0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Article |

Using Dimensional Models of Externalizing Psychopathology to Aid in Gene Identification FREE

Danielle M. Dick, PhD; Fazil Aliev, PhD; Jen C. Wang, PhD; Richard A. Grucza, PhD; Marc Schuckit, MD; Samuel Kuperman, MD; John Kramer, PhD; Anthony Hinrichs, PhD; Sarah Bertelsen, MS; John P. Budde, BA; Victor Hesselbrock, PhD; Bernice Porjesz, PhD; Howard J. Edenberg, PhD; Laura Jean Bierut, MD; Alison Goate, PhD
[+] Author Affiliations

Author Affiliations: Washington University in St Louis, St Louis, Missouri (Drs Dick, Aliev, Wang, Grucza, Hinrichs, Bierut, and Goate, and Ms Bertelsen and Mr Budde); Ankara University, Ankara, Turkey (Dr Aliev); University of California, San Diego VA Medical Center, San Diego (Dr Schuckit); University of Iowa College of Medicine, Iowa City (Drs Kuperman and Kramer); University of Connnecticut Health Center, Farmington (Dr Hesselbrock); State University of New York Downstate Medical Center, Brooklyn (Dr Porjesz); and Indiana University School of Medicine, Indianapolis (Dr Edenberg). Dr Dick is now with Virginia Commonwealth University, Richmond.


Arch Gen Psychiatry. 2008;65(3):310-318. doi:.
Text Size: A A A
Published online

Context  Twin studies provide compelling evidence that alcohol and drug dependence, childhood conduct disorder, adult antisocial behavior, and disinhibitory personality traits share an underlying genetic liability that contributes to a spectrum of externalizing behaviors. However, this information has not been widely used in gene identification efforts, which have focused on specific disorders diagnosed using traditional psychiatric classification systems.

Objective  To test the utility of using a multivariate externalizing phenotype in (1) linkage analyses and (2) association analyses to identify genes that contribute broadly to a spectrum of externalizing disorders.

Design  Data were analyzed from the Collaborative Study on the Genetics of Alcoholism. Linkage analyses were conducted using data from a genome-wide 10-cM microsatellite scan. Association analyses were conducted on 27 single-nucleotide polymorphisms genotyped across a candidate gene, the muscarinic acetylcholine receptor M2 gene (CHRM2).

Setting  Six centers across the United States.

Other Participants  Approximately 2300 individuals from 262 families.

Main Outcome Measures  Lifetime symptom counts of alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder and novelty seeking, sensation seeking, and general externalizing component scores consisting of a composite of the previous 6 variables.

Results  Principal component analyses indicated that the 6 individual variables loaded on a single externalizing factor. Linkage analyses using the resultant component scores identified a region on chromosome 7 consistent with a gene that broadly predisposes individuals to externalizing behavior. Association analyses of a candidate gene, CHRM2, previously of interest in the Collaborative Study on the Genetics of Alcoholism, suggest that it is involved in a general externalizing phenotype.

Conclusions  Broader conceptualizations of psychiatric disorders, such as studying a spectrum of externalizing psychopathology, may aid in identifying susceptibility genes and understanding the pathways through which genetic factors affect vulnerability for a variety of poor outcomes.

Figures in this Article

Efforts to identify genes involved in psychiatric disorders have largely used categorical models of diagnosis. Consequently, there are separate, large-scale gene identification projects under way that each focus on a particular psychiatric outcome as a qualitative phenotype. For example, these funded projects concentrate on identifying genes involved in alcohol dependence,1 schizophrenia,2 bipolar disorder,3 autism,4 major depression,5 attention-deficit/hyperactivity disorder,6 nicotine dependence,7 and illicit drug dependence.8 This likely reflects, in part, the ubiquitous influence of the DSM for the classification of psychiatric disorders in research as well as in practice.

While there is evidence that this strategy has been successful in identifying replicable associations between specific genes and a handful of psychiatric disorders (eg, GABRA2 and ADH4 associated with alcohol dependence914 and dystrobrevin binding protein 1 [DTNBP1] and neuregulin 1 [NRG1] with schizophrenia15,16), a narrow focus on specific psychiatric outcomes in isolation may lead us to miss some important genetic variants that influence susceptibility through pathways shared across psychiatric outcomes. Twin studies have been pivotal in demonstrating shared genetic liability across a variety of psychiatric disorders. One of the largest studies of this kind, conducted by Kendler and colleagues,17 examined the underlying structure of genetic and environmental risk factors across 10 common psychiatric disorders using data from the Virginia Twin Study. They found that genetic factors predispose individuals to 2 broad groups of behavior: externalizing disorders and internalizing disorders. Alcohol dependence, drug abuse/dependence, adult antisocial behavior, and childhood conduct disorder all loaded on 1 genetic factor, while major depression and anxiety disorders loaded on a second genetic factor.17 These results indicate that some genetic factors broadly predispose individuals to a variety of externalizing disorders, with a parallel interpretation for the internalizing disorders. This does not preclude the possibility that some genetic influences are disorder specific; in particular, alcohol and drug dependence showed evidence for substantial disorder-specific genetic risk factors, which may reflect genes involved in the metabolism of drugs, such as the involvement of the ADH and ALDH genes in alcohol dependence.12,1820 However, most of the genetic variance for alcohol dependence, drug abuse/dependence, adult antisocial behavior, and childhood conduct disorder in the study by Kendler et al17 was shared across the externalizing disorders, suggesting that an underlying genetic liability may contribute to a spectrum of externalizing disorders. Similarly, most of the genetic variance on major depression, generalized anxiety disorder, and phobias was shared across the disorders. These findings are consistent with the clinical observation of patterns of comorbidity across psychiatric disorders.21,22 Furthermore, model-fitting approaches have demonstrated that phenotypic patterns of comorbidity across externalizing disorders are better represented by dimensional models of psychopathology, as opposed to categorical models, again supporting an argument for using dimensional models of externalizing in research efforts.23 We will focus our review on externalizing disorders, as this dimension of psychiatric problems is most relevant to the analyses reported herein, though we will return to the implications of our results for a number of psychiatric outcomes in the discussion.

A number of other studies lend further support to the premise that shared genetic factors influence externalizing disorders. A family study examining the transmission of alcohol dependence, drug abuse/dependence, adult antisocial personality disorder, and childhood conduct disorder suggested that a general vulnerability to externalizing disorders largely accounted for familial resemblance, with this general liability being highly heritable (h2 = 0.80).24Several twin studies also suggest that a latent externalizing factor, including conduct disorder, adult antisocial behavior, alcohol and drug abuse/dependence, and disinhibitory personality traits, is highly heritable (80%-85%).25,26Thus, this latent externalizing factor appears to be more heritable than the individual disorders themselves, which show individual heritabilities of approximately 50%.27 A final piece of evidence suggesting a shared genetic liability across externalizing psychopathology comes from the electrophysiological literature in which a number of electrophysiological endophenotypes thought to represent markers of genetic vulnerability are shared across the spectrum of externalizing disorders, including alcohol dependence, other forms of substance dependence, childhood externalizing disorders, and adult antisocial personality disorder.2835

Despite overwhelming evidence for shared genetic factors that influence a spectrum of externalizing psychopathology, this information has not been widely used in gene identification efforts. Herein, we report analyses from the Collaborative Study on the Genetics of Alcoholism (COGA), in which we have examined a broad phenotype of externalizing behavior by creating component scores composed of lifetime symptoms of alcohol dependence, illicit drug dependence, adult antisocial behavior, and childhood conduct disorder, along with disinhibitory personality traits. We report results from 2 sets of analyses aimed at exploring the utility of a broad externalizing phenotype in genetic studies. First, we report genome-wide linkage analyses using these externalizing component scores. Second, we report results from association analyses with a candidate gene that has previously been associated with alcohol dependence36,37 and electrophysiological endophenotypes38 in the COGA sample, the muscarinic acetylcholine receptor M2 gene (CHRM2). The rationale for examining this gene in relation to general externalizing behavior is based on follow-up analyses of CHRM2, which indicated that the evidence for association with alcohol dependence in the COGA sample was driven entirely by alcohol-dependent individuals with comorbid drug dependence.39 This subgroup was also characterized by higher rates of antisocial personality disorder and conduct disorder, suggesting that the associated subgroup may represent individuals with a predisposition toward general disinhibitory psychopathology. In addition, the gene was associated with evoked electroencephalography oscillations in the COGA sample,38 an electrophysiological endophenotype that is shared across externalizing disorders.32 Accordingly, we present results from both linkage and association analyses, illustrating the use of externalizing scores across genetic methodologies. We believe the results converge to illustrate that broader conceptualizations of psychiatric disorders may help us to identify genes involved in susceptibility of psychiatric problems and to understand the pathways through which genetic factors operate to influence such disorders.

