Bookmark and Share
Share

Alcohol Alter

National Institute on Alcohol Abuse and Alcoholism              No. 48           July 2000

 


From Genes to Geography: The Cutting Edge of Alcohol Research

The development of alcohol use problems, including alcoholism, is influenced by multiple genes (i.e., what we inherit), the environment (i.e., where and how we live), and interactions between the two. Defining precisely which genes and environmental factors are involved and how they interact in the development of alcohol use problems are complex tasks. Fortunately, a number of major technological advances are helping investigators make significant progress toward this goal. The alcoholism-related interactions explored in this issue of Alcohol Alert occur within settings ranging from brain cells to city streets.

Alcohol and the Brain

All brain functions, including addiction, involve communication among nerve cells (i.e., neurons) in the brain. This communication involves both a "sending" neuron and a "receiving neuron" that communicate across minute gaps between them called synapses. Messages are carried across synapses by chemicals called neurotransmitters. Alcohol causes many of its physical effects (e.g., intoxication and sleepiness) by affecting communication between neurons.

After its release, a neurotransmitter crosses the synapse and activates a receptor protein in the receiving neuron. Activating a receptor can cause the receiving neuron to change or adapt. Prolonged or repeated exposure to alcohol can cause such changes in neurons that in susceptible people can lead to the development of alcoholism. Adaptation to the presence of alcohol is also thought to underlie such phenomena as tolerance, withdrawal, and the persistent craving for alcohol that has been postulated to provoke relapse.

Measuring Neuronal Activity

The communication between neurons creates electrical activity. Groups of neurons with similar functions extend from one brain region to another, forming neural circuits. Circuits interact with one another to integrate the functions of the brain, including complex emotional, cognitive, and motivational processes. To understand the link between alcohol use and these complex processes, alcohol researchers needed a way to relate the chemistry of individual neurons to the integrated activity of neuronal circuits. A recent approach to the problem involves the simultaneous measurement of electrical activity within selected neuronal circuits. This technique has been used in both rats and humans. For example, in a preliminary study, Woodward and colleagues (1) used this technique to trace the sequence of neuronal activity in rats as they responded to the presence of alcohol. This technique has also been applied to human studies using electroencephalography (EEG). Researchers have identified at least three brainwave patterns with EEG that have been associated with alcoholism and which may help experimenters identify people at increased risk (2-6).

Alcoholism and Genetics

The blueprint for the human body is encoded in its genes. Genes govern the expression of specific genetic traits and account for trait differences that help distinguish one individual from another. Each gene directs the synthesis of a different protein. Abnormal gene variants may give rise to defective proteins that can contribute to disease. Vulnerability to complex diseases like alcoholism requires changes in multiple genes. Because genetics studies indicate that between 40 and 60 percent of alcoholism vulnerability has a genetic basis (7), finding the genes that are involved in alcoholism vulnerability is a high priority for alcohol research. Genetics studies, such as the Collaborative Study on the Genetics of Alcoholism, have already identified several sites in the brain where the genes for alcoholism may be located. The map of the human genome will no doubt help lead investigators to the discovery of the genes that play a role in increasing an individual's vulnerability to alcoholism.

In search for the genes for alcoholism, alcohol investigators are taking full advantage of the new genetic engineering techniques. For example, researchers can inactivate, or knock out, a gene, creating a line of mice that lack a particular receptor or other protein thought to influence a specific genetic trait. Conversely, scientists can insert an additional gene into an animal's genetic material (8,9). Animals with an added gene are called transgenic. The response of the genetically engineered animal to alcohol can be compared with that of a genetically unaltered animal to help determine the role of the gene in mediating a particular alcohol-induced behavior (e.g., incoordination) (10,11).

Of the many different knockouts, at least three have implicated brain proteins involved in high alcohol preference in mice (12-14). Knockout (15-17) and transgenic (15,18) experiments also have implicated some of the same receptors and brain proteins in both sensitivity and preference to alcohol. In the animal experiments, mice that initially display high resistance (i.e., are less sensitive) to alcohol-induced sedation usually develop a high preference for alcohol consumption. These laboratory findings are consistent with Schuckit's (19) observation that low sensitivity to alcohol may predict future development of alcoholism. If these results are confirmed in humans, they may provide a means to help identify high-risk youth for targeted intervention programs.

