more likely to be alcoholics, and the heritability
estimates range from 50 to 60%. Heritability is
estimated to be particularly high in male Type II
alcohol dependence.39It has been estimated that
heritable factors account for 22–34% of the variance
in addiction to substances other than alcohol and
One methodological limitation of estimates of this
kind is that limited availability of illicit substances is
likely to reduce the influence of genes on their use
and dependence. The influence of genes on behavior
manifests itself fully when there is less environmental
constraint. Ironically, a lack of environmental con-
straints on substance use maximizes the impact of
genes on the initiation of use and on addiction. For
example, the impact of heritability on smoking is
more apparent when cigarette use is more widely
accepted.63In the current societal and legal environ-
ment, nicotine and alcohol are by far more accessible
to the general population than are illicit substances.
Thus, nicotine and alcohol serve as model substances
to determine the genetic component of addiction.
Human association studies have suggested that
specific genes contribute to comorbid behavioral
traits as well as to the susceptibility to dependence/
addiction. Polymorphisms in various monoamine
genes are a likely basis for comorbid behavioral traits
as well as susceptibility to dependence/addiction.
There are several comprehensive reviews on these
candidate genes.64–69In general, genes related to
dopamine and serotonin have been implicated in
novelty seeking and antisocial behaviors, as well as
dependence/addiction susceptibility. However, the
impact of polymorphisms in each of the single genes
on addiction susceptibility is thought to be small, and
many association studies have yielded conflicting
results in different population samples.
Animal studies are more suitable than human
association studies for isolating the impact of specific
genes on behavior. When various strains of rats and
mice are evaluated, it becomes apparent that certain
strains are prone to addiction. Outbred rats (eg,
Sprague–Dawley) show considerable individual var-
iations in their locomotor response to a novel open
field and in the reinforcing and rewarding effects of
substances. A subpopulation of outbred rats that
show heightened responsiveness to a novel open
field also exhibits a higher degree of addiction to
substances, compared to those showing low locomo-
tor responses.70Given that outbred rats are genetically
undefined, such individual variations in behavior
could reflect genetic and/or environmental factors.
A number of inbred mouse lines have been used to
examine the role of genetic variation or polymorph-
isms in behavior. Mice within a single inbred strain
are genetically identical, but those of different inbred
lines are genetically distinct. Thus, group differences
among separate inbred mouse lines can be attributed
to genetic impacts; individual differences within each
mouse line are likely to reflect nongenetic, environ-
mental influences such as stress, developmental
events, and interindividual factors. Behaviors exhib-
ited by various inbred mouse lines can be compared
to determine the degree to which a specific behavioral
trait is influenced by genetic variation. If multiple
genes control a behavioral trait, separate lines of
between two inbred mouse lines at the extreme ends
of the spectrum of a behavioral trait, would be
expected to show gradual differences, but not an
Locomotor activity in a novel, inescapable environ-
ment is thought to reflect an animal’s responsiveness
to novelty and is correlated with individual variations
in responsiveness to addictive substances.71–74Since
recombinant inbred lines generated by crossing
C57BL/10 and A/Jax mice or C57BL and BALB mouse
strains show gradual, bidirectional segregation of
Genes and addiction
N Hiroi and S Agatsuma
levels of locomotor activity in a novel, inescapable
open field across generations, this behavior is thought
to be multigenetic in origin.75Moreover, this trait
continues to segregate during 30 generations of
crosses of BALB/cJ and C57BL/6J mice, indicating
that a large number of genes contribute to the
behavior exhibited in a novel, inescapable open
field.75Since a similar strain difference exists for an
animal’s responsiveness to addictive substances,
addictive behaviors also are likely to be influenced
by multiple genes.76
Recent animal studies have begun to examine the
correlation of addiction susceptibility and comorbid
traits directly, using genetically engineered mice or
constitutive knockout mice. These mice have dele-
tions in specific genes throughout development and
are suitable for modeling the impact of specific
genetic factors on behavior in humans. In humans,
genetic polymorphisms are present throughout devel-
opment and are likely to influence neuroanatomical
development as well as behavior.
Another advantage of the constitutive knockout
mouse is that the complete deletion of a gene would
be expected to have more impact on behavior than
would a slight sequence variation induced by poly-
morphisms in inbred mice and humans. As the
contribution of any individual gene to behavior is
thought to be relatively small, this is a significant
Studies of various knockout mice have shown that a
number of genes contribute to dependence/addic-
tion,77but far fewer genes have been shown to
contribute to a response to novelty as well as
addiction. These studies suggest that genes can be
categorized into three classes. First, genes could
contribute to both addiction susceptibility and a
behavioral response to a novel environment. Second,
genes could affect a response to novelty without
affecting addictive behavior. Third, some other genes
could affect susceptibility to addiction but not a
response to novelty.
A small number of genes have been found to affect
both addiction susceptibility and a behavioral res-
ponse to novelty. One of these, the transcription factor
FosB/DFosB, is a postsynaptic molecule in the dopa-
mine signaling cascade. This transcription factor is
induced by cocaine, amphetamine, morphine, nico-
tine, and ethanol along the mesolimbic dopamine
pathway, a neuronal substrate critical for addiction.78,79
Once activated, FosB/DFosB regulates the expres-
sion of a number of downstream target genes.80–82
FosB knockout mice show heightened locomotor
response in a novel, inescapable environment and
heightened behavioral responses to cocaine.79This
category of genes also includes the serotonin 5HT-1B
FosB/DFosB is more strongly induced by chronic
cocaine treatment in the core region of the nucleus
accumbens than in the shell region; both regions are
targets of the mesolimbic dopamine pathway.79
Lesions of the core subregion of the nucleus accum-
bens impair an animal’s ability to value large, delayed
rewards over small, immediate rewards.85Thus, this
brain region may be one locus in which FosB/DFosB
contributes to impulsivity, one of the parameters of
novelty seeking/sensation seeking in humans.
Certain genes are known to exert opposing influ-
ences on addiction susceptibility and novelty re-
sponse. The presence of these genes suggests that a
behavioral response to novelty is not necessarily a
prerequisite for susceptibility to addiction. A loco-
motor response to a novel environment is increased,
but behavioral responses to addictive substances are
reduced in mice that lack the dopamine transporter
gene86,87(but see Sora et al88). Similarly, deletion of
the dopamine D4 receptor gene89,90or the norepi-
nephrine transporter gene91reduces behavioral reac-
tion to a novel environment, but increases behavioral
responses to addictive substances.
There are also genes that influence either addiction
susceptibility or a behavioral response to novelty, but
not both. Mice lacking the monoamine oxidase-B
(MAO-B) gene exhibit normal nicotine intake but are
deficient in habituating to a novel, inescapable open
field.92Genes whose deletion or attenuation enhances
addiction susceptibility without affecting a behavior-
al response to novelty include the serotonin transpor-
ter (SERT)88,93and glial-derived neurotrophic factor
Lerman and Niaura67suggested that genetic influ-
ences on addiction susceptibility are mediated partly
by individual differences in comorbid personality
traits, as well as individual differences in the
reinforcing effects of substances. These animal stu-
dies suggest that, under certain circumstances, genet-
ic variationscould enhance
independently of addiction susceptibility, however.
Taken together, these animal studies support the
notion that some pre-existing genetic variations exert
complex modes of influence on susceptibility to
addiction and on behavioral responses to a novel
environment. A goal of future studies is to more
precisely delineate the genetic basis by which genes
contribute to comorbidity or addiction susceptibility,
Hypothetical addiction models
How do genetic variations influence addiction sus-
ceptibility in humans? For this discussion, we divide
addiction models into two broad categories (Figure 1).
First, addiction could be the direct consequence of
plasticity triggered by a substance. Model 1 proposes
that a substance with dependence potential causes
plastic alterations in the brain in response to chronic
use. This plasticity, in turn, causes addiction and
dependence. Specific genes might influence the
rate of plasticity, thereby affecting the vulnerability
to addiction. Consistent with this model, Fischer
and Lewis inbred lines of rats exhibit different rates
of plastic gene expression in the brain in response
to addictive substances that correlate with their
Genes and addiction
N Hiroi and S Agatsuma
behavioral response to addictive substances.95–98The
fact that the degree of addiction is correlated with
the degree of molecular alteration in the brain is
consistent with the hypothesis that no addiction
could occur without some neuroplastic alterations
in the brain.
