Is Alcohol Addiction Genetic?

Is Alcohol Addiction Genetic
How do genes influence alcohol use disorder? Alcohol use disorder (AUD) often seems to run in families, and we may hear about scientific studies of an “alcoholism gene.” Genetics certainly influence our likelihood of developing AUD, but the story isn’t so simple.

Research shows that genes are responsible for about half of the risk for AUD. Therefore, genes alone do not determine whether someone will develop AUD. Environmental factors, as well as gene and environment interactions account for the remainder of the risk. Multiple genes play a role in a person’s risk for developing AUD.

There are genes that increase a person’s risk, as well as those that may decrease that risk, directly or indirectly. For instance, some people of Asian descent carry a gene variant that alters their rate of alcohol metabolism, causing them to have symptoms like flushing, nausea, and rapid heartbeat when they drink.

Many people who experience these effects avoid alcohol, which helps protect them from developing AUD.** As we have learned more about the role genes play in our health, researchers have discovered that different factors can alter the expression of our genes. This field is called epigenetics. Scientists are learning more and more about how epigenetics can affect our risk for developing AUD.

Can our genes affect alcohol treatment? Scientists are also exploring how genes may influence the effectiveness of treatments for AUD. For instance, the drug naltrexone has been shown to help some, but not all, patients with AUD to reduce their drinking.

Research has shown that patients with AUD who also have variations in a specific gene respond positively to treatment with the drug, while those without the specific gene do not. A fuller understanding of how genes influence treatment outcomes will help doctors prescribe the treatment that is most likely to help each patient.*** What is NIAAA doing to learn more? NIAAA has funded the Collaborative Studies on Genetics of Alcoholism (COGA) since 1989, with the goal of identifying the specific genes that influence alcohol use disorder.

In addition, NIAAA funds investigators’ research in this important field, and also has an in-house research emphasis on the interaction of genes and the environment. NIAAA is committed to learning more about how genes affect AUD so that treatment—and prevention efforts—can continue to be developed and improved.

Is addiction passed through genetics?

Genetics: The Blueprint of Health and Disease – Why do some people become addicted while others don’t? Family studies that include identical twins, fraternal twins, adoptees, and siblings suggest that as much as half of a person’s risk of becoming addicted to nicotine, alcohol, or other drugs depends on his or her genetic makeup.

Finding the biological basis for this risk is an important avenue of research for scientists trying to solve the problem of drug addiction. Genetics is the study of genes. Genes are functional units of DNA that make up the human genome. They provide the information that directs a body’s basic cellular activities.

Research on the human genome has shown that, on average, the DNA sequences of any two people are 99.9 percent the same. However, that 0.1 percent variation is profoundly important—it accounts for three million differences in the nearly three billion base pairs of DNA sequence! These differences contribute to visible variations, like height and hair color, and invisible traits, such as increased risk for or protection from certain diseases such as heart attack, stroke, diabetes, and addiction.

  • Some diseases, such as sickle cell anemia or cystic fibrosis, are caused by a change, known as a mutation, in a single gene.
  • Some mutations, like the BRCA 1 and 2 mutations that are linked to a much higher risk of breast and ovarian cancer, have become critical medical tools in evaluating a patient’s risk for serious diseases.

Medical researchers have had striking success at unraveling the genetics of these single-gene disorders, though finding treatments or cures has not been as simple. Most diseases, including addiction, are complex, and variations in many different genes contribute to a person’s overall level of risk or protection.

What percentage of addiction is genetic?

Rutgers Researchers Delve Deep Into the Genetics of Addiction, a professor of psychiatry at Robert Wood Johnson Medical School who leads the, has spent decades hunting genes that contribute to drug and alcohol addiction. While much remains unknown, improving technology has sped the rate of discovery.

  • Dick’s lab has published five studies in the past month.
  • How much of addiction is genetic? More than half of the differences in how likely people are to develop substance use problems stem from DNA differences, though it varies a little bit by substance.
  • Research suggests alcohol addiction is about 50 percent heritable, while addiction to other drugs is as much as 70 percent heritable.

How many genetic risk factors have we discovered? Hundreds, but there are hundreds more to be discovered. We just did where we measured how well the best current polygenic scores, combined with environmental risk factors, predicted substance use disorders in 15,000 people who participated in long-term studies, and we found that they only predicted about 10 percent of the outcome variations we saw.

That said, people with the highest levels of risk were four times more likely to develop a substance use disorder than people with the lowest levels of risk, so we can already help people understand their risk level and optimize their health choices. Are the risky genetic variants the same for all substances, or can someone have a high risk of alcoholism but little risk of opioid addiction? Most of the genes that influence substance use disorders are shared across many forms of addiction.

That means that people carrying risk genes are at risk for a variety of substance use problems. A we recently published found that a large part of the genetic risk is related to self-regulation, which reflects how differently wired brains process risk and reward.

  • Some people have brains primed toward greater impulsivity than others, and this can put them at risk for numerous forms of addiction.
  • Other genes are specific to the individual substances (e.g., just influence alcohol problems).
  • Do any of the big genetic testing companies tell users about increased risk for addiction? Not right now.

The science is still maturing, and many of these discoveries are very new. Genetic information alone will never be fully predictive of substance use because the environment also plays an important role. We are currently working on how to combine genetic and environmental information to help people understand their level of risk.

  • Would knowing about increased risk of addiction help people avoid addiction? That’s also the topic of from our group.
  • The current literature finds no consistent evidence that receiving information about genetic risk for things like cancer inspires people to change their behavior.
  • Future studies need to test strategies based on behavioral science to help people at elevated risk connect to resources to maximize their health and well-being.

Are there ways people can infer their genetic risk from their behavior? Yes. We know that individuals who are more risk-taking or impulsive are at elevated risk, as are individuals who are prone to depression or anxiety. In of nearly 5,000 college students, we found that motives for drinking reflected different types of genetic risk.

Individuals who drink to cope were at elevated risk of developing problems, as compared to individuals who drink to socialize. But those who drank to have fun were more likely to binge drink, which we know is associated with experiencing more alcohol-related accidents and consequences like fights or unwanted sexual experiences.

Any others? The best-known indicator of genetic risk is having a parent with a substance use disorder, but the transmission of risk from parent to child isn’t purely genetic. found that resident children of parents who have substance use disorders and related behavioral challenges will engage in similar behaviors more than the genetics of the child would predict.

  • The parents not only pass on their genes but create a riskier environment for the kids.
  • Additionally, kids with elevated genetic risk, who may be more challenging for parents, also had lower parent-child closeness and communication, which further elevated their risk.
  • We’re just starting to untangle the ways that kids’ and parents’ genes and environments come together to contribute to risk and resilience.

: Rutgers Researchers Delve Deep Into the Genetics of Addiction

Is depression and alcoholism genetic?

Evidence of Co–Occurring Alcoholism and Depression in Animal Models – The potential link between depression and alcohol use also has been investigated in laboratory animals. Although depression in animals cannot be assessed the same way as in humans, some behavioral tests can be interpreted as representing counterparts of human depression.

  • Examples of these tests are the “Porsolt” or forced swim test, in which rats or mice are observed for the duration of their attempt to escape from a beaker of water, and the restrained stress test, a measure of the animals’ locomotor activity following a period of restraint in a plastic tube.
  • In both of these tests, the animals exhibit greater activity when they are pretreated with antidepressant drugs.

Researchers have compared the results of behavioral tests for depression with voluntary alcohol consumption in defined strains of rodents. The results demonstrate variability in these animal models, similar to what is observed in human patients with depression and alcohol use disorders.

  • For example, a rat strain called Flinders sensitive rat (FSL), which is thought to be particularly vulnerable to behavioral depression, does not voluntarily consume alcohol (see table) (Overstreet et al.1992).
  • Conversely, Fawn–hooded rats (Rezvani et al.2002) and C57 mice (Elmer et al.1987), both of which also demonstrate behavioral depression, will drink alcohol.

Finally, P rats, which have been selectively bred for alcohol preference over many generations, do not respond to tests of behavioral depression (Godfrey et al.1997). Researchers also investigated the responses of these various animal strains to drugs that act on messenger chemicals implicated in alcohol’s effects on the brain.

These analyses found that animals that are sensitive to depression also are sensitive to drugs which are similar to the messenger chemical but show variable responses to drugs that affect the messenger chemical (for a review, see Rezvani et al.2002). These findings lead to the conclusion that, as in humans, animal models for both alcohol intake and depression show variability and that the relationship between the two behaviors varies with the model used.

— John I. Nurnberger, Jr., Tatiana Foroud, Leah Flury, Eric T. Meyer, Ryan Wiegand References ELMER, G.I.; MEISCH, R.A.; and GEORGE, F.R. Mouse strain differences in operant self–administration of ethanol. Behavior Genetics 17(5):439–451, 1987. GODFREY, C.D.; FROEHLICH, J.C.; STEWART, R.B.; et al.

  1. Comparison of rats selectively bred for high and low ethanol intake in a forced–swim–test model of depression: Effects of desipramine.
  2. Physiology and Behavior 62:729–733, 1997.
  3. OVERSTREET, D.H.; REZVANI, A.H.; and JANOWSKY, D.S.
  4. Genetic animal models of depression and ethanol preference provide support for cholinergic and serotonergic involvement in depression and alcoholism.

Biological Psychiatry 31:919–936, 1992. REZVANI, A.H.; PARSIAN, A.; and OVERSTREET, D.H. The Fawn–hooded (FH/Wjd) rat: A genetic animal model of comorbid depression and alcoholism. Psychiatric Genetics 12(1):1–16, 2002.

Relationship Between Behavioral Depression, as Indicated by Behavior in the “Forced Swim” and “Stress–Open Field” Tests, and Voluntary Alcohol Consumption in Genetically Defined Rodent Strains

Strain Forced Swim Test Stress–Open Field Test Voluntary Alcohol Consumption
Flinders sensitive rat ? + 0
P rat 0 ++
Fawn–hooded rat ? + +
C57 mouse ++ + +

KEY: ? = response unknown + = sensitive to behavioral depression; voluntary alcohol consumption ++ = very sensitive to behavioral depression; high levels of voluntary alcohol consumption 0 = no sensitivity to behavioral depression; no voluntary alcohol consumption – = not tested The COGA project, conducted at several research centers across the United States, seeks to identify genes contributing to the development of alcoholism and related characteristics (i.e., phenotypes).

  • This article describes some of the methods used by COGA investigators to define phenotypes related to the comorbidity of alcoholism and depression and summarizes data on both disorders in the COGA participants.
  • Finally, the article discusses the implications of these findings for a potential genetic relationship between alcoholism and depression.

DESIGN AND METHODS OF THE COGA STUDY Between 1988 and 1998, investigators at six COGA sites used a common protocol to gather clinical information and biological data (including DNA and neurophysiologic measures) from families of subjects with alcoholism.

Participants were recruited among patients undergoing alcoholism treatment (i.e., the probands) and their first–degree relatives. Control families were recruited from dental clinics, motor vehicle records, or random mailings at the six sites. Control families were not excluded if a family member had alcoholism or another psychiatric disorder; thus, these families represent a comparison group not selected with respect to psychopathology.

Each control family included at least two parents and three children ages 14 and older. All participants were interviewed using a screening instrument called the Semi–Structured Assessment for the Genetics of Alcoholism (SSAGA) (Bucholz et al.1994), which allows for diagnostic assessment of various disorders, including alcoholism and depression.

For the analyses presented here, participants were diagnosed with alcoholism (ALC) if they met the diagnostic criteria for alcohol dependence specified in the Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised (DSM–III–R) (American Psychiatric Association 1987) as well as the criteria for “definite alcoholism” established by Feighner and colleagues (1972).

Participants were diagnosed with depression (DEP) if they met the DSM–III–R criteria for major depressive disorder or if they had “depressive syndrome.” (Subjects were classified as having depressive syndrome if they met all the criteria for major depressive disorder, except that the depression could have been caused by alcohol or other drug use or another illness.) Participants with both ALC and DEP were included in the phenotype “alcoholism and depression” (AAD).

People meeting the criteria for either ALC or DEP were combined into a phenotype called “alcoholism or depression” (AorD). Separate analyses were conducted for participants with the DEP phenotype—that is, with depression or depressive syndrome (which can occur in both alcoholics and nonalcoholics). The COGA researchers performed statistical analyses of differences in the prevalence of alcoholism and/or depression in various subgroups of study participants and tested interactions between variables.

These data were calculated for all families of alcoholic probands and for control families where appropriate. After the diagnostic assessment, a subset of families with at least two alcoholic members in addition to the initially recruited proband were invited to participate in a second stage of assessment, which included blood collection for genetic analyses.

  • For these analyses, the investigators checked a total of 336 short, repeated DNA sequences located throughout all chromosomes (for more information, see Reich et al.1998; Nurnberger et al.2001).
  • These sequences are useful as markers because they vary in size from one person to another and their inheritance pattern can therefore be easily determined.

This screening process was carried out with two groups of participants. The first group (the “initial data set”) included 987 people from 105 families, and the second group (the “replication data set”) included 1,295 people from 157 families. To investigate the molecular genetics of alcoholism and depression, the COGA investigators performed linkage analyses.

  1. This means that they compared the presence of certain variants (i.e., alleles) of the markers in people with the ALC, AAD, AorD, and DEP phenotypes to identify chromosomal regions that were more similar in people with a given phenotype than would be expected by chance.
  2. Such regions would be considered genetically “linked” to the phenotype—that is, they are located near a gene that influences the phenotype.

Because many genes appear to contribute to the risk for developing alcoholism, the investigators employed statistical methods that do not rely on specific models of susceptibility for the phenotype. All these statistical methods are based on the sharing of gene sequences that are identical by descent (IBD).

Such sequences are considered IBD if both members of a sibling pair have inherited the sequence from the same parent. (For further discussion of linkage analysis for complex disorders, see Nurnberger and Berrettini 1998.) The investigators conducted multipoint linkage analyses, in which multiple markers were evaluated simultaneously for evidence of allele (gene sequence) sharing using the computer program ASPEX ( ftp://lahmed.stanford.edu/pub/aspex/index.html ).

RESULTS OF THE COGA STUDY Prevalence of Alcoholism and/or Depression The COGA researchers first determined the prevalence of major depression and depressive syndrome in the families of the alcoholic probands (see table 2). These studies found that among both males and females, major depression was not more common in alcoholic participants than in nonalcoholic participants.

Table 2 Prevalence of DSM–III–R Depression and Depressive Syndrome in Adult COGA Probands and Their Alcoholic and Nonalcoholic Relatives

COGA Probands and their Alcoholic Relatives Nonalcoholic Relatives Relative Risk Among COGA Probands and their Alcoholic Relatives
Males
Major Depression 11.0% (257/2,337) 10.5% (151/1,436) 1.05
Depressive Syndrome 30.3% a (707/2,337) 6.0% (86/1,436) 5.05
Total 41.2% a (964/2,337) 16.5% (237/1,436) 2.50
Females
Major Depression 24.2% b (311/1,288) 22.4% c (704/3,138) 1.08
Depressive Syndrome 32.8% a (423/1,288) 11.3% c (356/3,138) 2.90
Total 57.0% b (734/1,288) 33.8% c (1,060/3,138) 1.69

a X 2 ≥ 204 (actual values 315.4, 250.9, 290.9, 204.0, from top to bottom), df = 1, p < 10 –45 vs. nonalcoholic subjects. b X 2 ≥ 82 (actual values 108.6, 82.6), df = 1, p < 10 –18 vs. males. c X 2 ≥ 32 (actual values 92.1, 32.4, 144.7), df = 1, p < 10 –7 vs. males. NOTE: The data are from COGA Master File 86 (1999). The combination of alcohol dependence and depression (i.e., the AAD phenotype) appears to run in families, as demonstrated by an analysis of first–degree relatives of alcoholic probands with or without depression and first–degree relatives of control subjects. This analysis found that AAD occurred in 15.9 percent of first–degree relatives of probands with AAD (489 out of 3,069 people), compared with 11.7 percent of first–degree relatives of probands with alcoholism alone (287 out of 2,462) and 3.6 percent of first–degree relatives of control subjects (42 out of 1,164). Thus, the prevalence of AAD was significantly greater among the first–degree relatives of probands with AAD than among relatives of probands with alcoholism alone or relatives of control subjects (Nurnberger et al.2001). Next, the investigators determined the risks of alcoholism or depression for the relatives of three types of alcoholic probands—those with alcoholism alone, those with alcoholism and depressive syndrome, and those with alcoholism and major depression. The risk of alcoholism was significantly increased in the relatives of probands with both types of depression compared with probands with alcoholism alone (see table 3). Similarly, the risk of depression was increased in relatives of alcoholic probands with major depression and, to a lesser extent, in relatives of alcoholic probands with depressive syndrome. These findings support the idea that the AAD phenotype may represent a genetically distinct condition. This notion is further supported by the finding that depression in relatives of probands with AAD typically does not occur independently but only in combination with alcoholism. That is, the prevalence of major depression alone is not increased in those relatives. The prevalence of AAD, however, is increased twofold in relatives of probands with alcoholism plus depressive syndrome (i.e., 4.4 percent) and increased nearly fourfold in relatives of probands with alcoholism plus major depression (i.e., 8.4 percent) when compared with relatives of control subjects (i.e., 2.2 percent ). Another analysis (not shown on the table) found that the prevalence of depression alone is not significantly increased in relatives of probands with alcoholism alone (19.6 percent) or with the AAD phenotype (21.2 percent) compared with relatives of control subjects (19.3 percent). The prevalence of the AAD phenotype, however, is increased in relatives of probands with alcoholism only (10.2 percent) and in relatives of probands with AAD (14.3 percent) compared with relatives of control subjects (3.4 percent). These findings argue for a model in which some families carry susceptibility factors for both conditions. Finally, the increase in the prevalence of the AAD phenotype was seen in both male and female relatives of probands with alcoholism only or AAD.