The use of microarrays is another powerful new technology in alcoholism research. This technique permits the simultaneous study of many genes and provides scientists with new power to understand changes in gene expression that relate to the vulnerability to developing alcoholism. The long-term adaptation of the brain's neurons to alcohol may result, in part, from changes in gene function (20). Genes direct the synthesis of proteins, such as receptors. A gene's level of activity, therefore, can be used to obtain indirect information about its proteins.

Because alcohol is known to affect gene-induced protein production (i.e., gene expression) (21), levels of genetic activity can be tracked to determine how genes associated with an alcohol-induced effect are expressed. Tracking the activity of a single gene takes time; given the large number of genes that may be involved in producing alcohol's effects, the task of linking specific genes to specific effects might be formidable. However, by using microarrays, alcohol scientists can track up to 10,000 selected genes simultaneously. In this approach, the genes of interest are affixed to a glass slide, silicon chip, or similar surface--often as small as a postage stamp--forming a so-called microarray. An automated operating system scans the microarray and can calculate the relative expression levels of up to 10,000 selected genes simultaneously (22). As more alcoholism researchers begin to employ this procedure, it may become possible to identify virtually every gene and its protein that play a significant role in alcohol-related behavior.

Alcoholism Treatment

Developing a reliable biological marker of recent alcohol consumption has long been on the "wish list" of alcohol researchers and clinicians alike. Such markers could enable researchers to confirm self-reported drinking behavior by study participants and could help clinicians monitor patients undergoing alcoholism treatment. Most currently available markers (e.g., gamma-glutamyl transferase) are alterations in blood chemistry that can be induced directly or indirectly by alcohol. However, many of the markers lack specificity (i.e., altered marker levels are not necessarily the result of alcohol consumption) or sensitivity (i.e., altered marker levels are difficult to detect at low levels of consumption). In addition, some marker levels are not useful until serious alcohol-related organ damage has occurred (23,24). Carbohydrate-deficient transferrin (CDT) is a blood protein that increases in concentration after alcohol consumption has exceeded approximately five standard drinks (i.e., 60 grams) per day for 2 to 3 weeks (25). CDT concentrations then remain elevated for up to 2 weeks after drinking ceases, potentially enabling relatively early detection of relapse among alcoholics in treatment (26). Interest in using CDT as a biological marker of alcohol consumption has increased because of its relatively high sensitivity and specificity. Research is underway to improve the precision of CDT measurement (27,28). A kit designed to measure CDT levels in patients will soon be commercially available for clinical use.

Geocoding: Mapping Environmental Influences in Drinking Behavior

The problems caused by alcohol are influenced by a variety of cultural, demographic, and social factors that may differ significantly between geographic areas (29,30). Geocoding is the process of associating descriptive data to fixed geographic points for the purpose of correlating events with where and when they take place (30). For example, Gruenewald and colleagues (31) used geocoding to relate the availability of alcohol in different communities to local rates of single-vehicle nighttime crashes, a measure thought to reflect rates of drinking and driving. Major advances in computer science now permit the results of geocoding to be analyzed statistically and displayed clearly in maps that can be linked to data available from the U.S. Bureau of the Census and other sources (31). As research in this area matures, alcohol-related geocoding research could become a useful guide to social policy.


From Genes to Geography: The Cutting Edge of Alcohol Research-A Commentary by NIAAA Director Enoch Gordis, M.D.

The advances described in this Alcohol Alert offer a glimpse of the way in which cutting-edge technology is being used by alcohol scientists to undertake complex studies more quickly and with greater efficiency. We share this glimpse with our readers for two important reasons. First, much of what we have learned in recent years about alcohol and the brain and the genetic basis of alcohol dependency would not have even been possible without the type of technological capability available to scientists today. The more we understand about the mechanisms of dependence, the more likely it is that we can design effective prevention and treatment. Second, many of us tend to think of technology only in terms of basic research. However, it is equally important to understand that technology also contributes to other important arenas of the alcohol use problems field, such as policy analysis, prevention planning, and clinical practice.