SAMPLE

The COGA is a project in which families were recruited from 6 centers across the United States: Indiana University, Downstate University of New York Health Science Center, University of Connecticut, University of Iowa, University of California at San Diego, and Washington University in St Louis. Probands identified through inpatient or outpatient alcohol treatment programs by each of these 6 sites were invited to participate if they had a sufficiently large family (usually sibships > 3 with parents available) with 2 or more members in a COGA catchment area.40 The institutional review boards of all participating centers approved the study and written consent was obtained from all participants. Additional details about the study have been published previously.1,40 The sample available for genetic analyses consisted of 262 families with 2131 genotyped and phenotyped individuals, 1007 males and 1124 females, who were members of families in which at least 3 first-degree relatives met DSM criteria for alcohol dependence.

PHENOTYPES

All individuals were administered the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) interview.41,42 Lifetime alcohol dependence was assessed using DSM-IV criteria.43 Other lifetime diagnoses (drug dependence, antisocial personality disorder, and childhood conduct disorder) were assessed using DSM-IIIR criteria, as DSM-IV was under development at the time interviews were initiated; only the alcohol dependence section was adapted to emulate DSM-IV diagnoses. Symptom counts for each of the disorders (alcohol dependence, drug dependence, antisocial personality disorder, and childhood conduct disorder) were used in linkage and association analyses. Symptom counts were log transformed to reduce the skewness of their distributions.

In addition, 2 personality variables that were hypothesized to be related to the externalizing spectrum were included in analyses and computation of the externalizing component scores: novelty seeking scores from the Tridimensional Personality Questionnaire44 and sensation seeking scores from the Zuckerman Sensation Seeking Scale.45

STATISTICAL ANALYSES
Computation of Component Scores

Principal component analysis was used to evaluate the factor structure of lifetime alcohol dependence symptoms, drug dependence symptoms, antisocial personality disorder symptoms, conduct disorder symptoms, and novelty and sensation seeking scores. Components with eigenvalues greater than 1 were retained. Analyses were conducted using SAS, version 8 (SAS Institute Inc, Cary, North Carolina).

Linkage Analyses

Genotyping for the microsatellite linkage scan was carried out in laboratories at Indiana University and Washington University in St Louis using radioactive- and fluorescence-based detection systems, as described previously.46 The current analyses are based on a map of 315 autosomal microsatellite markers with a mean intermarker distance of 11.5 cM. Pedigrees were checked for nonmendelian inheritance using the GeneMaster database and the programs CRIMAP, version 2.4 (Phil Green, Washington University, St Louis, Missouri), and USERM13 (University of Michigan, Ann Arbor).47 Recombination-based marker maps were generated from the sample using CRIMAP. Maximum likelihood estimates of marker allele frequencies were computed from the data using USERM13. Multipoint linkage analyses were carried out using MERLIN Regress software (University of Michigan, Ann Arbor).48 This regression-based approach to quantitative trait linkage, based on the work of Sham and colleagues,49 can handle nonrandomly ascertained samples and deviations from multivariate normality of the observed data but retains the statistical power of variance-components linkage methods. The complexity of several large, multigenerational COGA families required that familial structures be simplified to make data analysis feasible and efficient with available hardware; 7 families were divided into separate branches. The mean family size in the analysis data file was 8.13 members, and the mean number of generations per family was 2.89 (range, 2-5). There were 2386 sibling, 152 half-sibling, 1971 parent-child, 249 grandparent-grandchild, 1509 avuncular, and 707 cousin pairs used in analyses. We used a heritability estimate of 80% in our analyses for the externalizing factor scores and 50% for other phenotypes based on existing twin literature. Multipoint lod scores were estimated. Evidence for a chromosomal region containing a gene that broadly predisposes individuals to externalizing behaviors would be suggested by a pattern of results in which the strongest evidence for linkage was found using the component scores, with the individual phenotypes showing more modest evidence of linkage to the same region (since quantitative symptom counts were analyzed for the individual disorders, sample size is virtually identical across phenotypes allowing for direct comparison of lod scores). Chromosomal regions that yielded results following this pattern with an overall externalizing lod score of 1.5 or higher are presented here.

Association Analyses

Publicly available databases, dbSNP (http://www.ncbi.nlm.nih.gov/SNP/) and the International HapMap Project (http://www.hapmap.org), were used to identify single-nucleotide polymorphisms (SNPs) within and flanking CHRM2. In addition, a number of novel SNPs were identified by DNA sequencing. We genotyped 27 SNPs within and flanking CHRM2.50 Single nucleotide polymorphisms were selected to cover the single coding exon as well as all 5 exons in the promoter region and a region in intron 3 that is conserved across multiple species. The minor allele frequency was greater than 0.10 in all cases (mean, 0.45). Genotyping was done with a modified single nucleotide extension reaction, with allele detection by mass spectroscopy (Sequenom MassARRAY System; Sequenom, San Diego, California). All genotypic data were checked for mendelian inheritance of marker alleles with the USERM1347 option of the MENDEL linkage computer programs (University of Michigan, Ann Arbor), which was then used to estimate marker allele frequencies. Trio data from white individuals genotyped in the COGA data set were entered into the Haploview program51 to examine the linkage disequilibrium structure of the genotyped SNPs. Six linkage disequilibrium blocks were identified in our data set, with several SNPs located in interblock regions. Information about the linkage disequilibrium block structure of the SNPs is included in Table 1.

Table Graphic Jump LocationTable 1. Family-Based Association Analyses of Externalizing Psychopathology Symptoms and Scores

Association was evaluated with the Quantitative Pedigree Disequilibrium Test using the QPDTPHASE program contained in the UNPHASED software suite (MRC Human Genome Mapping Project Resource Centre, Cambridge, England).52 QPDTPHASE implements the quantitative trait in the Pedigree Disequilibrium Test described by Monks and Kaplan,53 with extensions to deal with haplotypes and missing data. The null hypothesis is no linkage or no association, in which the trait and genotypes are uncorrelated. The covariance is estimated within each family and the estimates combined across the data set by the central limit theorem. We tested for association with each of the SNPs genotyped in CHRM2 and the externalizing component scores, as well as each of the component phenotypes (eg, log-transformed symptom counts for each of the 4 externalizing disorders and the 2 personality scales) that composed the component scores.

PRINCIPAL COMPONENT ANALYSES

Table 2 presents the correlations across the externalizing variables used in the principal component analyses. Only 1 component was extracted with an eigenvalue greater than 1.0. The first component had an eigenvalue of 3.20 and accounted for 53% of the variance. There was an eigenvalue difference of 2.30 between the first and second factors, and all other factors accounted for less than 15% of the variance. All variables loaded onto the first factor. The component loadings for each of the variables were as follows: alcohol dependence symptoms, 0.74; antisocial personality disorder symptoms, 0.83; conduct disorder symptoms, 0.69; drug dependence symptoms, 0.76; novelty seeking scores, 0.65; and sensation seeking scores, 0.71. Component scores for this first latent component, which were composed of the 6 externalizing variables, were computed for all individuals and used in linkage and association analyses.

