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The Journal of Neuroscience, November 1, 2001, 21(21):8324-8327
Psychogenomics: Opportunities for Understanding Addiction
Eric J.
Nestler
Department of Psychiatry and Center for Basic Neuroscience, The
University of Texas Southwestern Medical Center, Dallas, Texas
75390-9070
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ABSTRACT |
The term psychogenomics is used here to describe the process of
applying the powerful tools of genomics and proteomics to achieve a
better understanding of the biological substrates of normal behavior
and of diseases of the brain that manifest themselves as behavioral
abnormalities. Applying psychogenomics to the study of drug addiction
will lead to the identification of genes and their protein products
that control the reward pathways of the brain and their adaptations to
drugs of abuse, as well as variations in these genes that confer
genetic risk for addiction and related disorders. The ultimate goal is
to use this information to develop more effective treatments for these
disorders as well as objective diagnostic tools, preventive measures,
and eventually cures.
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ARTICLE |
Drug addiction, like all other
psychiatric disorders, is diagnosed today solely on the basis of the
behavioral abnormalities that patients exhibit. For example, addiction
can be defined as compulsive drug seeking and taking despite adverse
consequences or as loss of control over drug use. However, there is no
objective diagnostic information we can offer individuals concerning
their risk for addiction in general, let alone addiction for a specific substance, nor can we offer patients informed advice concerning their
risk for relapse. Moreover, current treatments for drug addiction are
inadequate for most individuals.
The goal of this review is to outline ways in which recent advances in
functional genomics and proteomics can be expected to dramatically
improve psychiatric practice overall and the treatment of addictive
disorders in particular. Two major areas of advances in this evolving
field of "psychogenomics" are seen: (1) identification of genes
that confer risk for an addiction and (2) identification of genes and
proteins that contribute to the regulation of reward, motivation, and
cognition under normal circumstances and to abnormalities in these
behaviors that characterize an addicted state. There is now
considerable optimism that these advances will lead one day to
objective diagnostic tests, improved treatments, and eventually preventive measures and cures.
Identification of addiction vulnerability genes
Epidemiological studies have indicated that drug addiction is a
highly heritable disorder. Approximately 40-60% of the risk for
alcohol, cocaine, or opiate addiction appears to be genetic (Nestler,
2000 ). Data are not yet available for nicotine or other substances,
although anecdotal information suggests similar degrees of
heritability. In addition, we do not yet know the genetic risk for
other forms of compulsive behavior, such as to food, sex, and gambling.
The evolving knowledge that these disorders involve some of the same
neural mechanisms as drug addiction would suggest a significant genetic
risk as well. Despite this genetic basis, however, efforts to identify
specific genes involved in drug addiction have not to date been
successful. The difficulty in finding such genes is comparable with the
difficulty in finding genes for other common conditions (e.g.,
hypertension, congestive heart failure, and asthma) (Burmeister, 1999 ).
One possibility is that these diseases are caused by a relatively large
number of genes, such that it is extremely difficult to identify the
individual genes involved, each of which is only responsible for a
small percentage of the overall risk. Another possibility is that the
tools for fine genome-wide scans in large numbers of individuals have
only recently become available, such that the pessimism is premature.
Two major approaches have been used to identify the genetic causes of
addiction. One is a candidate gene approach, in which genes and
proteins implicated in the pathophysiology or in animal models of
addiction are considered as human risk factors. The validity of the
candidate gene approach is supported by situations in which obvious
candidate genes have been related to human disease. An example is
Alzheimer's disease, which is characterized by the accumulation of
-amyloid in the brain, and where rare familial variants of the
disorder are caused by mutations in amyloid precursor protein (APP),
from which -amyloid is derived (Selkoe, 2001 ). Another example is
frontotemporal dementia, which is characterized by hyperphosphorylation
of the microtubule-associated protein ; this disorder
is caused in some families by mutations in the gene
(Pickering-Brown et al., 2000 ). However, use of the candidate gene
approach in the addiction field is hampered by our still limited
knowledge of the pathophysiology of these disorders in humans.
Consequently, investigators have focused on genes implicated in animal
models, which are only now being revealed and have not yet been
evaluated in human populations (see below).
