Download Can Your Genes Make You Do It?

 ADDICTION
& THE BRAIN
Can Your Genes “Make You Do It”?
L i n d a M a r t i n - M o r r i s , H e l e n T. B u c k l a n d, S u s a n n a L . C u n n i n g h a m
Genetic Predisposition to
Addiction
A friend used to say “I don’t gamble because
I have an addictive personality.” She felt that
she was somehow predisposed to lose volitional control over her gambling. Indeed, curiosity about a putative genetic predisposition
to addiction has not been restricted to a few
would-be gambling addicts.
It is estimated that 40–60% of the “addiction” trait is controlled by gene products (Uhl,
2004). For example, the risk of becoming an
alcoholic is elevated five- to eightfold if a primary relative is an alcoholic (Merikangas et al.,
1998). For twins, genetically identical pairs
show more sharing of alcoholism than fraternal
twin pairs (Prescott & Kendler, 1999). But
what are the genes implicated in addiction?
The thirst for understanding of, and
potentially treatment for, addiction has pressured many to jump hastily to the conclusion
that “THE” addiction gene has been identified.
But it is clear that addiction, like any complex
behavioral trait, is influenced by MANY genes
and that these genes are only part of the story.
An estimated 1500 (or more) genes influence
addictive behaviors (Li et al., 2008). This complexity means that a prediction about an individual’s risk is impossibly hard to make. But it
does not prevent us from trying to identify specific genes associated with addiction.
There are two main methods for identifying
genes that predispose a person to addiction.
The “candidate-gene” approach is hypothesisdriven but biased. It starts by hypothesizing
that a specific gene (and ­therefore is biased to
the genes one wants to investigate) involved in
some drug-related process or pathway, if mutated,
could influence the user’s experience with the
drug. Many genes have been investigated in this
­candidate-gene approach (Goldman et al., 2005).
For instance, alleles that manufacture nonoptimal
versions of many drug-­metabolizing enzymes
result in a reduced frequency of drug use. The
candidate-gene approach has also led to the analysis of genes that make receptors to which drugs
or neurotransmitters bind. Because the reward
pathway we previously discussed (Cunningham
et al., 2012) is involved in addiction to many
drugs, the dopamine-receptor encoding gene,
D2DR, has been strongly implicated in a complex
trait referred to as “reward deficiency syndrome”
(Blum et al., 1996). In summary, the candidategene approach has led to many fruitful discoveries about genes that specifically influence drug
response as well as those that might more generally predispose a person to use substances.
A “genome-surveillance” approach (Liu et al.,
2005) is less biased because it makes no assumptions about the nature of the proteins encoded
by addiction-influencing genes. However, this
approach has been likened to finding the proverbial needle in the haystack. The human genome
has some 25,000 genes. Nearly 1500 of them
have been implicated in some way in addiction
(Li et al., 2008). How do we find the ones correlated with a specific behavior? The answer
involves years, an international collection of
labs, and an extremely thorough bioinformatics
analysis. In 2009, just such a bioinformatics
approach investigated 30 years’ worth of research
encompassing more than 2000 studies (Li & Burmeister, 2009, fig. 1). This analysis focused on
five genetic pathways, including “old standards”
Figure 1. Genes mapped to 11 of our 23 chromosomes are implicated in single-drug
addiction or, in some cases, addiction to multiple substances (from Li & Burmeister, 2009).
See ABT online for color figure.
The American Biology Teacher, Vol. 74, No. 9, pages 652–653. ISSN 0002-7685, electronic ISSN 1938-4211. ©2012 by National Association of Biology Teachers. All rights reserved.
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DOI: 10.1525/abt.2012.74.9.10
652
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volume 74, No. 9, November/December 2012
as well as new gene candidates that are implicated in addiction, generally. These pathways
include the ­glutamate-reinforcing pathway, a
pathway implicated in learning and memories related to addiction, and one that involves
MAPK (mitogen-­activated protein kinase), which
may underlie synaptic changes that occur during
use of addictive drugs. Again, they point to the
importance of the reward pathway but also illuminate other important aspects of brain function, such as glutamate systems.
Although genetics can predispose a person
to addiction, it is irresponsible to imagine that a
person can reasonably “blame” genes for addiction. Similarly, a person with predisposing alleles
should not despair that addiction is inevitable.
You have to participate in the use of an addictive
substance to become an addict. Understanding
one’s genetic predisposition can actually help
an individual avoid behaviors that could lead
to addiction. As with the woman who avoided
gambling because she had an “addictive personality,” avoiding addictive habits is entirely possible. In addition, addictive patterns can also be
turned around; this same courageous woman
overcame a three-pack-a-day nicotine addiction
that had plagued her for 46 years.
The next piece in this series will highlight the role of learning in addiction. Recent
evidence suggests that this may be an important factor to consider. Join us to explore the
evidence underlying this premise.
Acknowledgments
This project was funded by the National Institute on Drug Abuse, National Institutes of
Health, through grant no. R25DA028796.
References
Blum, K., Sheridan, P.J., Wood, R.C., Braverman, E.R.,
Chen, T.J., Cull, J.G. & Comings, D.E. (1996). The
D2 dopamine receptor gene as a determinant
of reward deficiency syndrome. Journal of the
Royal Society of Medicine, 89, 396–400.
Cunningham, S., Buckland, H.T. & Martin-Morris,
L. (2012). What is the link between eating,
reproducing, & addiction? American Biology
Teacher, 74, 590–591.
Goldman, D., Oroszi, G. & Ducci, F. (2005). The
genetics of addictions: uncovering the genes.
Nature Review Genetics, 6, 521–532.
Li, C.-Y., Mao, X. & Wei, L. (2008). Genes and
(common) pathways underlying drug addiction.
PLoS Computational Biology, 4(1), e2.
Li, M.D. & Burmeister, M. (2009). New insights into
the genetics of addiction. Nature Reviews
Genetics, 10, 225–231.
Liu, Q.R., Drgon, T., Walther, D., Johnson, C.,
Poleskaya, O., Hess, J. & Uhl, G.R. (2005). Pooled
association genome scanning: validation and
The World’s Leading Supplier of Osteological Specimens!
use to identify addiction vulnerability loci
in two samples. Proceedings of the National
Academy of Sciences USA, 102, 11864–11869.
Merikangas, K.R., Stolar, M., Stevens, D.E., Goulet, J.,
Preisig, M.A., Fenton, B., Zhang, H., O’Malley, S.S.
& Rounsaville, B.J. (1998). Familial transmission
of substance use disorders. Archives of
General Psychiatry, 55, 973–979.
Prescott, C.A. & Kendler, K.S. (1999). Genetic and
environmental contributions to alcohol abuse
and dependence in a population-based
sample of male twins. American Journal of
Psychiatry, 156, 34–40.
Uhl, G.R. (2004). Molecular genetic underpinnings
of human substance abuse vulnerability: likely
contributions to understanding addiction as
a mnemonic process. Neuropharmacology,
47(Supplement 1), 140–147.
SUSANNA L. CUNNINGHAM is Professor at the
University of Washington, School of Nursing, T618B
Health Sciences, 1959 NE Pacific Street, Seattle,
WA 98195-7266; e-mail: [email protected]. HELEN
T. BUCKLAND is Project Director of the Online
Neuroscience Education about Drug Addiction at
the University of Washington, School of Nursing,
T610A Health Sciences, 1959 NE Pacific Street, Seattle,
WA 98195-7266; e-mail: [email protected]. LINDA
MARTIN-MORRIS is Senior Lecturer at the University
of Washington, Department of Biology, Box 355320,
University of Washington, Seattle, WA 98195-5320;
e-mail: [email protected]. For questions about this article,
please contact Helen T. Buckland at [email protected].
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