Acknowledgments

The National Institute on Alcohol Abuse and Alcoholism wishes to acknowledge the following individuals who have contributed their time and expertise to the development of the Alcohol Alert series during the past 2 years: John Doria; Mary Dufour, M.D., M.P.H.; Michael Eckardt, Ph.D.; Richard Fuller, M.D.; David Goldman, M.D.; Brenda Hewitt; Daniel Hommer, M.D.; William Lands, Ph.D.; Susan Martin, Ph.D.; Diane Miller; Antonio Noronha, Ph.D.; Eve Shapiro; Kenneth Warren, Ph.D.; Dianne Welsh; Ellen Witt, Ph.D.; and Sam Zakhari, Ph.D.


References

(1) Woodward, D.J.; Janak, P.H.; and Chang, J.Y. Ethanol action of neural networks studied with multineuron recording in freely moving animals. Alcohol Clin Exp Res 22(1):10-22, 1998. (2) Begleiter, H., and Porjesz, B. What is inherited in the predisposition toward alcoholism? A proposed model. Alcohol Clin Exp Res 23(7):1125-1135, 1999. (3) Porjesz, B.; Begleiter, H.; Reich, T.; et al. Amplitude of visual P3 event-related potential as a phenotypic marker for a predisposition to alcoholism: Preliminary results from the COGA project. Alcohol Clin Exp Res 22(6):1317-1323, 1998. (4) Hill, S.Y. Biological phenotypes associated with individuals at high risk for developing alcohol-related disorders: Part I. Addict Biol 5:5-22, 2000. (5) Lukas, S.E. Topographical brain mapping during drug-induced behaviors. In: Johnson, B.A., and Roache, J.D., eds. Drug Addiction and Its Treatment: Nexus of Neuroscience and Behavior. Philadelphia, PA: Lippincott-Raven, 1997. pp. 259-275. (6) Enoch, M.-A.; White, K.V.; Harris, C.R.; et al. Association of low-voltage alpha EEG with a subtype of alcohol use disorders. Alcohol Clin Exp Res 23(8):1312-1319, 1999. (7) Kendler, K.S.; Prescott, C.A.; Neale, M.C.; and Pedersen, N.L. Temperance Board registration for alcohol abuse in a national sample of Swedish male twins, born 1902 to 1949. Arch Gen Psychiatry 54(2):178-184, 1997. (8) Wehner, J.M., and Bowers, B.J. Use of transgenics, null mutants, and antisense approaches to study ethanol's actions. Alcohol Clin Exp Res 19(4):811-820, 1995. (9) Crabbe, J.C. Genetic modification as a tool for the study of behavioral consequences of signaling processes. In: Hoek, J.B.; Gordon, A.S.; Mochly-Rosen, D.; and Zakhari, S., eds. Ethanol and Intracellular Signaling: From Molecules to Behavior. NIAAA Research Monograph No. 35. NIH Pub No. 00-4579. Bethesda, MD: NIAAA, 2000. pp. 137-144. (10) Anders, D.L.; Blevins, T.; Smothers, C.T.; and Woodward, J.J. Reduced ethanol inhibition of N-methyl-D-aspartate receptors by deletion of the NR1 C0 domain or overexpression of alpha-actinin-2 proteins. J Biol Chem 275(20):15019-15024, 2000. (11) Boehm, II, S.L.; Schafer, G.L.; and Phillips, T.J. Sensitivity to ethanol-induced motor incoordination in 5-HT1B receptor null mutant mice is task-dependent: Implications for behavioral assessment of genetically altered mice. Behav Neurosci 114(2):401-409, 2000. (12) Hwang, B.H.; Zhang, J.K.; Ehlers, C.L.; Lumeng, L.; and Li, T.K. Innate differences of neuropeptide Y (NPY) in hypothalamic nuclei and central nucleus of the amygdala between selectively bred rats with high and low alcohol preference. Alcohol Clin Exp Res 23(6):1023-1030, 1999. (13) Risinger, F.O.; Doan, A.M.; and Vickrey, A.C. Oral operant ethanol self-administration in 5-HT1b knockout mice. Behav Brain Res 102(1/2):211-215, 1999. (14) Roberts, A.J.; McDonald, J.S.; Heyser, C.J.; et al. mu-opioid receptor knockout mice do not self-administer alcohol. J Pharm Exp Ther 293(3):1002-1008, 2000. (15) Thiele, T.E.; Marsh, D.J.; Ste. Marie, L.; et al. Ethanol consumption and resistance are inversely related to neuropeptide Y levels. Nature 396(6709):366-369, 1998. (16) Bowers, B.J.; Owen, E.H.; Collins, A.C.; et al. Decreased ethanol sensitivity and tolerance development in gamma-protein kinase C null mutant mice is dependent on genetic background. Alcohol Clin Exp Res 23(3):387-397, 1999. (17) Yagi, T.; Yasuda, M.; and Niki, H. Ethanol sensitivity and molecular function of Fyn tyrosine kinase. In: Hoek, J.B.; Gordon, A.S.; Mochly-Rosen, D.; and Zakhari, S., eds. Ethanol and Intracellular Signaling: From Molecules to Behavior. NIAAA Research Monograph No. 35. NIH Pub No. 00-4579. Bethesda, MD: NIAAA, 2000. pp. 195-202. (18) Engel, S.R., and Allan, A.M. 5-HT3 receptor over-expression enhances ethanol sensitivity in mice. Psychopharm 144(4):411-415, 1999. (19) Schuckit, M.A. Biological, psychological and environmental predictors of the alcoholism risk: A longitudinal study. J Stud Alcohol 59(5):485-494, 1998. (20) Miles, M.F. Alcohol's effects on gene expression. Alcohol Health Res World 19(3)237-243, 1995. (21) Bachtell, R.K.; Wang, Y.-M.; Freeman, P.; et al. Alcohol drinking produces brain-region selective changes in expression of inducible transport factors. Brain Res 847(2):157-165, 1999. (22) Ermolaeva, O.; Rastogi, M.; Pruitt, K.D.; et al. Data management and analysis for gene expression arrays. Nature Genetics 20:19-23, 1998. (23) Allen, J., and Sillanaukee, P. Carbohydrate-deficient transferrin is a useful marker for the detection of chronic alcohol abuse. Eur J Clin Invest 29(10):899-900, 1999. (24) Salaspuro, M. Carbohydrate-deficient transferrin as compared to other markers of alcoholism: A systematic review. Alcohol 19(3):261-271, 1999. (25) Sillanaukee, P. Laboratory markers of alcohol abuse. Alcohol Alcohol 31(6)613-616, 1996. (26) Mundle, G.; Ackerman, K.; and Mann, K. Biological markers as indicators for relapse in alcohol-dependent patients. Addict Biol 4:209-214, 1999. (27) Bean, P. Carbohydrate-deficient transferrin in the assessment of harmful alcohol consumption: Diagnostic performance and clinical significance. Addict Biol 4:151-161, 1999. (28) Lieber, C.S. Carbohydrate deficient transferrin in alcoholic liver disease: Mechanisms and clinical implications. Alcohol 19(3):249-254, 1999. (29) Gruenewald, P.J.; Millar, A.; Ponicki, W.R.; and Brinkley, G. Physical and economic access to alcohol: The application of geostatistical methods to small area analysis in community settings. In: Wilson, R.A., and Dufour, M.C., eds. The Epidemiology of Alcohol Problems in Small Geographic Areas. NIAAA Research Monograph No. 36. NIH Pub. No. 00-4357. Bethesda, MD: NIAAA, 2000. pp. 163-212. (30) Wieczorek, W.F. Using geographic information systems for small area analysis. In: Wilson, R.A., and Dufour, M.C., eds. The Epidemiology of Alcohol Problems in Small Geographic Areas. NIAAA Research Monograph No. 36. NIH Pub. No. 00-4357. Bethesda, MD: NIAAA, 2000. pp. 137-162. (31) Gruenewald, P.J.; Millar, A.B.; Treno, A.J.; et al. The geography of availability and driving after drinking. Addict 91(7):967-983, 1996.


All material contained in the Alcohol Alert is in the public domain and may be used or reproduced without permission from NIAAA.
Citation of the source is appreciated.

Copies of the Alcohol Alert are available free of charge from the National Institute on Alcohol Abuse and Alcoholism
Publications Distribution Center, P.O. Box 10686, Rockville, MD 20849-0686.

Full text of this publication is available on NIAAA's World Wide Web site at http://www.niaaa.nih.gov


HHS Logo U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES


Public Health Service * National Institutes of Health
Updated: October 2000