The Genetic and Environmental Sources of Resemblance Between Normative Personality and Personality Disorder Traits

Recent work has suggested a high level of congruence between normative personality, most typically represented by the big five factors, and abnormal personality traits. In 2,293 Norwegian adult twins ascertained from a population-based registry, the authors evaluated the degree of sharing of genetic and environmental influences on normative personality, assessed by the Big Five Inventory (BFI), and personality disorder traits (PDTs), assessed by the Personality Inventory for DSM-S-Norwegian Brief Form (PID-5NBF). For four of the five BFI dimensions, the strongest genetic correlation was observed with the expected PID-5-NBF dimension (e.g., neuroticism with negative affectivity [+], conscientiousness with disinhibition [-]). However, neuroticism, conscientiousness, and agreeableness had substantial genetic correlations with other PID-S-NBF dimensions (e.g., neuroticism with compulsivity [+], agreeableness with detachment [-]). Openness had no substantial genetic correlations with any PID-5-NBF dimension. The proportion of genetic risk factors shared in aggregate between the BFI traits and the PID-5-NBF dimensions was quite high for conscientiousness and neuroticism, relatively robust for extraversion and agreeableness, but quite low for openness. Of the six PID-S-NBF dimensions, three (negative affectivity, detachment, and disinhibition) shared, in aggregate, most of their genetic risk factors with normative personality traits. Genetic factors underlying psychoticism, antagonism, and compulsivity were shared to a lesser extent, suggesting that they are influenced by etiological factors not well indexed by the BFI

A genetic analysis of coffee consumption in a sample of Dutch twins

Caffeine is by far the most commonly used psycho-active substance. Caffeine is consumed regularly as an ingredient of coffee. Coffee consumption and coffee preference was explored in a sample of 4,495 twins (including 1,231 pairs) registered with the Netherlands Twin Registry. Twin resemblance was assessed by tetrachoric correlations and the influence of both genetic and environmental factors was explored with model fitting analysis in MX. Results showed moderate genetic influences (39%) on coffee consumption. The remaining variance was explained by shared environmental factors (21%) and unique environmental factors (40%). The variance in coffee preference (defined as the proportion of coffee consumption relative to the consumption of coffee and tea in total) was explained by genetic factors (62%) and unique environmental factors (38%)

Patterns of co-morbidity with anxiety disorders in Chinese women with recurrent major depression

BACKGROUND: Studies conducted in Europe and the USA have shown that co-morbidity between major depressive disorder (MDD) and anxiety disorders is associated with various MDD-related features, including clinical symptoms, degree of familial aggregation and socio-economic status. However, few studies have investigated whether these patterns of association vary across different co-morbid anxiety disorders. Here, using a large cohort of Chinese women with recurrent MDD, we examine the prevalence and associated clinical features of co-morbid anxiety disorders. METHOD: A total of 1970 female Chinese MDD patients with or without seven co-morbid anxiety disorders [including generalized anxiety disorder (GAD), panic disorder, and five phobia subtypes] were ascertained in the CONVERGE study. Generalized linear models were used to model association between co-morbid anxiety disorders and various MDD features. RESULTS: The lifetime prevalence rate for any type of co-morbid anxiety disorder is 60.2%. Panic and social phobia significantly predict an increased family history of MDD. GAD and animal phobia predict an earlier onset of MDD and a higher number of MDD episodes, respectively. Panic and GAD predict a higher number of DSM-IV diagnostic criteria. GAD and blood-injury phobia are both significantly associated with suicidal attempt with opposite effects. All seven co-morbid anxiety disorders predict higher neuroticism. CONCLUSIONS: Patterns of co-morbidity between MDD and anxiety are consistent with findings from the US and European studies; the seven co-morbid anxiety disorders are heterogeneous when tested for association with various MDD features

Eating disorders: from twin studies to candidate genes and beyond

Substantial effort has been put into the exploration of the biological background of eating disorders, through family, twin and molecular genetic studies. Family studies have shown that anorexia (AN) and bulimia nervosa (BN) are strongly familial, and that familial etiologic factors appear to be shared by both disorders. Twin studies often focus on broader phenotypes or subthreshold eating disorders. These studies consistently yielded moderate to substantial heritabilities. In addition, there has been a proliferation of molecular genetic studies that focused on Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) AN and BN. Seven linkage regions have been identified in genome-wide screens. Many genetic association studies have been performed, but no consistent association between a candidate gene and AN or BN has been reported. Larger genetic association studies and collaborations are needed to examine the involvement of several candidate genes and biological pathways in eating disorders. In addition, twin studies should be designed to assist the molecular work by further exploring genetic determinants of endophenotypes, evaluating the magnitude of contribution to liability of measured genotypes as well as environmental risk factors related to eating disorders. In this manner twin and molecular studies can move the field forward in a mutually informative way

Binge eating disorder: a symptom-level investigation of genetic and environmental influences on liability

Recent behavioral genetic studies have emphasized the importance of investigating eating disorders at the level of individual symptoms, rather than as overall diagnoses. We examined the heritability of binge eating disorder (BED) using an item-factor analytic approach, which estimates contributions of additive genetic (A), common environmental (C), and unique environmental (E) influences on liability to BED as well as individual symptoms

A twin study of specific bulimia nervosa symptoms

Twin studies have suggested that additive genetic factors significantly contribute to liability to bulimia nervosa (BN). However, the diagnostic criteria for BN remain controversial. In this study, an item-factor model was used to examine the BN diagnostic criteria and the genetic and environmental contributions to BN in a population-based twin sample. The validity of the equal environment assumption (EEA) for BN was also tested

A prospective longitudinal model predicting early adult alcohol problems:evidence for a robust externalizing pathway

BACKGROUND: Risk factors for alcohol problems (AP) include biological and environmental factors that are relevant across development. The pathways through which these factors are related, and how they lead to AP, are optimally considered in the context of a comprehensive developmental model. METHOD: Using data from a prospectively assessed, population-based UK cohort, we constructed a structural equation model that integrated risk factors reflecting individual, family and peer/community-level constructs across childhood, adolescence and young adulthood. These variables were used to predict AP at the age of 20 years. RESULTS: The final model explained over 30% of the variance in liability to age 20 years AP. Most prominent in the model was an externalizing pathway to AP, with conduct problems, sensation seeking, AP at age 17.5 years and illicit substance use acting as robust predictors. In conjunction with these individual-level risk factors, familial AP, peer relationships and low parental monitoring also predicted AP. Internalizing problems were less consistently associated with AP. Some risk factors previously identified were not associated with AP in the context of this comprehensive model. CONCLUSIONS: The etiology of young adult AP is complex, influenced by risk factors that manifest across development. The most prominent pathway to AP is via externalizing and related behaviors. These findings underscore the importance of jointly assessing both biologically influenced and environmental risk factors for AP in a developmental context

Assessing the heritability of anorexia nervosa symptoms using a marginal maximal likelihood approach

Assessment of eating disorders at the symptom level can facilitate the refinement of phenotypes. We examined genetic and environmental contributions to liability to anorexia nervosa (AN) symptoms in a population-based twin sample using a genetic common pathway model

Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk