Jaime Derringer

Behavioral disinhibition (BD) is a quantitative measure designed to capture the heritable variation encompassing risky and impulsive behaviors. As a result, BD represents an ideal target for discovering genetic loci that predispose individuals to a wide range of antisocial behaviors and substance misuse that together represent a large cost to society as a whole. Published genome-wide association studies (GWAS) have examined specific phenotypes that fall under the umbrella of BD (e.g. alcohol dependence, conduct disorder); however no GWAS has specifically examined the overall BD construct. We conducted a GWAS of BD using a sample of 1,901 adolescents over-selected for characteristics that define high BD, such as substance and antisocial behavior problems, finding no individual locus that surpassed genome-wide significance. Although no single SNP was significantly associated with BD, restricted maximum likelihood analysis estimated that 49.3 % of the variance in BD within the Caucasian sub-sample was accounted for by the genotyped SNPs (p = 0.06). Gene-based tests identified seven genes associated with BD (p ≤ 2.0 × 10(-6)). Although the current study was unable to identify specific SNPs or pathways with replicable effects on BD, the substantial sample variance that could be explained by all genotyped SNPs suggests that larger studies could successfully identify common variants associated with BD.

A recent study in a sample of Plains Indians showed association between eight single nucleotide polymorphisms (SNPs) located in the SGIP1 gene and resting θ electroencephalogram (EEG) power. This association appeared to generalize to alcohol use disorders, for which EEG power is a potential endophenotype. We analyzed a large, diverse sample for replication of the association of these implicated SGIP1 SNPs (genotyped on the Illumina 1M platform) with alcohol dependence (N=3988) and θ EEG power (N=1066). We found no evidence of association of the earlier implicated SGIP1 SNPs with either alcohol dependence or θ EEG power (all P>0.15) in this sample. The earlier implicated SNPs located in SGIP1 gene showed no association with alcohol dependence or θ EEG power in this sample of individuals with European and/or African ancestry. This failure to replicate may be the result of differences in ancestry between this sample and the original sample.

The DSM-IV model of personality disorders is composed of trait sets arranged into 10 theoretically distinct, polythetically assessed categories, with little regard for how the traits comprising these disorders are interrelated and structured. Research since the publication of DSM-III has shown that this model is untenable. The question is not whether this model needs revision; rather, the question is how to move from the existing DSM-IV framework to a model better connected with data. Empirically-based models of personality trait variation provide a starting point for DSM-5, and ongoing research will be used to delineate further the empirical structure of personality traits in the pathological range. The ultimate goal is to frame future DSMs in a way that is maximally useful for clinicians as well as researchers. It is also critical to understand that the DSM-5 is intended to be a living document that will facilitate novel inquiry and clinical applications, as opposed to a document designed to promote and perpetuate a fixed set of constructs. Thus, we view a proposed trait system as a first step on a path to a well-validated, clinically-useful structure.

The transition from the Diagnostic and Statistical Model of Mental Disorders (4th ed., text revision [DSM-IV-TR]; American Psychiatric Association, 2000 ) to the fifth edition (DSM-5) represents an unprecedented opportunity to integrate dimensional personality trait models into the official nosology. Not surprisingly, a variety of issues have arisen in contemplating this challenging integration. In this article, we address how a dimensional personality trait model could be a helpful component of DSM-5, from the perspective of our roles as work group members and advisors involved in the creation of a trait model and corresponding assessment instrument. We focus in particular on two potential roles for a trait model in DSM-5 that are under official consideration. First, a dimensional personality trait model might be helpful in delineating the content of personality disorders. Second, a trait model might assist in organizing the "metastructure" of DSM-5 (i.e., the arrangement of chapters and other broader classificatory rubrics).