Table Graphic Jump LocationTable 2. Pearson Correlations Between Externalizing Variables
LINKAGE ANALYSES

We found 1 region of the genome that yielded the hypothesized pattern of results, with the strongest evidence of linkage associated with the externalizing component score and more modest evidence with the individual phenotypes. This region was on chromosome 7, with a peak lod score for the component score of 1.57 at 101.9 cM at the marker D7S1797 (Figure 1). We have previously reported linkage using affected sibling pair analyses with COGA alcohol dependence diagnoses (defined by a DSM-IIIR diagnosis of alcohol dependence and Feighner definite criteria) in this region on chromosome 7.36 The peak lod score with COGA alcohol dependence was approximately 20 cM more distal. Those analyses used a dichotomous affection status method of analysis. Accordingly, they differed from our report both in the breadth of the phenotype (alcohol dependence vs a broader externalizing phenotype) and the methodology. To further explore the possibility that a gene in this region more generally predisposes individuals to externalizing disorders, we conducted secondary linkage analyses on chromosome 7 using an affected sibling pair method to more closely mimic analyses used in the study of linkage to alcohol dependence by Wang et al.36 We used the sib_ibd option in the program ASPEX,54 which limits the analyses to only affected sibling pairs with genotyped parents, allowing for unambiguous estimation of identity by descent. We ran analyses separately using sibling pairs affected with each disorder: DSMIV alcohol dependence (557 pairs from 231 families), adult antisocial personality disorder (471 pairs from 191 families), childhood conduct disorder (113 pairs from 67 families), and illicit drug dependence (405 pairs from 175 families). Finally, we analyzed a combined, dichotomous externalizing disorder phenotype, whereby individuals were considered affected if they met criteria for any of the 4 aforementioned disorders (948 pairs from 290 families). Thus, for this externalizing disorder phenotype, an affected sibling pair could consist of a pair in which, for example, 1 sibling was affected with alcohol dependence and the other sibling met criteria for antisocial behavior. These analyses differed in that they used binary diagnoses (affected/unaffected) rather than quantitative symptom counts. In addition, we could not include the quantitative personality scores in the analyses. However, performing linkage analysis with this externalizing phenotype again tests the hypothesis that these disorders are alternative manifestations of a shared underlying vulnerability, the specific expression of which may depend on additional genes and/or the environment. Although the results from the affected sibling pair analyses should be interpreted while keeping in mind that the sample size changed across phenotypes and that lod scores are influenced by sample size, the pattern of results replicates that seen with the quantitative externalizing component score analyses: modest evidence of allele sharing with each of the individual disorders, with the strongest evidence for linkage in the region found with the broad externalizing disorder phenotype (Figure 2). The peak lod score was 2.11 at 122.9 cM near the marker D7S1796.

Place holder to copy figure label and caption
Figure 1.

Linkage analyses from chromosome 7 using MERLIN Regress software (University of Michigan, Ann Arbor)48 for externalizing component scores and component phenotypes. AD indicates alcohol dependence symptoms; ASPD, antisocial personality disorder symptoms; CD, conduct disorder symptoms; DD, drug dependence symptoms; NS, novelty seeking score; SS, sensation seeking score.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Linkage analyses from chromosome 7 using affected sibling pair methods in ASPEX.54 AD indicates alcohol dependence diagnosis; ASPD, antisocial personality disorder diagnosis; CD, conduct disorder diagnosis; DD, drug dependence diagnosis; ExtDis, any externalizing disorder.

Graphic Jump Location
ASSOCIATION ANALYSES

The results from association analyses between SNPs genotyped across CHRM2 and each of the quantitative phenotypes (symptom counts of alcohol dependence, drug dependence, antisocial personality disorder, and childhood conduct disorder; novelty seeking and sensation seeking scores; and general externalizing component scores) are presented in Table 1. Although all phenotypes show some SNPs to be significant (P < .05), the association is strongest with the general externalizing component score, with 6 of the 27 SNPs yielding P < .01 compared with 1 SNP significant at this level with alcohol dependence symptoms, 0 with antisocial personality disorder or conduct disorder symptoms, 2 with drug dependence symptoms, 2 with novelty seeking scores, and 2 with sensation seeking scores. Furthermore, the component score appears to concentrate the evidence for association to the third linkage disequilibrium block, located on intron 3 to 4, with 5 of 7 SNPs in this block significant (P < .01) and the other 2 SNPs in the block yielding P values of .15 and .01 with general externalizing component scores. Table 3 presents the linkage disequilibrium across the SNPs located in block 3 and also includes the SNP located between blocks 2 and 3, which shows evidence of an association with the component scores. Although the D′ is very high across the SNPs, the r2 values are less than 1.0, indicating that these SNPs are not purely redundant and do yield some independent evidence for association.

Table Graphic Jump LocationTable 3. Linkage Disequilibrium (LD) Across the SNPs Located in CHRM2 LD Block 3a

Gene identification studies in psychiatry have traditionally focused on clinically diagnosed psychiatric disorders. Recognition of the limitations of this approach has led to increasing interest in using endophenotypes in gene identification projects, based on the hypothesis that these may represent simpler phenotypes more proximal to the underlying genetic effects.5557 In this article, we argue that another strategy to advance our understanding of genetic contributions to psychiatric outcome is to use information from twin and family studies about the underlying structure of genetic influences on behavior to define relevant phenotypes for genetic analysis.

There is a large body of evidence suggesting that shared genetic factors influence a spectrum of externalizing disorders, including alcohol dependence, illicit drug dependence, conduct disorder, antisocial behavior, and disinhibitory personality traits. However, up to this point, this information has not been integrated largely into efforts to identify genes involved in the externalizing spectrum as a whole, with a recent exception in a study of adolescents.58 Here, we analyzed multivariate externalizing phenotypes that encompassed information across alcohol dependence symptoms, illicit drug dependence symptoms, conduct disorder symptoms, antisocial personality disorder symptoms, and disinhibitory personality traits. We found evidence of linkage to a region of chromosome 7, which appears to contain a gene (or genes) conferring risk to the spectrum of externalizing psychopathology. Although the linkage is modest in this region (maximum lod score, 1.6), our confidence in this finding is bolstered by the parallel pattern of results yielded by affected sibling pair analyses. In addition, we ascertained the sample through alcohol-dependent probands at treatment centers, which can lead to skewed estimates of the mean and variance of the quantitative traits and weaken the power to detect linkage (though there is no evidence that this ascertainment scheme would inflate a type 1 error).49 A genome-wide linkage scan of the P3 event-related potential in a sample of 647 twins/siblings from 311 families in Australia also found significant evidence of linkage (lod score, 3.88) to the same region of chromosome 7q.59 To the extent that the P3 event-related potential reflects a predisposition toward general externalizing disorders,33,60 these results further support our conclusion of genetic factors in this region predisposing individuals to a constellation of disinhibitory behaviors.

In addition, we found evidence from association analyses that CHRM2 predisposes individuals to a spectrum of externalizing behaviors. We note that although CHRM2 is located on chromosome 7, it is not located under the linkage peak but is rather approximately 55 cM distal to the externalizing component scores peak. It was originally genotyped and analyzed in relation to alcohol dependence in the COGA sample36 owing to its proximity to a linkage peak observed with the visual oddball paradigm theta frequency band–evoked oscillation, which is the primary constituent of the P3-evoked component.38 To the extent that the linkage at CHRM2 was observed with an electrophysiological endophenotype known to index general risk to a spectrum of externalizing disorders, it is encouraging that we found evidence that the association observed with CHRM2 similarly fits this pattern. Although CHRM2 is not directly under the linkage peak identified here, simulations have demonstrated that the exact location of linkage peaks can be imprecise in relation to the underlying gene(s) involved61; accordingly, to test whether the association of CHRM2 was related to the linkage signal, we performed the linkage analyses again with the externalizing component scores using the most significantly associated SNP in CHRM2 (rs1378646) as a covariate. The evidence for linkage was virtually unchanged (maximum lod at peak, 1.49, compared with 1.57 without covariate), suggesting that CHRM2 had an independent influence on general externalizing behavior and that the linkage signal identified here on chromosome 7 reflects additional genetic variants in the region that influences general externalizing behavior.