This model assumes that neural plasticity is the
causal event for the development of dependence/
addiction. However, there is a paucity of evidence
that plastic alterations, such as those seen in rodents,
actually occur in the brains of human substance users
with dependence/addiction. Alterations in expres-
sion of the genes for various monoamine and
glutamatergic receptors and related neuropeptides
have been demonstrated in the brains of substance
users with dependence.99–101However, it remains
unclear from these studies whether these alterations
are the pre-existing conditions of substance users, the
consequence of chronic substance use, or the result of
an acute overdose. Given the technical limitations in
identifying plastic alterations as the causative factors
for addiction in humans, this model can only be
evaluated in experimental animals and so suffers
from the limitations inherent in generalizing animal
findings to humans. Moreover, this model does not
fully account for the presence of pre-existing comor-
bid traits in addicts.
Another conceptual framework for understanding
dependence/addiction is to identify genetic varia-
tions as the primary factor for the development of
addiction (Model 2). The primary difference between
these two models is that Model 1 emphasizes that
plastic alterations induced by addictive substances
are central for the development of addiction, whereas
Model 2 assumes that the development of addiction is
determined by pre-existing genetic differences. Model
2 does not assume, albeit it does not deny, that plastic
alterations cause the development of addiction and
dependence. It could be that Gdand Gdcinfluence the
rate of plastic alterations upon exposure to addictive
substances. Alternatively, Gdand Gdcmight prewire a
brain so that a few exposures to a substance are
sufficient for the development of addiction and
dependence without plastic alterations.
One obvious advantage of Model 2 is that it can be
tested in both animals and humans. A large body of
evidence clearly suggests that pre-existing genetic
variations influence the behavioral responses to
addictive substances in inbred mouse and rat lines.76
Recent studies of genetically engineered mice have
identified a number of specific genes that influence
the degree of dependence/addiction or comorbid
traits or both. In humans, pre-existing genetic varia-
tions can be identified before the onset of depen-
dence/addiction. As such, Model 2 has a heuristic
Some pre-existing genetic variations could increase
both the probability of exhibiting specific behavioral
traits such as novelty seeking and antisocial behavior
and the probability of developing dependence and
addiction (see Gdc). In other cases, genes could
influence either addiction susceptibility (see Gd) or
comorbid traits (see Gc), but not both. Our finding that
deletion of MAO-B alters habituation in a novel
environment without affecting nicotine intake is
consistent with Gc.92Model 2 predicts that effective
treatments for addiction/dependence should also
target the pre-existing genetic variations.
Model 2 assumes that dependence susceptibility is
influenced by a large number of genes and that these
genes affect multiple brain regions, as distinct aspects
of addiction are likely to involve different brain
regions.102This is particularly true given that depen-
dence is a multifaceted phenomenon.
Summary and conclusions
A majority of substance users do not develop
addiction to nicotine, alcohol, or opiates. Currently
available plasticity-based models of addiction do not
adequately account for the limited prevalence of
addiction among chronic substance users and the
presence of pre-existing, comorbid traits. The genetic
model (Model 2) of addiction predicts that addiction
is more likely to develop after initial substance use in
dependence. ‘Dependence’ is defined as physical depen-
dence and behavioral dependence (ie, addiction). In Model
1, an individual’s genetic makeup affects the degree of
plastic alterations triggered by addictive substances, which
alter the development of and the ultimate degree of
dependence. In Model 2, the onset and development of
dependence is partially determined (together with environ-
mental factors) by genetic susceptibility. Genetic variations
could affect either dependence alone (Gd, eg, SERT and
GDNF) or comorbidity alone (Gc, eg, MAO-B); some of the
genetic variations could manifest themselves, in the
absence of exposure to addictive substances, as comorbid
traits only, but are simultaneously associated with depen-
dence susceptibility in the presence of addictive substances
(Gdc) (eg, fosB and 5HT-1B). In the absence of genetic
susceptibility to dependence (Gdor Gdc), the probability of
developing dependence and addiction upon exposure to
addictive substances diminishes. The impact of genes on
dependence results from the combined effects of many
genes, making it a probabilistic rather than all-or-none
Hypothetical models of genetic influence on
Genes and addiction
N Hiroi and S Agatsuma
individuals with genetic susceptibility, which is also
associated with comorbid traits in some (Gdc), but not
all cases (Gd). Model 2 highlights the need for a new
direction in addiction research as well as new
This work was supported by the NIDA (R01DA13232)
and by funds from the Department of Psychiatry and
Behavioral Sciences, Albert Einstein College of
Medicine (Dr T Byram Karasu and Dr Donald Faber);
by funds from the Program in Human Genetics/
Howard Hughes Funds, Albert Einstein College of
Medicine to NH; and by funds from the Albert
Einstein College of Medicine/Montefiore Medical
Center to SA. This article is dedicated to T Klein.
