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Common Psychiatric Disorders and Caffeine Use, Tolerance, and Withdrawal: An Examination of Shared Genetic and Environmental Effects

Published online by Cambridge University Press:  05 July 2012

Jocilyn E. Bergin  and
Kenneth S. Kendler
Jocilyn E. Bergin*
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
Kenneth S. Kendler
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
*
address for correspondence: Jocilyn Bergin, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126 MCV; Richmond, VA 23298, USA. E-mail: jdellava@vcu.edu

Abstract

Background: Previous studies examined caffeine use and caffeine dependence and risk for the symptoms, or diagnosis, of psychiatric disorders. The current study aimed to determine if generalized anxiety disorder (GAD), panic disorder, phobias, major depressive disorder (MDD), anorexia nervosa (AN), or bulimia nervosa (BN) shared common genetic or environmental factors with caffeine use, caffeine tolerance, or caffeine withdrawal. Method: Using 2,270 women from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, bivariate Cholesky decomposition models were used to determine if any of the psychiatric disorders shared genetic or environmental factors with caffeine use phenotypes. Results: GAD, phobias, and MDD shared genetic factors with caffeine use, with genetic correlations estimated to be 0.48, 0.25, and 0.38, respectively. Removal of the shared genetic and environmental parameter for phobias and caffeine use resulted in a significantly worse fitting model. MDD shared unique environmental factors (environmental correlation = 0.23) with caffeine tolerance; the genetic correlation between AN and caffeine tolerance and BN and caffeine tolerance were 0.64 and 0.49, respectively. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN, which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance. GAD had modest genetic correlations with caffeine tolerance, 0.24, and caffeine withdrawal, 0.35. Conclusions: There was suggestive evidence of shared genetic and environmental liability between psychiatric disorders and caffeine phenotypes. This might inform us about the etiology of the comorbidity between these phenotypes.

Keywords

anxiety disordersdepressioneating disorderscaffeineheritability

Information

Type
Articles
Information
Twin Research and Human Genetics , Volume 15 , Issue 4 , August 2012 , pp. 473 - 482
Copyright
Copyright © The Authors 2012

Common psychiatric disorders have consistently been shown to be comorbid with substance use disorders (Grant et al., Reference Grant, Hasin, Stinson, Dawson, June Ruan, Goldstein, Smith, Saha and Huang2005; O'Neil et al., Reference O'Neil, Conner and Kendall2011; Root et al., Reference Root, Pisetsky, Thornton, Lichtenstein, Pedersen and Bulik2010; Salbach-Andrae et al., Reference Salbach-Andrae, Lenz, Simmendinger, Klinkowski, Lehmkuhl and Pfeiffer2008). It has been estimated that worldwide caffeine is consumed daily by 80% of individuals (James, Reference James1997) and can be considered a substance for potential abuse. Similar to other psychoactive substances with potential for abuse, caffeine use can be associated with symptoms of tolerance and withdrawal (Griffiths et al., Reference Griffiths, Juliano and Chausmet2003). The Diagnostic and Statistical Manual for Mental Disorders (DSM)-IV contains several caffeine use diagnoses (American Psychiatric Association, 1994). A genome-wide association study has suggested several genes may be associated with coffee drinking (Amin et al., Reference Amin, Byrne, Johnson, Chenevix-Trench, Walter, Nolte, Vink, Rawal, Mangino, Teumer, Keers, Verwoert, Baumeister, Biffar, Petersmann, Dahmen, Doering, Isaacs, Broer, Wray, Montgomery, Levy, Psaty, Gudnason, Chakravarti, Sulem, Gudbjartsson, Kiemeney, Thorsteinsdottir, Stefansson, van Rooij, Aulchenko, Hottenga, Rivadeneira, Hofman, Uitterlinden, Hammond, Shin, Ikram, Witteman, Janssens, Snieder, Tiemeier, Wolfenbuttel, Oostra, Heath, Wichmann, Spector, Grabe, Boomsma, Martin and van Duijn2011). Evidence suggested that caffeine dependence might be related to other substances with abuse potential. Caffeine dependence symptoms shared a common genetic factor with alcohol and nicotine dependence symptoms and a common unique environmental factor with alcohol, nicotine, cannabis, and cocaine dependence symptoms (Kendler et al., Reference Kendler, Myers and Prescott2007). Given that there is a high comorbidity between other licit and illicit substance use and psychiatric disorders, studying the comorbidity between caffeine use, caffeine tolerance, and caffeine withdrawal and common psychiatric disorders, like anxiety disorders and depression, is of potential interest.

Thus far, some research has explored the comorbidity between caffeine use and psychiatric disorders. Caffeine use in women was associated with an increased risk of poor mental health defined as scoring four or higher on the Japanese version of the general health questionnaire (Shimbo et al., Reference Shimbo, Nakamura, Shi, Kizuki, Seino, Inose and Takano2005). Caffeine intake, heavy caffeine use, caffeine toxicity, and symptoms of caffeine dependence were associated with an increased risk for developing major depressive disorder (MDD), generalized anxiety disorder (GAD), panic disorder, adult antisocial personality disorder, and illicit drug abuse and dependence (Kendler et al., Reference Kendler, Myers and O'Gardner2006). In a separate study, some eating disorder symptoms (binge eating, concern about weight and shape, self-perception of being overweight, and expressing a fear of gaining weight) were associated with caffeine abuse (Baker et al., Reference Baker, Mitchell, Neale and Kendler2010).

Results of studies have also indicated that caffeine consumption can trigger or worsen anxiety. Caffeine has been shown to have anxiogenic effects in individuals with panic disorder (Breier et al., Reference Breier, Charney and Heninger1986; Charney et al., Reference Charney, Heninger and Jatlow1985; Nardi et al., Reference Nardi, Lopes, Valenca, Freire, Veras, de-Melo-Neto, Nascimento, King, Mezzasalma, Soares-Filho and Zin2007, Reference Nardi, Lopes, Freire, Veras, Nascimento, Valenca, de-Melo-Neto, Soares-Filho, King, Araújo, Mezzasalma, Rassi and Zin2009), performance social anxiety disorder (Nardi et al., Reference Nardi, Lopes, Freire, Veras, Nascimento, Valenca, de-Melo-Neto, Soares-Filho, King, Araújo, Mezzasalma, Rassi and Zin2009), and major depression with panic attacks (Nardi et al., Reference Nardi, Lopes, Valenca, Freire, Veras, de-Melo-Neto, Nascimento, King, Mezzasalma, Soares-Filho and Zin2007). Despite consuming similar amounts of caffeine as individuals without psychological disorders, those with depression expressed higher sensitivity to the anxiogenic effects of caffeine (Lee et al., Reference Lee, Flegel, Greden and Cameron1988). Taken together, there may be shared genetic or environmental factors between psychiatric disorders and caffeine use phenotypes.