We believe these analyses demonstrate that the strategy of using multivariate externalizing phenotypes can be useful in both linkage and association analyses in identifying genes that broadly predispose individuals to a spectrum of risk that spans traditional psychiatric classification systems. Groups studying other psychiatric conditions have also adopted this approach. For example, ongoing gene identification projects in both Virginia and the Netherlands are capitalizing on the literature that demonstrates that depression and anxiety share a common genetic etiology62 and are using multivariate phenotypes consisting of symptoms of depressive and anxious disorders, as well as the related personality trait, neuroticism,63 in genetic studies.64,65 Furthermore, genetic findings of schizophrenia overlap with those of bipolar disorder, suggesting that there may be shared susceptibility across these disorders, perhaps through involvement of psychosis.66

Identification of genes that confer vulnerability across psychiatric conditions may provide insight into the pathways through which specific genes are involved in outcome. For example, although we previously reported an association between CHRM2 and alcohol dependence,36 these analyses, demonstrating involvement in a broader spectrum of externalizing, suggest that CHRM2 is involved in risk for alcohol dependence via more general disinhibitory pathways. The means through which genetic variants in CHRM2 contribute to functional differences remain unknown. However, clues about the mechanism through which CHRM2 may be involved in a variety of behavioral outcomes can be found in the electrophysiological literature. Our COGA colleagues have previously proposed a model in which they suggest that evoked response potential abnormalities, evident in individuals at risk for a number of forms of externalizing psychopathology, represent a deficit of central nervous system inhibition and/or an excess of central nervous system excitation.67 This central nervous system hyperexcitability reflects a disequilibrium in the homeostatic mechanisms that are responsible for maintaining a balance between excitation and inhibition. The inverse relationship between severity of alcohol dependence and P3 amplitude supports the idea that an imbalance in central nervous system excitation and inhibition has implications for behavior. Variations in CHRM2 may be involved in creating this homeostatic imbalance, which may in turn increase risk for a number of outcomes. We note that in addition to the association with externalizing disorders reported here, CHRM2 has also been associated with performance on IQ tests,50,68,69 heart rate recovery after exercise,70 and depression.36 Accordingly, this muscarinic receptor appears to have broad-based effects on behavior, and there may be multiple variants in the gene affecting different outcomes.50 Better understanding of the biologic alterations associated with genetic variation in CHRM2 will be necessary to understand exactly how this gene affects outcome.

In this article, we have compared the results from genetic analyses that separately examined clinical phenotypes that fall under the spectrum of externalizing psychopathology (ie, alcohol dependence, antisocial personality disorder, conduct disorder, and illicit drug dependence) with results from analyses of a composite phenotype that combined information across forms of externalizing psychopathology. As previously stated, twin studies have suggested that much of the genetic variation is shared across these disorders by a general externalizing factor, with some evidence for residual disorder-specific variance. Analyses of the separate psychiatric disorders essentially combine both the general (common) and specific genetic components. In our analyses reported here, we focused on the general component by analyzing the latent externalizing composite scores. We also conducted secondary analyses examining the residual scores for each of the clinical phenotypes (eg, the residual variance in alcohol dependence symptom scores after the externalizing scores were regressed out). There was no longer evidence for linkage on chromosome 7 with any of the residual scores (lod scores < 0.1). Similarly, there was little evidence of association of SNPs in CHRM2 with the residual scores. These analyses suggest that the strongest contribution to the linkage peak on chromosome 7 and, separately, the association observed with CHRM2 are due to a general influence on externalizing psychopathology.

With the development of the DSM-V under way, there has been much discussion about the use of dimensional models of psychiatric diagnoses, with a suggestion that augmenting traditional categorical diagnoses with dimensional information will be critical for the future of psychiatric research.23,71 Here, we demonstrate that gene identification in psychiatry is one area that could benefit from dimensional models of psychopathology.

Correspondence: Danielle M. Dick, PhD, Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA 23298-0126 (ddick@vcu.edu).

Submitted for Publication: February 22, 2007; final revision received May 22, 2007; accepted June 26, 2007.

Financial Disclosure: None reported.

Funding/Support: The COGA is supported by grant U10AA08401 from the National Institute on Alcohol Abuse and Alcoholism and the National Institute on Drug Abuse.

Additional Contributions: The COGA (principal investigators, Drs Bierut, Edenberg, Hesselbrock, and Porjesz) includes 9 different centers where data collection, analysis, and storage take place. The 9 sites (and principal investigators and coinvestigators) are the University of Connecticut, Farmington (Victor Hesselbrock, PhD); Indiana University, Indianapolis (Dr Edenberg; John Nurnberger Jr, MD, PhD; P. Michael Conneally, PhD; Tatiana Foroud, PhD); University of Iowa, Iowa City (Dr Kuperman and Raymond Crowe, MD); State University of New York Downstate Medical Center, Brooklyn (Dr Porjesz); Washington University in St Louis (Drs Bierut and Goate, and John Rice, PhD); University of California at San Diego (Dr Schuckit); Howard University, Washington, DC (Robert Taylor, MD, PhD); Rutgers University, New Brunswick, New Jersey (Jay Tischfield, PhD); and Southwest Foundation for Biomedical Research, San Antonio, Texas (Laura Almasy, PhD). Zhaoxia Ren, PhD, serves as the National Institute on Alcohol Abuse and Alcoholism staff collaborator. This study is in memory of Henri Begleiter, PhD, and Theodore Reich, MD, principal and coprincipal investigators of COGA; we acknowledge their immeasurable and fundamental scientific contributions to COGA and the field.