Table 4 Prevalence of Alcoholism and Depression in the Relatives of Alcoholic and Control Probands in the COGA Study

Diagnosis in Relatives
Proband Diagnosis Alcoholism with or without Depressive Syndrome Major Depression Only Alcoholism and Major Depression
Control 10.2% (74/725) 14.6% (106/725) 2.2% (16/725)
Alcoholism with or without Depressive Syndrome 25.6% a (1,112/4,348) 13.1% (571/4,348) 4.4% a (191/4,348)
Alcoholism with Major Depression 24.0% a (132/549) 14.2% (78/549) 8.4%† (46/549)

p <,01 vs. control † p <,001 vs. alcoholism only and control NOTE: The data were derived from COGA Master File 86 (1999). The researchers also explored the order in which alcoholism or depression developed in both the probands and their relatives. For this purpose, the investigators determined the ages of onset of alcoholism and depression, which according to the DSM–III–R are defined as the ages at which three symptoms of alcoholism or the first major depressive episode, respectively, occurred. The analyses found that in approximately 50 percent of subjects with AAD, the onset of major depression occurred prior to the onset of alcohol dependence (see table 5). (For comparison, mania occurred first in about 42 percent of subjects with both mania and alcoholism.) This finding may indicate that even in this group of families with multiple cases of alcohol dependence, a substantial number of people develop alcoholism secondary to an underlying mood disorder. However, there was a notable gender effect in the order of disease onset: Males tend to develop alcohol dependence before the onset of the affective disorder, whereas this order tended to be reversed in females.

Table 5 Chronological Order of Disease Development in COGA Participants with Alcoholism and an Affective Disorder (i.e., Major Depression or Mania)

Onset of Alcoholism First Onset of Depression First Same Time of Onset for Both Disorders
Alcoholism and Depression
Males (N = 267) 143 (53.6%) 104 (39.0%) 20 (7.5%)
Females (N = 325) 115 (35.4%) 193 (59.4%) 17 (5.2%)
Total (N = 592) 258 (43.6%) 297 (50.2%) 37 (6.3%)
Alcoholism and Mania
Males (N = 33) 22 (66.7%) 9 (23.7%) 2 (6.1%)
Females (N = 33) 13 (39.4%) 19 (57.6%) 1 (3.0%)
Total (N = 66) 35 (53.0%) 28 (42.4%) 3 (4.5%)

NOTE: The diagnoses and age of onset are based on data from COGA Master File 118 (2002). Linkage Analyses Because the data presented in the previous section suggested some interaction of vulnerability factors for alcoholism and depression, the COGA investigators performed genetic linkage analyses using DNA samples from sibling pairs with the AAD, AorD, and DEP phenotypes in order to identify chromosomal regions linked to these phenotypes.

In the sibling pairs, both siblings had the phenotype under investigation. This analysis included 224 AAD pairs (57 percent male), 1,359 AorD pairs (56 percent male), and 440 DEP pairs (49 percent male). The AorD phenotype is the most inclusive because it refers to people with either the ALC or DEP phenotypes.

Most of the sibling pairs added to the ALC data set to generate the AorD data set (59 percent of all added pairs and 94 percent of the mixed gender pairs) consisted of an alcoholic brother with a depressed sister. The results pointed to an area of interest on chromosome 1 for the AorD phenotype (Nurnberger et al.2001).

  1. Increased allele sharing was seen near two markers called D1S1648 and D1S1588 between 100 and 110 centi–Morgan (cM) 1 from the origin.
  2. 1 A centi–Morgan is a unit of measurement for distances along chromosomes.
  3. The largest human chromosome, chromosome 1, has a length of approximately 325 centi–Morgan.

One can also express the location of markers as their distance in centi–Morgan from the tip of the chromosome.) This increased sharing was observed in the initial data set, to a lesser extent in the replication data set, and was still evident when the two data sets were combined.

  • Overall, the analyses found evidence for genetic linkage over a relatively large portion of chromosome 1 (i.e., 60 cM).
  • For a summary of other linkage results from these data sets, including results for the AAD and DEP phenotypes, see Nurnberger and colleagues 2001; see also the articles in this issue by Bierut and colleagues, pp.208–213 and by Edenberg, pp.214–218.) The same portion of chromosome 1 that exhibited linkage with the AorD phenotype also has shown suggestive linkage with the ALC phenotype (Reich et al.1998).

Analysis of all possible sibling pairs with the ALC phenotype in the initial data set identified a region near a marker called D1S1675. In sibling pairs with the ALC phenotype, allele sharing in that area was similar to the allele sharing observed in sibling pairs with the AorD phenotype.

In these families, the same genetic characteristics may predispose some people to depression and others to alcoholism. IMPLICATIONS OF THE STUDY RESULTS The COGA study supports the conclusion of other investigators (Merikangas and Gelernter 1990; Merikangas et al.1994) that alcoholism and depression tend to occur together and that comorbid alcoholism tends to aggregate in the relatives of probands with both disorders.

The definition of depression in this analysis includes both major depression (i.e., primary depression) and depressive syndrome, which may be caused by alcohol and other drug use (i.e., secondary depression). However, primary and secondary depressive syndromes may not truly be distinct.

  1. Many people with alcohol problems spend a substantial portion of their lives drinking and thus have less opportunity to demonstrate independent episodes of depression.
  2. An alcoholic with true vulnerability for depression may, by the natural course of the two illnesses, have no demonstrably independent episodes.

The genetic analyses demonstrated evidence for linkage of the AorD phenotype with a region on chromosome 1, and the same region also showed evidence, though less substantial, of linkage with the ALC phenotype. This chromosome 1 region also showed possible linkage with mania and depression among the participants in the NIMH Genetics Initiative Bipolar Study (Rice et al.1997).

  1. Preliminary results suggested that this finding may be accounted for by families in which the probands have both alcoholism and mania.
  2. Thus, although the interpretation of linkage results in complex diseases is the subject of ongoing controversy and must be done cautiously, it appears likely that a locus on chromosome 1 accounts for some of the familial aggregation of alcoholism and depression in the COGA study.

The findings suggest that this region contains one or more genes associated with different clinical phenotypes (e.g., alcoholism, depression, and mania), a phenomenon called pleiotropy. The gene or genes associated with these phenotypes have not yet been identified.

However, several genes that may influence central nervous system function have been mapped to that region on chromosome 1. (For more information on genes located in that region, which is also referred to as the 1p13–35 region, see the Web site www.ncbi.nlm.nih.gov/locuslink,) Researchers await the results of other studies that may confirm these findings.

However, replication of linkage findings in complex disorders such as alcoholism and depression is likely to be difficult (Suarez et al.1994). In disorders to which multiple genetic factors contribute but for which no single factor is absolutely necessary, evidence for specific effects can differ among different data sets (i.e., for different study samples).

Accordingly, the replication of any given effect may require several studies with data sets of a size equivalent to the original data set. The majority of participants with alcoholism in the COGA data set were male, and the majority of participants with depression were female. Of the sibling pairs added to the data set of alcoholic sibling pairs for the linkage analyses for the AorD phenotype, many consisted of a brother with alcoholism and a sister with depression.

Consequently, the gene or genes contributing to these vulnerabilities may have variable expression in men and women. This result is reminiscent of the concept of depressive spectrum disease as postulated by Winokur and colleagues (1971). The findings summarized in this article suggest a genetic relationship between depression and alcohol dependence in some families where both disorders are transmitted.

  1. This conclusion is consistent with the idea that depression can be caused by many different genes (i.e., is a genetically heterogeneous condition).
  2. The results obtained so far have no direct implications for the treatment of patients with depression and/or alcohol dependence.
  3. However, they do reinforce the idea that some heavy drinkers may have genetic vulnerability to depression, as well as the observation that treatment of depressed alcoholic patients with antidepressants has generally had beneficial effects on the depression, and sometimes on the drinking as well (McGrath et al.2000).

In the future, genetic studies are likely to contribute to clinical treatment by identifying specific genes and their biochemical pathways, which could result in new therapeutic options for patient subgroups. The major advantage of the COGA study is its multisite design with similar methods employed at each site, which allowed the investigators to generate very large data sets.

One limitation of the study is that by design it focused on families densely affected with alcohol dependence for linkage analysis (although all families of alcoholic probands are included in the prevalence studies). Although such families are ideal for genetic studies, they may not be fully representative of the spectrum of people who suffer from alcoholism, depression, or both.

Despite this limitation, the study’s results, in combination with prior studies, suggest that the pattern of disorders in the family is a reasonable clinical characteristic to use for the differentiation of subgroups within alcoholism. ACKNOWLEDGMENTS We acknowledge administrative support for the COGA project and these analyses from Henri Begleiter, M.D.; Ingrid Schmidt, at the State University of New York, Brooklyn; and Ting–Kai Li, M.D., at Indiana University.

  1. COGA involves nine different centers across the United States where data collection, analysis, and/or storage take place.
  2. The principal investigator of COGA is H.
  3. Begleiter, State University of New York, Health Science Center at Brooklyn.T.
  4. Reich, Washington University, is co–principal investigator.
  5. The study sites and their principal investigators and co–investigators are: Indiana University (T.K.

Li; J. Nurnberger, Jr.; P.M. Conneally; H. Edenberg); University of Iowa (R. Crowe, S. Kuperman); University of California at San Diego (M. Schuckit); University of Connecticut (V. Hesselbrock); State University of New York, Health Science Center at Brooklyn (B.

  • Porjesz, H.
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  • Cloninger, J. Rice, A.
  • Goate); Howard University (R.
  • Taylor); Rutgers University (J.
  • Tischfield); and Southwest Foundation (L. Almasy).
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  5. A Family Study of Alcohol Dependence: Combining Sources of Diagnostic Information.” Paper presented at the International Genetic Epidemiology Society Meeting, New Orleans, November 2002.

REICH, T.; EDENBERG, H.J.; GOATE, A.; et al. Genome–wide search for genes affecting the risk for alcohol dependence. American Journal of Medical Genetics (Neuropsychiatric Genetics) 81:207–215, 1998. RICE, J.P.; GOATE, A.; WILLIAMS, J.T.; et al. Initial genome scan of the NIMH Genetics Initiative bipolar pedigrees: Chromosomes 1, 6, 8, 10 and 12.

American Journal of Medical Genetics (Neuropsychiatric Genetics) 74:247–253, 1997. SCHLESSER, M.A.; WINOKUR, G.; and SHERMAN, B.M. Genetic subtypes of unipolar primary depressive illness distinguished by hypothalmic pituitary adrenal axis activity. Lancet 1:739–741, 1979. SUAREZ, B.K.; HAMPE, C.L.; and VAN EERDEWEGH, P.

Problems of replicating linkage claims in psychiatry. In: Gershon, E.S., and Cloninger, C.R., eds. Genetic Approaches to Mental Disorders. Washington, DC: American Psychiatric Press, 1994. pp.23–46. WINOKUR, G.; CADORET, R.; DORZAB, J.; and BAKER, M. Depressive disease: A genetic study.

Is smoking and drinking hereditary?

Study of Millions Finds Genetic Links to Smoking and Drinking A study surveying more than 3.4 million people has found nearly 4,000 genetic variants related to the use of alcohol and tobacco, scientists reported Wednesday (Dec 7) in, More than 1,900 of the variants had not previously been linked to substance use behaviors, study coauthor and statistical geneticist at the Penn State College of Medicine Dajiang Liu states in a,

  1. The novel findings were aided by the fact that a fifth of the genomic samples came from individuals of non-European ancestry, Liu says.
  2. This is a great study.
  3. It demonstrates the power of using large samples from multiple ancestry groups in well-designed analyses,” geneticist and neuroscientist Joel Gelernter of Yale University tells,

Although scientists have conducted similar genome-wide association studies (GWAS) in the past, Liu tells New Scientist that the majority of those surveys were conducted primarily on people of European descent. Although social situations and policies may influence a person’s inclination towards smoking and drinking, there is substantial evidence that a person’s genetic makeup may also predispose them towards and tobacco usage.

  • We’re at a stage where genetic discoveries are being translated into clinical,” Liu tells,
  • If we can forecast someone ‘ s risk of developing nicotine or alcohol dependence using this information, we can intervene early and potentially prevent a lot of deaths.” Liu collaborated with more than a hundred other scientists to evaluate the millions of genomic datasets, employing machine learning techniques to link genetic variants to smoking and drinking–related factors.

These factors ranged from the age at which a person began the habit to how many cigarettes or drinks they had per day or week or how likely they were to give up the habit. The analyses uncovered nearly 2,500 genetic variants linked to regular smoking, as well as an additional 243 variants linked to how many cigarettes a person smokes per day, 206 linked to whether a person gave up smoking, and 39 linked to the age a person started the habit.

Meanwhile, 849 variants were associated with how much alcohol a person drank per week. In all, nearly 4,000 alcohol and tobacco use–associated variants were identified, some of which were found in genes that are associated with the secretion and regulation of the hormone dopamine, New Scientist reports.

Intriguingly, 721 of the total variants were only found as a result of the multi-ancestry testing, Nature reports. Liu tells the publication that most of these variants had similar effects across all ancestries, although risk scores generated only for those of European ancestry were not good predictors of risk for other ancestry groups.

  1. It is promising to see that the same genes are associated with addictive behaviors across ancestries,” Liu states in the press release.
  2. Having more robust and diverse data will help us develop predictive risk factor tools that can be applied to all populations.” Despite being the largest genetic study of tobacco and alcohol use thus far, experts say there is still room for improvement.

Ananyo Choudhury, a geneticist at the University of the Witwatersrand in Johannesburg, South Africa, tells Nature that the similar effects seen across ancestries could be a result of most of the study subjects living in the United States. Other experts add that incorporating analyses of more international populations would improve the study’s outcome, the publication reports.

How genetics play a role in addiction?

Genes matter in addiction Feature

June 2008, Vol 39, No.6Print version: page 142 min read

At least half of a person’s susceptibility to drug addiction can be linked to genetic factors. Presenters at an April 8 congressional hearing outlined new research on the genetic basis for addiction and recommended ways to incorporate those findings into treatment.

The hearing was organized by APA’s Science Government Relations Office. Researchers first need to overcome public misunderstanding and distrust regarding genetic testing. That means physicians and the public need to better understand the interactions between genetics and addiction, said Alexandra Shields, PhD, director of the Harvard University/Massachusetts General Hospital Center on Genomics, Vulnerable Populations and Health Disparities.

According to a national survey, only 5 percent of primary-care physicians feel confident in their ability to interpret genetic tests, and only 4 percent would feel confident suggesting treatment based on genetics. There are very good reasons for physicians to pay attention to the impact advances in genetic testing are likely to have on their ability to treat patients, said Nora Volkow, MD, director of the National Institute on Drug Abuse.

Understanding the complex interactions between the factors involved in drug abuse and addiction is critical to their effective prevention and treatment,” she said. With new data quickly piling up, physicians might soon be able to incorporate genetic tests in their practice, allowing them to better match specific treatments to individuals.

For example, Volkow explained that the number of a certain type of dopamine receptor, known as D2, might someday be used to predict whether someone will become addicted to alcohol, cocaine and heroin. Brain imaging suggests that people with fewer D2 receptors are more likely to become addicted than those with many of the receptors-and how many of these receptors people have is, in part, genetically determined.

  1. Of course, environmental factors also play a role, so propensity isn’t destiny, Volkow added.
  2. First a person has to experiment with drugs, then he or she has to repeatedly use them.
  3. At that point, genetic vulnerability helps determine who winds up addicted.
  4. When it comes to tobacco, genetics account for about 75 percent of a person’s inclination to begin smoking, said University of Pennsylvania psychologist Caryn Lerman, PhD.

Genes also account for 60 percent of the tendency to become addicted and 54 percent of one’s ability to quit. Because not all smokers are created equal, it’s possible to look at genetic factors to determine the best way to quit. The genetically determined speed at which the body can metabolize nicotine, for example, makes a difference as to whether a nicotine patch or a nicotine nasal spray will work better long term.

What genes are associated with alcoholism?

Can Alcoholism Skip a Generation? – There are many genes, and variations of genes, that impact a person’s risk of developing an alcohol use disorder.7 There is no one “alcohol gene” that leads to the development of an alcohol use disorder.7,8 Researchers have found more than 400 locations in all the genetic information in an organism (genome) and at least 566 variants within these locations that could influence the extent that someone may suffer from alcohol abuse.9 Genes that relate to alcohol metabolism, particularly ADH1B and ALDH2, seem to be closest tied to the risk for problem drinking.7 A family history of alcohol use disorders may increase the risk of genetic predisposition to developing an alcohol use disorder, with risks heightened for parent-child transmission.8 Environmental factors also play a role in developing an alcohol use disorder when an individual has a family history of alcohol misuse.

What gene is responsible for addiction?

The A1 form (allele) of the dopamine receptor gene DRD2 is more common in people addicted to alcohol, cocaine, and opioids. The variation likely affects how drugs influence the reward pathway.

What gene makes alcohol euphoric?

Context Innate differences in opioid neurotransmission are hypothesized to influence abuse liability of alcohol. In humans, a variant of the μ-opioid receptor gene ( OPRM1A118G ) increases receptor affinity, alcohol-induced euphoria, and risk for alcohol use disorders.

Objective To determine whether a variant in the μ-opioid receptor gene ( OPRM1C77G ) that increases affinity of the receptor is associated with alcohol response and consumption in macaques. Design Young adult rhesus macaques ( Macaca mulatta ) were intravenously administered 2.0 to 2.1 g of ethanol per kilogram of body weight and assessed for alcohol response.

Animals were later given simultaneous access to an aspartame-sweetened 8.4% (vol/vol) ethanol solution and a vehicle for 1 hour per day, 5 days a week, for a period of 6 weeks. Animals (N = 82) were genotyped for the OPRM1C77G polymorphism; the effects of the genotype on alcohol response and consumption were determined by analysis of variance, with sex included as a nominal independent variable.

Main Outcome Measures Alcohol response (ataxia, stimulation, and sedation), average alcohol consumption, the percentage of days during which an animal consumed alcohol at a level sufficient to produce intoxication (≥0.67 g of alcohol per kilogram of body weight), and alcohol preference (calculated as 100 × ).

Results Increased alcohol-induced stimulation was observed among male macaques carrying the OPRM1C77G allele. OPRM1C77G allele carriers consumed more ethanol and exhibited increased ethanol preference. Male carriers of the OPRM1C77G allele exhibited higher alcohol preference and consumption, and drank to intoxication more frequently than did C/C males.

  • Conclusions These findings demonstrate that the rhesus macaques’ equivalent of the OPRM1A118G variant is associated with increased alcohol response, consumption, and preference.
  • Our results reveal effects of the OPRM1C77G genotype to be male-restricted or more marked among male macaques.
  • This is of interest, given the fact that early-onset type II alcoholism is more common among men and that, among addicted individuals, men are more responsive to μ-opioid receptor blockade.

Endogenous opioid peptides mediate natural rewards as well as ethanol-induced positive reinforcement (ie, psychomotor stimulation and euphoria).1 – 3 The exact mechanism for these actions remains to be determined but may involve both dopamine-dependent and dopamine-independent mechanisms.

