Steven H. Aggen

Multiple Independent Loci at Chromosome 15q25.1 Affect Smoking Quantity: a Meta-Analysis and Comparison with Lung Cancer and COPD

Recently, genetic association findings for nicotine dependence, smoking behavior, and smoking-related diseases converged to implicate the chromosome 15q25.1 region, which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes. In particular, association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies. Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence, tagged by rs578776 and rs588765. One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP) is to elucidate the associations among these markers and dichotomous smoking quantity (heavy versus light smoking), lung cancer, and chronic obstructive pulmonary disease (COPD). We performed a meta-analysis across 34 datasets of European-ancestry subjects, including 38,617 smokers who were assessed for cigarettes-per-day, 7,700 lung cancer cases and 5,914 lung-cancer-free controls (all smokers), and 2,614 COPD cases and 3,568 COPD-free controls (all smokers). We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking (mutually adjusted p-values<10−35 and <10−8 respectively). Because the risk alleles at these loci are negatively correlated, their association with smoking is stronger in the joint model than when each SNP is analyzed alone. Rs578776 also demonstrates association with smoking after adjustment for rs16969968 (p<10−6). In models adjusting for cigarettes-per-day, we confirm the association between rs16969968 and lung cancer (p<10−20) and observe a nominally significant association with COPD (p = 0.01); the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968. This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior. This study is also the first report of association between rs588765 (and correlates) and smoking that achieves genome-wide significance; these SNPs have previously been associated with mRNA levels of CHRNA5 in brain and lung tissue.

Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood.

CONTEXT While both environmental and genetic factors are important in the etiology of psychoactive substance use (PSU), we know little of how these influences differ through development. OBJECTIVE To clarify the changing role of genes and environment in PSU from early adolescence through middle adulthood. DESIGN Retrospective assessment by life history calendar, with univariate and bivariate structural modeling. SETTING General community. PARTICIPANTS A total of 1796 members of male-male pairs from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. MAIN OUTCOME MEASURES Levels of use of alcohol, caffeine, cannabis, and nicotine recorded for every year of the respondents life. RESULTS For nicotine, alcohol, and cannabis, familial environmental factors were critical in influencing use in early adolescence and gradually declined in importance through young adulthood. Genetic factors, by contrast, had little or no influence on PSU in early adolescence and gradually increased in their effect with increasing age. The sources of individual differences in caffeine use changed much more modestly over time. Substantial correlations were seen among levels of cannabis, nicotine, and alcohol use and specifically between caffeine and nicotine. In adolescence, those correlations were strongly influenced by shared effects from the familial environment. However, as individuals aged, more and more of the correlation in PSU resulted from genetic factors that influenced use of both substances. CONCLUSIONS These results support an etiologic model for individual differences in PSU in which initiation and early patterns of use are strongly influenced by social and familial environmental factors while later levels of use are strongly influenced by genetic factors. The substantial correlations seen in levels of PSU across substances are largely the result of social environmental factors in adolescence, with genetic factors becoming progressively more important through early and middle adulthood.

The Structure of Genetic and Environmental Risk Factors for Syndromal and Subsyndromal Common DSM-IV Axis I and All Axis II Disorders

OBJECTIVE The authors sought to clarify the structure of the genetic and environmental risk factors for 22 DSM-IV disorders: 12 common axis I disorders and all 10 axis II disorders. METHOD The authors examined syndromal and subsyndromal axis I diagnoses and five categories reflecting number of endorsed criteria for axis II disorders in 2,111 personally interviewed young adult members of the Norwegian Institute of Public Health Twin Panel. RESULTS Four correlated genetic factors were identified: axis I internalizing, axis II internalizing, axis I externalizing, and axis II externalizing. Factors 1 and 2 and factors 3 and 4 were moderately correlated, supporting the importance of the internalizing-externalizing distinction. Five disorders had substantial loadings on two factors: borderline personality disorder (factors 3 and 4), somatoform disorder (factors 1 and 2), paranoid and dependent personality disorders (factors 2 and 4), and eating disorders (factors 1 and 4). Three correlated environmental factors were identified: axis II disorders, axis I internalizing disorders, and externalizing disorders versus anxiety disorders. CONCLUSIONS Common axis I and II psychiatric disorders have a coherent underlying genetic structure that reflects two major dimensions: internalizing versus externalizing, and axis I versus axis II. The underlying structure of environmental influences is quite different. The organization of common psychiatric disorders into coherent groups results largely from genetic, not environmental, factors. These results should be interpreted in the context of unavoidable limitations of current statistical methods applied to this number of diagnostic categories.