Begleiter  HReich  THesselbrock  VPorjesz  BLi  TKSchuckit  MEdenberg  HJRice  J The Collaborative Study on the Genetics of Alcoholism. Alcohol Health Res World 1995;19228- 236
Levinson  DFHolmans  PStraub  REOwen  MJWildenauer  DBGejman  PVPulver  AELaurent  CKendler  KSWalsh  DNorton  NWilliams  NMSchwab  SLerer  BMowry  BJSander  AAntonarakis  SEBlouin  JLDeLeuze  JFMallet  J Multicenter linkage study of schizophrenia candidate regions on chromosomes 5q, 6q, 10p, and 13q: schizophrenia linkage collaborative group III. Am J Hum Genet 2000;67 (3) 652- 663
PubMed
 Genomic survey of bipolar illness in the NIMH Genetics Initiative pedigrees: a preliminary report. Am J Med Genet 1997;74 (3) 227- 237
PubMed
Hutcheson  HBBradford  YFolstein  SEGardiner  MBSantangelo  SLSutcliffe  JSHaines  JL Defining the autism minimum candidate gene region on chromosome 7. Am J Med Genet B Neuropsychiatr Genet 2003;117 (1) 90- 96
PubMed
Levinson  DFZubenko  GSCrowe  RDePaulo  JRScheftner  WSWeissman  MMHolmans  PZubenko  WNBoutelle  SMurphy-Eberenz  KMacKinnon  DFMcInnis  MGMarta  DHAdams  PBSassoon  SKnowles  JAThomas  JChellis  J Genetics of recurrent early-onset depression (GenRED): design and preliminary clinical characteristics of a repository sample for genetic linkage studies. Am J Med Genet B Neuropsychiatr Genet 2003;119 (1) 118- 130
PubMed
Faraone  SV Report from the 4th international meeting of the attention deficit hyperactivity disorder molecular genetics network. Am J Med Genet B Neuropsychiatr Genet 2003;121 (1) 55- 59
PubMed
Madden  PASaccone  SFPergadia  MLAgrawal  ATodorov  AADick  DMLoukola  ABroms  UMaunu  HHeikkila  KWiden  EMontgomery  GPeltonen  LKaprio  JMartin  NGRice  J Genetic vulnerability for nicotine dependence: linkage results from the NAG (Nicotine Addiction Genetics) project. Am J Med Genet B Neuropsychiatr Genet 2005;13816
 NIDA Genetics Consortium. http://www.drugabuse.gov/about/organization/Genetics/consortium/. Accessed December 21, 2007
Edenberg  HJDick  DMXuei  XTian  HAlmasy  LBauer  LOCrowe  RGoate  AHesselbrock  VJones  KAKwon  JLi  TKNurnberger  JI  JrO'Connor  SJReich  TRice  JSchuckit  MPorjesz  BForoud  TBegleiter  H Variations in GABRA2, encoding the α2 subunit of the GABA-A receptor are associated with alcohol dependence and with brain oscillations. Am J Hum Genet 2004;74 (4) 705- 714
PubMed
Covault  JGelernter  JHesselbrock  VNellissery  MKranzler  HR Allelic and haplotypic association of GABRA2 with alcohol dependence. Am J Med Genet B Neuropsychiatr Genet 2004;129 (1) 104- 109
PubMed
Drgon  TD'Addario  CUhl  GR Linkage disequilibrium, haplotype and association studies of a chromosome 4 GABA receptor gene cluster: candidate gene variants for addictions. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics) 2006;141 (8) 854- 860
PubMed
Edenberg  HJXuei  XChen  H-JTian  HWetherill  LFDick  DMAlmasy  LBierut  LBucholz  KKGoate  AHesselbrock  VKuperman  SNurnberger  JI  JrPorjesz  BRice  JSchuckit  MTischfield  JABegleiter  HForoud  T Association of alcohol dehydrogenase genes with alcohol dependence: a comprehensive analysis. Hum Mol Genet 2006;15 (9) 1539- 1549
PubMed
Luo  XKranzler  HZuo  LLappalainen  JYang  BZGelernter  J ADH4 gene variation is associated with alcohol dependence and drug dependence in European Americans: results from HWD tests and case-control association studies. Neuropsychopharmacology 2006;31 (5) 1085- 1095
PubMed
Luo  XKranzler  HRZuo  LYang  BZLappalainen  JGelernter  J ADH4 gene variation is associated with alcohol dependence and drug dependence in European Americans: results from family-controlled and population-structured association studies. Pharmacogenet Genomics 2005;15 (11) 755- 768
PubMed
Norton  NWilliams  HJOwen  M An update on the genetics of schizophrenia. Curr Opin Psychiatry 2006;19 (2) 158- 164
PubMed
Riley  BKendler  KS Molecular genetic studies of schizophrenia. Eur J Hum Genet 2006;14 (6) 669- 680
PubMed
Kendler  KSPrescott  CMyers  JNeale  MC The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Arch Gen Psychiatry 2003;60 (9) 929- 937
PubMed
Whitfield  JB Meta-analysis of the effects of alcohol dehydrogenase genotype on alcohol dependence and alcoholic liver disease. Alcohol Alcohol 1997;32 (5) 613- 619
PubMed
Shen  Y-CFan  J-HEdenberg  HJLi  TKCui  Y-HWang  Y-FTian  C-HZhou  C-FZhou  R-LWang  JZhao  Z-LXia  G-Y Polymorphism of ADH and ALDH genes among four ethnic groups in China and effects upon the risk for alcoholism. Alcohol Clin Exp Res 1997;21 (7) 1272- 1277
PubMed
Luo  XKranzler  HRZuo  LWang  SLappalainen  JSchork  NJGelernter  J Diplotype trend regression (DTR) analysis of the ADH gene cluster and ALDH2: multiple significant associations for alcohol dependence. Am J Hum Genet 2006;78 (6) 973- 987
PubMed
Kessler  RCChui  WTDemler  OWalters  EE Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005;62 (6) 617- 627[erratum published in Arch Gen Psychiatry. 2005;62(7):709. Merikangas KR added].
PubMed
Krueger  RFMarkon  KE Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annu Rev Clin Psychol 2006;2111- 133
PubMed
Krueger  RFMarkon  KEPatrick  CJIacono  WG Externalizing psychopathology in adulthood: A dimensional-spectrum conceptualization and its implications for DSM-VJ Abnorm Psychol 2005;114 (4) 537- 550
PubMed
Hicks  BMKrueger  RFIacono  WGMcGue  MPatrick  CJ Family transmission and heritability of externalizing disorders: a twin-family study. Arch Gen Psychiatry 2004;61 (9) 922- 928
PubMed
Krueger  RFHicks  BMPatrick  CJCarlson  SRIacono  WGMcGue  M Etiologic connections among substance dependence, antisocial behavior, and personality: modeling the externalizing spectrum. J Abnorm Psychol 2002;111 (3) 411- 424
PubMed
Young  SEStallings  MCCorley  RPKrauter  KSHewitt  JK Genetic and environmental influences on behavioral disinhibition. Am J Med Genet 2000;96 (5) 684- 695
PubMed
Moffitt  TE Genetic and environmental influences on antisocial behaviors: evidence from behavioral-genetic research. Adv Genet 2005;5541- 104
PubMed
Yoon  HHIacono  WGMalone  SMMcGue  M Using the brain P300 response to identify novel phenotypes reflecting genetic vulnerability for adolescent substance misuse. Addict Behav 2006;31 (6) 1067- 1087
PubMed
Iacono  WGCarlson  SRMalone  SMMcGue  M P3 event-related potential amplitude and the risk for disinhibitory disorders in adolescent boys. Arch Gen Psychiatry 2002;59 (8) 750- 757
PubMed
Malone  SMIacono  WGMcGue  M Event-related potentials and comorbidity in alcohol-dependent adult males. Psychophysiology 2001;38 (3) 367- 376
PubMed
Ehlers  CLWall  TLGarcia-Andrade  CPhillips  E Visual P3 findings in Mission Indian youth: relationship to family history of alcohol dependence and behavioral problems. Psychiatry Res 2001;105 (1-2) 67- 78
PubMed
Porjesz  BRangaswamy  MKamarajan  CJones  KPadmanabhapillai  ABegleiter  H The utility of neurophysiological markers in the study of alcoholism. Clin Neurophysiol 2005;116 (5) 993- 1018
PubMed
Patrick  CJBernat  EMMalone  SMIacono  WGKrueger  RFMcGue  M P300 amplitude as an indicator of externalizing in adolescent males. Psychophysiology 2006;43 (1) 84- 92
PubMed
Bauer  LOHesselbrock  V P300 decrements in teenagers with conduct problems: Implications for substance abuse risk and brain development. Biol Psychiatry 1999;46 (2) 263- 272
PubMed