In experimental animals, activation of μ-opioid receptors in the ventral tegmental area activates dopamine neurons by releasing them from tonic inhibition by γ-aminobutyric acid interneurons 4, 5 ; alcohol activates dopamine release in the ventral tegmental area in a manner sensitive to blockade of μ receptors.6 In addition, direct opioid inputs to the nucleus accumbens are capable of producing psychomotor stimulation in a dopamine-independent manner, 7, 8 likely contributing to positive reinforcement of alcohol actions.

As predicted by the mechanisms outlined, blockade of opioid signaling results in suppression of alcohol consumption in several animal models with alcohol dependence.9 Among the 3 cloned opioid receptors, the μ subtype is likely key to opioid-mediated ethanol reinforcement.

This interpretation is consistent with the lack of ethanol self-administration in the null mutants of the μ-opioid receptor gene ( Oprm1 ).10, 11 Blockade of μ-opioid receptors decreases ethanol drinking in nonselected Wistar rats.12, 13 μ-Antagonism also appears to be effective in suppressing the pharmacologically significant elevations in ethanol consumption that are demonstrated in animal models of alcoholism based on genetic selection.

This reduction appears to be unrelated to effects on ethanol palatability and, therefore, presumably reflects direct attenuation of alcohol’s reinforcing actions.14 – 16 Supporting a role of endogenous opioids in addiction vulnerability, altered function of endogenous opioid systems has been demonstrated in several ethanol-preferring lines.17, 18 Numerous studies have demonstrated an efficacy of the opioid receptor antagonist naltrexone in clinical treatment of alcohol dependence.19 – 21 Despite 1 large negative trial, 22 meta-analyses support naltrexone efficacy on several drinking variables.23, 24 Family history of alcohol dependence has been reported as a predictor of therapeutic response to naltrexone.25, 26 Together these findings point to an intriguing possibility that the modest overall effect size of naltrexone in treatment of alcohol dependence reflects heterogeneity in patient responses and may be considerably improved in appropriately selected patient populations.

Data demonstrating that family history of alcoholism is a predictor of naltrexone response are converging with recent findings that suggest that the role of opioid signaling in ethanol reward, as well as alcoholism treatment response, is linked to genetic factors. For instance, laboratory drinking studies have shown that subjects with a genetic risk for alcoholism experience increased ethanol-induced euphoria, which is selectively sensitive to naltrexone.

Subjects at low genetic risk have a diminished euphorigenic ethanol response, and, consequently, naltrexone is shown to have an effect in blocking ethanol-induced euphoria in this group.27 Several polymorphisms exist in the human μ-opioid receptor gene ( OPRM1 ).

  1. One of these, A118G, is a functional nonsynonymous single nucleotide polymorphism ( ASN40ASP ); in vitro studies have demonstrated that this polymorphism confers a 3-fold increase in the affinity of the μ-opioid receptor for β-endorphin.
  2. The functional importance of this variant in vivo is supported by the data indicating that carriers of the OPRM1118G allele have significantly elevated pain thresholds and also experience increased euphoria (subjective high) following consumption of alcohol.28, 29 The latter leads to the prediction that OPRM1118G carriers may be more susceptible to developing alcohol dependence.

Although results are mixed, 30, 31 several studies have linked the OPRM1118G allele to alcohol dependence.32, 33 More importantly, recent data suggest that, among alcohol-dependent individuals, carrying the OPRM1118G allele predicts a therapeutic response to naltrexone.34 This observation potentially links the previously established role of family history in alcoholism vulnerability, enhanced alcohol-induced euphoria, and naltrexone response.

Specifically, it may be that increased positive reinforcement response to alcohol mediated by the OPRM1118G allele of OPRM1 could be a heritable factor that increases susceptibility to both initiation and maintenance of alcohol dependence. Because of this, reversal of enhanced alcohol reinforcement by naltrexone might provide a particular therapeutic benefit in this group.

The role of the OPRM1A118G single nucleotide polymorphism cannot be addressed experimentally in rodents, but rhesus macaques ( Macaca mulatta ) may offer an opportunity to do so. In rhesus macaques, there is a single nucleotide polymorphism ( OPRM1C77G ) that causes an amino acid change ( ARG26PRO ) in the N-terminal arm of the μ-opioid receptor, conferring a 3.5-fold increase in the affinity for β-endorphin.35 We therefore wanted to address the hypothesis emerging from the human studies that predicts that the OPRM1C77G polymorphism would be associated with enhanced alcohol stimulation and, therefore, consumption, in rhesus macaques.

It has previously been reported that early life stress in the form of peer rearing leads to elevated alcohol consumption in rhesus macaques 36 and that rearing history and sex interact with a functional variant in the serotonin transporter–linked polymorphic region ( 5 – HTTLPR ) to modulate alcohol intake.37 Therefore, sex and rearing history were included in the analyses to evaluate whether they modified potential effects of the OPRM1C77G genotype.

See also:  How Long Does Alcohol Stays In The Blood?

As the OPRM1A118G polymorphism and naltrexone treatment influence the frequency of alcohol consumption, we also wanted to determine whether carriers of the OPRM1C77G allele more frequently consumed alcohol to intoxication. Finally, endogenous opioids are known to influence feeding behavior and, in particular, increase preference for sweet solutions.38, 39 To exclude the potential confound of altered ethanol palatability, we determined preference for the 8.4% (vol/vol) alcohol solution over the sweetened vehicle.

Study animals were 82 young adult rhesus macaques obtained from 6 birth-year cohorts, ranging in age from 2.8 to 4.5 years (mean ± SD, 3.8 ± 0.4 years) at the initiation of the alcohol self-administration study. The sample size for each dependent measure, broken down by sex and genotype, is indicated in each respective figure ( Figures 1, 2, 3, and 4 ).

Animals were socially housed in sex-limited, age-matched groups and were tested within their respective social groups in runs at the National Institutes of Health Animal Center. The animals’ weights ranged from 4.1 to 9.3 kg (mean ± SD, 6.2 ± 0.15 kg).

  • Protocols for the use of experimental animals were approved by the Institutional Animal Care and Use Committee of the National Institute on Alcohol Abuse and Alcoholism.
  • To assess ethanol sensitivity, each animal was removed from its home cage and restrained on a flat surface while ethanol (16.8%, United States Pharmacopeia) was infused into the saphenous vein (males, 2.1 g/kg of body weight; females, 2.0 g/kg of body weight) at a constant rate for 15 minutes.

The rationale for administering a higher dose to males is that, as in humans, rhesus males have less body fat than females and have been shown to require more alcohol per kilogram of body weight to produce identical blood alcohol concentrations.40, 41 Doses were based on pilot data showing that with a dose of 1.0 g of alcohol per kilogram of body weight, a small number of monkeys showed no evidence of intoxication, and with a dose of 3.0 g of alcohol per kilogram of body weight, some animals became unconscious.

Pilot data also supported our theory that females required a lower dose than males did, with the differential dosing producing identical blood ethanol contents (BECs). Each animal went through 2 separate alcohol infusion and behavioral testing sessions so that averages could be taken. At 5, 10, and 60 minutes following initiation of the infusion, blood samples were obtained from the femoral vein for assessment of BEC; BECs were quantified enzymatically using a commercial kit (Sigma-Aldrich Corp, St Louis, Mo).

Assessment of ethanol sensitivity Following the intravenous ethanol infusions, animals were placed in a testing room for 30 minutes. Because there was a potential for severely ataxic animals to injure themselves, the floor was cushioned with 30 to 45 cm of wood shavings.

  1. Each subject’s general motor behavior was scored for 30 minutes by experienced investigators (blind to each subject’s genotype) who observed the subject through a 1-way viewing window.
  2. Scored behaviors included locomotion, passivity, stumbling, falling, hitting a wall, swaying, unsuccessful jumping, and successful jumping.

Locomotion and passivity were recorded as seconds in duration, while the remaining behaviors were recorded as frequencies. Descriptions of the objectively defined behaviors are as follows:

  • Locomotion: any directed movement across the substrate, either vertical or horizontal.
  • Passivity: absence of directed movement.
  • Stumbling: when the animal loses balance and appears to trip over its own feet or lose its footing while moving.
  • Falling: any time the animal involuntarily drops from a higher to a lower area of the substrate, either while moving or while stationary; or when the animal loses balance and involuntarily topples over and drops to the floor or shelf (depending on where the animal is located), either while moving or while stationary.
  • Hitting a wall: when the animal’s body hits the sides of the Plexiglas box while attempting to escape or the inside wall of the animal room while moving or while stationary.
  • Swaying: each time the animal’s body veers in any direction (forward, back, left, or right) out of a controlled, upright posture, either while passive or while moving.
  • Unsuccessful jumping: when an animal falls down or misses its target when attempting a leap either vertically or horizontally across the substrate. This behavior is mutually exclusive with falling,
  • Successful jumping: when an animal leaps either vertically or horizontally across the substrate.

After a period of at least 1 month, animals were allowed to freely consume an aspartame-sweetened 8.4% (vol/vol) alcohol solution for 1 hour per day, 5 days a week in their home cages.42 This standardized method consisted of 3 phases:

  1. Spout training. The animals were trained for 1 hour per day during a 1-week period to drink from nipple-like spouts dispensing aspartame-sweetened water. This phase lasted 5 days, during which all animals consumed more than 50 mL of the vehicle.
  2. Initial alcohol exposure. This phase was designed to ensure that all animals experienced the pharmacological effects of alcohol before beginning the experimental phase of the study. To begin this phase, the color of the sweetened vehicle was changed, and alcohol was added to the vehicle to produce an 8.4% (vol/vol) alcohol solution. During the initial alcohol exposure phase, animals were given free access to the alcohol solution for 1 hour per day. Each of the animals included in this phase of the study fulfilled a pre-established criterion of consuming more than 0.67 g of the ethanol solution per kilogram of body weight per hour (a dose shown to produce signs of intoxication in rhesus macaques) on 2 or more occasions. Once all animals met the criterion, both nonalcoholic and 8.4% (vol/vol) alcoholic aspartame-sweetened solutions were available (in addition to normal drinking water) for 1 hour per day. No special methods, such as deprivation of food or water, were used to induce ethanol consumption; animals established stable consumption patterns within 2 weeks.
  3. Experimental period. During the 6-week experimental phase, alcohol and the vehicle were dispensed 5 days a week (Monday-Friday) from 1 PM to 2 PM while the animals were in their home cage environment. Animals were fitted with a collar that was implanted with an identifier chip so that consumed volumes could be recorded for each individual. Although the vehicle was available for all cohorts tested, levels of consumption of the vehicle were recorded for only 2 of the testing cohorts.