1 American Psychiatric Association. Diagnostic and Statistical
Manual of Mental Disorders, 4th edn. Text revision, American
Psychiatric Press: Washington, DC, 2000.
2 Nestler EJ. Molecular basis of long-term plasticity underlying
addiction. Nat Rev Neurosci 2001; 2: 119–128.
3 Hyman SE, Nestler EJ. The Molecular Foundations of Psychiatry.
American Psychiatry Press, Inc.: Washington, DC, 1993.
4 Hyman SE, Malenka RC. Addiction and the brain: the neurobio-
logy of compulsion and its persistence. Nat Rev Neurosci 2001; 2:
5 Anthony JC, Warner LA, Kessler RC. Comparative epidemiology
of dependence on tobacco, alcohol, controlled substances, and
inhalants: Basic findings from the National Comorbidity Survey.
Exp Clin Psychopharmacol 1994; 2: 244–268.
6 Substance Abuse and Mental Health Services Administration
(SAMHSA). Results from the 2002 National Survey on Drug Use
and Health: National Findings NHSDA Series H-22, DHHS
Publication No. SMA 03-3836. Office of the Applied Studies:
Rockville, MD, 2003.
7 Pickworth WB, Fant RV, Nelson RA, Rohrer MS, Henningfield JE.
Pharmacodynamic effects of new de-nicotinized cigarettes.
Nicotine Tob Res 1999; 1: 357–364.
8 Shahan TA, Bickel WK, Madden GJ, Badger GJ. Comparing the
reinforcing efficacy of nicotine-containing and de-nicotinized
cigarettes: a behavioral economic analysis. Psychopharmacology
(Berl) 1999; 147: 210–216.
9 Barker D. Reasons for tobacco use and symptoms of nicotine
withdrawal among adolescent and young adult tobacco users—
United States, 1993. MMWR Morb Mortal Wkly Rep 1994; 43:
10 DiFranza JR, Rigotti NA, McNeill AD, Ockene JK, Savageau JA,
St Cyr D et al. Initial symptoms of nicotine dependence in
adolescents. Tob Control 2000; 9: 313–319.
11 Keuthen NJ, Niaura RS, Borrelli B, Goldstein M, DePue J, Murphy
C et al. Comorbidity, smoking behavior and treatment outcome.
Psychother Psychosom 2000; 69: 244–250.
12 Owen N, Kent P, Wakefield M, Roberts L. Low-rate smokers. Prev
Med 1995; 24: 80–84.
13 Shiffman S. Tobacco ‘chippers’—individual differences in tobacco
dependence. Psychopharmacology (Berl) 1989; 97: 539–547.
14 Shiffman S, Kassel JD, Paty J, Gnys M, Zettler-Segal M. Smoking
typology profiles of chippers and regular smokers. J Subst Abuse
1994; 6: 21–35.
15 Shiffman S, Paty JA, Gnys M, Kassel JD, Elash C. Nicotine
withdrawal in chippers and regular smokers: subjective and
cognitive effects. Health Psychol 1995; 14: 301–309.
16 Shiffman S, Paty J, Kassel JD, Gnys M, Zettler-Segal M. Smoking
behavior and smoking history of tobacco chippers. Exp Clin
Psychopharm 1994; 2: 126–142.
17 Shiffman S, Fischer LB, Zettler-Segal M, Benowitz NL. Nicotine
exposure among nondependent smokers. Arch Gen Psychiatry
1990; 47: 333–336.
18 Shiffman S, Zettler-Segal M, Kassel J, Paty J, Benowitz NL,
O’Brien G. Nicotine elimination and tolerance in non-dependent
19 Robins LN, Davis DH, Goodwin DW. Drug use by US army
enlisted men in Vietnam: a follow-up on their return home. Am J
Epidemiol 1974; 99: 235–249.
20 Robins LN, Helzer JE, Davis DH. Narcotic use in southeast Asia
and afterward. An interview study of 898 Vietnam returnees.
Arch Gen Psychiatry 1975; 32: 955–961.
21 Robins LN. Vietnam veterans’ rapid recovery from heroin
addiction: a fluke or normal expectation? Addiction 1993; 88:
22 Inturrisi CE. Clinical pharmacology of opioids for pain. Clin J
Pain 2002; 18: S3–S13.
23 Fishbain DA, Rosomoff HL, Rosomoff RS. Drug abuse, depen-
dence, and addiction in chronic pain patients. Clin J Pain 1992; 8:
24 Sproule BA, Busto UE, Somer G, Romach MK, Sellers EM.
Characteristics of dependent and nondependent regular users of
codeine. J Clin Psychopharmacol 1999; 19: 367–372.
25 Zuckerman M, Cloninger CR. Relationships between Cloninger’s,
Zuckerman’s and Eysenck’s dimensions of personality. Person
Indiv Diff 1996; 21: 283–285.
26 Cloninger CR. Neurogenetic adaptive mechanisms in alcoholism.
Science 1987; 236: 410–416.
27 Svrakic DM, Whitehead C, Przybeck TR, Cloninger CR. Diffe-
rential diagnosis of personality disorders by the seven-factor
model of temperament and character. Arch Gen Psychiatry 1993;
28 Zuckerman M, Kuhlman DM. Personality and risk-taking:
common biosocial factors. J Pers 2000; 68: 999–1029.
29 Perkins KA, Gerlach D, Broge M, Grobe JE, Wilson A. Greater
sensitivity to subjective effects of nicotine in nonsmokers
high in sensation seeking. Exp Clin Psychopharmacol 2000; 8:
30 Carton S, Le Houezec J, Lagrue G, Jouvent R. Relationships
between sensation seeking and emotional symptomatology
during smoking cessation with nicotine patch therapy. Addict
Behav 2000; 25: 653–662.
31 Heath AC, Madden PA, Slutske WS, Martin NG. Personality and
the inheritance of smoking behavior: a genetic perspective. Behav
Genet 1995; 25: 103–117.
32 Kassel JD, Shiffman S, Gnys M, Paty J, Zettler-Segal M.
Psychosocial and personality differences in chippers and regular
smokers. Addict Behav 1994; 19: 565–575.
33 Lipkus IM, Barefoot JC, Feaganes J, Williams RB, Siegler IC.
A short MMPI scale to identify people likely to begin smoking.
J Pers Assess 1994; 62: 213–222.
34 Masse LC, Tremblay RE. Behavior of boys in kindergarten and the
onset of substance use during adolescence. Arch Gen Psychiatry
1997; 54: 62–68.
35 Sher KJ, Bartholow BD, Wood MD. Personality and substance use
disorders: a prospective study. J Consult Clin Psychol 2000; 68:
36 Basiaux P, le Bon O, Dramaix M, Massat I, Souery D, Mendlewicz
J et al. Temperament and Character Inventory (TCI): personality
profile and sub-typing in alcoholic patients: a controlled study.
Alcohol Alcohol 2001; 36: 584–587.
37 Cloninger CR, Sigvardsson S, Bohman M. Childhood personality
predicts alcohol abuse in young adults. Alcohol Clin Exp Res
1988; 12: 494–505.
38 Hallman J, von Knorring L, Oreland L. Personality disorders
according to DSM-III-R and thrombocyte monoamine oxidase
activity in type 1 and type 2 alcoholics. J Stud Alcohol 1996; 57:
39 Sigvardsson S, Bohman M, Cloninger CR. Replication of the
Stockholm Adoption Study of alcoholism. Confirmatory cross-
fostering analysis. Arch Gen Psychiatry 1996; 53: 681–687.
40 Finn PR, Mazas CA, Justus AN, Steinmetz J. Early-onset
alcoholism with conduct disorder: go/no go learning deficits,
Genes and addiction
N Hiroi and S Agatsuma
working memory capacity, and personality. Alcohol Clin Exp Res
2002; 26: 186–206.
41 Lynskey MT, Fergusson DM, Horwood LJ. The origins of
the correlations between tobacco, alcohol, and cannabis use
during adolescence. J Child Psychol Psychiatry 1998; 39:
42 Mabry EA, Khavari KA. Attitude and personality correlates of
hallucinogenic drug use. Int J Addict 1986; 21: 691–699.
43 Wills TA, Vaccaro D, McNamara G. Novelty seeking, risk
taking, and related constructs as predictors of adolescent
substance use: an application of Cloninger’s theory. J Subst
Abuse 1994; 6: 1–20.
44 Conway KP, Kane RJ, Ball SA, Poling JC, Rounsaville BJ.
Personality, substance of choice, and polysubstance involvement
among substance dependent patients. Drug Alcohol Depend
2003; 71: 65–75.
45 Barry KL, Fleming MF, Manwell LB, Copeland LA. Conduct
disorder and antisocial personality in adult primary care
patients. J Fam Pract 1997; 45: 151–158.
46 Boyle MH, Offord DR. Psychiatric disorder and substance use in
adolescence. Can J Psychiatry 1991; 36: 699–705.
47 Rohde P, Kahler CW, Lewinsohn PM, Brown RA. Psychiatric
disorders, familial factors, and cigarette smoking: II. Associations
with progression to daily smoking. Nicotine Tob Res 2004; 6:
48 Rohde P, Kahler CW, Lewinsohn PM, Brown RA. Psychiatric
disorders, familial factors, and cigarette smoking: III. Associa-
tions with cessation by young adulthood among daily smokers.
Nicotine Tob Res 2004; 6: 509–522.
49 Serman N, Johnson JG, Geller PA, Kanost RE, Zacharapoulou
among American and Greek adolescents. Adolescence 2002; 37:
50 Finn PR, Sharkansky EJ, Brandt KM, Turcotte N. The effects of
familial risk, personality, and expectancies on alcohol use and
abuse. J Abnorm Psychol 2000; 109: 122–133.
51 Tomasson K, Vaglum P. A nationwide representative sample of
treatment-seeking alcoholics: a study of psychiatric comorbidity.
Acta Psychiatr Scand 1995; 92: 378–385.
52 Brown SA, Gleghorn A, Schuckit MA, Myers MG, Mott MA.
Conduct disorder among adolescent alcohol and drug abusers.
J Stud Alcohol 1996; 57: 314–324.
53 Carbonneau R, Tremblay RE, Vitaro F, Dobkin PL, Saucier JF, Pihl
RO. Paternal alcoholism, paternal absence and the development
of problem behaviors in boys from age six to twelve years. J Stud
Alcohol 1998; 59: 387–398.
54 Hawkins JD, Catalano RF, Miller JY. Risk and protective factors
for alcohol and other drug problems in adolescence and early
adulthood: implications for substance abuse prevention. Psychol
Bull 1992; 112: 64–105.
55 Lynskey MT, Fergusson DM. Childhood conduct problems,
attention deficit behaviors, and adolescent alcohol, tobacco,
and illicit drug use. J Abnorm Child Psychol 1995; 23: 281–302.
56 Windle M. A longitudinal study of antisocial behaviors in
early adolescence as predictors of late adolescent substance
use: gender and ethnic group differences. J Abnorm Psychol 1990;
57 Young SE, Mikulich SK, Goodwin MB, Hardy J, Martin CL,
Zoccolillo MS et al. Treated delinquent boys’ substance use:
onset, pattern, relationship to conduct and mood disorders. Drug
Alcohol Depend 1995; 37: 149–162.
58 Feingold A, Ball SA, Kranzler HR, Rounsaville BJ. General-
izability of the type A/type B distinction across different
psychoactive substances. Am J Drug Alcohol Abuse 1996; 22:
59 Rounsaville BJ, Anton SF, Carroll K, Budde D, Prusoff BA, Gawin
F. Psychiatric diagnoses of treatment-seeking cocaine abusers.
Arch Gen Psychiatry 1991; 48: 43–51.
60 Sullivan PF, Kendler KS. The genetic epidemiology of smoking.
Nicotine Tob Res 1999; 1(Suppl 2): S51–S57.
61 Pickens RW, Svikis DS, McGue M, Lykken DT, Heston LL,
Clayton PJ. Heterogeneity in the inheritance of alcoholism. A
study of male and female twins. Arch Gen Psychiatry 1991; 48:
62 Tsuang MT, Lyons MJ, Eisen SA, Goldberg J, True W, Lin N.
Genetic influences on DSM-III-R drug abuse and dependence:
a study of 3372 twin pairs. Am J Med Genet 1996; 67: 473–477.
63 Kendler KS, Thornton LM, Pedersen NL. Tobacco consumption
in Swedish twins reared apart and reared together. Arch Gen
Psychiatry 2000; 57: 886–892.
64 Arinami T, Ishiguro H, Onaivi ES. Polymorphisms in genes
involved in neurotransmission in relation to smoking. Eur J
Pharmacol 2000; 410: 215–226.
65 Enoch MA. Pharmacogenomics of alcohol response and addic-
tion. Am J Pharmacogenomics 2003; 3: 217–232.
66 Kreek MJ, Nielsen DA, LaForge KS. Genes associated with
addiction: alcoholism, opiate, and cocaine addiction. Neuro-
molecular Med 2004; 5: 85–108.
67 Lerman C, Niaura R. Applying genetic approaches to the treatment
of nicotine dependence. Oncogene 2002; 21: 7412–7420.
68 Uhl GR, Liu QR, Naiman D. Substance abuse vulnerability loci:
converging genome scanning data. Trends Genet 2002; 18: 420–425.
69 Walton R, Johnstone E, Munafo M, Neville M, Griffiths S. Genetic
clues to the molecular basis of tobacco addiction and progress
towards personalized therapy. Trends Mol Med 2001; 7: 70–76.
70 Deroche-Gamonet V, Belin D, Piazza PV. Evidence for addiction-
like behavior in the rat. Science 2004; 305: 1014–1017.
71 Bardo MT, Donohew RL, Harrington NG. Psychobiology of
novelty seeking and drug seeking behavior. Behav Brain Res
1996; 77: 23–43.
72 Klebaur JE, Bevins RA, Segar TM, Bardo MT. Individual
differences in behavioral responses to novelty and amphetamine
self-administration in male and female rats. Behav Pharmacol
2001; 12: 267–275.
73 Orsini C, Buchini F, Piazza PV, Puglisi-Allegra S, Cabib S.
Susceptibility to amphetamine-induced place preference is
predicted by locomotor response to novelty and amphetamine
in the mouse. Psychopharmacology (Berl) 2004; 172: 264–270.
74 Piazza PV, Deminiere JM, Le Moal M, Simon H. Factors that
predict individual vulnerability to amphetamine self-adminis-
tration. Science 1989; 245: 1511–1513.
75 DeFries JC, Gervais MC, Thomas EA. Response to 30 generations
of selection for open-field activity in laboratory mice. Behav
Genet 1978; 8: 3–13.
76 Crabbe JC. Genetic contributions to addiction. Annu Rev Psychol
2002; 53: 435–462.
77 Laakso A, Mohn AR, Gainetdinov RR, Caron MG. Experimental
genetic approaches to addiction. Neuron 2002; 36: 213–228.
78 Chao J, Nestler EJ. Molecular neurobiology of drug addiction.
Annu Rev Med 2004; 55: 113–132.
79 Hiroi N, Brown JR, Haile CN, Ye H, Greenberg ME, Nestler EJ.
FosB mutant mice: loss of chronic cocaine induction of
Fos-related proteins and heightened sensitivity to cocaine’s
psychomotor and rewarding effects. Proc Natl Acad Sci USA
1997; 94: 10397–10402.
80 Hiroi N, Marek GJ, Brown JR, Ye H, Saudou F, Vaidya VA
et al. Essential role of the fosB gene in molecular, cellular,
and behavioral actions of chronic electroconvulsive seizures.
J Neurosci 1998; 18: 6952–6962.
81 Kelz MB, Chen J, Carlezon Jr WA, Whisler K, Gilden L, Beckmann
AM et al. Expression of the transcription factor deltaFosB in the
brain controls sensitivity to cocaine. Nature 1999; 401: 272–276.
82 Chen J, Zhang Y, Kelz MB, Steffen C, Ang ES, Zeng L et al.
Induction of cyclin-dependent kinase 5 in the hippocampus
by chronic electroconvulsive seizures: role of [Delta]FosB.
J Neurosci 2000; 20: 8965–8971.
83 Malleret G, Hen R, Guillou JL, Segu L, Buhot MC. 5-HT1B
receptor knock-out mice exhibit increased exploratory activity
and enhanced spatial memory performance in the Morris water
maze. J Neurosci 1999; 19: 6157–6168.
84 Rocha BA, Scearce-Levie K, Lucas JJ, Hiroi N, Castanon N, Crabbe
JC et al. Increased vulnerability to cocaine in mice lacking the
serotonin-1B receptor. Nature 1998; 393: 175–178.