Costa  LBauer  LOKuperman  SPorjesz  BO'Connor  SJHesselbrock  VPolich  JRohrbaugh  JBegleiter  H Frontal P300 decrements, alcohol dependence, and antisocial personality disorder. Biol Psychiatry 2000;47 (12) 1064- 1071
PubMed
Wang  JCHinrichs  ALStock  HBudde  JAllen  RBertelsen  SKwon  JMWu  WDick  DMJones  KNurnberger  JI  JrTischfield  JAPorjesz  BEdenberg  HJHesselbrock  VCrowe  RSchuckit  MBegleiter  HReich  TGoate  ABierut  L Evidence of common and specific genetic effects: association of the muscarinic acetylcholine receptor M2 (CHRM2) gene with alcohol dependence and major depressive syndrome. Hum Mol Genet 2004;13 (17) 1903- 1911
PubMed
Luo  XKranzler  HRZuo  LWang  SBlumberg  HPGelernter  J CHRM2 gene predisposes to alcohol dependence, drug dependence, and affective disorders: results from an extended case-control structured association study. Hum Mol Genet 2005;14 (16) 2421- 2432
PubMed
Jones  KAPorjesz  BAlmasy  LBierut  LGoate  AWang  JCDick  DMHinrichs  ALKwon  JRice  JRohrbaugh  JStock  HWu  WBauer  LOChorlian  DBCrowe  RREdenberg  HJForoud  THesselbrock  VKuperman  SNurnberger  JI  JrO'Connor  SJSchuckit  MStimus  ATischfield  JAReich  TBegleiter  H Linkage and linkage disequilibrium of evoked EEG oscillations with CHRM2 receptor gene polymorphisms: implications for human brain dynamics and cognition. Int J Psychophysiol 2004;53 (2) 75- 90
PubMed
Dick  DMAgrawal  AWang  JCHinrichs  ALBertelsen  SBucholz  KSchuckit  MKramer  JNurnberger  JI  JrTischfield  JAEdenberg  HJGoate  ABierut  L Alcohol dependence with comorbid drug dependence: genetic and phenotypic associations suggest a more severe form of the disorder with stronger genetic contribution to risk. Addiction 2007;102 (7) 1131- 1139
PubMed
Reich  T A genomic survey of alcohol dependence and related phenotypes: results from the Collaborative Study on the Genetics of Alcoholism (COGA). Alcohol Clin Exp Res 1996;20 (8) ((suppl)) 133A- 137A
PubMed
Bucholz  KKCadoret  RCloninger  CRDinwiddie  SHHesselbrock  VMNurnberger  JI  JrReich  TSchmidt  ISchuckit  MA A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. J Stud Alcohol 1994;55 (2) 149- 158
PubMed
Hesselbrock  MEaston  CBucholz  KKSchuckit  MHesselbrock  V A validity study of the SSAGA: a comparison with the SCAN. Addiction 1999;94 (9) 1361- 1370
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. ed 4. Washington, DC American Psychiatric Association1994;
Cloninger  CRed The Tridimensional Personality Questionnaire.  St Louis, MO Washington University School of Medicine1987;
Zuckerman  M Sensation Seeking: Beyond the Optimal Level of Arousal.  Hillsdale, NJ Erlbaum1979;
Reich  TEdenberg  HJGoate  AWilliams  JTRice  JPVan Eerdewegh  PForoud  THesselbrock  VSchuckit  MABucholz  KPorjesz  BLi  TKConneally  PMNurnberger  JI  JrTischfield  JACrowe  RRCloninger  CRWu  WShears  SCarr  KCrose  CWillig  CBegleiter  H  Genome-wide search for genes affecting the risk for alcohol dependence. Am J Med Genet 1998;81 (3) 207- 215
PubMed
Boehnke  M Allele frequency estimation from pedigree data. Am J Hum Genet 1991;48 (1) 22- 25
PubMed
Abecasis  GRCerny  SSCookson  WOCardon  LR Merlin: rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 2002;30 (1) 97- 101
PubMed
Sham  PCPurcell  SCherny  SSAbecasis  GR Powerful regression-based quantitative-trait linkage analysis of general pedigrees. Am J Hum Genet 2002;71 (2) 238- 253
PubMed
Dick  DMAliev  FKramer  JWang  JCHinrichs  ALBertelsen  SKuperman  SSchuckit  MNurnberger  JI  JrEdenberg  HJPorjesz  BBegleiter  HHesselbrock  VGoate  ABierut  L Association of CHRM2 with IQ: converging evidence for a gene influencing intelligence. Behav Genet 2007;37 (2) 265- 272
PubMed
Barrett  JCFry  BMaller  JDaly  MJ Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21 (2) 263- 265
PubMed
Dudbridge  F Pedigree disequilibrium tests for multilocus haplotypes. Genet Epidemiol 2003;25 (2) 115- 121
PubMed
Monks  SAKaplan  NL Removing the sampling restrictions from family-based tests of association for a quantitative trait locus. Am J Hum Genet 2000;66 (2) 576- 592
PubMed
Hinds  DRisch  N The ASPEX package: affected sib-pair exclusion mapping. 1999;
Gottesman  IIGould  TD The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 2003;160 (4) 636- 645
PubMed
Dick  DMJones  KSaccone  NHinrichs  ALWang  JCGoate  ABierut  LAlmasy  LSchuckit  MHesselbrock  VTischfield  JAForoud  TEdenberg  HJPorjesz  BBegleiter  H Endophenotypes successfully lead to gene identification: results from the Collaborative Study on the Genetics of Alcoholism. Behav Genet 2006;36 (1) 77- 86
PubMed
Frederick  JAIacono  WG Beyond the DSM: defining endophenotypes for genetic studies of substance abuse. Curr Psychiatry Rep 2006;8 (2) 144- 150
PubMed
Stallings  MCCorley  RPDennehey  BHewitt  JKKrauter  KSLessem  JMMikulich-Gilbertson  SKRhee  SHSmolen  AYoung  SECrowley  TJ A genome-wide search for quantitative trait loci that influence antisocial drug dependence in adolescence. Arch Gen Psychiatry 2005;62 (9) 1042- 1051
PubMed
Wright  MJLuciano  MHansell  NKGeffen  GMMontgomery  GWMartin  NG Genome-wide scan for loci influencing the P3: an endophenotype for psychopathology. Alcohol Clin Exp Res 2006;30 ((suppl)) 62A
Iacono  WGMalone  SMMcGue  M Substance use disorders, externalizing psychopathology, and P300 event-related potential amplitude. Int J Psychophysiol 2003;48 (2) 147- 178
PubMed
Roberts  SBMacLean  CJNeale  MCEaves  LJKendler  KS Replication of linkage studies of complex traits: an examination of variation in location estimates. Am J Hum Genet 1999;65 (3) 876- 884
PubMed
Kendler  KSNeale  MCKessler  RCHeath  ACEaves  LJ Major depression and generalized anxiety disorder: same genes, (partly) different environments? Arch Gen Psychiatry 1992;49 (9) 716- 722
PubMed
Hettema  JMNeale  MCMyers  JMPrescott  CKendler  KS A population-based twin study of the relationship between neuroticism and internalizing disorders. Am J Psychiatry 2006;163 (5) 857- 864
PubMed
Hettema  JMAn  SSNeale  MCBukszar  Jvan den Oord  EJKendler  KSChen  X Association between glutamic acid decarboxylase genes and anxiety disorders, major depression, and neuroticism. Mol Psychiatry 2006;11 (8) 752- 762
PubMed
Boomsma  DIBeem  ALvan den Berg  MDolan  CVKoopmans  JRVink  JMde Geus  EJSlagboom  PE Netherlands twin family study of anxious depression (NETSAD). Twin Res 2000;3 (4) 323- 334
PubMed
Craddock  NO'Donovan  MCOwen  M The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J Med Genet 2005;42 (3) 193- 204
PubMed
Begleiter  HPorjesz  B What is inherited in the predisposition toward alcoholism? a proposed model. Alcohol Clin Exp Res 1999;23 (7) 1125- 1135
PubMed
Comings  DEWu  SRostamkhani  MMcGue  MIacono  WGCheng  LSMacMurray  JP Role of the cholinergic muscarinic 2 receptor (CHRM2) gene in cognition. Mol Psychiatry 2003;8 (1) 10- 13
PubMed
Gosso  MFvan Belzen  Mde Geus  EJPolderman  JCHeutink  PBoomsma  DIPosthuma  D Association between the CHRM2 gene and intelligence in a sample of 304 Dutch families. Genes Brain Behav 2006;5 (8) 577- 584
PubMed
Hautala  AJRankinen  TKiviniemi  AMMakikallio  THHuikuri  HVBouchard  CTulppo  MP Heart rate recovery after maximal exercise is associated with acetylcholine receptor M2 (CHRM2) gene polymorphism. Am J Physiol Heart Circ Physiol 2006;291 (1) H459- H466
PubMed
Helzer  JEKraemer  HCKrueger  RF The feasibility and need for dimensional psychiatric diagnoses [published online ahead of print August 15, 2006]. Psychol Med 2006;36 (12) 1671- 1680
PubMed10.1017/S003329170600821X

