Polymorphisms of three different dopaminergic genes, dopamine D2 receptor (DRD2), dopamine β‐hydroxylase (DβH), and dopamine transporter (DAT1), were examined in Tourette syndrome (TS) probands, their relatives, and controls. Each gene individually showed a significant correlation with various behavioral variables in these subjects. The additive and subtractive effects of the three genes were examined by genotyping all three genes in the same set of subjects. For 9 of 20 TS associated comorbid behaviors there was a significant linear association between the degree of loading for markers of three genes and the mean behavior scores. The behavior variables showing the significant associations were, in order, attention deficit hyperactivity disorder (ADHD), stuttering, oppositional defiant, tics, conduct, obsessive‐compulsive, mania, alcohol abuse, and general anxiety‐behaviors that constitute the most overt clinical aspects of TS. For 16 of the 20 behavior scores there was a linear progressive decrease in the mean score with progressively lesser loading for the three gene markers. These results suggest that TS, ADHD, stuttering, oppositional defiant and conduct disorder, and other behaviors associated with TS, are polygenic, due in part to these three dopaminergic genes, and that the genetics of other polygenic psychiatric disorders may be deciphered using this technique. © 1996 Wiley‐Liss, Inc.

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Summary1. Meta-analysis and meta-regression are statistical methods for synthesizing and modelling the results of different studies, and are critical research synthesis tools in ecology and evolutionary biology (E&E). However, many E&E researchers carry out meta-analyses using software that is limited in its statistical functionality and is not easily updatable. It is likely that these software limitations have slowed the uptake of new methods in E&E and limited the scope and quality of inferences from research syntheses. 2. We developed OpenMEE: Open Meta-analyst for Ecology and Evolution to address the need for advanced, easy-to-use software for meta-analysis and meta-regression. OpenMEE has a cross-platform, easy-to-use graphical user interface (GUI) that gives E&E researchers access to the diverse and advanced statistical functionalities offered in R, without requiring knowledge of R programming. 3. OpenMEE offers a suite of advanced meta-analysis and meta-regression methods for synthesizing continuous and categorical data, including meta-regression with multiple covariates and their interactions, phylogenetic analyses, and simple missing data imputation. OpenMEE also supports data importing and exporting, exploratory data analysis, graphing of data, and summary table generation. 4.As intuitive, open-source, free software for advanced methods in meta-analysis, OpenMEE meets the current and pressing needs of the E&E community for teaching meta-analysis and conducting high-quality syntheses. Because OpenMEE's statistical components are written in R, new methods and packages can be rapidly incorporated into the software. To fully realize the potential of OpenMEE, we encourage community development with an aim to advance the capabilities of meta-analyses in E&E.

--These results suggest the A1 allele of the DRD2 gene is associated with a number of behavior disorders in which it may act as a modifying gene rather than as the primary etiological agent.

Abnormalities in the dopaminergic reward pathways have frequently been implicated in substance abuse and addictive behaviors. Recent studies by Self and coworkers have suggested an important interaction between the dopamine D 1 and D 2 receptors in cocaine abuse. To test the hypothesis that the DRD1 gene might play a role in addictive behaviors we examined the alleles of the Dde I polymorphism in three independent groups of subjects with varying types of compulsive, addictive behaviors -Tourette syndrome probands, smokers and pathological gamblers. In all three groups there was a significant increase in the frequency of homozygosity for the DRD1 Dde I 1 or 2 alleles in subjects with addictive behaviors. The DRD1 11 or 22 genotype was present in 41.3% of 63 controls and 57.3% of 227 TS probands (P = 0.024). When 23 quantitative traits were examined by ANOVA those carrying the 11 genotype consistently had the highest scores. Based on these results, we examined the prevalence of the 11 genotype in controls, TS probands without a specific behavior, and TS probands with a specific behavior. There was a progressive, linear increase, significant at ␣ Յ 0.005 for scores for gambling, alcohol use and compulsive shopping. Problems with three additional behaviors, drug use, compulsive eating and smoking were significant at ␣ Յ 0.05. All six variables were related to addictive behaviors. In a totally separate group of controls and individuals attending a smoking cessation clinic, and smoking at least one pack per day, 39.3% of the controls versus 66.1% of the smokers carried the 11 or 22 genotype (P = 0.0002). In a third independent group of pathological gamblers, 55.8% carried the 11 or 22 genotype (P = 0.009 vs the combined controls). In the TS group and smokers there was a significant additive effect of the DRD1 and DRD2 genes. The results for both the DRD1 and DRD2 genes, which have opposing effects on cyclic AMP, were consistent with negative and positive heterosis, respectively. These results support a role for genetic variants of the DRD1 gene in some addictive behaviors, and an interaction of genetic variants at the DRD1 and DRD2 genes.