85 Cardinal RN, Pennicott DR, Sugathapala CL, Robbins TW, Everitt
BJ. Impulsive choice induced in rats by lesions of the nucleus
accumbens core. Science 2001; 292: 2499–2501.
86 Giros B, Jaber M, Jones SR, Wightman RM, Caron MG.
Hyperlocomotion and indifference to cocaine and amphetamine
Genes and addiction
N Hiroi and S Agatsuma
in mice lacking the dopamine transporter. Nature 1996; 379: Download full-text
87 Rocha BA, Fumagalli F, Gainetdinov RR, Jones SR, Ator R, Giros
B et al. Cocaine self-administration in dopamine-transporter
knockout mice. Nat Neurosci 1998; 1: 132–137.
88 Sora I, Wichems C, Takahashi N, Li XF, Zeng Z, Revay R et al.
Cocaine reward models: conditioned place preference can be
established in dopamine- and in serotonin-transporter knockout
mice. Proc Natl Acad Sci USA 1998; 95: 7699–7704.
89 Dulawa SC, Grandy DK, Low MJ, Paulus MP, Geyer MA.
Dopamine D4 receptor-knock-out mice exhibit reduced explora-
tion of novel stimuli. J Neurosci 1999; 19: 9550–9556.
90 Rubinstein M, Phillips TJ, Bunzow JR, Falzone TL, Dziewcza-
polski G, Zhang G et al. Mice lacking dopamine D4 receptors are
supersensitive to ethanol, cocaine, and methamphetamine. Cell
1997; 90: 991–1001.
91 Xu F, Gainetdinov RR, Wetsel WC, Jones SR, Bohn LM, Miller
GW et al. Mice lacking the norepinephrine transporter are
supersensitive to psychostimulants. Nat Neurosci 2000; 3:
92 Lee M, Chen K, Shih JC, Hiroi N. MAO-B knockout mice exhibit
deficient habituation of locomotor activity but normal nicotine
intake. Genes Brain Behav 2004; 3: 216–227.
93 Sora I, Hall FS, Andrews AM, Itokawa M, Li XF, Wei HB
et al. Molecular mechanisms of cocaine reward: combined
dopamineand serotonin transporter
cocaine place preference. Proc Natl Acad Sci USA 2001; 98:
94 Messer CJ, Eisch AJ, Carlezon Jr WA, Whisler K, Shen L, Wolf DH
et al. Role for GDNF in biochemical and behavioral adaptations to
drugs of abuse. Neuron 2000; 26: 247–257.
95 Haile CN, Hiroi N, Nestler EJ, Kosten TA. Differential behavioral
responses to cocaine are associated with dynamics of mesolimbic
dopamine proteins in Lewis and Fischer 344 rats. Synapse 2001;
96 Kabbaj M, Yoshida S, Numachi Y, Matsuoka H, Devine DP,
Sato M. Methamphetamine differentially regulates hippocampal
glucocorticoid and mineralocorticoid receptor mRNAs in Fischer
and Lewis rats. Mol Brain Res 2003; 117: 8–14.
97 Werme M, Olson L, Brene S. NGFI-B and nor1 mRNAs are
upregulated in brain reward pathways by drugs of abuse: different
effects in Fischer and Lewis rats. Mol Brain Res 2000; 76: 18–24.
98 Werme M, Thoren P, Olson L, Brene S. Running and cocaine both
upregulate dynorphin mRNA in medial caudate putamen. Eur J
Neurosci 2000; 12: 2967–2974.
99 Hurd YL, Svensson P, Ponten M. The role of dopamine,
dynorphin, and CART systems in the ventral striatum and
amygdala in cocaine abuse. Ann NYAcad Sci 1999; 877: 499–506.
100 Staley JK, Mash DC. Adaptive increase in D3 dopamine receptors
in the brain reward circuits of human cocaine fatalities.
J Neurosci 1996; 16: 6100–6106.
101 Tang WX, Fasulo WH, Mash DC, Hemby SE. Molecular profiling
of midbrain dopamine regions in cocaine overdose victims.
J Neurochem 2003; 85: 911–924.
102 White NM. Addictive drugs as reinforcers: multiple partial
actions on memory systems. Addiction 1996; 91: 921–949.
Genes and addiction
N Hiroi and S Agatsuma