Figures

Place holder to copy figure label and caption
Figure 1.

Linkage analyses from chromosome 7 using MERLIN Regress software (University of Michigan, Ann Arbor)48 for externalizing component scores and component phenotypes. AD indicates alcohol dependence symptoms; ASPD, antisocial personality disorder symptoms; CD, conduct disorder symptoms; DD, drug dependence symptoms; NS, novelty seeking score; SS, sensation seeking score.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Linkage analyses from chromosome 7 using affected sibling pair methods in ASPEX.54 AD indicates alcohol dependence diagnosis; ASPD, antisocial personality disorder diagnosis; CD, conduct disorder diagnosis; DD, drug dependence diagnosis; ExtDis, any externalizing disorder.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Family-Based Association Analyses of Externalizing Psychopathology Symptoms and Scores
Table Graphic Jump LocationTable 2. Pearson Correlations Between Externalizing Variables
Table Graphic Jump LocationTable 3. Linkage Disequilibrium (LD) Across the SNPs Located in CHRM2 LD Block 3a

References

Begleiter  HReich  THesselbrock  VPorjesz  BLi  TKSchuckit  MEdenberg  HJRice  J The Collaborative Study on the Genetics of Alcoholism. Alcohol Health Res World 1995;19228- 236
Levinson  DFHolmans  PStraub  REOwen  MJWildenauer  DBGejman  PVPulver  AELaurent  CKendler  KSWalsh  DNorton  NWilliams  NMSchwab  SLerer  BMowry  BJSander  AAntonarakis  SEBlouin  JLDeLeuze  JFMallet  J Multicenter linkage study of schizophrenia candidate regions on chromosomes 5q, 6q, 10p, and 13q: schizophrenia linkage collaborative group III. Am J Hum Genet 2000;67 (3) 652- 663
PubMed
 Genomic survey of bipolar illness in the NIMH Genetics Initiative pedigrees: a preliminary report. Am J Med Genet 1997;74 (3) 227- 237
PubMed
Hutcheson  HBBradford  YFolstein  SEGardiner  MBSantangelo  SLSutcliffe  JSHaines  JL Defining the autism minimum candidate gene region on chromosome 7. Am J Med Genet B Neuropsychiatr Genet 2003;117 (1) 90- 96
PubMed
Levinson  DFZubenko  GSCrowe  RDePaulo  JRScheftner  WSWeissman  MMHolmans  PZubenko  WNBoutelle  SMurphy-Eberenz  KMacKinnon  DFMcInnis  MGMarta  DHAdams  PBSassoon  SKnowles  JAThomas  JChellis  J Genetics of recurrent early-onset depression (GenRED): design and preliminary clinical characteristics of a repository sample for genetic linkage studies. Am J Med Genet B Neuropsychiatr Genet 2003;119 (1) 118- 130
PubMed
Faraone  SV Report from the 4th international meeting of the attention deficit hyperactivity disorder molecular genetics network. Am J Med Genet B Neuropsychiatr Genet 2003;121 (1) 55- 59
PubMed
Madden  PASaccone  SFPergadia  MLAgrawal  ATodorov  AADick  DMLoukola  ABroms  UMaunu  HHeikkila  KWiden  EMontgomery  GPeltonen  LKaprio  JMartin  NGRice  J Genetic vulnerability for nicotine dependence: linkage results from the NAG (Nicotine Addiction Genetics) project. Am J Med Genet B Neuropsychiatr Genet 2005;13816
 NIDA Genetics Consortium. http://www.drugabuse.gov/about/organization/Genetics/consortium/. Accessed December 21, 2007
Edenberg  HJDick  DMXuei  XTian  HAlmasy  LBauer  LOCrowe  RGoate  AHesselbrock  VJones  KAKwon  JLi  TKNurnberger  JI  JrO'Connor  SJReich  TRice  JSchuckit  MPorjesz  BForoud  TBegleiter  H Variations in GABRA2, encoding the α2 subunit of the GABA-A receptor are associated with alcohol dependence and with brain oscillations. Am J Hum Genet 2004;74 (4) 705- 714
PubMed
Covault  JGelernter  JHesselbrock  VNellissery  MKranzler  HR Allelic and haplotypic association of GABRA2 with alcohol dependence. Am J Med Genet B Neuropsychiatr Genet 2004;129 (1) 104- 109
PubMed
Drgon  TD'Addario  CUhl  GR Linkage disequilibrium, haplotype and association studies of a chromosome 4 GABA receptor gene cluster: candidate gene variants for addictions. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics) 2006;141 (8) 854- 860
PubMed
Edenberg  HJXuei  XChen  H-JTian  HWetherill  LFDick  DMAlmasy  LBierut  LBucholz  KKGoate  AHesselbrock  VKuperman  SNurnberger  JI  JrPorjesz  BRice  JSchuckit  MTischfield  JABegleiter  HForoud  T Association of alcohol dehydrogenase genes with alcohol dependence: a comprehensive analysis. Hum Mol Genet 2006;15 (9) 1539- 1549
PubMed
Luo  XKranzler  HZuo  LLappalainen  JYang  BZGelernter  J ADH4 gene variation is associated with alcohol dependence and drug dependence in European Americans: results from HWD tests and case-control association studies. Neuropsychopharmacology 2006;31 (5) 1085- 1095
PubMed
Luo  XKranzler  HRZuo  LYang  BZLappalainen  JGelernter  J ADH4 gene variation is associated with alcohol dependence and drug dependence in European Americans: results from family-controlled and population-structured association studies. Pharmacogenet Genomics 2005;15 (11) 755- 768
PubMed
Norton  NWilliams  HJOwen  M An update on the genetics of schizophrenia. Curr Opin Psychiatry 2006;19 (2) 158- 164
PubMed
Riley  BKendler  KS Molecular genetic studies of schizophrenia. Eur J Hum Genet 2006;14 (6) 669- 680
PubMed
Kendler  KSPrescott  CMyers  JNeale  MC The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Arch Gen Psychiatry 2003;60 (9) 929- 937
PubMed
Whitfield  JB Meta-analysis of the effects of alcohol dehydrogenase genotype on alcohol dependence and alcoholic liver disease. Alcohol Alcohol 1997;32 (5) 613- 619
PubMed
Shen  Y-CFan  J-HEdenberg  HJLi  TKCui  Y-HWang  Y-FTian  C-HZhou  C-FZhou  R-LWang  JZhao  Z-LXia  G-Y Polymorphism of ADH and ALDH genes among four ethnic groups in China and effects upon the risk for alcoholism. Alcohol Clin Exp Res 1997;21 (7) 1272- 1277
PubMed
Luo  XKranzler  HRZuo  LWang  SLappalainen  JSchork  NJGelernter  J Diplotype trend regression (DTR) analysis of the ADH gene cluster and ALDH2: multiple significant associations for alcohol dependence. Am J Hum Genet 2006;78 (6) 973- 987
PubMed
Kessler  RCChui  WTDemler  OWalters  EE Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005;62 (6) 617- 627[erratum published in Arch Gen Psychiatry. 2005;62(7):709. Merikangas KR added].
PubMed
Krueger  RFMarkon  KE Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annu Rev Clin Psychol 2006;2111- 133
PubMed
Krueger  RFMarkon  KEPatrick  CJIacono  WG Externalizing psychopathology in adulthood: A dimensional-spectrum conceptualization and its implications for DSM-VJ Abnorm Psychol 2005;114 (4) 537- 550
PubMed
Hicks  BMKrueger  RFIacono  WGMcGue  MPatrick  CJ Family transmission and heritability of externalizing disorders: a twin-family study. Arch Gen Psychiatry 2004;61 (9) 922- 928
PubMed
Krueger  RFHicks  BMPatrick  CJCarlson  SRIacono  WGMcGue  M Etiologic connections among substance dependence, antisocial behavior, and personality: modeling the externalizing spectrum. J Abnorm Psychol 2002;111 (3) 411- 424
PubMed
Young  SEStallings  MCCorley  RPKrauter  KSHewitt  JK Genetic and environmental influences on behavioral disinhibition. Am J Med Genet 2000;96 (5) 684- 695
PubMed
Moffitt  TE Genetic and environmental influences on antisocial behaviors: evidence from behavioral-genetic research. Adv Genet 2005;5541- 104
PubMed
Yoon  HHIacono  WGMalone  SMMcGue  M Using the brain P300 response to identify novel phenotypes reflecting genetic vulnerability for adolescent substance misuse. Addict Behav 2006;31 (6) 1067- 1087
PubMed
Iacono  WGCarlson  SRMalone  SMMcGue  M P3 event-related potential amplitude and the risk for disinhibitory disorders in adolescent boys. Arch Gen Psychiatry 2002;59 (8) 750- 757
PubMed
Malone  SMIacono  WGMcGue  M Event-related potentials and comorbidity in alcohol-dependent adult males. Psychophysiology 2001;38 (3) 367- 376
PubMed
Ehlers  CLWall  TLGarcia-Andrade  CPhillips  E Visual P3 findings in Mission Indian youth: relationship to family history of alcohol dependence and behavioral problems. Psychiatry Res 2001;105 (1-2) 67- 78
PubMed
Porjesz  BRangaswamy  MKamarajan  CJones  KPadmanabhapillai  ABegleiter  H The utility of neurophysiological markers in the study of alcoholism. Clin Neurophysiol 2005;116 (5) 993- 1018
PubMed
Patrick  CJBernat  EMMalone  SMIacono  WGKrueger  RFMcGue  M P300 amplitude as an indicator of externalizing in adolescent males. Psychophysiology 2006;43 (1) 84- 92
PubMed
Bauer  LOHesselbrock  V P300 decrements in teenagers with conduct problems: Implications for substance abuse risk and brain development. Biol Psychiatry 1999;46 (2) 263- 272
PubMed
Costa  LBauer  LOKuperman  SPorjesz  BO'Connor  SJHesselbrock  VPolich  JRohrbaugh  JBegleiter  H Frontal P300 decrements, alcohol dependence, and antisocial personality disorder. Biol Psychiatry 2000;47 (12) 1064- 1071
PubMed
Wang  JCHinrichs  ALStock  HBudde  JAllen  RBertelsen  SKwon  JMWu  WDick  DMJones  KNurnberger  JI  JrTischfield  JAPorjesz  BEdenberg  HJHesselbrock  VCrowe  RSchuckit  MBegleiter  HReich  TGoate  ABierut  L Evidence of common and specific genetic effects: association of the muscarinic acetylcholine receptor M2 (CHRM2) gene with alcohol dependence and major depressive syndrome. Hum Mol Genet 2004;13 (17) 1903- 1911
PubMed
Luo  XKranzler  HRZuo  LWang  SBlumberg  HPGelernter  J CHRM2 gene predisposes to alcohol dependence, drug dependence, and affective disorders: results from an extended case-control structured association study. Hum Mol Genet 2005;14 (16) 2421- 2432
PubMed
Jones  KAPorjesz  BAlmasy  LBierut  LGoate  AWang  JCDick  DMHinrichs  ALKwon  JRice  JRohrbaugh  JStock  HWu  WBauer  LOChorlian  DBCrowe  RREdenberg  HJForoud  THesselbrock  VKuperman  SNurnberger  JI  JrO'Connor  SJSchuckit  MStimus  ATischfield  JAReich  TBegleiter  H Linkage and linkage disequilibrium of evoked EEG oscillations with CHRM2 receptor gene polymorphisms: implications for human brain dynamics and cognition. Int J Psychophysiol 2004;53 (2) 75- 90
PubMed
Dick  DMAgrawal  AWang  JCHinrichs  ALBertelsen  SBucholz  KSchuckit  MKramer  JNurnberger  JI  JrTischfield  JAEdenberg  HJGoate  ABierut  L Alcohol dependence with comorbid drug dependence: genetic and phenotypic associations suggest a more severe form of the disorder with stronger genetic contribution to risk. Addiction 2007;102 (7) 1131- 1139
PubMed
Reich  T A genomic survey of alcohol dependence and related phenotypes: results from the Collaborative Study on the Genetics of Alcoholism (COGA). Alcohol Clin Exp Res 1996;20 (8) ((suppl)) 133A- 137A
PubMed
Bucholz  KKCadoret  RCloninger  CRDinwiddie  SHHesselbrock  VMNurnberger  JI  JrReich  TSchmidt  ISchuckit  MA A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. J Stud Alcohol 1994;55 (2) 149- 158
PubMed
Hesselbrock  MEaston  CBucholz  KKSchuckit  MHesselbrock  V A validity study of the SSAGA: a comparison with the SCAN. Addiction 1999;94 (9) 1361- 1370
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. ed 4. Washington, DC American Psychiatric Association1994;
Cloninger  CRed The Tridimensional Personality Questionnaire.  St Louis, MO Washington University School of Medicine1987;
Zuckerman  M Sensation Seeking: Beyond the Optimal Level of Arousal.  Hillsdale, NJ Erlbaum1979;
Reich  TEdenberg  HJGoate  AWilliams  JTRice  JPVan Eerdewegh  PForoud  THesselbrock  VSchuckit  MABucholz  KPorjesz  BLi  TKConneally  PMNurnberger  JI  JrTischfield  JACrowe  RRCloninger  CRWu  WShears  SCarr  KCrose  CWillig  CBegleiter  H  Genome-wide search for genes affecting the risk for alcohol dependence. Am J Med Genet 1998;81 (3) 207- 215
PubMed
Boehnke  M Allele frequency estimation from pedigree data. Am J Hum Genet 1991;48 (1) 22- 25
PubMed
Abecasis  GRCerny  SSCookson  WOCardon  LR Merlin: rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 2002;30 (1) 97- 101
PubMed
Sham  PCPurcell  SCherny  SSAbecasis  GR Powerful regression-based quantitative-trait linkage analysis of general pedigrees. Am J Hum Genet 2002;71 (2) 238- 253
PubMed
Dick  DMAliev  FKramer  JWang  JCHinrichs  ALBertelsen  SKuperman  SSchuckit  MNurnberger  JI  JrEdenberg  HJPorjesz  BBegleiter  HHesselbrock  VGoate  ABierut  L Association of CHRM2 with IQ: converging evidence for a gene influencing intelligence. Behav Genet 2007;37 (2) 265- 272
PubMed
Barrett  JCFry  BMaller  JDaly  MJ Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21 (2) 263- 265
PubMed
Dudbridge  F Pedigree disequilibrium tests for multilocus haplotypes. Genet Epidemiol 2003;25 (2) 115- 121
PubMed
Monks  SAKaplan  NL Removing the sampling restrictions from family-based tests of association for a quantitative trait locus. Am J Hum Genet 2000;66 (2) 576- 592
PubMed
Hinds  DRisch  N The ASPEX package: affected sib-pair exclusion mapping. 1999;
Gottesman  IIGould  TD The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 2003;160 (4) 636- 645
PubMed
Dick  DMJones  KSaccone  NHinrichs  ALWang  JCGoate  ABierut  LAlmasy  LSchuckit  MHesselbrock  VTischfield  JAForoud  TEdenberg  HJPorjesz  BBegleiter  H Endophenotypes successfully lead to gene identification: results from the Collaborative Study on the Genetics of Alcoholism. Behav Genet 2006;36 (1) 77- 86
PubMed
Frederick  JAIacono  WG Beyond the DSM: defining endophenotypes for genetic studies of substance abuse. Curr Psychiatry Rep 2006;8 (2) 144- 150
PubMed
Stallings  MCCorley  RPDennehey  BHewitt  JKKrauter  KSLessem  JMMikulich-Gilbertson  SKRhee  SHSmolen  AYoung  SECrowley  TJ A genome-wide search for quantitative trait loci that influence antisocial drug dependence in adolescence. Arch Gen Psychiatry 2005;62 (9) 1042- 1051
PubMed
Wright  MJLuciano  MHansell  NKGeffen  GMMontgomery  GWMartin  NG Genome-wide scan for loci influencing the P3: an endophenotype for psychopathology. Alcohol Clin Exp Res 2006;30 ((suppl)) 62A
Iacono  WGMalone  SMMcGue  M Substance use disorders, externalizing psychopathology, and P300 event-related potential amplitude. Int J Psychophysiol 2003;48 (2) 147- 178
PubMed
Roberts  SBMacLean  CJNeale  MCEaves  LJKendler  KS Replication of linkage studies of complex traits: an examination of variation in location estimates. Am J Hum Genet 1999;65 (3) 876- 884
PubMed
Kendler  KSNeale  MCKessler  RCHeath  ACEaves  LJ Major depression and generalized anxiety disorder: same genes, (partly) different environments? Arch Gen Psychiatry 1992;49 (9) 716- 722
PubMed
Hettema  JMNeale  MCMyers  JMPrescott  CKendler  KS A population-based twin study of the relationship between neuroticism and internalizing disorders. Am J Psychiatry 2006;163 (5) 857- 864
PubMed
Hettema  JMAn  SSNeale  MCBukszar  Jvan den Oord  EJKendler  KSChen  X Association between glutamic acid decarboxylase genes and anxiety disorders, major depression, and neuroticism. Mol Psychiatry 2006;11 (8) 752- 762
PubMed
Boomsma  DIBeem  ALvan den Berg  MDolan  CVKoopmans  JRVink  JMde Geus  EJSlagboom  PE Netherlands twin family study of anxious depression (NETSAD). Twin Res 2000;3 (4) 323- 334
PubMed
Craddock  NO'Donovan  MCOwen  M The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J Med Genet 2005;42 (3) 193- 204
PubMed
Begleiter  HPorjesz  B What is inherited in the predisposition toward alcoholism? a proposed model. Alcohol Clin Exp Res 1999;23 (7) 1125- 1135
PubMed
Comings  DEWu  SRostamkhani  MMcGue  MIacono  WGCheng  LSMacMurray  JP Role of the cholinergic muscarinic 2 receptor (CHRM2) gene in cognition. Mol Psychiatry 2003;8 (1) 10- 13
PubMed
Gosso  MFvan Belzen  Mde Geus  EJPolderman  JCHeutink  PBoomsma  DIPosthuma  D Association between the CHRM2 gene and intelligence in a sample of 304 Dutch families. Genes Brain Behav 2006;5 (8) 577- 584
PubMed
Hautala  AJRankinen  TKiviniemi  AMMakikallio  THHuikuri  HVBouchard  CTulppo  MP Heart rate recovery after maximal exercise is associated with acetylcholine receptor M2 (CHRM2) gene polymorphism. Am J Physiol Heart Circ Physiol 2006;291 (1) H459- H466
PubMed
Helzer  JEKraemer  HCKrueger  RF The feasibility and need for dimensional psychiatric diagnoses [published online ahead of print August 15, 2006]. Psychol Med 2006;36 (12) 1671- 1680
PubMed10.1017/S003329170600821X

Correspondence

CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles
JAMAevidence.com

Users' Guides to the Medical Literature
Alcohol Abuse or Dependence

The Rational Clinical Examination
Make the Diagnosis: Alcohol Abuse