Using standard extraction methods, DNA was isolated from whole blood, which was collected from the femoral vein under ketamine anesthesia (15 mg/kg of body weight, administered intramuscularly). Genotyping was performed using the procedure modified from the method reported by Miller et al.35 A portion of OPRM1 exon 1 was amplified from 25 ng of genomic DNA by flanking oligonucleotide primers museekr (5′-TCAGTACCATGGACAGCAGCGCTGTCCCCACGAA-3″) and museekr1 (5′-GTCGGACAGGTTGCCATCTAAGTG-3′) in 15-μL reactions using AmpliTaq Gold (Applied Biosystems, Foster City, Calif) and 2.5 mmol of magnesium chloride per liter, according to the manufacturers’ instructions (Invitrogen, Carlsbad, Calif). Amplifications were performed on a PerkinElmer 9700 thermocycler (PerkinElmer, Wellesley, Mass) with 1 cycle at 96°C, followed by 30 cycles at 94°C for 15 seconds, 56°C for 15 seconds, and 72°C for 30 seconds, and a final 3-minute extension at 72°C. Restriction digest by Fnu 4HI (New England Biolabs, Beverly, Mass) was then performed using 0.5 μL of polymerase chain reaction product in a total volume of 20 μL for 2 hours at 37°C. Samples were separated by electrophoresis on 10% polyacrylamide gels, and the OPRM177C and OPRM177G alleles were identified by direct visualization following ethidium bromide staining.35 For the behaviors scored during alcohol intoxication, factor analysis was performed to yield alcohol response factors to be used as dependent variables in analysis of variance (ANOVA). Scores for each behavior were expressed as the mean frequency or duration of the behavior for the 2 testing periods. Factor analysis was performed using principal components extraction and varimax rotation. To determine whether the OPRM1C77G genotype influenced alcohol response, we performed ANOVA using rotated orthogonal factor scores as dependent variables. Analysis of variance was also performed to assess the effects of the OPRM1C77G genotype on alcohol consumption and preference. Three-way ANOVA was conducted initially, with genotype, sex, and rearing included as independent variables. The rearing conditions have been described in detail in previous publications.37, 43, 44 Because rearing history did not yield a main effect or interact with sex or genotype on any of the dependent variables in our study, it was dropped from the analysis, and 2-way ANOVA with genotype and sex as independent variables was ultimately performed. The influences of these variables on alcohol consumption, the number of days during which an animal consumed alcohol at a level above 0.67 g/kg of body weight per hour, and alcohol preference were determined. Post hoc comparisons were performed using the Newman-Keuls test. Previous studies in our laboratory have demonstrated that alcohol consumption varies among testing cohorts. It is thought that this occurs as a result of specific social group dynamics or external disturbances that globally influence alcohol intake (eg, inclement weather, infectious disease, and procedures or social conflicts occurring in adjacent runs). Because ethanol consumption (grams per kilogram of body weight per hour) differed significantly among the testing cohorts used in this study, even after controlling for sex differences, a z score for alcohol consumption that controlled for cohort was generated to test the effects of OPRM1C77G on ethanol intake. To determine alcohol preference in the 2 birth-year cohorts in which vehicle consumption was recorded, average volumes of alcoholic and nonalcoholic (sweetened vehicle) solutions consumed during the course of the drinking study were calculated as 100 ×, The average identity by descent for the animals included in the study was 1.45%. This indicates that 2 randomly selected macaques would share only 1.45% of their genes by descent (approximately equivalent to a degree of relationship that is observed between second cousins once removed and third cousins). This demonstrates that most pairs of individuals have a low degree of relationship, approximating the relationship observed in some human study populations. Because the identity by descent was sufficiently low, standard statistical procedures were applied for testing the association of OPRM1C77G with ethanol consumption.43 The frequency of the OPRM177G allele was 18%, and genotype frequencies did not deviate from the Hardy-Weinberg equilibrium (χ 2 = 0.23; P =,89). Because preliminary analyses demonstrated no difference in outcomes between G/G and C/G animals, these were collapsed into an OPRM177G allele carrier group for all the analyses performed. There were no OPRM1C77G frequency differences among the cohorts tested, nor were there any frequency differences according to sex or dominance rank, or between Chinese- and Indian-derived rhesus macaques (n = 8 and n = 74, respectively). The Kolmogorov-Smirnov test demonstrated that alcohol consumption data did not deviate from normality. All analyses were performed using StatView Statistical software (StatView, Cary, NC). The criterion for significance was set at P ≤.05. Factor analysis of alcohol sensitivity measures yielded 3 factors—disinhibition, stimulation, and ataxia—which together accounted for 74% of the variance ( Table ). There were no main effects of the OPRM1C77G genotype or of sex on stimulation factor scores (F 1,69 = 2.35, P =,13, and F 1,69 = 1.37, P =,25, respectively); however, there was a significant interaction between the 2 (F 1,69 = 5.25; P =,02) ( Figure 1 ). Post hoc testing demonstrated that this was attributable to male OPRM177G carriers exhibiting significantly higher stimulation scores than males homozygous for the OPRM177C allele ( P <.05). There were no main effects of sex or of the OPRM1C77G genotype, nor were there any interactions between the 2 for disinhibition or ataxia scores (data not shown). Because of the potential confound of variation in BECs or age to influence alcohol response, analyses were repeated including only 3- and 4-year-old animals with 10-minute BECs between 0.2% and 0.3%, but results remained the same (F 1,37 = 4.1; P <.05; data not shown). To rule out a pharmacokinetic effect of the OPRM1C77G polymorphism, repeated measures of ANOVA were also performed with sex and genotype as independent and BEC as the dependent variable. Follow-up ANOVA was performed at each time point, with body weight included as a continuous independent variable. There were no effects of OPRM1C77G nor were there any interactive effects of OPRM1C77G and sex on BECs ( Figure 1 ). There was a main effect of the OPRM1C77G genotype on alcohol consumption (F 1,78 = 4.62; P <.04), with carriers of the OPRM177G allele consuming more ethanol than C/C animals ( Figure 2 A). In addition, there was an interactive effect between genotype and sex (F 1,78 = 4.0; P ≤.05). Post hoc comparison demonstrated that male carriers of the OPRM177G allele consumed more ethanol than C/C males ( P <.05) ( Figure 2 A). When using z scores to statistically control for cohort effects, these effects remained and were strengthened. We observed a main effect of the OPRM1 gene variation (F 1,78 = 7.2; P =,009) but not of sex (F 1,78 = 0.49; P =,48), in addition to an interactive effect between the OPRM1 genotype and sex (F 1,78 = 7.4; P =,008). Post hoc comparisons demonstrated that male carriers of the OPRM1G allele consumed more alcohol than did all other groups of the study ( P <.05) ( Figure 2 B). There was a main effect of OPRM1C77G on alcohol preference (F 1,42 = 9.6; P <.008). Carriers of the OPRM177G allele exhibited increased alcohol preference compared with OPRM177C homozygotes ( P <.05) ( Figure 3 ). There was also a main effect of sex with a higher level of alcohol preference in males than in females (F 1,42 = 17.4; P =,008). Finally, the OPRM1 genotype and sex interacted to influence alcohol preference (F 1,42 = 4.2; P =,05). Post hoc comparisons demonstrated the effect of OPRM1C77G to be present among male but not female rhesus macaques; males that were carriers of the OPRM177G allele exhibited higher alcohol preference than did C/C males ( P <.01) ( Figure 3 ). There was a main effect of genotype on the number of study days during which an animal consumed an amount of ethanol that exceeded 0.67 g/kg of body weight per hour (F 1,78 = 4.4; P <.04) but not of sex (F 1,78 = 0.012; P =,92) ( Figure 4 ). OPRM177G allele carriers consumed alcohol to intoxication more frequently than did OPRM177C homozygotes. Similar to the other dependent variables considered, there was an interactive effect between OPRM1C77G and sex (F 1,78 = 4.2; P <.05), and post hoc comparison demonstrated that, among males, those carrying the OPRM177G allele consumed doses of alcohol sufficient to produce intoxication more frequently than did those homozygous for the OPRM177C allele ( P <.05) ( Figure 4 ). The human OPRM1118G allele confers increased affinity of the receptor for β-endorphin and has, therefore, been referred to as a gain-of-function polymorphism.45 Although recent findings of decreased allelic transcription efficiency of this variant suggest the possibility of a more complex picture, 46 human in vivo findings would seem to support the original proposal, because the OPRM1118G variant has been associated with elevated pain thresholds, 28 increases in both euphorigenic response to alcohol and susceptibility to alcohol use disorders in some populations, 29, 33 and a higher probability of treatment response to the opioid antagonist naltrexone.34, 47 However, human data are mostly limited to correlative studies. Available results from alcohol-challenge experiments are obtained at relatively low BECs because of ethical constraints. Furthermore, in human studies, complex conditioned effects may interact with direct pharmacological actions of alcohol to determine psychostimulant responses. Nonhuman primates therefore offer an attractive model system to evaluate the functional role of the OPRM1 genetic variation for alcohol responses and alcohol preference. We found that an OPRM1 variant in rhesus macaques that has similar functional effects in vitro to the human 118G allele increased ethanol-induced psychomotor stimulation, a commonly used marker of euphorigenic and positively reinforced alcohol actions.48 This effect was behaviorally selective, in that ethanol-induced ataxia and disinhibition were not affected by genotype. The effect was only observed in males carrying the OPRM177G allele, and, congruent with the alcohol-challenge data, our alcohol consumption and preference data support the notion that positively reinforcing effects of alcohol are more pronounced in male OPRM177G carriers. Male carriers of the OPRM177G allele consumed more alcohol under free-choice limited-access conditions, consumed it more frequently, and exhibited increased preference for the alcohol solution over the sweetened vehicle. In humans, it was originally reported that attenuated, rather than elevated, alcohol responses are characteristic of family history–positive subjects, 49 in addition to being associated with increased risk for later developing alcoholism.50 Subsequent work in family history–positive subjects, however, demonstrated that attenuated responses are primarily seen during late stages, while increased stimulation is observed among the same subjects during the early phases of alcohol exposure.51 Based on these findings, a differentiator model has been proposed, according to which, family history–positive individuals are motivated to drink because they exhibit both greater initial responses and greater acute tolerance to alcohol 52 ; our data appear to be in agreement with this model. Modulation of alcohol reinforcement by genetic variation at the OPRM1 locus in humans may relate to μ-opioid receptor control of hypothalamic-pituitary-adrenal axis responses. Suppression of alcohol self-administration and craving by naltrexone is accompanied by activation of the hypothalamic-pituitary-adrenal axis, 53 and the human OPRM1118G variant confers an elevated adrenocorticotropic hormone response to naltrexone.54 We and others have found that the OPRM177G allele is associated with differences in hypothalamic-pituitary-adrenal axis output in rhesus macaques under a variety of testing conditions, 36 including following alcohol challenge (C.S.B., unpublished data, 2006). In our study, macaques were given limited access to alcohol in social groups. Alcohol intake under these conditions is lower than in animals tested in isolation or in continuous access paradigms. This is in part because of competition for access to alcohol dispensers but (presumably) also because of the social pressures that come with being housed in an enclosure containing a troop of animals and the possible repercussions of becoming intoxicated in that setting. The fact that we did not observe an effect of rearing history on alcohol consumption in this data set may also be partially attributed to the application of these testing conditions; peer-reared monkeys are not only lower in social rank, potentially minimizing their access to the alcohol dispensers, but also tend to be more stress reactive and anxious.37, 43 On average, animals tested in our social groups consumed only 0.3 g of alcohol per kilogram of body weight per hour. However, male carriers of the OPRM177G allele exhibited average levels of consumption that were almost twice that amount. This rate of alcohol consumption, though still considerably lower than that seen in alcohol-dependent animals that have had access to alcohol for years, 55 is pharmacologically active, as shown by its ability to produce signs of intoxication in rhesus macaques in our colony (J.D.H., unpublished data, 1998). Consumption at this level is, therefore, likely to occur at least in part because of the reinforcing pharmacological properties of alcohol, rather than because of its taste or caloric content alone. This is further supported by the observation that, opposite to the consumption of alcohol, intake of the sweetened vehicle solution was somewhat diminished in male carriers of the OPRM177G allele. Moreover, these subjects consumed alcohol to intoxication on almost 30% of testing days, whereas animals in the other groups did so on only 8% of testing days. This parallels data indicating that the human OPRM1118G allele is associated with an increase in the number of days during which alcohol-dependent subjects consume alcohol 34 and that, conversely, blockade of μ-opioid receptors with naltrexone results in a decreased frequency of heavy alcohol consumption.23 Although the observed effects of the OPRM177G allele on alcohol intake appears to be attributable to potentiated alcohol reinforcement, it is noteworthy that altered nociception may potentially contribute to the drinking phenotype. Carriers of the human OPRM1118G variant are more resistant to pain.28 If the same is true in the macaque, it might render OPRM177G carriers less avoidant of aggressive encounters in a social setting and thus more likely to gain and retain access to the alcohol dispensers during social drinking sessions. Potentially related to this point, the OPRM177G allele is also associated with increased alcohol-induced aggression in our colony (C.S.B., unpublished data, 2005) and has been associated with aggression in another colony of rhesus macaques, even in the absence of alcohol exposure.35 It remains to be established whether the observed increased aggression, increased alcohol intake, and altered pain sensitivity are interrelated. However, neither altered nociception nor generally altered motivation for consummatory behavior are in our opinion likely to directly account for the increased alcohol consumption in OPRM177G carriers observed in our study, because, contrary to the alcoholic fluid intake, consumption of the sweetened vehicle was, if anything, decreased. The male-restricted influence of the OPRM177G variant is of particular interest. Alcohol dependence is clinically and genetically heterogeneous. A distinct form characterized by a family history of alcoholism, an early onset of alcohol problems, and a psychostimulant-like response to alcohol is predominantly found in men.56 The relevance of this heterogeneity has recently been validated by the demonstration of differential treatment response to the 5-HT 3 antagonist ondansetron, which has beneficial effects exclusively in early-onset subjects.57 In a suggestive parallel, a growing body of evidence suggests that the role of opioid transmission for alcohol-related phenotypes is sex-restricted both in rodents and humans. Studies in mice have shown a sexual dichotomy with regard to the influence of Oprm1 knockout on alcohol consumption 11 ; alcohol-dependent human subjects who are either men or who are carriers of the OPRM1118G allele are more responsive to μ-opioid receptor blockade.34, 47 Our findings are in agreement with these observations. A possible conclusion is that in one population of men, in particular those with an early onset of alcohol problems and a positive family history, alcohol intake is more likely to be driven by the positively reinforcing effects of alcohol (reward craving), while in late-onset men and a majority of women, alcohol intake may be more often affected by negative reinforcement of alcohol (relief craving).58 In this study, we employed function-guided association with the coding nonsynonymous single nucleotide polymorphism ( OPRM1C77G ) rather than identifying and genotyping additional markers in the OPRM1 locus and applying a haplotype-based approach in relating behavior to genetic variation. This decision was based on 2 considerations. First, the OPRM1C77G marker has been demonstrated to be functional and alter OPRM1 binding.35 This prompts specific testable hypotheses about its consequences at a systems level, which merit evaluation. Second, the number of animals tested under uniform conditions and available for sequence analysis gave us insufficient power for a haplotype-based approach. Future analyses may therefore reveal additional coding variants or other functionally important variants in noncoding regions that are in linkage disequilibrium with the OPRM1C77G polymorphism and may contribute to the observed phenotype. Although the pathway to alcoholism is influenced by many factors, repeated exposures to alcohol constitute a minimum requirement for the pathogenesis of this condition. We have found that a variant of the μ-opioid receptor gene ( OPRM1C77G ) is associated with increased sensitivity to the psychomotor stimulant properties of alcohol and influences early patterns of alcohol consumption in rhesus macaques. Male carriers of the variant allele exhibit increased alcohol preference and consume alcohol to intoxication more frequently. Our data support and extend emerging human literature that suggest that genetic variability at the OPRM1 locus modulates alcohol reinforcement and preference, that these effects are moderated by sex, and that μ-opioid transmission primarily influences susceptibility for alcohol use and treatment responses in males. Correspondence: Christina Barr, VMD, PhD, Laboratory of Clinical and Translational Studies, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, National Institutes of Health Animal Center, PO Box 529, Poolesville, MD 20837 ( [email protected] ). Submitted for Publication: April 4, 2006; final revision received July 14, 2006; accepted July 14, 2006. Financial Disclosure: None reported. Funding/Support: Supported by the National Institute of Child Health & Human Development and National Institute on Alcohol Abuse and Alcoholism Intramural Research Programs. Previous Presentation: This paper was presented as a poster at the Research Society on Alcoholism meeting in Santa Barbara, Calif, on June 26, 2005. Acknowledgment: The authors would like to acknowledge Amelia Chapelle, BA, Sue Higley, BA, Kelli Chisholm, BA, Courtney Shannon, BA, Ruth Woodward, DVM, Michelle Keawphalouk, BS, and Clarissa Parker, BA, for their support of this research.2. Kranzler HRAnton RF Implications of recent neuropsychopharmacologic research for understanding the etiology and development of alcoholism. J Consult Clin Psychol 1994;621116- 1126 PubMed Google Scholar Crossref 4. Spanagel RHerz AShippenberg TS Opposing tonically active endogenous opioid systems modulate the mesolimbic dopaminergic pathway. Proc Natl Acad Sci U S A 1992;892046- 2050 PubMed Google Scholar Crossref 5. Johnson SWNorth RA Opioids excite dopamine neurons by hyperpolarization of local interneurons. J Neurosci 1992;12483- 488 PubMed Google Scholar 6. 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What mental disorders cause alcoholism?

Ramesh Shivani, M.D., R. Jeffrey Goldsmith, M.D., and Robert M. Anthenelli, M.D. – Ramesh Shivani, M.D., is an addiction psychiatry fellow; R. Jeffrey Goldsmith, M.D., is a clinical professor of psychiatry at and director of the Addiction Fellowships Program; and Robert M. Anthenelli, M.D., is an associate professor of psychiatry and director of the Addiction Psychiatry Division and of the Substance Dependence Program; all three at the University of Cincinnati College of Medicine, Cincinnati Veterans’ Affairs Medical Center, Cincinnati, Ohio.

Clinicians working with alcohol–abusing or alcohol–dependent patients sometimes face a difficult task assessing their patient’s psychiatric complaints because heavy drinking associated with alcoholism can coexist with, contribute to, or result from several different psychiatric syndromes.

In order to improve diagnostic accuracy, clinicians can follow an algorithm that distinguishes among alcohol–related psychiatric symptoms and signs, alcohol–induced psychiatric syndromes, and independent psychiatric disorders that are commonly associated with alcoholism. The patient’s gender, family history, and course of illness over time also should be considered to attain an accurate diagnosis.

Moreover, clinicians need to remain flexible with their working diagnoses and revise them as needed while monitoring abstinence from alcohol. Key words: AODD (alcohol and other drug dependence); diagnostic algorithm; diagnostic criteria; screening and diagnostic method for potential AODD; patient assessment; AODR (AOD related) mental disorder; behavioral and mental disorder; symptom; comorbidity; major depression; manic–depressive psychosis; personality disorder; anxiety; patient family history; medical history The evaluation of psychiatric complaints in patients with alcohol use disorders (i.e., alcohol abuse or dependence, which hereafter are collectively called alcoholism) can sometimes be challenging.

Heavy drinking associated with alcoholism can coexist with, contribute to, or result from several different psychiatric syndromes. As a result, alcoholism can complicate or mimic practically any psychiatric syndrome seen in the mental health setting, at times making it difficult to accurately diagnose the nature of the psychiatric complaints (Anthenelli 1997; Modesto–Lowe and Kranzler 1999).

When alcoholism and psychiatric disorders co–occur, patients are more likely to have difficulty maintaining abstinence, to attempt or commit suicide, and to utilize mental health services (Helzer and Przybeck 1988; Kessler et al.1997). Thus, a thorough evaluation of psychiatric complaints in alcoholic patients is important to reduce illness severity in these individuals.

  1. This article presents an overview of the common diagnostic difficulties associated with the comorbidity of alcoholism and other psychiatric disorders.
  2. It then briefly reviews the relationship between alcoholism and several psychiatric disorders that commonly co–occur with alcoholism and which clinicians should consider in their differential diagnosis.

The article also provides some general guidelines to help clinicians meet the challenges encountered in the psychiatric assessment of alcoholic clients. DIAGNOSTIC DIFFICULTIES IN ASSESSING PSYCHIATRIC COMPLAINTS IN ALCOHOLIC PATIENTS A Case Example A 50–year–old man presents to the emergency room complaining: “I’m going to end it all,

Life’s just not worth living.” The clinician elicits an approximate 1–week history of depressed mood, feelings of guilt, and occasional suicidal ideas that have grown in intensity since the man’s wife left him the previous day. The client denies difficulty sleeping, poor concentration, or any changes in his appetite or weight prior to his wife’s departure.

He appears unshaven and slightly unkempt, but states that he was able to go to work and function on the job until his wife left. The scent of alcohol is present on the man’s breath. When queried about this, he admits to having “a few drinks to ease the pain” earlier that morning, but does not expand on this theme.

He seeks help for his low mood and demoralization, acknowledging later in the interview that “I really don’t want to kill myself; I just want my life back to the way it used to be.” The above case is a composite of many clinical examples observed across mental health settings each day, illustrating the challenges clinicians face when evaluating psychiatric complaints in alcoholic patients.

The questions facing the clinician in this example include:

Is the patient clinically depressed in the sense that he has a major depressive episode requiring aggressive pharmacological and psychosocial treatment? What role, if any, is alcohol playing in the patient’s complaints? How does one tease out whether drinking is the cause of the man’s mood problems or the result of them? If the man’s condition is not a major depression, what is it, what is its likely course, and how can it be treated?

As is usually the case (Anthenelli 1997; Helzer and Przybeck 1988), the patient in this example does not volunteer his alcohol abuse history but comes to the hospital for help with his psychological distress. The acute stressor leading to the distress is his wife’s leaving him; only further probing during the interview uncovers that the reason for the wife’s action is the man’s excessive drinking and the effects it has had on their relationship and family.

  1. Thus, a clinician who lacks adequate training in this area or who carries too low a level of suspicion of alcohol’s influence on psychiatric complaints may not consider alcohol misuse as a contributing or causative factor for the patient’s psychological problems.
  2. In general, it is helpful to consider psychiatric complaints observed in the context of heavy drinking as falling into one of three categories—alcohol–related symptoms and signs, alcohol–induced psychiatric syndromes, and independent psychiatric disorders that co–occur with alcoholism.

These three categories are discussed in the following sections. Alcohol–Related Psychiatric Symptoms and Signs Heavy alcohol use directly affects brain function and alters various brain chemical (i.e., neurotransmitter) and hormonal systems known to be involved in the development of many common mental disorders (e.g., mood and anxiety disorders) (Koob 2000).

  1. Thus, it is not surprising that alcoholism can manifest itself in a broad range of psychiatric symptoms and signs.
  2. The term “symptoms” refers to the subjective complaints a patient describes, such as sadness or difficulty concentrating, whereas the term “signs” refers to objective phenomena the clinician directly observes, such as fidgeting or crying.) In fact, such psychiatric complaints often are the first problems for which an alcoholic patient seeks help (Anthenelli and Schuckit 1993; Helzer and Przybeck 1988).

The patient’s symptoms and signs may vary in severity depending upon the amounts of alcohol used, how long it was used, and how recently it was used, as well as on the patient’s individual vulnerability to experiencing psychiatric symptoms in the setting of excessive alcohol consumption (Anthenelli and Schuckit 1993; Anthenelli 1997).

For example, during acute intoxication, smaller amounts of alcohol may produce euphoria, whereas larger amounts may be associated with more dramatic changes in mood, such as sadness, irritability, and nervousness. Alcohol’s disinhibiting properties may also impair judgment and unleash aggressive, antisocial behaviors that may mimic certain externalizing disorders, such as antisocial personality disorder (ASPD) (Moeller et al.1998).

(Externalizing disorders are discussed in the section “ASPD and Other Externalizing Disorders.”) Psychiatric symptoms and signs also may vary depending on when the patient last used alcohol (i.e., whether he or she is experiencing acute intoxication, acute withdrawal, or protracted withdrawal) and when the assessment of the psychiatric complaints occurs.

For instance, an alcohol–dependent patient who appears morbidly depressed when acutely intoxicated may appear anxious and panicky when acutely withdrawing from the drug (Anthenelli and Schuckit 1993; Anthenelli 1997). In addition to the direct pharmacological effects of alcohol on brain function, psychosocial stressors that commonly occur in heavy–drinking alcoholic patients (e.g., legal, financial, or interpersonal problems) may indirectly contribute to ongoing alcohol–related symptoms, such as sadness, despair, and anxiety (Anthenelli 1997; Anthenelli and Schuckit 1993).

Alcohol–Induced Psychiatric Syndromes It is clinically useful to distinguish between assorted commonly occurring, alcohol–induced psychiatric symptoms and signs on the one hand and frank alcohol–induced psychiatric syndromes on the other hand. A syndrome generally is defined as a constellation of symptoms and signs that coalesce in a predictable pattern in an individual over a discrete period of time.

Such syndromes largely correspond to the sets of diagnostic criteria used for classifying mental disorders throughout the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM–IV) (American Psychiatric Association 1994) and its successor, the DSM–IV Text Revision (DSM–IV–TR) (APA 2000).

Publication of the DSM–IV marked the first time that clinicians could specifically diagnose several “alcohol–induced disorders” rather than having to lump alcohol–related conditions under the more generic rubric of an “organic mental syndrome” (Anthenelli 1997).

Given the broad range of effects heavy drinking may have on psychological function, these alcohol–induced disorders span several categories of mental disorders, including mood, anxiety, psychotic, sleep, sexual, delirious, amnestic, and dementia disorders. According to the DSM–IV, the essential feature of all these alcohol–induced disorders is the presence of prominent and persistent symptoms, which are judged—based on their onset and course as well as on the patient’s history, physical exam, and laboratory findings—to be the result of the direct physiological effects of alcohol.

To be classified as alcohol–induced disorders, these conditions also must occur within 4 weeks of the last use of or withdrawal from alcohol and should be of clinical significance beyond what is expected from typical alcohol withdrawal or intoxication (APA 1994).

The diagnostic criteria of the DSM–IV and DSM–IV–TR do not clearly distinguish between alcohol–related psychiatric symptoms and signs and alcohol–induced psychiatric syndromes. Instead, these criteria sets state more broadly that any alcohol–related psychiatric complaint that fits the definition given in the paragraph above and which “warrants independent clinical attention” be labeled an alcohol–induced disorder (APA 1994, 2000).

In other words, alcohol–related psychiatric symptoms and signs can be labeled an alcohol–induced psychiatric disorder in DSM–IV or DSM–IV–TR without qualifying as syndromes. Alcohol–induced psychiatric disorders may initially be indistinguishable from the independent psychiatric disorders they mimic.

However, what differentiates these two groups of disorders is that alcohol–induced disorders typically improve on their own within several weeks of abstinence without requiring therapies beyond supportive care (Anthenelli and Schuckit 1993; Anthenelli 1997; Brown et al.1991, 1995). Thus, the course and prognosis of alcohol–induced psychiatric disorders are different from those of the independent major psychiatric disorders, which are discussed in the next section.

Alcoholism with Comorbid, Independent Psychiatric Disorders Alcoholism is also associated with several psychiatric disorders that develop independently of the alcoholism and may precede alcohol use and abuse. These independent disorders may make certain vulnerable patients more prone to developing alcohol–related problems (Helzer and Przybeck 1988; Kessler et al.1997; Schuckit et al.1997 b ).

One of the most common of these comorbid conditions is ASPD, an axis II personality disorder 1 ( 1 The DSM–IV classifies mental disorders along several levels, or axes. In this classification, axis II disorders include personality disorders, such as ASPD or obsessive–compulsive disorder, as well as mental retardation; axis I disorders include all other mental disorders, such as anxiety, eating, mood, psychotic, sleep, and drug–related disorders.) marked by a longstanding pattern of irresponsibility and violating the rights of others that generally predates the problems with alcohol.

Axis I disorders commonly associated with alcoholism include bipolar disorder, certain anxiety disorders (e.g., social phobia, panic disorder, and post–traumatic stress disorder ), schizophrenia, and major depression (Helzer and Przybeck 1988; Kessler et al.1997).

PSYCHIATRIC DISORDERS COMMONLY ASSOCIATED WITH ALCOHOLISM Independent Major Depression Mood disturbances (which frequently are not severe enough to qualify as “disorders”) are arguably the most common psychiatric complaint among treatment–seeking alcoholic patients, affecting upwards of 80 percent of alcoholics at some point in their drinking careers (Brown and Schuckit 1988; Anthenelli and Schuckit 1993). In keeping with the three broad categories described above into which such complaints may fall, mood problems may be characterized as one of the following:

An expected, time–limited consequence of alcohol’s depressant effects on the brain A more organized constellation of symptoms and signs (i.e., a syndrome) reflecting an alcohol–induced mood disorder with depressive features An independent major depressive disorder coexisting with or even predating alcoholism.

When one applies these more precise definitional criteria and classifies only those patients as depressive who meet the criteria for a syndrome of a major depressive episode, approximately 30 to 40 percent of alcoholics experience a comorbid depressive disorder (Anthenelli and Schuckit 1993; Schuckit et al.1997 a ).

  • Some controversy exists as to the precise cause–and–effect relationship between depression and alcoholism, with some authors pointing out that depressive episodes frequently predate the onset of alcoholism, especially in women (Kessler et al.1997; Helzer and Przybeck 1988; Hesselbrock et al.1985).
  • Several studies found that approximately 60 percent of alcoholics who experience a major depressive episode, especially men, meet the criteria for an alcohol–induced mood disorder with depressive features (Schuckit et al.1997 a ; Davidson 1995).

The remaining approximately 40 percent of alcoholic women and men who suffer a depressive episode likely have an independent major depressive disorder—that is, they experienced a major depressive episode before the onset of alcoholism or continue to exhibit depressive symptoms and signs even during lengthy periods of abstinence.

  1. In a study of 2,954 alcoholics, Schuckit and colleagues (1997 a ) found that patients with alcohol–induced depression appear to have different characteristics from patients with independent depressive disorders.
  2. For example, compared with patients with alcohol–induced depression, patients with independent depression were more likely to be Caucasian, married, and female; less experienced with other illicit drugs; less often treated for alcoholism; more likely to have a history of a prior suicide attempt; and more likely to have a family history of a major mood disorder.
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Bipolar Disorder According to two major epidemiological surveys conducted in the past 20 years (Helzer and Przybeck 1988; Kessler et al.1997), bipolar disorder (i.e., mania or manic–depressive illness) is the second–most common axis I disorder associated with alcohol dependence.2 ( 2 The axis I disorders most commonly associated with alcoholism are other drug use disorders.) Among manic patients, 50–60 percent abuse or become dependent on alcohol or other drugs (AODs) at some point in their illness (Brady and Sonne 1995).

Diagnosing bipolar disorder in alcoholic patients can be particularly challenging. Several factors, such as the underreporting of symptoms (particularly symptoms of mania), the complex effects of alcohol on mood states, and common features shared by both illnesses (e.g., excessive involvement in pleasurable activities with high potential for painful consequences) reduce diagnostic accuracy.

Bipolar patients are also likely to abuse drugs other than alcohol (e.g., stimulant drugs such as cocaine or methamphetamine), further complicating the diagnosis. As will be described in greater detail later, it can be helpful for an accurate diagnosis to obtain a careful history of the chronological order of both illnesses because approximately 60 percent of patients with both alcoholism and bipolar disorder started using AODs before the onset of affective episodes (Strakowski et al.2000).

  1. Anxiety Disorders Overall, anxiety disorders do not seem to occur at much higher rates among alcoholics than among the general population (Schuckit and Hesselbrock 1994).
  2. For example, results from the Epidemiologic Catchment Area survey indicated that among patients who met the lifetime diagnosis of alcohol abuse or dependence, 19.4 percent also carried a lifetime diagnosis of any anxiety disorder.

This corresponds to only about 1.5 times the rate for anxiety disorders in the general population (Regier et al.1990; Kranzler 1996). Specific anxiety disorders, such as panic disorder, social phobia, and PTSD, however, appear to have an increased co–occurrence with alcoholism (Schuckit et al.1997 b ; Kranzler 1996; Brady et al.1995).

As with alcohol–induced depression, it is important to differentiate alcohol–induced anxiety from an independent anxiety disorder. This can be achieved by examining the onset and course of the anxiety disorder. Thus, symptoms and signs of alcohol–induced anxiety disorders typically last for days to several weeks, tend to occur secondary to alcohol withdrawal, and typically resolve relatively quickly with abstinence and supportive treatments (Kranzler 1996; Brown et al.1991).

In contrast, independent anxiety disorders are characterized by symptoms that predate the onset of heavy drinking and which persist during extended sobriety. ASPD and Other Externalizing Disorders Among the axis II personality disorders, ASPD (and the related conduct disorder, which often occurs during childhood in people who subsequently will develop ASPD) has long been recognized to be closely associated with alcoholism (Lewis et al.1983).

  1. Epidemiologic analyses found that compared with nonalcoholics, alcohol–dependent men are 4–8 times more likely, and alcoholic women are 12–17 times more likely, to have comorbid ASPD (Helzer and Przybeck 1988; Kessler et al.1997).
  2. Thus, approximately 15 to 20 percent of alcoholic men and 10 percent of alcoholic women have comorbid ASPD, compared with 4 percent of men and approximately 0.8 percent of women in the general population.

Patients with ASPD are likely to develop alcohol dependence at an earlier age than their nonantisocial counterparts and are also more prone to having other drug use disorders (Cadoret et al.1984; Anthenelli et al.1994). In addition to ASPD, other conditions marked by an externalization of impulsive aggressive behaviors, such as attention deficit hyperactivity disorder (ADHD) (Sullivan and Rudnik–Levin 2001), are also associated with increased risk of alcohol–related problems.

(For more information on the relationship between alcoholism and ADHD, see the article by Smith and colleagues, pp.122–129.) A BASIC APPROACH TO DIAGNOSING PATIENTS WITH ALCOHOLISM AND COEXISTING PSYCHIATRIC COMPLAINTS Clinicians working in acute mental health settings often encounter patients who present with psychiatric complaints and heavy alcohol use.

The following sections discuss one approach to diagnosing these challenging patients (also see the figure).

Schematic representation of a diagnostic algorithm for evaluating psychiatric complaints in patients for whom alcoholism may be a contributing factor. The algorithm helps the clinician decide if the complaints represent alcohol–induced symptoms, or an alcohol–induced syndrome that will resolve with abstinence, or an independent psychiatric disorder that requires treatment. SOURCE: Anthenelli 1997.

Inquiring About Alcohol Use When Evaluating Psychiatric Complaints As illustrated by the case example described earlier, patients seldom volunteer information about their alcohol use patterns and problems when they present their psychiatric complaints (Helzer and Przybeck 1988; Anthenelli and Schuckit 1993; Anthenelli 1997).

  1. Unless they are asked directly about their alcohol use, the patients’ denial and minimization of their alcohol–related problems lead them to withhold this important information, which makes assessment and diagnosis difficult.
  2. In addition, heavy alcohol use can impair memory, which may make the patient’s information during history–taking less reliable.

Therefore, clinicians should gather information from several resources when assessing patients with possible alcohol–related problems, including collateral informants, the patient’s medical history, laboratory tests, and a thorough physical examination.

  • After obtaining a patient’s permission, his or her history should be obtained from both the patient and a collateral informant (e.g., a spouse, relative, or close friend).
  • The information these collateral informant interviews yield can serve several purposes.
  • First, by establishing how patterns of alcohol use relate to psychiatric symptoms and their time course, a clinician obtains additional information that can be used in the longitudinal evaluation of the patient’s psychiatric and alcohol problems, as described later.

Second, by defining the role alcohol use plays in a patient’s psychiatric complaints, the clinician is starting to confront the patient’s denial, which is the patient’s defense mechanism for avoiding conscious analysis of the association between drinking and other symptoms.

  • Third, by knowing that the clinician will be talking to a family member, the patient may be more likely to offer more accurate information.
  • Fourth, if the patient observes that the clinician is interested enough in the case to contact family members, this may help establish a more trustful therapeutic relationship.

Fifth, by involving family members early in the course of treatment, the clinician begins to lay the groundwork toward establishing a supporting network that will become an important part of the patient’s recovery program. Finally, the collateral informant can provide supplemental information about the family history of alcoholism and other psychiatric disorders that can improve diagnostic accuracy (Anthenelli 1997; Anthenelli and Schuckit 1993).

  1. A review of the patient’s medical records is another potentially rich source of information.
  2. This review should look for evidence of previous psychiatric complaints or of laboratory results that might further implicate alcohol in the patient’s psychiatric problems (Allen et al.2000).
  3. Pertinent laboratory results could include positive breath or blood alcohol tests; an elevation in biochemical markers of heavy drinking, such as the liver enzyme gamma–glutamyltransferase (GGT); and changes in the mean volume of the red blood cells (i.e., mean corpuscular volume), which also is an indicator of heavy drinking.

Laboratory tests, such as breathalyzer analyses or determination of blood alcohol concentrations, should also be performed to search for evidence of recent alcohol use that might aid in the assessment. These results also can provide indirect evidence of tolerance to alcohol (one of the diagnostic criteria of alcohol dependence) if the clinician documents relatively normal cognitive, behavioral, and psychomotor performance in the presence of blood alcohol concentrations that would render most people markedly impaired.

  1. Subsequent laboratory testing may also need to include other diagnostic procedures, such as brain imaging studies, to rule out indirect alcohol–related medical causes of the psychiatric complaints.
  2. For example, alcoholics suffering from head trauma might have hematomas (i.e., “blood blisters”) in the brain or other traumatic brain injuries that could cause psychiatric symptoms and signs (Anthenelli 1997).

Finally, all patients should undergo a complete physical examination. During this examination, the clinician should pay attention to physical manifestations of heavy alcohol use, such as an enlarged, tender liver. The combination of positive results on laboratory tests and physical examination points strongly to a diagnosis of alcohol abuse or dependence.

  1. This information can be used later on, when the physician presents his or her diagnosis to the patient and begins to confront the denial associated with the addiction (Anthenelli 1997).
  2. Differentiating Alcohol–Related Symptoms from Syndromic Mental Disorders If the clinician suspects a diagnosis of alcoholism is appropriate, the next step is to evaluate the psychiatric complaints in this context.

As mentioned earlier, alcohol produces its mind–altering and reinforcing effects by causing changes in the same neurotransmitter and receptor 3 ( 3 Receptors are protein molecules located on the surface of a cell that interact with extracellular signaling molecules, such as neurotransmitters and hormones, and convey that signal to the cell’s interior to induce the appropriate response.) systems that are associated with most major psychiatric disease states.

  • Partly as a result of these direct brain effects, heavy alcohol use causes psychiatric symptoms and signs that can mimic most major psychiatric disorders.
  • These changes occur both in the absence and presence of alcohol, and during the initial assessment the clinician should determine when in the patient’s drinking cycle (i.e., during intoxication, acute withdrawal, protracted withdrawal, or stable abstinence for at least 3 months) these complaints are occurring.

Because heavy alcohol use can cause psychological disturbances, patients who present with co–occurring psychiatric and alcohol problems often do not suffer from two independent disorders (i.e., do not require two independent diagnoses). Therefore, the clinician’s job is to combine the data obtained from the multiple resources cited in the previous section and to establish a working diagnosis.

  1. It may be helpful to begin this process by differentiating between alcohol–related symptoms and signs and alcohol–induced syndromes.
  2. Thus, the preferred definition of the term “diagnosis” here refers to a constellation of symptoms and signs, or a syndrome, with a generally predictable course and duration of illness as outlined by DSM–IV.

Although heavy, prolonged alcohol use can produce psychiatric symptoms or, in some patients, more severe and protracted alcohol–induced psychiatric syndromes, these alcohol–related conditions are likely to improve markedly with abstinence. This characteristic distinguishes them from the major independent psychiatric disorders they mimic.

Distinguishing Between Alcohol–Induced Syndromes and Independent Comorbid Disorders Even after determining that a patient’s constellation of symptoms and signs has reached syndromic levels and warrants a diagnosis of a mood, anxiety, or psychotic disorder, the possibility remains that the patient has an independent comorbid disorder that may require treatment rather than an alcohol–induced syndrome that resolves with abstinence.

Although some people experience more persistent alcohol–induced conditions (and some controversy remains over how to treat those patients), only clients with independent comorbid disorders should be labeled as having a dual diagnosis. One approach to distinguishing independent versus alcohol–induced diagnoses is to start by analyzing the chronology of development of symptom clusters (Schuckit and Monteiro 1988).

Using this technique as well as the DSM–IV guidelines, one can identify alcohol–induced disorders as those conditions in which several symptoms and signs occur simultaneously (i.e., cluster) and cause significant distress in the setting of heavy alcohol use or withdrawal (APA 1994). For example, a patient who exhibits psychiatric symptoms and signs only during recurrent alcohol use and after he or she has met the criteria for alcohol abuse or dependence is likely to have an alcohol–induced psychiatric condition.

In contrast, a patient who exhibits symptoms and signs of a psychiatric condition (e.g., bipolar disorder) in the absence of problematic AOD use most likely has an independent disorder that requires appropriate treatment. Establishing a timeline of the patient’s comorbid conditions (Anthenelli and Schuckit 1993; Anthenelli 1997), using collateral information from outside informants and the data obtained from the review of the medical records, may be helpful in determining the chronological course of the disorders.

In this context the clinician should focus on the age at which the patient first met the criteria for alcohol abuse or dependence rather than on the age when the patient first imbibed or became intoxicated. This strategy provides more specific information about the onset of problematic drinking that typically presages the onset of alcoholism (Schuckit et al.1995).

If the clinician cannot determine exactly the time point when the patient met the criteria for abuse or dependence, this information can be approximated by determining when the patient developed alcohol–related problems that interfered with his or her life in a major way and affected the ability to function.

Probing for such problems typically includes four areas— legal, occupational, and medical problems as well as social relationships. The age–at–onset of alcoholism then is estimated by establishing the first time that alcohol actually interfered in two or more of these major domains or the first time an individual received treatment for alcoholism.

Further questioning should address whether the patient ever developed tolerance to the effects of alcohol or suffered from signs and symptoms of withdrawal when he or she stopped using the drug, both of which are diagnostic criteria for alcohol dependence.

  1. After establishing the chronology of the alcohol problems, the patient’s psychiatric symptoms and signs are reviewed across the lifespan.
  2. The patient’s recollection of when these problems appeared can be improved by framing the interview around important landmarks in time (e.g., the year the patient graduated, her or his military discharge date, and so forth) and by the collateral information obtained.

This method not only ensures the most accurate chronological reconstruction of a patient’s problems, but also, on a therapeutic basis, helps the patient recognize the relationship between his or her AOD abuse and psychological problems. Thus, this approach begins to confront some of the mechanisms that help the patient deny these associations (Anthenelli and Schuckit 1993; Anthenelli 1997).

  1. While establishing this chronological history, it is important for the clinician to probe for any periods of stable abstinence that a patient may have had, noting how this period of sobriety affected the patient’s psychiatric problems.
  2. Using a somewhat conservative approach, such a probe should focus on periods of abstinence lasting at least 3 months because some mood, psychovegetative (e.g., altered energy levels and sleep disturbance), perceptual, and behavioral symptoms and signs related to AOD use can persist for some time.

By using this timeline approach, the clinician generally can arrive at a working diagnosis that helps to predict the most likely course of the patient’s condition and can begin putting together a treatment plan. Considering Other Patient Characteristics When evaluating the likelihood of a patient having an independent psychiatric disorder versus an alcohol–induced condition, it also may be helpful to consider other patient characteristics, such as gender or family history of psychiatric illnesses.

For example, it is well established that women are more likely than men to suffer from independent depressive or anxiety disorders (Kessler et al.1997). Not surprisingly, alcoholic women are also more prone than alcoholic men to having independent mood or anxiety disorders (Kessler et al.1997). Alcoholic women and men also seem to differ in the temporal order of the onset of these conditions, with most mood and anxiety disorders predating the onset of alcoholism in women (Kessler et al.1997).

Given these observations, it is especially important in female patients to perform a thorough psychiatric review that probes for major mood disorders (i.e., major depression and bipolar disorder) and anxiety disorders (e.g., social phobia). Knowledge of the psychiatric illnesses that run in the patient’s family also may enhance diagnostic accuracy.

  • For example, men and women with alcohol dependence and independent major depressive episodes have been found to have an increased likelihood of having a family history of major mood disorders (Schuckit et al.1997 a ).
  • Similar findings have been obtained for alcohol–dependent bipolar patients (Preisig et al.2001).