The Structure of Genetic and Environmental Risk Factors for DSM-IV Personality Disorders: A Multivariate Twin Study

CONTEXT Although both genetic and environmental factors affect risk of individual personality disorders (PDs), we know little of how they contribute to the pattern of comorbidity between the PDs in the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV). OBJECTIVE To clarify the structure of the genetic and environmental risk factors for the 10 DSM-IV PDs. DESIGN Assessment of PDs at personal interview and multivariate twin modeling with the Mx program. SETTING General community. PARTICIPANTS A total of 2794 young adult members of the Norwegian Institute of Public Health Twin Panel. Main Outcome Measure Number of endorsed criteria for the 10 DSM-IV PDs. RESULTS The best-fit multivariate twin model required 3 genetic and 3 individual-specific environmental factors and genetic and individual-specific factors unique to each PD. The first genetic factor had high loadings on PDs from all 3 clusters including paranoid, histrionic, borderline, narcissistic, dependent, and obsessive-compulsive. The second genetic factor had substantial loadings only on borderline and antisocial PD. The third genetic factor had high loadings only on schizoid and avoidant PD. Several PDs had substantial disorder-specific genetic risk factors. The first, second, and third individual-specific environmental factors had high loadings on the cluster B, A, and C PDs, respectively, with 1 exception: obsessive-compulsive PD loaded with cluster B and not cluster C PDs. CONCLUSIONS Genetic risk factors for DSM-IV PDs do not reflect the cluster A, B, and C typology. Rather, 1 genetic factor reflects a broad vulnerability to PD pathology and/or negative emotionality. The 2 other genetic factors are more specific and reflect high impulsivity/low agreeableness and introversion. Unexpectedly, the cluster A, B, and C typology is well reflected in the structure of environmental risk factors, suggesting that environmental experiences may be responsible for the tendency of cluster A, B, and C PDs to co-occur.

Critical slowing down as early warning for the onset and termination of depression

Significance As complex systems such as the climate or ecosystems approach a tipping point, their dynamics tend to become dominated by a phenomenon known as critical slowing down. Using time series of autorecorded mood, we show that indicators of slowing down are also predictive of future transitions in depression. Specifically, in persons who are more likely to have a future transition, mood dynamics are slower and different aspects of mood are more correlated. This supports the view that the mood system may have tipping points where reinforcing feedbacks among a web of symptoms can propagate a person into a disorder. Our findings suggest the possibility of early warning systems for psychiatric disorders, using smartphone-based mood monitoring. About 17% of humanity goes through an episode of major depression at some point in their lifetime. Despite the enormous societal costs of this incapacitating disorder, it is largely unknown how the likelihood of falling into a depressive episode can be assessed. Here, we show for a large group of healthy individuals and patients that the probability of an upcoming shift between a depressed and a normal state is related to elevated temporal autocorrelation, variance, and correlation between emotions in fluctuations of autorecorded emotions. These are indicators of the general phenomenon of critical slowing down, which is expected to occur when a system approaches a tipping point. Our results support the hypothesis that mood may have alternative stable states separated by tipping points, and suggest an approach for assessing the likelihood of transitions into and out of depression.

Short-Term Fluctuations in Elderly People’s Sensorimotor Functioning Predict Text and Spatial Memory Performance: The MacArthur Successful Aging Studies

Background: While age-related increases of between-person variability in a variety of cognitive measures are commonly reported in cross-sectional studies, the nature of short-term intraindividual fluctuation in elderly people’s performance is relatively unexplored. Objective: The goal of the present study is to examine short-term fluctuations in elderly people’s sensorimotor functioning and their relations to individual differences in verbal and spatial memory. Methods: Fluctuations in old adults’ (mean = 75.71 years, SD = 6.93 years) sensorimotor performance were investigated by biweekly measurements spanning approximately 7 months. Sensorimotor performance was measured by three walking tasks, including the duration and the number of steps taken to walk a 360-degree circle and to walk 10 feet both at normal and fast pace. Performances of verbal and spatial memory were assessed by weekly measurements of digit memory span, memory for short text and spatial recognition. Results: The magnitude of intraindividual fluctuation in most sensorimotor and memory tasks examined was at least half as great as the level of individual differences across persons. In addition, intraindividual fluctuation in sensorimotor performance is a relatively stable individual attribute, which correlates positively with age and negatively with the levels of sensorimotor, text and spatial memory performance. Although a substantial amount of individual differences in intraindividual fluctuation was shared with mean performance level, variance component and hierarchical regression analyses showed that intraindividual fluctuation in walking steps added significant independent contribution over and above that given by level of performance in predicting text and spatial memory. Conclusion: Taking these results together, we suggest that intraindividual fluctuations in elderly people’s performance should not be ignored or simply treated as measurement error; rather, they are potentially important empirical variables for understanding sensory and cognitive aging and the nature of intraindividual response variations in general.

Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't Like Parties if You Don't Like People

In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality as a system of connected affective, cognitive and behavioural components. We hypothesize that these components do not hang together because they measure the same underlying dimension; they do so because they depend on one another directly for causal, homeostatic or logical reasons (e.g. if one does not like people and it is harder to enjoy parties). From this ‘network perspective’, personality dimensions emerge out of the connectivity structure that exists between the various components of personality. After outlining the network theory, we illustrate how it applies to personality research in four domains: (i) the overall organization of personality components; (ii) the distinction between state and trait; (iii) the genetic architecture of personality; and (iv) the relation between personality and psychopathology. Copyright

The Joint Structure of DSM–IV Axis I and Axis II Disorders

The Diagnostic and Statistical Manual (4th ed. [DSM-IV]; American Psychiatric Association, 1994) distinction between clinical disorders on Axis I and personality disorders on Axis II has become increasingly controversial. Although substantial comorbidity between axes has been demonstrated, the structure of the liability factors underlying these two groups of disorders is poorly understood. The aim of this study was to determine the latent factor structure of a broad set of common Axis I disorders and all Axis II personality disorders and thereby to identify clusters of disorders and account for comorbidity within and between axes. Data were collected in Norway, through a population-based interview study (N = 2,794 young adult twins). Axis I and Axis II disorders were assessed with the Composite International Diagnostic Interview (CIDI) and the Structured Interview for DSM-IV Personality (SIDP-IV), respectively. Exploratory and confirmatory factor analyses were used to investigate the underlying structure of 25 disorders. A four-factor model fit the data well, suggesting a distinction between clinical and personality disorders as well as a distinction between broad groups of internalizing and externalizing disorders. The location of some disorders was not consistent with the DSM-IV classification; antisocial personality disorder belonged primarily to the Axis I externalizing spectrum, dysthymia appeared as a personality disorder, and borderline personality disorder appeared in an interspectral position. The findings have implications for a meta-structure for the DSM.

A longitudinal study of personality and major depression in a population-based sample of male twins

BACKGROUND The relationship between personality and psychiatric illness is complex. It is not clear whether one directly causes the other. METHOD In a population-based sample of male twins (n=3030), we attempted to predict major depression (MD) from neuroticism (N) and extraversion (E) and vice versa, to evaluate the causal, scar, state, and prodromal hypotheses. In a longitudinal, structural equation twin model, we decomposed the covariation between N and MD into (a) genetic and environmental factors that are common to both traits, as well as specific to each one and (b) direct causal effects of N at time 1 on subsequent MD, as well as between MD and subsequent N. RESULTS E was negatively correlated with lifetime and one-year prevalence of MD. N predicted the new onset of MD, and was predicted by both current and past MD. It did not predict the time to onset of MD. All of the covariation between N and MD was due to additive genetic and individual-specific environmental factors shared by both traits and a direct causal path between MD and N assessed later. No genetic factors were unique to either trait. CONCLUSIONS In men, N may be a vulnerability factor for MD but does not cause it directly. However, MD may have a direct causal effect on N. The genetic overlap between N and MD in men may be greater than in women.

Genomewide association analysis of symptoms of alcohol dependence in the molecular genetics of schizophrenia (MGS2) control sample.

BACKGROUND While genetic influences on alcohol dependence (AD) are substantial, progress in the identification of individual genetic variants that impact on risk has been difficult. METHODS We performed a genome-wide association study on 3,169 alcohol consuming subjects from the population-based Molecular Genetics of Schizophrenia (MGS2) control sample. Subjects were asked 7 questions about symptoms of AD which were analyzed by confirmatory factor analysis. Genotyping was performed using the Affymetrix 6.0 array. Three sets of analyses were conducted separately for European American (EA, n = 2,357) and African-American (AA, n = 812) subjects: individual single nucleotide polymorphisms (SNPs), candidate genes and enriched pathways using gene ontology (GO) categories. RESULTS The symptoms of AD formed a highly coherent single factor. No SNP approached genome-wide significance. In the EA sample, the most significant intragenic SNP was in KCNMA1, the human homolog of the slo-1 gene in C. Elegans. Genes with clusters of significant SNPs included AKAP9, phosphatidylinositol glycan anchor biosynthesis, class G (PIGG), and KCNMA1. In the AA sample, the most significant intragenic SNP was CEACAM6 and genes showing empirically significant SNPs included KCNQ5, SLC35B4, and MGLL. In the candidate gene based analyses, the most significant findings were with ADH1C, nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1) and ankyrin repeat and kinase domain containing 1 (ANKK1) in the EA sample, and ADH5, POMC, and CHRM2 in the AA sample. The ALIGATOR program identified a significant excess of associated SNPs within and near genes in a substantial number of GO categories over a range of statistical stringencies in both the EA and AA sample. CONCLUSIONS While we cannot be highly confident about any single result from these analyses, a number of findings were suggestive and worthy of follow-up. Although quite large samples will be needed to obtain requisite power, the study of AD symptoms in general population samples is a viable complement to case-control studies in identifying genetic risk variants for AD.