Previous studies with various non-human animals have revealed that they possess an evolved predator recognition mechanism that specifies the appearance of recurring threats. We used the preferential looking and habituation paradigms in three experiments to investigate whether 5-month-old human infants have a perceptual template for spiders that generalizes to real-world images of spiders. A fourth experiment assessed whether 5-month-olds have a perceptual template for a non-threatening biological stimulus (i.e., a flower). The results supported the hypothesis that humans, like other species, may possess a cognitive mechanism for detecting specific animals that were potentially harmful throughout evolutionary history.

Genome-wide studies of psychiatric conditions frequently fail to explain a substantial proportion of variance, and replication of individual SNP effects is rare. We demonstrate a selective scoring approach, in which variants from several genes known to directly affect the dopamine system are considered concurrently to explain individual differences in cocaine dependence symptoms. 273 SNPs from eight dopamine-related genes were tested for association with cocaine dependence symptoms in an initial training sample. We identified a four-SNP score that accounted for 0.55% of the variance in a separate testing sample (p = 0.037). These findings suggest that (1) limiting investigated SNPs to those located in genes of theoretical importance improves the chances of identifying replicable effects by reducing statistical penalties for multiple testing, and (2) considering top-associated SNPs in the aggregate can reveal replicable effects that are too small to be identified at the level of individual SNPs.

To examine whether DSM-IV symptoms of substance dependence are psychometrically equivalent between existing community-sampled and clinically overselected studies. A total of 2476 adult twins born in Minnesota and 4121 unrelated adult participants from a case-control study of alcohol dependence. Life-time DSM-IV alcohol, marijuana and cocaine dependence symptoms and ever use of each substance. We fitted a hierarchical model to the data, in which ever use and dependence symptoms for each substance were indicators of alcohol, marijuana or cocaine dependence which were, in turn, indicators of a multi-substance dependence factor. We then tested the model for measurement invariance across participant groups, defined by study source and participant sex. The hierarchical model fitted well among males and females within each sample [comparative fit index (CFI) > 0.96, Tucker-Lewis index (TLI) > 0.95 and root mean square error of approximation (RMSEA) < 0.04 for all], and a multi-group model demonstrated that model parameters were equivalent across sample- and sex-defined groups (ΔCFI = 0.002 between constrained and unconstrained models). Differences between groups in symptom endorsement rates could be expressed solely as mean differences in the multi-substance dependence factor. Life-time substance dependence symptoms fitted a dimensional model well. Although clinically overselected participants endorsed more dependence symptoms, on average, than community-sampled participants, the pattern of symptom endorsement was similar across groups. From a measurement perspective, DSM-IV criteria are equally appropriate for describing substance dependence across different sampling methods.

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central n...

We conducted a genome-wide association study of subjective well-being (SWB) in 298,420 individuals. We also performed auxiliary analyses of depressive symptoms ("DS";N= 161,460) and neuroticism (N= 170,910), both of which have a substantial genetic correlation with SWB (ρ≈-0.8). We identify three SNPs associated with SWB at genome-wide significance. Two of them are significantly associated with DS in an independent sample. In our auxiliary analyses, we identify 13 additional genome-wide-significant associations: two with DS and eleven with neuroticism, including two inversion polymorphisms. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are enriched. The discovery of genetic loci associated with the three phenotypes we study has proven elusive; our findings illustrate the payoffs from studying them jointly.

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted ex...

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

Human longevity and personality traits are both heritable and are consistently linked at the phenotypic level. We test the hypothesis that candidate genes influencing longevity in lower organisms are associated with variance in the five major dimensions of human personality (measured by the NEO-FFI and IPIP inventories) plus related mood states of anxiety and depression. Seventy single nucleotide polymorphisms (SNPs) in six brain expressed, longevity candidate genes (AFG3L2, FRAP1, MAT1A, MAT2A, SYNJ1, and SYNJ2) were typed in over 1,000 70-year old participants from the Lothian Birth Cohort of 1936 (LBC1936). No SNPs were associated with the personality and psychological distress traits at a Bonferroni corrected level of significance (P < 0.0002), but there was an over-representation of nominally significant (P…