Twin studies have suggested that genetic factors play an important role in the etiology of all common psychiatric disorders that have been examined including GAD (Hettema et al., Reference Hettema, Neale and Kendler1995; Hettema et al., Reference Hettema, Neale and Kendler2001; Scherrer et al., Reference Scherrer, True, Xian, Lyons, Eisen, Goldberg, Lin and Tsuang2000), phobias (Kendler et al., Reference Kendler, Gardner, Annas, Neale, Eaves and Lichtenstein2008; Kendler et al., Reference Kendler, Karkowski and Prescott1999), panic (Hettema et al., Reference Hettema, Prescott and Kendler2001; Kendler et al., Reference Kendler, Gardner and Prescott2001; Middeldorp et al., Reference Middeldorp, Birley, Cath, Gillespie, Willemsen, Statham, de Geus, Andrews, van Dyck, Beem, Sullivan, Martin and Boomsma2005; Mosing et al., Reference Mosing, Gordon, Medland, Statham, Nelson, Heath, Martin and Wray2009), MDD (Bierut et al., Reference Bierut, Heath, Bucholz, Dinwiddie, Madden, Statham, Dunne and Martin1999; Kendler & Prescott, Reference Kendler and Prescott1999a; Sullivan et al., Reference Sullivan, Neale and Kendler2000), anorexia nervosa (AN; Dellava et al., Reference Dellava, Thornton, Lichtenstein, Pedersen and Bulik2010; Klump et al., Reference Klump, Miller, Keel, McGue and Iacono2001; Mazzeo et al., Reference Mazzeo, Mitchell, Bulik, Reichborn-Kjennerud, Kendler and Neale2009), and bulimia nervosa (BN; Bulik et al., Reference Bulik, Thornton, Root, Pisetsky, Lichtenstein and Pedersen2010; Kendler et al., Reference Kendler, MacLean, Neale, Kessler, Heath and Eaves1991; Kortegaard et al., Reference Kortegaard, Hoerder, Joergensen, Gillberg and Kyvik2001). Fewer studies have been conducted on caffeine use phenotypes. Of the existing twin studies, the heritability of caffeine use was estimated between 0.36 and 0.58 (Kendler & Prescott, Reference Kendler and Prescott1999b; Yang et al., Reference Yang, Palmer and de Wit2010), caffeine tolerance at 0.40 (Kendler & Prescott, Reference Kendler and Prescott1999b; Luciano et al., Reference Luciano, Kirk, Heath and Martin2005), and caffeine withdrawal at 0.35 (Kendler & Prescott, Reference Kendler and Prescott1999b). Despite the high comorbidity between psychiatric disorders and caffeine phenotypes, few twin studies have examined the nature of this comorbidity. Although no significant results were found, possibly due to sample size, in monozygotic (MZ) twins all odds ratios between caffeine use phenotypes and psychological disorders were non-significant; in the full sample including all twins, this relationship was significant. This indicated that these phenotypes likely share genetic liability (Kendler et al., Reference Kendler, Myers and O'Gardner2006). The genetic correlation between caffeine abuse/dependence and BN symptom count was estimated at 0.37 (Baker et al., Reference Baker, Mitchell, Neale and Kendler2010). A genetic correlation of 0.40 was found between caffeine use and sleep disturbance (Luciano et al., Reference Luciano, Zhu, Kirk, Gordon, Heath, Montgomery and Martin2007). Further research is needed to determine if there is shared genetic or environmental liability between specific psychiatric disorders and specific caffeine use phenotypes.

The aim of the current study was to determine the magnitude of the genetic and environmental correlations between common psychiatric disorders (GAD, panic disorder, phobias, MDD, AN-like syndrome, and BN-like syndrome) and key caffeine phenotypes (caffeine use, caffeine tolerance, and caffeine withdrawal) in women. In conducting these analyses, the possibility of the existence of consistent patterns among all the psychiatric phenotypes and caffeine phenotypes was explored. In addition, analyses could illustrate if each specific psychiatric phenotype displayed the same general relationship with all caffeine phenotypes. For all psychiatric phenotypes, broad diagnoses were used to maximize power.

Materials and Methods

Participants

This study consisted of females who participated in the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. This sample has previously been described (Kendler et al., Reference Kendler, Neale, Kessler, Heath and Eaves1992a, Reference Kendler, Neale, Kessler, Heath and Eaves1992b). Briefly, the female twin pair portion of this study consisted of 2,270 individuals from female–female twin pairs who completed the Wave 1 interview in person (89%) or by telephone (11%). Some of these women participated in up to three additional interview waves of data collection. Of the original 2,270 who participated in Wave 1, 1,937 participated in Wave 4 (Kendler & Prescott, Reference Kendler and Prescott1999a). For the current study, the most comprehensive psychiatric diagnoses, with the exception of panic disorder, were conducted in Wave 1 and therefore taken from Wave 1, panic disorder was best assessed and therefore taken from Wave 2, and caffeine use was only assessed and therefore taken from Wave 4. Phobia diagnosis was adapted from the Diagnostic Interview Schedule Version III-A (Robins & Helzer, Reference Robins and Helzer1985) for DSM-III criteria (American Psychiatric Association, 1980); GAD, panic disorder, MDD, AN, BN, and caffeine tolerance were adapted from Structured Clinical Interview for DSM-IIIR (Spitzer et al., Reference Spitzer, Williams, Gibbon and First1990) and are based on DSM-IIIR criteria (Spitzer et al., Reference Spitzer, Williams, Gibbon and First1988); and caffeine withdrawal was adapted from DSM-IV (American Psychiatric Association, 1994). Figure 1 illustrates the wave from which each phenotype was obtained.

FIGURE 1

Measurement of variables for current study.

Note: n = number; GAD = generalized anxiety disorder; PAN = panic disorder; PHO = phobia; MDD = major depressive disorder; AN = anorexia nervosa; BN = bulimia nervosa; N/A = not applicable.

Zygosity Determination

Zygosity determination, as previously been described (Kendler et al., Reference Kendler, Neale, Kessler, Heath and Eaves1992b), was based on standard questions regarding physical similarity of a twin with her co-twin (Eaves et al., Reference Eaves, Eysenck and Martin1989), photographs of the twin and her co-twin, and some DNA samples (Spence et al., Reference Spence, Corey, Nance, Marazita, Kendler and Schieken1988).

Psychiatric Phenotypes

Generalized anxiety disorder

GAD diagnosis in this sample has been well described (Kendler et al., Reference Kendler, Neale, Kessler, Heath and Eaves1992a). GAD was taken from Wave 1 and the one-month criterion was used (Kendler et al., Reference Kendler, Neale, Kessler, Heath and Eaves1992a) for the current study. The one- and six-month GAD criteria yield a sample with comparable characteristics (Breslau & Davis, Reference Breslau and Davis1985; Kendler et al., Reference Kendler, Neale, Kessler, Heath and Eaves1992a; Lee et al., Reference Lee, Tsang, Ruscio, Haro, Stein, Alonso, Angermeyer, Bromet, Demyttenaere, de Girolamo, de Graaf, Gureje, Iwata, Karam, Lepine, Levinson, Medina-Mora, Browne, Posada-Villa and Kessler2009). In the current sample, 539 women (25.9% of women with non-missing data) met criterion for GAD.