In a previous study (Comings DE et al. Comparison of the role of dopamine, serotonin, and noradrenergic genes in ADHD, ODD and conduct disorder. Multivariate regression analysis of 20 genes. Clin Genet 2000: 57: 178-196) we examined the role of 20 dopamine, serotonin and norepinephrine genes in attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD), using a multivariate analysis of associations (MAA) technique. We have now brought the total number of genes examined to 42 by adding an additional 22 candidate genes. These results indicate that even with the inclusion of these additional genes the noradrenergic genes still played a greater role in ADHD than any other group. Six other neurotransmitter genes were included in the regression equation - cholinergic, nicotinic, alpha 4 receptor (CHNRA4), adenosine A2A receptor (ADOA2A), nitric oxide synthase (NOS3), NMDAR1, GRIN2B, and GABRB3. In contrast to ADHD and ODD, CD preferentially utilized hormone and neuropeptide genes These included CCK, CYP19 (aromatase cytochrome P-450), ESR1, and INS (p = 0.005). This is consistent with our prior studies indicating a role of the androgen receptor (AR) gene in a range of externalizing behavors. We propose that the MAA technique, by focusing on the additive effect of multiple genes and on the cummulative effect of functionally related groups of genes, provides a powerful approach to the dissection of the genetic basis of polygenic disorders.

The present study is based on the proposal that complex disorders resulting from the effects of multiple genes are best investigated by simultaneously examining multiple candidate genes in the same group of subjects. We have examined the effect of 20 genes for dopamine, serotonin, and noradrenergic metabolism on a quantitative score for attention deficit hyperactivity disorder (ADHD) in 336 unrelated Caucasian subjects. The genotypes of each gene were assigned a score from 0 to 2, based on results from the literature or studies in an independent set of subjects (literature-based scoring), or results based on analysis of variance for the sample (optimized gene scoring). Multivariate linear regression analysis with backward elimination was used to determine which genes contributed most to the phenotype for both coding methods. For optimized gene scoring, three dopamine genes contributed to 2.3% of the variance, p = 0.052; three serotonin genes contributed to 3%, p = 0.015; and six adrenergic genes contributed to 6.9%, p = 0.0006. For all genes combined, 12 genes contributed to 11.6% of the variance, p = 0.0001. These results indicate that the adrenergic genes play a greater role in ADHD than either the dopaminergic or serotonergic genes combined. The results using literature-based gene scoring were similar. An examination of two additional comorbid phenotypes, conduct disorder and oppositional defiant disorder (ODD), indicated they shared genes with ADHD. For ODD different genotypes of the same genes were often used. These results support the value of the simultaneous examination of multiple candidate genes.

Cloninger (Cloninger CR. Neurogenetic adaptive mechanisms in alcoholism. Science 1987: 236: 410-416) proposed three basic personality dimensions for temperament: novelty seeking, harm avoidance, and reward dependence. He suggested that novelty seeking primarily utilized dopamine pathways, harm avoidance utilized serotonin pathways, and reward dependence utilized norepinephrine pathways. Subsequently, one additional temperament dimension (persistence) and three character dimensions (cooperativeness, self-directedness, and self-transcendence) were added to form the temperament and character inventory (TCI). We have utilized a previously described multivariate analysis technique (Comings DE, Gade-Andavolu R, Gonzalez N et al. Comparison of the role of dopamine, serotonin, and noradrenergic genes in ADHD, ODD and conduct disorder. Multivariate regression analysis of 20 genes. Clin Genet 2000: 57: 178-196; Comings DD, Gade-Andavolu R, Gonzalez N et al. Multivariate analysis of associations of 42 genes in ADHD, ODD and conduct disorder. Clin Genet 2000: in press) to examine the relative role of 59 candidate genes in the seven TCI traits and test the hypothesis that specific personality traits were associated with specific genes. While there was some tendency for this to be true, a more important trend was the involvement of different ratios of functionally related groups of genes, and of different genotypes of the same genes, for different traits.