Thus, a family history of a major psychiatric disorder other than alcoholism in an individual may increase the likelihood of that patient having a dual diagnosis. Remaining Flexible with Diagnosis and Follow Up Once a working diagnosis has been established, it is important for the clinician to remain flexible with his or her assessment and to continue to monitor the patient over time.

Like most initial psychiatric assessments, the basic approach described here is hardly foolproof. Therefore, it is important to monitor a patient’s course and, if necessary, revise the diagnosis, even if improvement occurs with abstinence and supportive treatment alone during the first weeks of sobriety.

The importance of continued followup for several weeks also is supported by empirical data showing that most major symptoms and signs are resolved within the first 4 weeks of abstinence. Therefore, unless there is ample evidence to suspect the patient has an independent psychiatric disorder, a 2– to 4–week observation period is usually advised before considering the use of most psychotropic medications.

  • The Case Example Revisited Recognizing that this was an emergency situation and that alcoholics have an increased rate of suicide (Hirschfeld and Russell 1997), the emergency room clinician admitted the patient to the acute psychiatric ward for an evaluation.
  • The clinician also obtained the patient’s permission to speak with his wife.

Despite the patient’s denial of alcoholism, this interview with a collateral informant corroborated the clinician’s suspicion that the man had long–standing problems with alcohol that dated back to his mid–20s. Laboratory tests showing an elevated GGT level supported the diagnosis.

  • Moreover, a review of the patient’s medical records showed a previous hospitalization for suicidal ideation and depression 2 years earlier, after the patient’s mother had died.
  • The clinician then formulated a working diagnosis of probable alcohol–induced mood disorder with depressive features, based on three pieces of information.

First, the patient had stated that his depression started about 1 week before admission, after his wife and family members confronted him about his drinking. This confrontation triggered a more intense drinking binge that ended only hours before his arrival in the emergency room.

The patient complained of irritable mood and increased feelings of guilt during the past week, and he admitted he had been drinking heavily during that period. However, he denied other symptoms and signs of a major depressive episode during that period. Second, the medical records indicated that the patient’s previous bout of depression and suicidal ideation had improved with abstinence and supportive and group psychotherapy during his prior hospitalization.

At that time, the patient had been transferred to the hospital’s alcoholism treatment unit after 2 weeks, where he had learned some of the principles that had led to his longest abstinence of 18 months. Third, both the patient and his wife said that during this period of prolonged abstinence the patient showed gradual continued improvement in his mood.

He had worked an active 12–step program of sobriety and had returned to his job as an office manager. During the first week of the current hospitalization, the patient’s suicidal ideation disappeared entirely and his mood gradually improved. He was transferred to the open unit and participated more actively in support groups.

His denial of his alcoholism waned with persistent gentle confrontation by his counselors, and he began attending the hospital’s 12–step program. Three weeks after admission, he continued to exhibit improvement in his mood but still complained of some difficulty sleeping.

  1. However, he felt reassured by the clinician’s explanation that the sleep disturbance was likely a remnant of his heavy drinking that should continue to improve with prolonged abstinence.
  2. Nevertheless, the clinician scheduled followup appointments with the patient to continue monitoring his mood and sleep patterns.

SUMMARY Alcohol abuse can cause signs and symptoms of depression, anxiety, psychosis, and antisocial behavior, both during intoxication and during withdrawal. At times, these symptoms and signs cluster, last for weeks, and mimic frank psychiatric disorders (i.e., are alcohol–induced syndromes).

  1. These alcohol–related conditions usually disappear after several days or weeks of abstinence.
  2. Prematurely labeling these conditions as major depression, panic disorder, schizophrenia, or ASPD can lead to misdiagnosis and inattention to a patient’s principal problem—the alcohol abuse or dependence.
  3. With knowledge of the different courses and prognoses of alcohol–induced psychiatric disorders, an understanding of the comorbid independent disorders one needs to rule out, an organized approach to diagnosis, ample collateral information, and practice, however, the clinician can improve diagnostic accuracy in this challenging patient population.

NOTE Parts of this paper were previously presented in: Anthenelli, R.M. A basic clinical approach to diagnosis in patients with comorbid psychiatric and substance use disorders. In: Miller, N.S., ed. Principles and Practice of Addictions in Psychiatry. Philadelphia: W.B.

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Is alcoholism a depressive disorder?

Some people say they drink alcohol to “drown their sorrows” after a bad breakup, job loss, or other major life stress, And yes, because alcohol makes you sleepy, a few beers or glasses of wine can seem to relax you and relieve anxiety, A drink once in a while when you’re stressed out or blue is one thing.

But when you need that cocktail every time a problem crops up, it could be a sign of alcohol use disorder, There’s also a strong link between serious alcohol use and depression, The question is, does regular drinking lead to depression, or are depressed people more likely to drink too much? Both are possible.

Learn more about alcohol and depression, Nearly one-third of people with major depression also have an alcohol problem. Often, the depression comes first. Research shows that depressed kids are more likely to have problems with alcohol a few years down the road.

Also, teens who’ve had a bout of major depression are twice as likely to start drinking as those who haven’t. Women are more than twice as likely to start drinking heavily if they have a history of depression, Experts say that women are more likely than men to overdo it when they’re down. Drinking will only make depression worse.

People who are depressed and drink too much have more frequent and severe episodes of depression, and are more likely to think about suicide, Heavy alcohol use also can make antidepressants less effective. Alcohol is a depressant. That means any amount you drink can make you more likely to get the blues.

  1. Drinking a lot can harm your brain and lead to depression.
  2. When you drink too much, you’re more likely to make bad decisions or act on impulse.
  3. As a result, you could drain your bank account, lose a job, or ruin a relationship.
  4. When that happens, you’re more likely to feel down, particularly if your genes are wired for depression.

It’s not always clear if depression makes you drink or vice versa. Studies of twins have shown that the same things that lead to heavy drinking in families also make depression more likely. Researchers have found at least one common gene. It’s involved in brain functions like memory and attention.

Variations in this gene might put people at risk for both alcohol misuse and depression. Home and social environment also play a role. Children who were abused or raised in poverty appear to be more likely to develop both conditions. It probably won’t hurt to have a glass of wine or beer once in a while for social reasons unless you have a health problem that prevents you from drinking.

But if you turn to alcohol to get you through the day, or if it causes trouble in your relationships, at work, in your social life, or with how you think and feel, you have a more serious problem. Alcohol misuse and depression are both serious problems that you shouldn’t ignore.

If you think you have a problem with either, talk to your doctor or therapist. There are lots of choices when it comes to medication that treats depression, and there are drugs that lower alcohol cravings and counter the desire to drink heavily. Your doctor will probably treat both conditions together.

You can also get help from Alcoholics Anonymous or an alcohol treatment center in your area.

What is the genetic heritability of alcoholism?

Those who have a family history of alcoholism have a higher risk of developing a drinking problem. Studies show that alcoholism is approximately 50% attributable to genetics.

Is drinking as bad as smoking?

The Hazards of Smoking – While drinking can be a threat to your health, smoking is certainly worse. Unlike alcohol at low or moderate levels, there is no benefit to tobacco use at any level. When you smoke, you inhale various chemicals that can injure cells, causing both cancer and artery damage (e.g.

heart attacks and strokes). Tobacco smoke can take a toll on your cholesterol levels as well. It’s known to lower HDL (or “good”) cholesterol, elevate LDL (or “bad”) cholesterol and also cause a rise in triglycerides — the same type of blood fat that can build up as a result of alcohol consumption. It also injures the arteries, making the “bad” LDL cholesterol more likely to stick and cause blockages.

As if these issues aren’t enough, smoking can harm your cardiovascular health in other ways too. Your blood becomes thicker, artery walls become stiffer and more inflamed, and blood circulation is negatively affected. Not to mention, your lungs literally become black from tar.

Are smokers more likely to become alcoholics?

David J. Drobes, Ph.D. – David J. Drobes, Ph.D., is an associate professor at the Moffitt Cancer Center & Research Institute, University of South Florida, Tampa, Florida. Preparation of this article was supported by National Institutes of Health grant AA–11157.

People who drink alcohol often also smoke and vice versa. Several mechanisms may contribute to concurrent alcohol and tobacco use. These mechanisms include genes that are involved in regulating certain brain chemical systems; neurobiological mechanisms, such as cross–tolerance and cross–sensitization to both drugs; conditioning mechanisms, in which cravings for alcohol or nicotine are elicited by certain environmental cues; and psychosocial factors (e.g., personality characteristics and coexisting psychiatric disorders).

  • Treatment outcomes for patients addicted to both alcohol and nicotine are generally worse than for people addicted to only one drug, and many treatment providers do not promote smoking cessation during alcoholism treatment.
  • Recent findings suggest, however, that concurrent treatment for both addictions may improve treatment outcomes.

Key words: comorbidity; AODD (alcohol and other drug dependence); alcoholic beverage; tobacco in any form; nicotine; smoking; genetic linkage; cross–tolerance; AOD (alcohol and other drug) sensitivity; neurotransmitters; brain reward pathway; cue reactivity; social AODU (AOD use); cessation of AODU; treatment outcome; combined modality therapy; literature review Alcohol consumption and tobacco use are closely linked behaviors.

  1. Thus, not only are people who drink alcohol more likely to smoke (and vice versa) but also people who drink larger amounts of alcohol tend to smoke more cigarettes.
  2. Furthermore, patients diagnosed with dependence on one of the drugs also are commonly diagnosed with dependence on the other drug (e.g., Zacny 1990).

In fact, smoking rates among alcoholics have been estimated to be as high as 90 percent, with approximately 70 percent of alcoholics smoking at least one pack of cigarettes per day (National Institute on Alcohol Abuse and Alcoholism 1998). Similarly, smokers are far more likely to consume alcohol than are nonsmokers, and smokers who are dependent on nicotine have a 2.7 times greater risk of becoming alcohol dependent than nonsmokers (e.g., Breslau 1995).

  • Finally, although the smoking rate in the general population has gradually declined over the past three decades, the smoking rate among alcoholics has remained persistently high (e.g., Hays et al.1999).
  • Concerns about the concurrent use of alcohol and tobacco are particularly salient given the detrimental impact of this drug combination on the individual and on society.

For instance, alcohol and tobacco when used together increase the risk of various forms of cancer (e.g., mouth and esophageal cancer), as well as cardiovascular disease, more than use of either drug alone (e.g., U.S. Department of Health and Human Services 1989).

The concurrent use of both drugs by pregnant women can also result in more severe prenatal damage and neurocognitive deficits in their offspring than use of either drug alone (e.g., Martin et al.1997). Furthermore, the combined use of alcohol and tobacco among adolescents is more predictive of illicit drug use and various personal and social problems among this population than use of either drug alone (e.g., Hoffman et al.2001).

Given the frequent occurrence and broad implications of concurrent alcohol and tobacco use, research and clinical efforts clearly must focus on people who abuse both drugs. Over the past decade, interactions between alcohol and tobacco have indeed received growing attention from both basic and clinical researchers.

  1. Alcohol dependence and smoking, individually and in combination, are complex forms of addictive behavior that may be influenced by a variety of genetic, neurobiological, conditioning, and psychosocial mechanisms, as described in this article.
  2. In addition to these mechanisms, the article discusses issues related to the treatment of alcoholic smokers.

This overview will necessarily be selective; for instance, there is little mention of sociocultural (e.g., economic and demographic) factors that also may contribute to concurrent use of alcohol and tobacco (see Bobo and Husten 2000). MECHANISMS UNDERLYING COMBINED ALCOHOL AND TOBACCO USE Genetic Factors The importance of genetic influences on both alcoholism and smoking has gained widespread recognition over the past decade.

Using behavioral genetic methods, such as twin and adoption studies, as well as genetic epidemiological approaches, researchers have established that both alcoholism and smoking have strong heritable components (e.g., Prescott and Kendler 1995). In general, heritability, which estimates the proportion of variability within an observed characteristic that can be attributed to genetic factors, appears to be slightly higher for smoking–related variables (e.g., smoking initiation and smoking persistence) than for alcoholism (e.g., Heath and Madden 1995).

Moreover, several researchers have indicated that a substantial shared genetic risk exists between smoking and alcoholism—that is, genetic factors that increase the risk for smoking also increase the risk for alcoholism and vice versa (e.g., Koopmans et al.1997; Prescott and Kendler 1995).

  • The relative contributions of genetic and environmental risk factors may depend on a person’s age and gender.
  • Thus, one study found that the combined risk for alcohol use and smoking in adolescents was primarily attributable to shared environmental features (e.g., peer influences) whereas in young adults, this risk was significantly influenced by genetic factors (Koopmans et al.1997).

Laboratory findings suggest that reduced subjective effects of alcohol (e.g., euphoria or sedation) among smokers may underlie this genetic association (Madden et al.1997), particularly among women. Recent molecular genetic studies have attempted to identify specific genetic factors that may underlie various forms of addictive behavior.

Perhaps the strongest evidence for individual genes that may contribute to both smoking and alcoholism involves the dopaminergic reward system. Dopamine is a brain chemical (i.e., neurotransmitter) that mediates the communication among brain cells in certain brain regions. Some of these brain regions play a role in the pleasant (i.e., rewarding) effects of drugs such as alcohol and nicotine.

To exert its effects, dopamine released by one brain cell interacts with specific protein molecules (i.e., receptors) on the surface of neighboring cells, and this interaction causes a biochemical reaction in those cells. Some evidence suggests that certain variants of genes that regulate the activity of dopamine or its receptors may be related to the risk of excessive alcohol consumption or smoking (e.g., Lerman et al.1999; Li 2000).

  1. The results at this stage are merely suggestive, but the application of molecular genetic research techniques to studies of complex behaviors such as alcohol and nicotine addiction is progressing rapidly and may yield important findings within the next decade.
  2. One development that most likely will accelerate researchers’ understanding of genetic factors contributing to alcoholism and smoking will be the establishment of valid and reliable endophenotypes for these addictive behaviors.

An endophenotype is an objective and measurable characteristic of a person that is thought to be more directly related to the person’s genetic makeup (i.e., genotype) than are typical diagnostic categorizations (e.g., alcohol abuse or dependence). Perhaps the best–established example of such an endophenotype in the drug addiction field is the P300 component of the event–related brain potential (ERP).

ERPs are brain waves elicited by a sudden stimulus (e.g., a light or sound). One component of an ERP typically can be measured approximately 300 milliseconds after the stimulus occurs and is therefore called the P300 signal. It is thought to represent cognitive, or attentional, processing of novel information.

This P300 signal commonly is reduced in size in people at risk for alcoholism (e.g., Porjesz et al.1998). Recent work has also shown that smokers may exhibit ERPs with a reduced P300 signal (e.g., Anokhin et al.2000). By replicating these findings and identifying additional valid endophenotypes for alcoholism and smoking, researchers hope to detect stronger relationships between these forms of addictive behavior and certain genes.

  • In addition, these studies may lead to a fuller understanding of the mechanisms through which these genes influence behavior.
  • Neurobiological Mechanisms Several neurobiological mechanisms may underlie the strong relationship between alcohol and tobacco use.
  • Both the ability of one drug to reduce the effects of the other drug (i.e., cross–tolerance) and the ability of one drug to increase the effects of the other drug (i.e., cross–reinforcement) may play important roles in mediating this relationship (Pomerleau 1995).

Such processes could act immediately when alcohol and nicotine are taken together, or they could involve changes in nerve cell function that occur over time with repeated usage of either one or both drugs. It is also possible that the two drugs when taken together create a combined reward effect that is qualitatively different from the effects of either drug taken alone.

The development of tolerance (and, by extension, cross–tolerance) to both pleasurable and aversive drug effects is thought to support the development or maintenance of an addiction. Thus, tolerance to pleasurable drug effects requires the user to consume increasing drug amounts to achieve the desired rewarding effects.

Conversely, tolerance to aversive drug effects enables the user to experience pleasant effects while not experiencing the initial aversive drug effects. Experimental evidence of cross–tolerance between alcohol and nicotine comes from several lines of research.

  • For instance, mice bred for different levels of sensitivity to certain alcohol effects (e.g., either extremely high or extremely low sensitivity to alcohol’s sedative effects) exhibit corresponding changes in their behavioral and physiological responses to nicotine (Collins 1990).
  • Also, mice that chronically receive nicotine (via intravenous infusion) or alcohol (via a liquid diet) show cross–tolerance to a drug–induced decrease in body temperature when the alternate drug is given (Collins et al.1988).

Finally, in a recent study, female adolescent mice treated with alcohol for 4 days displayed cross–tolerance to nicotine’s effects on body temperature and activity when they were tested 30 days later (Lopez et al.2001). Extending these demonstrations of cross–tolerance from animal models to the phenomenon of concurrent alcohol and nicotine dependence in humans, one could hypothesize that people who regularly consume both alcohol and nicotine may develop dependence on both drugs more rapidly than if they consumed only one drug, because the rate of tolerance development would be increased.

Alternatively, smoking may promote alcohol consumption through an immediate (i.e., acute) form of cross–tolerance. This means that smokers may be able to consume more alcohol because nicotine exerts a stimulatory effect that can directly counteract both the sedative properties of alcohol and the cognitive deficits associated with alcohol intoxication.

This hypothesis is supported by findings that nicotine administration directly increases alcohol consumption in animal models; this effect appears to be mediated through receptors for nicotine in the brain (e.g., L et al.2000). Similarly, earlier laboratory studies with humans showed that alcohol consumption increased the amount and rate at which participants smoked cigarettes (e.g., Mello et al.1980).

As mentioned earlier, components of the brain signaling system involving the neurotransmitter dopamine may play a role in the genetic basis for both alcohol and tobacco addiction. One brain system that uses dopamine as a primary neurotransmitter is the mesolimbic dopamine system, which has been implicated in the motivation to obtain various rewards, including alcohol and nicotine (e.g., Wise 1988).

This system encompasses several brain regions, most notably the ventral tegmental area, the nucleus accumbens, and the prefrontal cortex (see figure). Both alcohol and nicotine directly activate dopamine–releasing nerve cells within the ventral tegmental area, ultimately leading to dopamine release in the nucleus accumbens and prefrontal cortex.

These pathways appear to become sensitized with repeated use of either drug, a process called neuroadaptation (e.g., Robinson and Berridge 1993). One theoretical model called the incentive sensitization model (Robinson and Berridge 1993) posits that stimuli which have been closely associated with prior drug use (e.g., the sight of a beer bottle or a pack of cigarettes) gradually become more powerful (i.e., gain incentive salience) because of this sensitization.

According to this model, both alcohol– and nicotine–associated stimuli may activate the mesolimbic dopaminergic system in people who frequently use both drugs, thereby increasing the overall vulnerability to an addiction in those people. Dopaminergic pathways in the brain, including the mesolimbic dopaminergic system, which consists of the ventral tegmental area, the nucleus accumbens, and the prefrontal cortex. This system has been implicated in the motivation to obtain various rewards, including the positive reinforcement of alcohol and nicotine.

SOURCE: Adapted from Heimer, L. The Human Brain and Spinal Cord: Functional Neuroanatomy and Dissection Guide.2d ed. New York: Springer–Verlag, 1995. Another brain neurotransmitter system that may be involved in alcohol–tobacco interactions is the endogenous opiate system. Endogenous opiates are molecules produced naturally by the body that have effects similar to opiates (e.g., morphine).

Alcohol appears to stimulate the endogenous opiate system, which may contribute to alcohol’s pleasurable effects. Clinical and laboratory–based studies have shown that agents that block the effects of endogenous opiates (i.e., opiate antagonists) can reduce alcohol consumption (see Anton 2001).

The effects of nicotine may also be partly mediated through this opiate brain system, although studies on the effects of opiate antagonists on smoking behavior and other nicotine–related responses have provided equivocal results to date. Conditioning Mechanisms It is a common observation that people who drink alcohol and smoke tend to engage in these behaviors in particular situations (e.g., in a bar or at a party) and contemporaneously.

Furthermore, studies have confirmed that relapse to smoking following smoking cessation is strongly associated with alcohol consumption (e.g., Brandon et al.1990). These observations support the hypothesis that alcohol and smoking may become associated through a process called cue conditioning because of the frequent concurrent use of the two drugs.

In general, conditioning models of addiction suggest that cues previously paired with drug use (e.g., the sight of a liquor bottle or the smell of a lighted cigarette) will elicit conditioned responses, including cravings and associated physiological activity. These cue–elicited cravings and physiological reactions, in turn, can motivate ongoing drug use and increase the probability of relapse among people who are abstinent (e.g., Drobes and Tiffany 1997).

Numerous laboratory studies have supported this view, demonstrating that various alcohol and smoking–related cues can elicit cravings and physiological responses among alcoholics and smokers, respectively (for a review, see Carter and Tiffany 1999). Several human laboratory studies suggest a role for cue conditioning in the close association between alcohol use and smoking.

  • For instance, one study showed that the severity of nicotine dependence among alcoholic smokers was related to the strength of alcohol cravings elicited by alcohol cues (Abrams et al.1992).
  • Other findings have demonstrated that alcohol cues can simultaneously increase smoking urges and alcohol urges among alcoholic smokers (e.g., Gulliver et al.1995; Rohsenow et al.1997).

Overall, laboratory findings suggest that substantial overlap between alcohol and smoking cues may exist in promoting drug cravings and drug consumption—that is, both types of cues may elicit cravings and consumption of either drug. Even the administration of alcohol or nicotine can serve as a conditioned pharmacological or sensory cue.

  1. Accordingly, research that evaluates the effects of the administration of either drug on responding to the other drug can help determine the role of conditioning factors in concurrent alcohol and tobacco use.
  2. For instance, several early studies demonstrated that alcohol consumption can promote smoking (e.g., Mello et al.1980).

Furthermore, a more recent study of nonalcoholic smokers showed that cue–elicited cravings for nicotine increased when the participants first consumed alcohol (Burton and Tiffany 1997). However, craving increases in this study were not specific to smoking–related cues, which implies that alcohol consumption leads to a more general increase in cravings to smoke.

Finally, another laboratory study investigated how hard people who had been allowed to smoke or who were smoking deprived would work on a computer task to receive alcohol.1 ( 1 The effort a person puts into the task in order to receive alcohol is considered an indication of his or her motivation to drink.) Each participant was tested in two separate sessions involving either ad lib smoking or smoking deprivation prior to the session.

During each session, the task was performed twice, both before and after receiving a standard dose of alcohol. The study found that after the men had received a standard dose of alcohol, those who had been allowed to smoke before working on the task worked harder to obtain more alcohol than did men who had been deprived of nicotine overnight (Perkins et al.2000).

  1. This effect was not observed when the men were tested before they had received the alcohol, indicating that when it is combined with alcohol consumption, nicotine consumption can increase the motivation to drink alcohol.
  2. This interaction between nicotine and alcohol consumption was not observed in women, suggesting that important gender differences may exist with respect to pharmacological and motivational influences on alcohol and tobacco use.

Research has not yet directly examined acute nicotine effects on reactivity to alcohol cues, nor has the combined impact of alcohol and nicotine administration on cue–elicited craving, drug effects, or drug consumption been studied extensively (for a review, see Perkins 1997).

  1. Overall, the available research suggests that alcohol and nicotine can have interactive effects on the motivation to consume either drug.
  2. Further research is needed to obtain a better understanding of the interactive effects of various pharmacological and cue manipulations on cravings for and consumption of alcohol and nicotine.
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Psychosocial Factors Even at the earliest stages of drug use, which often occurs during adolescence, common psychosocial factors may promote the use of both alcohol and tobacco. For instance, personality characteristics that remain stable throughout a person’s life often have been implicated as playing a role in the initiation of both alcohol and tobacco use (e.g., Flay et al.1995).

These characteristics may include sensation seeking, impulsivity, compulsiveness, and neuroticism (i.e., trait anxiety). Such a role of personality characteristics in determining alcohol consumption and smoking is not incompatible with the genetic mechanisms discussed above. Indeed, many of these personality variables are themselves heritable, and the genetic risk for alcohol use and smoking may be mediated partly through these personality traits.

Another important psychosocial influence on the initiation of combined alcohol and tobacco use stems from family modeling. Thus, numerous studies show that adolescents who are exposed to older family members who smoke and drink are more liable to engage in these behaviors than are adolescents without such family members (e.g., Bobo and Husten 2000).

  • Accordingly, combined alcohol and tobacco use may become a self–propagating cycle across familial generations independent of any direct genetic influence.
  • Other important modeling influences for alcohol use and smoking behaviors are likely to be peer related.
  • As mentioned earlier, the impact of genetic factors on alcohol use and smoking may be somewhat less pronounced during adolescence than during early adulthood (Koopmans et al.1997).

This observation is consistent with findings supporting a strong role of parental and peer influences (e.g., Hoffman et al.2001). Furthermore, both alcohol use and smoking commonly serve as outlets for adolescent rebelliousness, and both behaviors are associated with illicit drug use and other problems among adolescents (Hoffman et al.2001).

Temporary psychological states in otherwise mentally healthy people also may contribute to the ongoing use of alcohol and tobacco. For example, both laboratory and field studies have found that situational stress and negative emotional states (e.g., anxiety and depression) can serve as cues that elicit alcohol or tobacco craving or consumption of these drugs in active drinkers or smokers (e.g., Tiffany and Drobes 1990).

People also may use alcohol and nicotine to alleviate stress or tension. Indeed, both drugs exhibit extreme versatility in their ability to regulate mood, in that they may be used either to help a person relax or to stimulate or energize the person. Alcohol and smoking also both frequently serve as “social lubricants” in social situations.

Rates of alcohol and tobacco consumption are disproportionately high among people with comorbid psychological disorders, particularly various affective (e.g., depression) and anxiety disorders. People with such disorders presumably use alcohol and tobacco to self–medicate their affective symptoms through the direct stimulatory or stress–reducing drug effects.

The order in which the psychological disorders and alcohol and tobacco use develop, however, is not always clear and may vary for different people. Thus, alcohol and tobacco use may represent a form of (maladaptive) coping with a preexisting psychological disorder or they may precede or exacerbate the development of psychopathology.

Finally, alcohol and tobacco use may be part of a broader constellation of symptoms associated with the comorbid condition. Further long–term studies with alcohol and tobacco users who exhibit or later develop various forms of psychopathology may clarify the causal pathways underlying these relationships.

Several other psychosocial variables have been tied theoretically or empirically to the risk of combined alcohol and tobacco use in various situations. These variables include life stressors (e.g., loss of a job or a loved one), social support, self–efficacy, coping skills, and expectancies (i.e., expectations about the effects of alcohol and tobacco on behavior).

These and other psychosocial factors most likely interact with genetic, biological, and conditioning mechanisms in unique ways throughout each person’s history of alcohol and nicotine use, including initiation, maintenance, cessation, and relapse, to determine that person’s risk of alcohol and nicotine abuse and dependence.

TREATMENT OF SMOKING IN ALCOHOLICS For people addicted to alcohol and nicotine, outcomes during treatment for alcoholism, smoking, or both are often less favorable than for people addicted to only one drug. For example, alcoholics who smoke generally are less successful in achieving and maintaining sobriety than are nonsmoking alcoholics (e.g., Hughes 1995).

Furthermore, in alcoholics treated for both addictions, relapse to smoking is considered a risk factor for alcohol relapse (e.g., Johnson and Jennison 1992). Similarly, nicotine dependence and the experience of nicotine withdrawal appear to be more severe in smokers with a history of alcohol dependence (e.g., Marks et al.1997), and rates of successful smoking cessation are lower among smokers with past or current alcohol problems (e.g., DiFranza and Guerrera 1990).

Consequently, improvements in treatment outcomes among smoking alcoholics remain an important challenge for the future. Until recently, treatment providers generally believed that smoking cessation was contraindicated during alcoholism treatment for several reasons.

  1. Some alcoholism program philosophies considered smoking a relatively benign problem compared with alcohol dependence.
  2. Another reason was the fear that smoking cessation would lead to poorer alcoholism treatment outcomes, either by increasing the clients’ stress or decreasing the effort that clients could devote to achieving abstinence from alcohol (e.g., Bobo and Gilchrist 1983).

Finally, many alcoholism treatment providers believed that smoking serves as an effective coping tool for dealing with alcohol cravings and with the stress associated with alcohol withdrawal or protracted abstinence. Consequently, these providers were unwilling to take away that coping tool.

  1. Despite longstanding fears from treatment providers that smoking cessation would interfere with alcoholism treatment, there are several reasons to anticipate that combined treatment for both addictions may lead to more favorable outcomes for both drugs.
  2. First, at a neurobiological level, alcohol and nicotine act, at least in part, on the same brain pathways involved in reward and craving.

Therefore, it may be advantageous to cease using both drugs to reverse the effects on these pathways. One important caveat here is that nicotine appears to serve an acute protective function concerning certain neurotoxic effects of alcohol withdrawal.

Therefore, extreme caution must be exercised in determining the optimal sequence of drug removal for patients desiring treatment for both addictions. Second, as discussed above, continued smoking or alcohol use may elicit or exacerbate craving for the other drug. Third, behavioral treatments based on coping–skill attainment may be more effective when developing skills are generalized to both types of addictive behavior.

For instance, people may be able to obtain more practice at using coping skills if they apply them to both alcohol consumption and smoking. And fourth, a treatment approach that encourages an overall milieu of healthy lifestyle changes would be more generally consistent with abstinence from both drugs.

  1. Another reason to support concurrent treatment for smoking and alcoholism is that more alcoholics will die from smoking–related illnesses than from alcohol–related causes (e.g., Hurt et al.1996).
  2. The numerous problems associated with smoking are well documented, and most alcoholics entering treatment are aware of these problems and appear quite willing to receive concurrent smoking cessation treatment (e.g., Saxon et al.1997).

Even without formal smoking cessation treatment, smoking rates appear to decrease and the motivation to quit smoking increases following successful alcoholism treatment (e.g., Monti et al.1995). Researchers have begun to evaluate the effectiveness of explicit smoking cessation attempts during alcoholism treatment as well as the impact of such attempts on the outcome of the alcoholism treatment (e.g., Martin et al.1997).

  • Findings to date generally do not confirm the traditional notion that only one addiction should be treated at a given time.
  • It is still too early to tell what treatment configuration will be most effective for smoking alcoholics.
  • In concert with recent advances in their understanding of neurobiological factors that contribute to the development and maintenance of addictive behavior, including alcoholism and smoking, researchers have been exploring potentially useful pharmacological treatments that may benefit various types of addiction.

Because it is likely that alcohol and nicotine act at least partially through the same brain reward pathways, it is reasonable to expect some overlap in the types of pharmacological treatments that may be effective in the treatment of alcoholism and smoking.

  1. For instance, as mentioned earlier, endogenous opioids play a role in mediating alcohol’s effects, and opiate antagonist medications (e.g., naltrexone and nalmefene) can be effective for the treatment of alcoholism.
  2. Recent studies have suggested that opiate pathways may also be involved in nicotine dependence (e.g., Pomerleau 1998).

However, the usefulness of opiate antagonists as a treatment for smokers in general or alcoholic smokers in particular remains to be determined. CONCLUSIONS Alcohol and tobacco use are highly correlated behaviors. For example, people who drink are very likely to smoke and vice versa; furthermore, people who are dependent on alcohol also are frequently dependent on nicotine.

  1. The costs of the combined use of these drugs to both the individual and society are substantial.
  2. Several potential mechanisms may promote the combined use of alcohol and nicotine.
  3. Although researchers have made substantial progress in delineating factors that may underlie alcohol and tobacco comorbidity, several research gaps remain.

For example, investigators and clinicians still need to fully elucidate and consider the roles of various genetic, neurobiological, conditioning, and psychosocial factors in developing a more thorough understanding of this dual addiction. Important potential gender differences in how these mechanisms operate also merit further research, as do potential differences in the treatment of male and female alcoholic smokers.

Despite long–held views that smoking cessation attempts should be deferred or discouraged among alcoholics undergoing treatment, researchers have begun to evaluate treatment programs designed to address alcohol and nicotine dependence simultaneously. Early results of these analyses are promising, although additional research is clearly needed to optimize treatment outcomes and to address important health and safety concerns.

The development of treatment programs for people dependent on both alcohol and nicotine will be greatly enhanced if such programs are based on a fundamental understanding of mechanisms that promote this dual addiction. Similarly, basic researchers should consider the clinical phenomenology of concurrent alcohol and tobacco use as a guiding force for investigating dual addictions in the laboratory.

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Can a smoker be a father?

Paternal smoking is linked to increased risk of congenital heart defects.

Is add ADHD hereditary?

Attention deficit hyperactivity disorder (ADHD) – Causes The exact cause of attention deficit hyperactivity disorder (ADHD) is not fully understood, although a combination of factors is thought to be responsible.

  • ADHD tends to run in families and, in most cases, it’s thought the genes you inherit from your parents are a significant factor in developing the condition.
  • Research shows that parents and siblings of someone with ADHD are more likely to have ADHD themselves.
  • However, the way ADHD is inherited is likely to be complex and is not thought to be related to a single genetic fault.
  1. Research has identified a number of possible differences in the brains of people with ADHD from those without the condition, although the exact significance of these is not clear.
  2. For example, studies involving brain scans have suggested that certain areas of the brain may be smaller in people with ADHD, whereas other areas may be larger.
  3. Other studies have suggested that people with ADHD may have an imbalance in the level of neurotransmitters in the brain, or that these chemicals may not work properly.

Certain people are also believed to be more at risk of ADHD, including people:

  • who were born prematurely (before the 37th week of pregnancy) or with a low birthweight
  • with epilepsy
  • with brain damage – which happened either in the womb or after a severe head injury later in life

Page last reviewed: 24 December 2021 Next review due: 24 December 2024 : Attention deficit hyperactivity disorder (ADHD) – Causes

Are mental Health issues genetic?

Remember – Mental disorders are the result of both genetic and environmental factors. There is no single genetic switch that when flipped causes a mental disorder. Consequently, it is difficult for doctors to determine a person’s risk of inheriting a mental disorder or passing on the disorder to their children.

Can depression be passed down by genetics?

How common is major depression? At least 10% of people in the U.S. will experience major depressive disorder at some point in their lives. Two times as many women as men experience major depression. How do we know that genes play a role in causing depression? Scientists look at patterns of illness in families to estimate their “heritability,” or roughly what percentage of their cause is due to genes.

  • To do this we find people with the disease who have a twin, and then find out whether the twin is also ill.
  • Identical (monozygotic) twins share 100% of their genes, while non-identical (“fraternal” or dizygotic) twins share 50% of their genes.
  • If genes are part of the cause, we expect a patient’s identical twin to have a much higher risk of disease than a patient’s non-identical twin.

That is the case for major depression. Heritability is probably 40-50%, and might be higher for severe depression. This could mean that in most cases of depression, around 50% of the cause is genetic, and around 50% is unrelated to genes (psychological or physical factors).

Or it could mean that in some cases, the tendency to become depressed is almost completely genetic, and in other cases it is not really genetic at all. We don’t know the answer yet. We can also look at adoption studies, to see whether an adopted person’s risk of depression is greater if a biological parent had depression.

This also seems to be the case. What about non-genetic factors? There are probably many non-genetic factors that increase risk of depression, many of which are probably not yet known. Severe childhood physical or sexual abuse, childhood emotional and physical neglect, and severe life stress are probably all risk factors.

Losing a parent early in life probably also increases risk to some extent. If someone has a family history of depression, are they at very high risk? If someone has a parent or sibling with major depression, that person probably has a 2 or 3 times greater risk of developing depression compared with the average person (or around 20-30% instead of 10%).

The situation is a little different if the parent or sibling has had depression more than once (“recurrent depression”), and if the depression started relatively early in life (childhood, teens or twenties). This form of depression is less common – the exact percentage of the population is not known, but is probably around 3-5%.

  • But the siblings and children of people with this form of depression probably develop it at a rate that is 4 or 5 times greater than the average person.
  • Is there a “depression gene”? Some diseases are caused by a single defective gene.
  • Cystic fibrosis, several kinds of muscular dystrophy, and Huntington’s disease are examples.

These are usually rare diseases. But many common disorders like depression, diabetes and high blood pressure are also influenced by genes. In these disorders, there seem to be combinations of genetic changes that predispose some people to become ill. We don’t yet know how many genes are involved in depression, but it is very doubtful that any one gene causes depression in any large number of people.

  1. So no one simply “inherits” depression from their mother or father.
  2. Each person inherits a unique combination of genes from their mother and father, and certain combinations can predispose to a particular illness.
  3. How are major depression and bipolar disorder related? Most people who suffer from depression do not have episodes of mania.

We use the term major depression for depression without mania. Most people who experience mania also have major depression. We use the term bipolar disorder (or manic-depression) for this pattern. Major depressive disorder and bipolar disorder are the two “major mood disorders.” For more information on the symptoms of mania abd bipolar disorder, see the links at the bottom of this page.

Most people with major depression do not have close relatives with bipolar disorder, but the relatives of people with bipolar disorder are at increased risk of both major depression and bipolar disorder. What about major depression and anxiety disorders? There are probably genetic changes that can increase the predisposition to both major depression and to certain anxiety disorders including generalized anxiety disorder, panic disorder and social phobia.

Also, some people have a more general lifelong tendency to experience unpleasant emotions and anxiety in response to stress. Psychologists use terms like “neuroticism” and “negative affectivity” to refer to this tendency, and people who have it are also more likely to experience major depression.

What is the most addictive personality type?

The Adventurous, Risk-Taking Trait – Some personality traits have higher risk of addiction than others. Individuals who like to take risks and who have little impulse control around experimenting and playing with new experiences and dangerous activities are more likely to try drugs. Is Alcohol Addiction Genetic People with high levels of dopamine in the brain may have a lower sensitivity to its effects, meaning that they need to have more intense experiences in order to feel the pleasure that this brain chemical causes. This, in turn, can be bound into the person’s experience using drugs and alcohol, which directly affect the dopamine system.

Can ADHD cause addiction?

Introduction – Research has shown that those with attention-deficit/hyperactivity disorder (ADHD) have an increased risk for addiction disorders like alcoholism and substance abuse. What is less clear is the mechanism(s) whereby ADHD gives rise to increased engagement in addictive behaviors, and whether there are sex differences in the ADHD-addiction propensity.

  1. Both ADHD and addictions have also been associated with personality traits such as impulsivity, reward seeking, anxiousness, and negative affect.
  2. In this study, we tested a moderator-mediation model, which predicted that both sex and ADHD-symptom status would make independent contributions to the variance in personality risk and in addictive behaviors, with males, and those with diagnosed ADHD, scoring higher on both dependent variables.

Our model also predicted that the effect of sex and ADHD-symptom status on addictive behaviors would be via the mediating or intervening influence of personality-risk factors.

Is nicotine addiction genetic?

Abstract – Globally, tobacco smoking is responsible for the deaths of five million people each year and increases the risk of developing numerous disorders, particularly pulmonary and cardiovascular disease, as well as many cancers. It has long been known that several environmental factors influence the decision to smoke.

However, in recent years, we have learned more about the role that genes play in the development of nicotine dependence. Twin and family studies have shown that there is not one specific gene that determines who will develop a smoking addiction but rather several genes that cause an individual to become more susceptible to being addicted to nicotine.

These genes are responsible for how certain neurotransmitters are produced and metabolized, the number of receptors that are available to act on and how rapidly nicotine is metabolized by the individual. The more we understand these processes, the better the opportunity will be to formulate effective treatments.

Can depression be passed down by genetics?

How common is major depression? At least 10% of people in the U.S. will experience major depressive disorder at some point in their lives. Two times as many women as men experience major depression. How do we know that genes play a role in causing depression? Scientists look at patterns of illness in families to estimate their “heritability,” or roughly what percentage of their cause is due to genes.

  1. To do this we find people with the disease who have a twin, and then find out whether the twin is also ill.
  2. Identical (monozygotic) twins share 100% of their genes, while non-identical (“fraternal” or dizygotic) twins share 50% of their genes.
  3. If genes are part of the cause, we expect a patient’s identical twin to have a much higher risk of disease than a patient’s non-identical twin.

That is the case for major depression. Heritability is probably 40-50%, and might be higher for severe depression. This could mean that in most cases of depression, around 50% of the cause is genetic, and around 50% is unrelated to genes (psychological or physical factors).

Or it could mean that in some cases, the tendency to become depressed is almost completely genetic, and in other cases it is not really genetic at all. We don’t know the answer yet. We can also look at adoption studies, to see whether an adopted person’s risk of depression is greater if a biological parent had depression.

This also seems to be the case. What about non-genetic factors? There are probably many non-genetic factors that increase risk of depression, many of which are probably not yet known. Severe childhood physical or sexual abuse, childhood emotional and physical neglect, and severe life stress are probably all risk factors.

Losing a parent early in life probably also increases risk to some extent. If someone has a family history of depression, are they at very high risk? If someone has a parent or sibling with major depression, that person probably has a 2 or 3 times greater risk of developing depression compared with the average person (or around 20-30% instead of 10%).

The situation is a little different if the parent or sibling has had depression more than once (“recurrent depression”), and if the depression started relatively early in life (childhood, teens or twenties). This form of depression is less common – the exact percentage of the population is not known, but is probably around 3-5%.

But the siblings and children of people with this form of depression probably develop it at a rate that is 4 or 5 times greater than the average person. Is there a “depression gene”? Some diseases are caused by a single defective gene. Cystic fibrosis, several kinds of muscular dystrophy, and Huntington’s disease are examples.

These are usually rare diseases. But many common disorders like depression, diabetes and high blood pressure are also influenced by genes. In these disorders, there seem to be combinations of genetic changes that predispose some people to become ill. We don’t yet know how many genes are involved in depression, but it is very doubtful that any one gene causes depression in any large number of people.

  • So no one simply “inherits” depression from their mother or father.
  • Each person inherits a unique combination of genes from their mother and father, and certain combinations can predispose to a particular illness.
  • How are major depression and bipolar disorder related? Most people who suffer from depression do not have episodes of mania.

We use the term major depression for depression without mania. Most people who experience mania also have major depression. We use the term bipolar disorder (or manic-depression) for this pattern. Major depressive disorder and bipolar disorder are the two “major mood disorders.” For more information on the symptoms of mania abd bipolar disorder, see the links at the bottom of this page.

  1. Most people with major depression do not have close relatives with bipolar disorder, but the relatives of people with bipolar disorder are at increased risk of both major depression and bipolar disorder.
  2. What about major depression and anxiety disorders? There are probably genetic changes that can increase the predisposition to both major depression and to certain anxiety disorders including generalized anxiety disorder, panic disorder and social phobia.

Also, some people have a more general lifelong tendency to experience unpleasant emotions and anxiety in response to stress. Psychologists use terms like “neuroticism” and “negative affectivity” to refer to this tendency, and people who have it are also more likely to experience major depression.

Is anxiety a genetic trait?

There’s clear research showing that anxiety is influenced by genetics. In fact, experts noticed a family connection for anxiety even before they understood how DNA or genes worked. If you have a close relative with anxiety, your chance of developing it’s about 2 to 6 times higher than if you don’t.

What percentage of people have an addictive personality?

Sign up for Scientific American ’s free newsletters. ” data-newsletterpromo_article-image=”https://static.scientificamerican.com/sciam/cache/file/4641809D-B8F1-41A3-9E5A87C21ADB2FD8_source.png” data-newsletterpromo_article-button-text=”Sign Up” data-newsletterpromo_article-button-link=”https://www.scientificamerican.com/page/newsletter-sign-up/?origincode=2018_sciam_ArticlePromo_NewsletterSignUp” name=”articleBody” itemprop=”articleBody”> In her new book Maia Szalavitz recalls her behavior as a child in school and at home. Anxious, bright and slightly obsessive, she didn’t seem to fit the stereotype of the “addictive personality”. Nevertheless, in college she would become addicted to heroin and cocaine, forcing her to reexamine her assumptions about addiction and its treatment. The following is an excerpt from Unbroken Brain: A Revolutionary New Way of Understanding Addiction, by Maia Szalavitz. Copyright © 2016 by Maia Szalavitz. Reprinted with permission of St. Martin’s Press, LLC. All rights reserved. – A weird little girl on the swings engaging in compulsive behavior to soothe herself is probably not what you picture when you think of an addicted person or her background. Our cultural images of addiction tend to be much less likely to engender sympathy. For one, they are racialized—so even though black and Hispanic people are not more likely than whites to become addicted, those with dark skin tend to be pictured in American media stories about addiction. And when whites are shown, we are typically described as not being “typical.” Second, in part as a result of the racism that has driven our drug policies, these images tend to depict people with addictions as “fiends” or “demons” whose debauchery is driven by a ravenous hedonism, not a human and understandable search for safety and comfort. The “addictive personality” is seen as a bad one: weak, unreliable, selfish, and out of control. The temperament from which it springs is seen as defective, unable to resist temptation. Even when we joke about having an addictive personality it’s usually to justify an indulgence or to signal our guilt about pleasure, even if only ironically. To understand the role of learning in addiction and in the temperaments that predispose people to it, we have to examine the relationship between addiction and personality more closely. Although addiction was originally framed by both Alcoholics Anonymous and psychiatry as a form of antisocial personality or “character” disorder, research did not confirm this idea. Despite decades of attempts, no single addictive personality common to everyone with addictions has ever been found. If you have come to believe that you yourself or an addicted loved one, by nature of having addiction, has a defective or selfish personality, you have been misled. As George Koob, the director of the National Institute on Alcohol Abuse and Alcoholism, told me, “What we’re finding is that the addictive personality, if you will, is multifaceted,” says Koob. “It doesn’t really exist as an entity of its own.” Fundamentally, the idea of a general addictive personality is a myth. Research finds no universal character traits that are common to all addicted people. Only half have more than one addiction (not including cigarettes)—and many can control their engagement with some addictive substances or activities, but not others. Some are shy; some are bold. Some are fundamentally kind and caring; some are cruel. Some tend toward honesty; others not so much. The whole range of human character can be found among people with addictions, despite the cruel stereotypes that are typically presented. Only 18% of addicts, for example, have a personality disorder characterized by lying, stealing, lack of conscience, and manipulative antisocial behavior. This is more than four times the rate seen in typical people, but it still means that 82% of us don’t fit that particular caricature of addiction. Although people with addictions or potential addicts cannot be identified by a specific collection of personality traits, however, it is often possible to tell quite early on which children are at high risk. Children who ultimately develop addictions tend to be outliers in a number of measurable ways. Yes, some stand out because they are antisocial and callous—but others stand out because they are overly moralistic and sensitive. While those who are the most impulsive and eager to try new things are at highest risk, the odds of addiction are also elevated in those who are compulsive and fear novelty. It is extremes of personality and temperament—some of which are associated with talents, not deficits—that elevates risk. Giftedness and high IQ, for instance, are linked with higher rates of illegal drug use than having average intelligence. Whether these extreme traits lead to addictions, other compulsive behaviors, developmental differences, mental illnesses, or some mixture depends not just on genetics but also on the environment, people’s own reactions to it, and those of others to them. Addictions and other neurodevelopmental disorders rely not just on our actual experience but on how we interpret it and how our parents and friends respond to and label the way we behave. They develop in brains designed to change with experience—and that leaves us vulnerable to learning things that create damaging patterns, not just useful habits. The impact of all these factors together can be seen most clearly in studies that follow participants from infancy into adulthood (which are rare because they take so long to conduct and are thus very expensive). In these types of data, some strong patterns emerge. One of the earliest and best known longitudinal studies related to drug use followed 101 children—mainly middle class, two-thirds white—raised in Berkeley in the 1970s. Conducted by psychologists Jonathan Shedler and Jack Block, then at the University of California, the research was published in 1990 and its main finding generated much controversy. The authors discovered that the most mentally and psychologically healthy teens were not those who abstained entirely from alcohol and other drugs, but rather the kids who experimented with weed and drinking, but didn’t overdo it. In this study, occasional teen drinking and marijuana use was normal adolescent behavior. However, while it was common, it was typically not problematic. Unsurprisingly the teens who became frequent users and drinkers had the problems you might expect, like depression, anxiety, and delinquent behavior. Then again, many of the same psychiatric problems were also seen in the adolescents who rejected the idea of drinking and drugs entirely. That’s probably because, in order to avoid any experimentation as a kid growing up around the Berkeley campus in the ’70s (when nearly two thirds of high school seniors nationally reported at least trying marijuana), you’d have to be either a loner with few friends or a person who was unusually fearful and/or resistant to peer pressure. Not using drugs may well have been a wise choice for these youth— but good decisions aren’t always made for healthy reasons. And indeed, that’s exactly what the study found. The youth who abstained did not tend to do so because they rationally recognized the risks. Instead, they were overly anxious, uptight, and lacking in social skills; some may not have had to say no because they didn’t even get the chance to say yes. Similar data have been published on teen drinking as well. Moderate drinkers—not nondrinkers—are the most well adjusted, at least in countries where drinking is a social norm. The healthiest patterns are found in the middle of the curve, not at the extremes. To understand how having these outlying traits increases risk for addiction, we have to look at how they affect development. Critically, in Shedler and Block’s data, the traits that marked both abstainers and heavy users could be seen long before drug use began. After all, the authors had started following these children in preschool. Once they knew how the participants behaved in adolescence, they could look back and see what early traits were linked to particular problems. Longitudinal studies looking at addiction risk have found three major pathways to it that involve temperamental traits, all of which can be seen in nascent form in young children. The first, which is more common in males, involves impulsivity, boldness, and a desire for new experience; it can lead to addiction because it makes it hard for people to control their own behavior. The second, which tends to be seen more in women, involves being sad, inhibited, and/or anxious. While these negative emotions can also deter experimentation, when they do not do so, people may find themselves on a “self-medicating” path to addiction, where drugs are used to cope with painful feelings. Being bold and adventurous and being sad and cautious seem like opposite personality types. However, these two paths to addiction are actually not mutually exclusive. The third way involves having both kinds of traits, where people alternatively fear and desire novelty and behavior swings from being impulsive and rash to being compulsive, fear driven, and stuck in rigid patterns. This is where some of the contradictions that have long confounded the study of addiction come into play—namely, some aspects seem precisely planned out, while others are obviously related to lack of restraint. My own story spirals around this paradoxical situation: I was driven enough to excel academically and fundamentally scared of change and of other people—yet I was also reckless enough to sell cocaine and shoot heroin. If we look more closely, however, the paradoxes disappear. All three pathways really involve the same fundamental problem: a difficulty with self-regulation. This may appear predominantly as an inability to inhibit strong impulses, it may be largely an impairment in modulating negative emotions like anxiety, or it may have elements of both. In any case, difficulties with self-regulation lay the groundwork for learning addiction and for creating a condition that is hard to understand. The brain regions that allow self-regulation need experience and practice in order to develop. If that experience is aberrant or if those brain regions are wired unusually, they may not learn to work properly. The importance of self-regulation is evident in the Shedler and Block data. From the very start, the children in the study who grew up to be heavy drug users were, as they put it, “visibly deviant from their peers, emotionally labile, inattentive and unable to concentrate, not involved in what they do,” and “stubborn.” This is a picture of emotional dysregulation—and it could have described me as a child, except for “not involved in what they do.” But while such children can be summed up as having “low self-control” or “impulse control problems”—and in the study, these kids tended to have lower grades—this doesn’t account for the compulsive side of addiction. In my case, when it came to schoolwork, I didn’t shirk. Indeed, I was desperate to be a good student and terrified of getting in trouble. Here, I had trouble stopping intellectual engagement, not starting it. Obsessiveness like this, however, also involves impaired self-regulation—in this case, at the other end of the spectrum. It’s a problem with stopping what has already been started, rather than starting an action that should have been stopped. In other words, while impulsiveness involves too little behavioral inhibition and a failure to prevent reckless behavior, obsession and compulsiveness is a problem with too much inhibition, a difficulty with getting out of a rut, rather than with preventing actions from being initiated. Further, inability to modulate fear and other emotions also involves a reduced capacity to self-regulate. In their studies, Shedler and Block found that the abstaining youth were “fastidious, conservative, proud of being ‘objective’ and rational, overly controlled and prone to delay gratification unnecessarily, not liked or accepted by people,” as well as “moralistic,” “not gregarious,” and “basically anxious.” Most of that could also have described me as a three-year-old. Indeed, it reads now as a somewhat judgmental description of the key traits of children with Asperger’s. My own behavior as a young child and elementary school student swung between the poles of being overly controlled to being out of control. Both behavioral extremes, however, result from a failure in self-regulation. And neuroscience now strongly suggests that such dysregulation plays a key role in addiction. In fact, similar brain circuits are involved in both addiction and obsessive-compulsive disorder (OCD): whether the problem is failing to stop an impulsive action or failing to end a habitual routine, many of the same regions are engaged. It is here that addiction is learned. The relevant areas of the brain include the prefrontal cortex (PFC), which imagines possible futures and plans and makes decisions accordingly. Of particular importance within the PFC is the orbitofrontal cortex, which helps determine the relative emotional and psychological value of your options and, therefore, your level of motivation and your tendency to make particular choices. The PFC works in concert with the nucleus accumbens (NAC), the region famed as the brain’s “pleasure or reward” center. This area is involved in determining the desirability of particular options and how much you want to seek or avoid them. Another region related to reward and motivation, the ventral pallidum, is also part of this brain system, as is the habenula, which seems to be involved primarily in aversion and disliking. The insula, which processes emotions like lust and disgust and also monitors internal states like hunger and thirst, is another node in this circuitry. So is the anterior cingulate, which looks for conflicts and errors and changes emotion accordingly. The anterior cingulate seems to be especially important for obsessive behaviors, perhaps because it creates a sense that things are “not right” until they are perfect or complete. In OCD, it may wrongly detect errors, which could cause constant anxiety. Finally, the amygdala is also in the loop. While best known for its role in processing fear, the almond-shaped amygdala is also involved in a variety of other emotions, including positive ones. Together, this whole neural network sets values, priorities, and goals. Crucially, parts of it can also simplify repeated behavior into programs for habits that can be engaged or disengaged with little conscious thought. Indeed, research shows that as a behavior is learned and becomes more automatic, it engages different parts of the striatum, which is the broader area that contains the nucleus accumbens. As a behavior moves from being a conscious choice to a habit, brain activity changes, moving up toward the top or “dorsal” portion of the striatum and away from the bottom or “ventral” area. In addiction and other compulsive behaviors, brain activity that is increasingly dorsal in the striatum seems to be linked with reduced ability of the prefrontal cortex to stop or control the behavior. One critical aspect of addiction, in fact, is an alteration in the balance between brain networks that drive habitual behavior and those that determine whether or not to execute those routines. Again, all of these regions are made to change with experience and are, as a result, developmentally vulnerable both in early childhood and adolescence. With any activity, as it is learned, it becomes easier, more automatic, and less conscious. This is essential when you are learning to play the piano or throw a ball—and it allows “muscle memory” to develop and hone your skills. However, it’s not such a great capacity to have when you are learning addiction because, by definition, more reflexive behavior is less under conscious control. It seems that the same regions that gave me my intense curiosity, obsessive focus, and ability to learn and memorize quickly also made me vulnerable to discovering potential bad habits and then rapidly getting locked into them.

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