Panic disorder

For the current study, panic disorder was taken from Wave 2, which has been described in detail (Kendler et al., Reference Kendler, Gardner and Prescott2001). In order to achieve adequate power, the ‘very broad’ definition of panic was used; this required a positive answer to the screen in question that was indicative of DSM-IIIR criterion A, two of the 13 symptoms listed in DSM-IIIR criterion C, and maximum panic intensity within 30 min of onset (Kendler et al., Reference Kendler, Gardner and Prescott2001). In the current sample, 235 women (13.6% of women with non-missing data) met the criterion for panic.

Phobia

Any phobia diagnosis was used in the current study and taken from Wave 1. Briefly, women were asked about 17 specific possible fears and could add in additional phobias; for phobia to be considered present, the woman had to respond affirmatively to the following: ‘the fear or its avoidance interfered with life or activities a lot’ (Kendler et al., Reference Kendler, Walters, Neale, Kessler, Heath and Eaves1995). This diagnosis has earlier been described in detail. In the current sample, 700 women (33.6% of women with non-missing data) met this criterion.

Major depressive disorder

Lifetime MDD was used for the current study taken from Wave 1. DSM-IIIR criteria were used as previously described (Kendler et al., Reference Kendler, Walters, Neale, Kessler, Heath and Eaves1995). In the current sample, 728 (35.0% of women with non-missing data) met criteria for lifetime MDD.

Anorexia nervosa like syndrome

In order to obtain sufficient power to evaluate AN, a broad definition of AN was used from Wave 1. This included women with definite, possible, or probable AN and has been described in detail (Walters & Kendler, Reference Walters and Kendler1995). There were 76 women (3.7% of women with non-missing data) meeting this diagnosis.

Bulimia nervosa like syndrome

Similar to AN, a broad definition of BN from Wave 1 was used. This diagnosis was derived from a computer algorithm and included definite, probable, or possible cases as previously described (Kendler et al., Reference Kendler, Walters, Neale, Kessler, Heath and Eaves1995). There were 118 women (5.7% of women with non-missing data) in the current sample meeting this definition of BN.

Caffeine Use Phenotypes

Caffeine use

In Wave 4, the women were asked to report caffeine consumption in the previous year by reporting consumption of caffeinated beverages; caffeine use was estimated based on standard amounts of caffeine in each type of beverage then divided into 10 use categories (Kendler & Prescott, Reference Kendler and Prescott1999b): <1,150 mg/month; 1,150–2409.9 mg/month; 2,410–4,149.9 mg/month; 4,150–5,709.9 mg/month; 5,710–7,209.9 mg/month; 7,210–8,709.9 mg/month; 8,710–10,959.9 mg/month; 10,960–13,659.9 mg/month; 13,660–19,209.9 mg/month; and 19,210+ mg/month. The number of women (percent of women with non-missing data) falling into each category is as follows: 161 (8.7%); 195 (10.5%); 161 (8.7%); 207 (11.1%); 185 (9.9%); 201 (10.8%); 173 (9.3%); 199 (10.7%); 187 (10.1%); and 192 (10.3%).

Caffeine tolerance

Caffeine tolerance was considered present if the woman responded ‘yes’ to either of the following questions: ‘During the time when you were consuming caffeinated beverages the most, did you find that you needed to drink a lot more to get the desired effect than you did when you first drank them?’ and ‘ What about finding out that when you drank the same amount, it had much less effect than before?’ (Kendler & Prescott, Reference Kendler and Prescott1999b). Using this diagnosis, 278 women (15.1% of those with non-missing data) met criteria for caffeine tolerance.

Caffeine withdrawal

Caffeine withdrawal was guided by DSM-IV (American Psychiatric Association, 1994) and considered present if headache was present along with either marked fatigue or drowsiness, marked anxiety or depression, or nausea or vomiting when caffeine was not consumed in its usual quantity (Kendler & Prescott, Reference Kendler and Prescott1999b). In the current sample, 256 women (22.3% of those with non-missing data) met criteria for caffeine withdrawal.

Statistical Methods

Biometrical twin modeling was conducted in OpenMx and based on the properties and assumptions of the classic twin design (Neale & Cardon, Reference Neale and Cardon1992). Additive genetic effects (a 2) were the genetic factors modeled in the current study. MZ twins are genetically identical, i.e., all genes are shared, and dizygotic (DZ) twins are no more similar than other siblings, i.e., about half of their genes are shared, identical by descent; common environmental factors (c 2; e.g., living in the same household as children) are shared by twins regardless of zygosity, and unique environmental factors (e 2; e.g., living in different cities as adults) are not common between any twins; the e 2 parameter contained the error term. Biometrical twin modeling was used and compared different patterns of similarities and differences of MZ and DZ twins to estimate genetic, common environmental, and unique environmental parameters (Neale & Cardon, Reference Neale and Cardon1992; Neale & Maes, Reference Neale and Maes1998).

For the current study, a Cholesky decomposition was used to estimate the unique and shared genetic and the unique and shared unique environmental components of psychiatric disorders and caffeine phenotype (Figure 2); this was repeated for each psychiatric phenotype and each caffeine phenotype. A priori, the c 2 parameter was fixed to zero for both psychiatric and caffeine phenotypes. This decision was based on univariate models, which indicated that the c 2 parameter was non-significant (data not shown). The Cholesky decomposition model contained a direct path from a genetic and unique environmental factor to the psychiatric phenotype and a second direct path from a genetic and unique environmental factor to the caffeine phenotype; there was then a cross path from the psychiatric phenotype to the caffeine phenotype, which allowed estimation of genetic and unique environmental correlation between phenotypes. The psychiatric phenotype was entered into the model first followed by the caffeine phenotype. The variable order had no effect on the results. Additional models were fit to determine if the genetic or environmental correlation parameters were statistically significant. This was done by fitting several submodels in which the genetic or environmental correlation parameters were fixed to zero. Model evaluation was done by likelihood ratio tests — the difference between –2 log-likelihood (–2LL) of the two models distributed as a chi-square — and Akaike's information criterion (AIC). Given that we had low statistical power to distinguish between the models, the genetic and environmental parameters were not removed from the model.

FIGURE 2

Bivariate model for psychiatric phenotypes (Psyc) and caffeine phenotypes (Caf).

Note: A = heritability component; E = unique environment component; r a = genetic correlation; r e = unique environmental/error.

Raw data were analyzed using full information maximum likelihood for parameter estimates and 95% confidence intervals (CI), which handled missing data (Neale & Cardon, Reference Neale and Cardon1992). All statistical analyses were conducted in the R software version 2.12.2 (R Development Core Team, 2010) and all twin modeling was conducted using OpenMx version 1.0.6 (Boker et al., Reference Boker, Neale, Maes, Wilde, Spiegel, Brick, Spies, Estabrook, Kenny, Bates, Mehta and Fox2011).

Results

Model fit statistics for the full model and submodels are contained in Table 1, and broken down by caffeine phenotype and psychiatric phenotype. The submodels contained in Table 1 indicate which genetic and environmental correlation parameters were significant. Parameter estimates for psychiatric phenotype and caffeine use are contained in Table 2. The genetic correlation between GAD and caffeine use was 0.48 (significantly different from zero). The genetic correlation between phobias and caffeine use was 0.25 and MDD and caffeine use was 0.38, which were also statistically significant. For panic disorder and caffeine use, there was a negative genetic correlation, –0.22, but this was not significantly different from zero. When both the genetic and environmental correlation parameters were fixed to zero, a significant deterioration of fit resulted for GAD, phobias, and MDD (data not shown). This indicated there was significant shared liability between these psychiatric disorders and caffeine use.

TABLE 1

Model Fit Statistics

Note: AIC = Akaike's information criterion; GAD = generalized anxiety disorder; PAN = panic disorder; PHO = phobia; MDD = major depressive disorder; AN = anorexia nervosa; BN = bulimia nervosa; –2LL = –2 log-likelihood; n/a = not applicable; r g = genetic correlation; r e = environmental correlation.

TABLE 2

Parameter Estimates for Psychiatric Phenotype Caffeine Use

Note: Common environmental parameter fixed to zero. Caf. = caffeine use; GAD = generalized anxiety disorder; PAN = panic disorder; PHO = phobia; MDD = major depressive disorder; AN = anorexia nervosa; BN = bulimia nervosa; A = genetic parameter; E = unique environmental parameter.

Parameter estimates and 95% CI for psychiatric phenotypes and tolerance are contained in Table 3. Here, MDD had an environmental correlation with caffeine tolerance of 0.23, AN had a genetic correlation of 0.64 with caffeine tolerance, and BN had a 0.49 genetic correlation with caffeine tolerance. These were statistically significant. GAD also showed modest genetic correlation with caffeine tolerance, 0.24; panic had a negative genetic correlation of –0.27 with caffeine tolerance and BN had a negative environmental correlation of –0.33 with caffeine tolerance, but these were not statistically significant. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN (data not shown), which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance.

TABLE 3

Parameter Estimates for Psychiatric Phenotype and Caffeine Tolerance

Note: Common environmental parameter fixed to zero. Tol. = tolerance; GAD = generalized anxiety disorder; PAN = panic disorder; PHO = phobia; MDD = major depressive disorder; AN = anorexia nervosa; BN = bulimia nervosa; A = genetic parameter; E = unique environmental parameter.

Psychiatric phenotypes and caffeine withdrawal parameter estimates are presented in Table 4. Although there were no statistically significant genetic or environmental correlation between psychiatric disorders and caffeine withdrawal, the genetic correlation between GAD and caffeine withdrawal was 0.35, with very little environmental correlation. MDD, AN, and BN also showed some evidence of genetic correlation with caffeine withdrawal; here, the parameter estimates were 0.26, 0.27, and 0.32, respectively. Further, removal of both the genetic and environmental correlation parameters resulted in a significantly worse fitting model for MDD (data not shown).

TABLE 4

Parameter Estimates for Psychiatric Phenotype and Caffeine Withdrawal

Note: Common environmental parameter fixed to zero. With. = withdrawal; GAD = generalized anxiety disorder; PAN = panic disorder; PHO = phobia; MDD = major depressive disorder; AN = anorexia nervosa; BN = bulimia nervosa; A = genetic parameter; E = unique environmental parameter.

Discussion

It was well known and accepted that caffeine has anxiogenic properties. Further, caffeine use has been associated with higher depression scores on the Beck Depression Inventory and higher anxiety scores on the Beck Anxiety Inventory (Dosh et al., Reference Dosh, Helmbrecht, Anestis, Guenthner, Kelly and Martin2010). This study explored the nature of the relationship between common psychiatric disorders, including a variety of anxiety disorders and depression, and caffeine use. Results suggested there might be a common etiology between some common psychiatric disorders and caffeine phenotypes. It did not seem that there was a consistent, universal pattern between all common psychiatric disorders and caffeine phenotypes. However, within some psychiatric disorders, fairly consistent patterns across caffeine phenotypes emerged.

Arguably, some of the strongest evidence for shared liability between psychiatric phenotypes and caffeine use phenotypes came from GAD. It was known that individuals with GAD were highly sensitive to the effects of caffeine, and caffeine caused a greater physiological and anxiogenic response in those with GAD relative to healthy controls (Bruce et al., Reference Bruce, Scott, Shine and Lader1992). Comorbidity between GAD and caffeine use phenotypes has also been established (Kendler et al., Reference Kendler, Myers and O'Gardner2006). In the current study, the genetic correlation between GAD and caffeine use, caffeine tolerance, and caffeine withdrawal were consistently among the highest correlations and exceeded 0.20 in all cases, with very little evidence of environmental correlations. This suggested that much of the shared liability between these phenotypes resulted from a common genetic composition. It is plausible that high caffeine consumption in women with GAD, coupled with symptoms of caffeine tolerance and withdrawal, contributed negatively to GAD.

Much of the previous research, which has been conducted on psychiatric disorders and caffeine use, has focused on panic disorder. It has been shown that individuals with panic disorder were more sensitive to the anxiogenic effects of caffeine (Breier et al., Reference Breier, Charney and Heninger1986; Charney et al., Reference Charney, Heninger and Jatlow1985; Nardi et al., Reference Nardi, Lopes, Valenca, Freire, Veras, de-Melo-Neto, Nascimento, King, Mezzasalma, Soares-Filho and Zin2007, Reference Nardi, Lopes, Freire, Veras, Nascimento, Valenca, de-Melo-Neto, Soares-Filho, King, Araújo, Mezzasalma, Rassi and Zin2009). In addition, both individuals with panic disorder and their first-degree relatives (without panic disorder) showed increased sensitivity to panic attack symptoms after a caffeine challenge test relative to control participants (Nardi et al., Reference Nardi, Valenca, Nascimento, Freire, Veras, de-Melo-Neto, Lopes, King, Soares-Filho, Mezzasalma, Rassi and Zin2008). This suggested the relationship between caffeine sensitivity and panic disorder symptoms was genetic in nature. In the current study, there was evidence of a negative genetic correlation between panic disorder and caffeine use and panic disorder and caffeine tolerance, with little indication of positive or negative environmental correlation. If individuals with panic disorder were truly more sensitive to the effects of caffeine, it is plausible and perhaps probable that these individuals would avoid high caffeine consumption and this could be genetically programmed.

Similar to individuals with anxiety disorders, those with MDD were also more sensitive to the anxiogenic effects of caffeine (Lee et al., Reference Lee, Flegel, Greden and Cameron1988; Nardi et al., Reference Nardi, Lopes, Valenca, Freire, Veras, de-Melo-Neto, Nascimento, King, Mezzasalma, Soares-Filho and Zin2007). In a psychiatric population, depressive symptoms overall have been associated with high caffeine use (Greden et al., Reference Greden, Fontaine, Lubetsky and Chamberlin1978). Although all associations between MDD and caffeine use phenotypes are in the same direction, results from the current study were a bit complex. There was fairly consistent evidence suggesting that MDD and caffeine phenotypes shared liability with estimates exceeding 0.20 in all models. However, for caffeine use and caffeine withdrawal the greatest evidence for shared liability was contained in the genetic parameter, and for caffeine tolerance the greatest evidence for shared liability was in the environmental parameter. This suggested that there was a complex relationship between these phenotypes. Several possible explanations exist. It is possible that genetic and environmental parameters were important for different components of the shared liability. It is also plausible that different endophenotypes of depression may have been more likely to share comorbidity with a specific caffeine phenotype and this different pattern of comorbidity resulted in either higher genetic or environmental correlation. An alternate possibility is that the current study had poor power to discriminate the sources of phenotypic correlation due to relatively small sample sizes.

In addition, there seemed to be some association between eating disorder phenotypes (AN and BN) and caffeine phenotypes. Inpatients with eating disorders had higher caffeine use than those with anxiety disorders (Ciapparelli et al., Reference Ciapparelli, Paggini, Carmassi, Taponecco, Consoli, Ciampa, Ramacciotti, Marazziti and Dell'Osso2010). Clinicians have reported very high caffeine consumption within individuals with AN (Sours, Reference Sours1983), and there was some evidence to suggest higher caffeine intake in women with AN (Striegel-Moore et al., Reference Striegel-Moore, Franko, Thompson, Barton, Schreiber and Daniels2006) than in women without AN. Although there was little shared liability between AN or BN and caffeine use, there was some evidence for shared liability between AN and BN and caffeine tolerance and caffeine withdrawal. Interestingly, for AN, shared genetic and shared environmental parameters are in opposite directions. For AN and BN, both caffeine tolerance and caffeine withdrawal had genetic correlations above 0.20. A high comorbidity between AN and anxiety was previously established (Dellava et al., Reference Dellava, Kendler and Neale2011; Godart et al., Reference Godart, Flament, Curt, Perdereau, Lang, Venisse, Halfon, Bizouard, Loas, Corcos, Jeammet and Fermanian2003; Raney et al., Reference Raney, Thornton, Berrettini, Brandt, Crawford, Fichter, Halmi, Johnson, Kaplan, LaVia, Mitchell, Rotondo, Strober, Woodside, Kaye and Bulik2008; Thornton et al., Reference Thornton, Dellava, Root, Lichtenstein and Bulik2011); it has been estimated that two-thirds of women with AN, BN, or both also suffer from an anxiety disorder (Kaye et al., Reference Kaye, Bulik, Thornton, Barbarich and Masters2004). Further, AN shared substantial genetic liability with GAD (Dellava et al., Reference Dellava, Kendler and Neale2011) and BN also shared a common genetic factor with some anxiety disorders (Kendler et al., Reference Kendler, Walters, Neale, Kessler, Heath and Eaves1995). It is therefore possible that there is a relationship among eating disorder, anxiety disorder, and caffeine phenotypes. Alternatively, it is possible that the genetic correlation between eating disorder and caffeine phenotypes increases anxiety.

Limitations

Several limitations should be kept in mind when considering study results. First, for some phenotypes although diagnoses were similar to DSM-IIIR, the criteria used might not have been precise enough to obtain full clinical diagnoses and therefore may represent partial syndromal diagnoses. However, in other reports multiple threshold models have been tested and show that these are milder phenotypes on the same continuum of liability as fully syndromal cases (Aggen et al., Reference Aggen, Neale and Kendler2005; Kendler et al., Reference Kendler, Neale, Kessler, Heath and Eaves1992a; Kendler et al., Reference Kendler, Gardner and Prescott2001; Neale et al., Reference Neale, Walters, Eaves, Kessler, Heath and Kendler1994; Walters & Kendler, Reference Walters and Kendler1995). Second, this study consisted only of Caucasian twin women born between 1934 and 1971 in mid-Atlantic states and may not generalize to other groups. Third, this study was underpowered. As a consequence of the study being underpowered, the 95% CI were quite large; as a result, some of the parameter estimates in which the 95% CIs crossed zero may become statistically significant in a larger sample. Many of the results that were not significant may become significant with larger sample sizes. In addition, the collection of the relevant variables over four waves may have attenuated the true underlying correlations. Fourth, we acknowledge that prevalence for some of the psychiatric phenotypes was higher than reported in other samples; however, a strength of this study was its use of clinically trained interviewers to arrive at diagnoses. This makes it more unlikely that these disorders were over diagnosed and suggests that the prevalences noted are accurate.

Conclusion

Results of the current study suggested that GAD and caffeine phenotypes likely have shared substantial genetic liability. There was evidence for shared liability between other common psychiatric disorders and caffeine phenotypes. Overall, these results might help provide better understanding of the etiology of the comorbidity between common psychiatric disorders and caffeine use, tolerance, and withdrawal.

Acknowledgments

This study was supported in part by grants MH-068643 and MH-49492 from the National Institute of Health (NIH). Dr Bergin was supported by NIMH T32MH20030 (PI: Michael C. Neale) and 5R37DA018673-07 (PI: Michael C. Neale). Linda Corey, PhD, provided assistance with the ascertainment of twins from the Virginia Twin Registry, now part of the Mid-Atlantic Twin Registry (MATR). The MATR, now directed by Judy Silberg, PhD, has received support from the NIH, the Carman Trust, and the W. M. Keck, John Templeton, and Robert Wood Johnson Foundations. We thank all the participants who made this research possible.

References

Aggen, S. H., Neale, M. C., & Kendler, K. S. (2005). DSM criteria for major depression: Evaluating symptom patterns using latent-trait item response models. Psychological Medicine, 35, 475–487.CrossRefGoogle ScholarPubMed
American Psychiatric Association. (1980). Diagnostic and statistical manual of mental disorders (3rd ed.). Washington, DC: American Psychiatric Association.Google Scholar
American Psychiatric Association. (1994). Diagnostic and statistical manual for psychiatric disorders (4th ed., DSM-IV). Washington, DC: American Psychiatric Press.Google Scholar
Amin, N., Byrne, E., Johnson, J., Chenevix-Trench, G., Walter, S., Nolte, I. M., Vink, J. M., Rawal, R., Mangino, M., Teumer, A., Keers, J. C., Verwoert, G., Baumeister, S., Biffar, R., Petersmann, A., Dahmen, N., Doering, A., Isaacs, A., Broer, L., Wray, N. R., Montgomery, G. W., Levy, D., Psaty, B. M., Gudnason, V., Chakravarti, A., Sulem, P., Gudbjartsson, D. F., Kiemeney, L. A., Thorsteinsdottir, U., Stefansson, K., van Rooij, F. J., Aulchenko, Y. S., Hottenga, J. J., Rivadeneira, F. R., Hofman, A., Uitterlinden, A. G., Hammond, C. J., Shin, S. Y., Ikram, A., Witteman, J. C., Janssens, A. C., Snieder, H., Tiemeier, H., Wolfenbuttel, B. H., Oostra, B. A., Heath, A. C., Wichmann, E., Spector, T. D., Grabe, H. J., Boomsma, D. I., Martin, N. G., & van Duijn, C. M. (2011). Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM. Moleular Psychiatry. Epub ahead of print, doi: 10.1038/mp.2011.101.CrossRefGoogle Scholar
Baker, J. H., Mitchell, K. S., Neale, M. C., & Kendler, K. S. (2010). Eating disorder symptomatology and substance use disorders: Prevalence and shared risk in a population based twin sample. International Journal of Eating Disorders, 43, 648–658.CrossRefGoogle Scholar
Bierut, L. J., Heath, A. C., Bucholz, K. K., Dinwiddie, S. H., Madden, P. A., Statham, D. J., Dunne, M. P., & Martin, N. G. (1999). Major depressive disorder in a community-based twin sample: Are there different genetic and environmental contributions for men and women? Archives of General Psychiatry, 56, 557–563.CrossRefGoogle Scholar
Boker, S., Neale, M. C., Maes, H. H., Wilde, M., Spiegel, M., Brick, T., Spies, J., Estabrook, R., Kenny, S., Bates, T., Mehta, P., & Fox, J. (2011). OpenMx: An open source extended structural equation modeling framework. Psychometrika, 76, 306–317.CrossRefGoogle ScholarPubMed
Breier, A., Charney, D. S., & Heninger, G. R. (1986). Agoraphobia with panic attacks: Development, diagnostic stability, and course of illness. Archives of General Psychiatry, 43, 1029–1036.CrossRefGoogle ScholarPubMed
Breslau, N., & Davis, G. C. (1985). DSM-III generalized anxiety disorder: An empirical investigation of more stringent criteria. Psychiatry Research, 15, 231–238.CrossRefGoogle ScholarPubMed
Bruce, M., Scott, N., Shine, P., & Lader, M. (1992). Anxiogenic effects of caffeine in patients with anxiety disorders. Archives of General Psychiatry, 49, 867–869.CrossRefGoogle ScholarPubMed
Bulik, C. M., Thornton, L. M., Root, T. L., Pisetsky, E. M., Lichtenstein, P., & Pedersen, N. L. (2010). Understanding the relation between anorexia nervosa and bulimia nervosa in a Swedish national twin sample. Biological Psychiatry, 67, 71–77.CrossRefGoogle Scholar
Charney, D. S., Heninger, G. R., & Jatlow, P. I. (1985). Increased anxiogenic effects of caffeine in panic disorders. Archives of General Psychiatry, 42, 233–243.CrossRefGoogle ScholarPubMed
Ciapparelli, A., Paggini, R., Carmassi, C., Taponecco, C., Consoli, G., Ciampa, G., Ramacciotti, C. E., Marazziti, D., & Dell'Osso, L. (2010). Patterns of caffeine consumption in psychiatric patients: An Italian study. European Journal of Psychiatry, 25, 230–235.CrossRefGoogle ScholarPubMed
Dellava, J. E., Kendler, K. S., & Neale, M. C. (2011). Generalized anxiety disorder and anorexia nervosa: Evidence of shared genetic variation. Depression and Anxiety, 28, 728–733.CrossRefGoogle ScholarPubMed
Dellava, J. E., Thornton, L. M., Lichtenstein, P., Pedersen, N. L., & Bulik, C. M. (2010). Impact of broadening definitions of anorexia nervosa on sample characteristics. Journal of Psychiatric Research, 45, 691–698.CrossRefGoogle ScholarPubMed
Dosh, T., Helmbrecht, T., Anestis, J., Guenthner, G., Kelly, T. H., & Martin, C. A. (2010). A comparison of the associations of caffeine and cigarette use with depressive and ADHD symptoms in a sample of young adult smokers. Journal of Addiction Medicine, 4, 52–54.CrossRefGoogle Scholar
Eaves, L. J., Eysenck, H. J., & Martin, N. G. (1989). Genes, culture and personality: An empirical approach. London: Oxford University Press.Google Scholar
Godart, N. T., Flament, M. F., Curt, F., Perdereau, F., Lang, F., Venisse, J. L., Halfon, O., Bizouard, P., Loas, G., Corcos, M., Jeammet, P., & Fermanian, J. (2003). Anxiety disorders in subjects seeking treatment for eating disorders: A DSM-IV controlled study. Psychiatry Research, 117, 245–258.CrossRefGoogle ScholarPubMed
Grant, B. F., Hasin, D. S., Stinson, F. S., Dawson, D. A., June Ruan, W., Goldstein, R. B., Smith, S. M., Saha, T. D., & Huang, B. (2005). Prevalence, correlates, co-morbidity, and comparative disability of DSM-IV generalized anxiety disorder in the USA: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Psychological Medicine, 35, 1747–1759.CrossRefGoogle ScholarPubMed
Greden, J. F., Fontaine, P., Lubetsky, M., & Chamberlin, K. (1978). Anxiety and depression associated with caffeinism among psychiatric inpatients. American Journal of Psychiatry, 135, 963–966.Google ScholarPubMed
Griffiths, R. R., Juliano, L. M., & Chausmet, A. L. (2003). Caffeine: Pharmacology and clinical effects. Chevy Chase, MD: American Society of Addiction Medicine.Google Scholar
Hettema, J., Neale, M., & Kendler, K. (1995). Physical similarity and the equal-environment assumption in twin studies of psychiatric disorders. Behavior Genetics, 25, 327–335.CrossRefGoogle ScholarPubMed
Hettema, J. M., Neale, M. C., & Kendler, K. S. (2001). A review and meta-analysis of the genetic epidemiology of anxiety disorders. American Journal of Psychiatry, 158, 1568–1578.CrossRefGoogle ScholarPubMed
Hettema, J. M., Prescott, C. A., & Kendler, K. S. (2001). A population-based twin study of generalized anxiety disorder in men and women. Journal of Nervous and Mental Disorders, 189, 413–420.CrossRefGoogle ScholarPubMed
James, K. (1997). Understanding caffeine: A biobehavioral analysis. Thousand Oaks, CA: Sage.Google Scholar
Kaye, W. H., Bulik, C. M., Thornton, L., Barbarich, N., & Masters, K. (2004). Comorbidity of anxiety disorders with anorexia and bulimia nervosa. American Journal of Psychiatry, 161, 2215–2221.CrossRefGoogle ScholarPubMed
Kendler, K. S., & Prescott, C. A. (1999a). A population-based twin study of lifetime major depression in men and women. Archives of General Psychiatry, 56, 39–44.CrossRefGoogle ScholarPubMed
Kendler, K. S., & Prescott, C. A. (1999b). Caffeine intake, tolerance, and withdrawal in women: A population-based twin study. American Journal of Psychiatry, 156, 223–228.CrossRefGoogle ScholarPubMed
Kendler, K. S., Gardner, C. O., Annas, P., Neale, M. C., Eaves, L. J., & Lichtenstein, P. (2008). A longitudinal twin study of fears from middle childhood to early adulthood: Evidence for a developmentally dynamic genome. Archives of General Psychiatry, 65, 421–429.CrossRefGoogle ScholarPubMed
Kendler, K. S., Gardner, C. O., & Prescott, C. A. (2001). Panic syndromes in a population-based sample of male and female twins. Psychological Medicine, 31, 989–1000.CrossRefGoogle Scholar
Kendler, K. S., Karkowski, L. M., & Prescott, C. A. (1999). Fears and phobias: Reliability and heritability. Psychological Medicine, 29, 539–553.CrossRefGoogle ScholarPubMed
Kendler, K. S., MacLean, C., Neale, M. C., Kessler, R. C., Heath, A. C., & Eaves, L. J. (1991). The genetic epidemiology of bulimia nervosa. American Journal of Psychiatry, 148, 1627–1637.Google ScholarPubMed
Kendler, K. S., Myers, J., & O'Gardner, C. (2006). Caffeine intake, toxicity and dependence and lifetime risk for psychiatric and substance use disorders: An epidemiologic and co-twin control analysis. Psychological Medicine, 36, 1717–1725.CrossRefGoogle ScholarPubMed
Kendler, K. S., Myers, J., & Prescott, C. A. (2007). Specificity of genetic and environmental risk factors for symptoms of cannabis, cocaine, alcohol, caffeine, and nicotine dependence. Archives of General Psychiatry, 64, 1313–1320.CrossRefGoogle ScholarPubMed
Kendler, K. S., Neale, M. C., Kessler, R. C., Heath, A. C., & Eaves, L. J. (1992a). Generalized anxiety disorder in women. Archives of General Psychiatry, 49, 267–272.CrossRefGoogle ScholarPubMed
Kendler, K. S., Neale, M. C., Kessler, R. C., Heath, A. C., & Eaves, L. J. (1992b). A population-based twin study of major depression in women: The impact of varying definitions of illness. Archives of General Psychiatry, 49, 257–266.CrossRefGoogle ScholarPubMed
Kendler, K. S., Walters, E. E., Neale, M. C., Kessler, R. C., Heath, A. C., & Eaves, L. J. (1995). The structure of the genetic and environmental risk factors for six major psychiatric disorders in women: Phobia, generalized anxiety disorder, panic disorder, bulimia, major depression and alcoholism. Archives of General Psychiatry, 52, 374–383.CrossRefGoogle ScholarPubMed
Klump, K. L., Miller, K. B., Keel, P. K., McGue, M., & Iacono, W. G. (2001). Genetic and environmental influences on anorexia nervosa syndromes in a population-based twin sample. Psychological Medicine, 31, 737–740.CrossRefGoogle Scholar
Kortegaard, L. S., Hoerder, K., Joergensen, J., Gillberg, C., & Kyvik, K. O. (2001). A preliminary population-based twin study of self-reported eating disorder. Psychological Medicine, 31, 361–365.CrossRefGoogle ScholarPubMed
Lee, M. A., Flegel, P., Greden, J. F., & Cameron, O. G. (1988). Anxiogenic effects of caffeine on panic and depressed patients. American Journal of Psychiatry, 145, 632–635.Google ScholarPubMed
Lee, S., Tsang, A., Ruscio, A. M., Haro, J. M., Stein, D. J., Alonso, J., Angermeyer, M. C., Bromet, E. J., Demyttenaere, K., de Girolamo, G., de Graaf, R., Gureje, O., Iwata, N., Karam, E. G., Lepine, J. P., Levinson, D., Medina-Mora, M. E., Oakley Browne, M. A., Posada-Villa, J., & Kessler, R. C. (2009). Implications of modifying the duration requirement of generalized anxiety disorder in developed and developing countries. Psychological Medicine, 39, 1163–1176.CrossRefGoogle ScholarPubMed
Luciano, M., Kirk, K. M., Heath, A. C., & Martin, N. G. (2005). The genetics of tea and coffee drinking and preference for source of caffeine in a large community sample of Australian twins. Addiction, 100, 1510–1517.CrossRefGoogle Scholar
Luciano, M., Zhu, G., Kirk, K. M., Gordon, S. D., Heath, A. C., Montgomery, G. W., & Martin, N. G. (2007). ‘No thanks, it keeps me awake’: The genetics of coffee-attributed sleep disturbance. Sleep, 30, 1378–1386.CrossRefGoogle ScholarPubMed
Mazzeo, S. E., Mitchell, K. S., Bulik, C. M., Reichborn-Kjennerud, T., Kendler, K. S., & Neale, M. C. (2009). Assessing the heritability of anorexia nervosa symptoms using a marginal maximal likelihood approach. Psychological Medicine, 39, 463–473.CrossRefGoogle ScholarPubMed
Middeldorp, C. M., Birley, A. J., Cath, D. C., Gillespie, N. A., Willemsen, G., Statham, D. J., de Geus, E. J., Andrews, J. G., van Dyck, R., Beem, A. L., Sullivan, P. F., Martin, N. G., & Boomsma, D. I. (2005). Familial clustering of major depression and anxiety disorders in Australian and Dutch twins and siblings. Twin Research and Human Genetics, 8, 609–615.CrossRefGoogle ScholarPubMed
Mosing, M. A., Gordon, S. D., Medland, S. E., Statham, D. J., Nelson, E. C., Heath, A. C., Martin, N. G., & Wray, N. R. (2009). Genetic and environmental influences on the co-morbidity between depression, panic disorder, agoraphobia, and social phobia: A twin study. Depress Anxiety, 26, 1004–1011.CrossRefGoogle ScholarPubMed
Nardi, A. E., Lopes, F. L., Freire, R. C., Veras, A. B., Nascimento, I., Valenca, A. M., de-Melo-Neto, V. L., Soares-Filho, G. L., King, A. L., Araújo, D. M., Mezzasalma, M. A., Rassi, A., & Zin, W. A. (2009). Panic disorder and social anxiety disorder subtypes in a caffeine challenge test. Psychiatry Research, 169, 149–153.CrossRefGoogle Scholar
Nardi, A. E., Lopes, F. L., Valenca, A. M., Freire, R. C., Veras, A. B., de-Melo-Neto, V. L., Nascimento, I., King, A. L., Mezzasalma, M. A., Soares-Filho, G. L., & Zin, W. A. (2007). Caffeine challenge test in panic disorder and depression with panic attacks. Comprehensive Psychiatry, 48, 257–263.CrossRefGoogle ScholarPubMed
Nardi, A. E., Valenca, A. M., Nascimento, I., Freire, R. C., Veras, A. B., de-Melo-Neto, V. L., Lopes, F. L., King, A. L., Soares-Filho, G. L., Mezzasalma, M. A., Rassi, A., & Zin, W. A. (2008). A caffeine challenge test in panic disorder patients, their healthy first-degree relatives, and healthy controls. Depression and Anxiety, 25, 847–853.CrossRefGoogle ScholarPubMed
Neale, M., & Cardon, L. (1992). Methodology for genetic studies of twins and families. Dordrecht, The Netherlands: Kluwer Academic.CrossRefGoogle Scholar
Neale, M., & Maes, H. (1998). Methodology for genetic studies of twins and families. Dordrecht, The Netherlands: Kluwer Academic.Google Scholar
Neale, M. C., Walters, E. E., Eaves, L. J., Kessler, R. C., Heath, A. C., & Kendler, K. S. (1994). Genetics of blood-injury fears and phobias: A population-based twin study. American Journal of Medical Genetics, 54, 326–334.CrossRefGoogle ScholarPubMed
O'Neil, K. A., Conner, B. T., & Kendall, P. C. (2011). Internalizing disorders and substance use disorders in youth: Comorbidity, risk, temporal order, and implications for intervention. Clinical Psychology Review, 31, 104–112.CrossRefGoogle ScholarPubMed
R Development Core Team. (2010). R: A language and environment for statistical computing (Version 2.11.1). Vienna: R Foundation for Statistical Computing.Google Scholar
Raney, T. J., Thornton, L. M., Berrettini, W., Brandt, H., Crawford, S., Fichter, M. M., Halmi, K. A., Johnson, C., Kaplan, A. S., LaVia, M., Mitchell, J., Rotondo, A., Strober, M., Woodside, D. B., Kaye, W. H., & Bulik, C. M. (2008). Influence of overanxious disorder of childhood on the expression of anorexia nervosa. International Journal of Eating Disorders, 41, 326–332.CrossRefGoogle ScholarPubMed
Robins, L. N., & Helzer, J. (1985). Diagnostic Interview Schedule (DIS): Version III-A. St. Louis, MO: Washington University School of Medicine.Google Scholar
Root, T. L., Pisetsky, E. M., Thornton, L., Lichtenstein, P., Pedersen, N. L., & Bulik, C. M. (2010). Patterns of co-morbidity of eating disorders and substance use in Swedish females. Psychological Medicine, 40, 105–115.CrossRefGoogle ScholarPubMed
Salbach-Andrae, H., Lenz, K., Simmendinger, N., Klinkowski, N., Lehmkuhl, U., & Pfeiffer, E. (2008). Psychiatric comorbidities among female adolescents with anorexia nervosa. Child Psychiatry and Human Development, 39, 261–272.CrossRefGoogle ScholarPubMed
Scherrer, J. F., True, W. R., Xian, H., Lyons, M. J., Eisen, S. A., Goldberg, J., Lin, N., & Tsuang, M. T. (2000). Evidence for genetic influences common and specific to symptoms of generalized anxiety and panic. Journal of Affective Disorders, 57, 25–35.CrossRefGoogle ScholarPubMed
Shimbo, M., Nakamura, K., Jing Shi, H., Kizuki, M., Seino, K., Inose, T., & Takano, T. (2005). Green tea consumption in everyday life and mental health. Public Health Nutrition, 8, 1300–1306.CrossRefGoogle ScholarPubMed
Sours, J. A. (1983). Case reports of anorexia nervosa and caffeinism. American Journal of Psychiatry, 140, 235–236.Google ScholarPubMed
Spence, J. E., Corey, L. A., Nance, W. E., Marazita, M. L., Kendler, K. S., & Schieken, R. M. (1988). Molecular analysis of twin zygosity using VNTR DNA probes. American Journal of Human Genetics, 43, A159.Google Scholar
Spitzer, R., Williams, J., Gibbon, M., & First, M. (1988). Structured clinical interview for DSM-III-R: Patient version (SCID-P). New York: Biometrics Research Department, State Psychiatric Institute.Google Scholar
Spitzer, R. L., Williams, J. B., Gibbon, M., & First, M. (1990). Structured clinical interview for DSM-III-R: Patient version. Washington, DC: American Psychiatric Press.Google Scholar
Striegel-Moore, R. H., Franko, D. L., Thompson, D., Barton, B., Schreiber, G. B., & Daniels, S. R. (2006). Caffeine intake in eating disorders. International Journal of Eating Disorders, 39, 162–165.CrossRefGoogle ScholarPubMed
Sullivan, P. F., Neale, M. C., & Kendler, K. S. (2000). Genetic epidemiology of major depression: Review and meta-analysis. American Journal of Psychiatry, 157, 1552–1562.CrossRefGoogle ScholarPubMed
Thornton, L. M., Dellava, J. E., Root, T. L., Lichtenstein, P., & Bulik, C. M. (2011). Anorexia nervosa and generalized anxiety disorder: Further explorations of the relation between anxiety and body mass index. Journal of Anxiety Disorders, 25, 727–730.CrossRefGoogle ScholarPubMed
Walters, E. E., & Kendler, K. S. (1995). Anorexia nervosa and anorexic-like syndromes in a population-based female twin sample. American Journal of Psychiatry, 152, 64–71.Google Scholar
Yang, A., Palmer, A. A., & de Wit, H. (2010). Genetics of caffeine consumption and responses to caffeine. Psychopharmacology, 211, 245–257.CrossRefGoogle ScholarPubMed
Figure 0

FIGURE 1 Measurement of variables for current study.Note: n = number; GAD = generalized anxiety disorder; PAN = panic disorder; PHO = phobia; MDD = major depressive disorder; AN = anorexia nervosa; BN = bulimia nervosa; N/A = not applicable.

Figure 1

FIGURE 2 Bivariate model for psychiatric phenotypes (Psyc) and caffeine phenotypes (Caf).Note: A = heritability component; E = unique environment component; ra = genetic correlation; re = unique environmental/error.

Figure 2

TABLE 1 Model Fit Statistics

Figure 3

TABLE 2 Parameter Estimates for Psychiatric Phenotype Caffeine Use

Figure 4

TABLE 3 Parameter Estimates for Psychiatric Phenotype and Caffeine Tolerance

Figure 5

TABLE 4 Parameter Estimates for Psychiatric Phenotype and Caffeine Withdrawal