The other approach is open-ended and involves genome-wide scans of
affected and unaffected individuals. The necessity of this approach is
based on the experience that the genetic abnormalities underlying most
of those neuropsychiatric disorders for which such abnormalities have
been found occur in genes that would never have been considered
candidates. Examples include a gene encoding a DNA
methylation-regulating protein in Rett's syndrome (an autism-like disorder) (Shahbazian and Zoghbi, 2001 ) and previously unknown genes in
Huntington's disease (Gutekunst et al., 2000 ), familial forms of
Parkinson's disease (de Silva et al., 2000 ), and neurofibromatosis (Parada, 2000 ), to name a few. The technology to complete genome-wide scans has improved dramatically in recent years, and there is currently
a great deal of anticipation that this approach will begin to identify
genetic factors related to addiction over the next 5-10 years.
Another open-ended approach involves searching for abnormal levels of
mRNAs or proteins in brain tissue obtained from addicted individuals at
autopsy. DNA microarrays and other methods of differential gene
expression have greatly augmented the ability of the field to find such
abnormalities, and some promising early studies have been published
recently for other psychiatric syndromes, such as schizophrenia
(Mirnics et al., 2000 ). One limitation of this approach is that in most
cases the brains are obtained long after the initial manifestation of
the disease, and this time delay may obscure primary pathophysiological
changes. Some of the observed changes might even represent normal
compensations to the primary abnormalities and not components of them.
Another limitation is that the exact locations of the primary pathology
in human addiction are not known with certainty, although animal models
have indicated several brain regions of likely importance (e.g., the
ventral striatum, prefrontal cortex, and midbrain dopamine nuclei)
(Koob et al., 1998 ; Wise, 1998 ).
Knowledge of genes that confer risk for addiction could one day be used
to select the optimal treatment program for an individual addict. For
example, in the depression field, some antidepressants are
serotonin-reuptake inhibitors, whereas others inhibit norepinephrine reuptake. There is a major effort today to identify genetic factors that can be used to predict whether a person with depression would respond better to one or the other. Such pharmacogenomic studies are in their early stages, and would appear premature for addiction, because treatments for drug addiction, and our knowledge of the underlying genetic factors, are still limited.
Once addiction vulnerability genes or genes that predict
pharmacological responses are discovered, the next step will be to place these genes in mice to enable studies of the underlying molecular
and neural mechanisms that link the genes to abnormal behavior. For
example, before the identification of genes that cause Alzheimer's
disease, Huntington's disease, or Rett's syndrome, animal models were
extremely limited. Now that the genetic abnormalities underlying these
disorders have been revealed, it has been possible to generate mice
that offer much better models for studying disease pathophysiology and
possible therapeutic interventions (Chen et al., 2001 ; Guidetti et al.,
2001 ; Selkoe, 2001 ). Such improved animal models of addiction would
offer a powerful means of identifying nongenetic factors that also
contribute to these disorders. In the absence of knowing the specific
genes involved, the field has had a difficult time defining specific
environmental risk factors for addiction, beyond rather vague
generalities such as stress, poverty, crime, and dysfunctional families.
Genetic dissection of complex behavior
Considerable progress has been made in identifying genes that
regulate complex behavior relevant to addiction in animal models. Such
discoveries have aided efforts to define neural circuits in the brain
that control these behaviors. They also have the potential of revealing
candidate genes that could be studied in human disorders. As with human
genetic studies, genomic and proteomic efforts in animals can be
divided between candidate and open-ended approaches.
Candidate approaches have offered major insights into the influence of
specific genes and proteins in the regulation of reward, motivation,
and cognitive function, to name a few behaviors. Such advances are much
too numerous to elaborate here. The role of specific neurotransmitter
receptors (e.g., for dopamine, glutamate, and serotonin), intracellular
signaling proteins (e.g., protein kinases, arrestins, and dopamine and
cAMP-regulated phosphoprotein of 32 kDa), and transcription
factors (e.g., cAMP response element-binding protein and
FosB) in these various behaviors are just some examples of the
important strides made in the past decade (Carlezon et al., 1998 ;
Fienberg et al., 1998 ; Stark et al., 1998 ; Kelz et al., 1999 ; Mayford
and Kandel, 1999 ; Bohn et al., 2000 ; Nestler, 2000 ).
The ability to relate a particular gene to a complex behavior requires
the ability to manipulate genes within an animal. First-generation transgenic and knock-out mice continue to represent the mainstay of
efforts in this field. However, there also is increasing recognition of
the need to manipulate a gene with much greater spatial and temporal
control (i.e., to induce the mutation in a specific brain region of an
adult animal). This need is attributable to the fact that
interpretation of transgenic and knock-out mice can be complicated by
developmental effects and the ubiquitous nature of the mutation. Some
of the tools that have been used to obtain greater spatial and temporal
control include antisense oligonucleotides, viral-mediated gene
transfer, and the creation of inducible, cell-targeted mutations in
mice. Although improvements are needed in these approaches, their
unique power to genetically dissect behavior has been demonstrated in
recent years (Carlezon et al., 1998 ; Kelz et al., 1999 ; Mayford and
Kandel, 1999 ; Pooga et al., 2001 ).
Several open-ended approaches also have been used. DNA microarrays are
just now beginning to be used to identify drug-induced changes in the
brain, and some early reports have appeared (Lewohl et al., 2000 ; Ang
et al., 2001 ; Bibb et al., 2001 ; Freeman et al., 2001 ). One limitation
of current microarray technology is its sensitivity (i.e., its ability
to detect low-abundance messages). This has directed efforts to
alternate methodologies of differential gene expression, which may
offer greater sensitivity (Gautvik et al., 1996 ). Likewise, the need
for proteomic approaches cannot be overstated. Most current
high-throughput efforts have for technical reasons focused on analysis
of mRNAs. Yet a major need in the field is to develop methods of
comparable throughput to study proteins, including total amounts of
proteins as well as their modification by phosphorylation,
glycosylation, etc. (Zhang et al., 2001 ). One example of the need for
proteomics is provided by consideration of the transcription factor
FosB (Nestler et al., 2001 ). FosB is induced in striatal regions
of brain uniquely after chronic exposure to drugs of abuse, and
persists in the brain for weeks to months after drug exposure ceases.
Increasing evidence indicates that FosB is an important molecular
substrate for addiction. However, the induction of FosB resides in
the protein, which is highly stable, and not in its mRNA, which is highly unstable. Thus, a genomics-only approach would never have succeeded in identifying FosB as a long-lasting adaptation
associated with addiction.
Large-scale mutagenesis studies, in which mutations are randomly
induced by chemical mutagens and resulting behavioral abnormalities are
explored in broad-based behavioral screens, are now getting underway. A
challenge in the addiction field is that behaviors that most closely
model human addiction (see below) are not amenable to the high
throughput needed in mutagenesis studies. As a result, more rapid
assays, such as stimulant-induced locomotor activity, are being used.
The potential of this strategy is indicated by recent studies, which
have identified novel genes involved in circadian rhythms (Lowrey and
Takahashi, 2000 ; Tarantino and Bucan, 2000 ). Quantitative trait locus
(QTL) analysis is another open-ended approach to find genes that
contribute to behavioral differences between inbred mice or rats,
including differential responses to drugs of abuse (Crabbe et al.,
1999 ). Numerous QTLs have been found, but it has been exceedingly
difficult to narrow these large chromosomal regions to specific genes.
Whether improved genomic tools now available will improve the situation
is unclear. Still, the potential of animal genetics is indicated by the
identification of the orexin receptor as the site of mutation in a
hereditary narcolepsy-like syndrome in dogs (Hungs and Mignot, 2001 ).
This, together with related findings in mice (see below), has provided a compelling scenario of the pathophysiology of narcolepsy in humans.
The ability to relate genes to complex behavior requires not only the
means of manipulating and detecting genes and their products but also
precise tests of complex behavior in laboratory animals as well as
accurate animal models of human disease. There are indeed numerous
tests of many types of behavior in rodents that have been used widely
in the field. Some examples include measures of cognitive function,
fear, and reward. In addition, whereas animal models of human
psychiatric disease have been problematic, the situation is better for
addiction, because it is possible to measure in animals not only acute
drug reward but also phenomena more referable to human addictions, such
as drug seeking and craving (Koob et al., 1998 ; Self and Nestler, 1998 ;
Wise, 1998 ). Such animal models should be improved further when genes
that contribute to addiction risk in humans can be put into rodents to
reproduce human vulnerability states.
Clinical applications of psychogenomics
As genomic and proteomic efforts succeed in identifying genes and
proteins involved in normal behavior and in addiction, several tangible
benefits will result. The most obvious is the identification of novel
targets for psychotherapeutic medications. All but a few currently used
psychiatric medications act on neurotransmitter receptors or
transporter proteins. Yet these proteins represent a miniscule fraction
of all neuronal proteins, and it is likely that among this remaining
array of proteins are viable drug targets, including targets for truly
effective anti-addiction medications. The challenge is to find them.
Several examples illustrate how genomics and proteomics provide a
rationale guide. In the Alzheimer's field, knowledge of the abnormal
processing of APP into -amyloid suggested the existence of a
-secretase that catalyzes this processing. Such an enzyme has now
been identified through genomic efforts and inhibitors are being
developed as possible treatment agents for Alzheimer's disease (Yan et
al., 1999 ). Another example is provided by the obesity field.
Identification of the leptin and leptin receptor genes, based on their
abnormalities in two spontaneous lines of mutant mice, the Ob (obese)
and Db (diabetic) mice, has led to explosive knowledge of the
regulation of eating behavior and to the identification of numerous
peptides and their receptors as potential targets for new medications
(Friedman and Halaas, 1998 ). Regulators of G-protein signaling (RGS)
proteins act by sharpening the responses of G-protein-coupled receptors
and perhaps by serving as scaffolding proteins (Berman and Gilman,
1998 ). They were discovered initially through genomic efforts in yeast
and worms. There is considerable diversity among RGS proteins, with 25 products now identified in mammals. Many are enriched in the brain,
where several show striking region-specific patterns of expression
(Gold et al., 1997 ). The pharmaceutical industry is now evaluating
whether drugs aimed at RGS subtypes might be useful in the treatment of psychiatric disorders including addiction. The serendipitous discovery of a narcolepsy-like syndrome in orexin knock-out mice (Chemelli et
al., 1999 ) and the related findings in dogs stated previously led to
the view that human narcolepsy is caused by a loss of orexin-containing neurons in the lateral hypothalamus. The development of orexin agonists
to treat narcolepsy is now a tangible goal. Similarly, as we define the
detailed etiology and pathophysiology of addiction, it should be
possible to develop medications that intervene in the addiction
process. Such medications will not replace psychosocial interventions
that are now offered to addicts but will likely make such
rehabilitation efforts far more useful. Indeed, psychosocial interventions may be doomed to failure in many patients until medications are developed to effectively counter the powerful biological forces that drive a state of addiction.
Advances in our understanding of the genetics and neurobiology of drug
addiction will have dramatic implications for diagnosis and prevention
as well. It is not farfetched to envision the day when a patient with a
behavioral abnormality, such as an addiction, undergoes a battery of
tests, including genetic tests and perhaps brain-imaging scans, to
define a disease entity and to choose the most effective course of
treatment. It might be possible to identify and educate individuals who
are particularly vulnerable to a specific drug (e.g., those for whom
even brief exposures to a drug of abuse pose a substantial risk for addiction).
The future of psychogenomics
Psychogenomics will probably be the last frontier of the
functional genomics revolution. This is because of the complexity of
the brain and the obstacles inherent in diagnosing and treating brain
diseases, such as the enclosure of the brain within the skull and the
lack of access to tissue from living patients. Within psychogenomics,
however, the addiction field may lead the way, based on the relative
ease of relating molecular events to meaningful animal models of the
human disorders. The fields of genomics and proteomics provide tools of
unprecedented power to identify genes and proteins that control complex
behavior under normal and pathological conditions. Eventually, these
discoveries can be exploited for clinical applications as diverse as
improved treatments, diagnostic tests, and ultimately disease
prevention and cure.
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FOOTNOTES |
This work was supported by grants from the National Institute
on Drug Abuse.
Correspondence should be addressed to Eric J. Nestler,
Department of Psychiatry and Center for Basic Neuroscience, The
University of Texas Southwestern Medical Center, 5323 Harry Hines
Boulevard, Dallas, TX 75390-9070. E-mail:
eric.nestler{at}utsouthwestern.edu.
 |
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